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Edge Case Research Secures $7M

Edge Case Research announced it secured $7 million in investment funding. The investment will expand the development of Hologram, an intelligent safety assessment platform for autonomous vehicle software that operates at the speed of modern machine learning development.

Chris Urmson, co-founder and CEO of Aurora, and ANSYS, the global leader in engineering simulation led the round with participation from Lockheed Martin Ventures, Liberty Mutual Strategic Ventures, Trucks VC, and Blue Tree Allied Angels. As a part of the investment, Chris Urmson and Matt Zack, vice president of corporate marketing and business development, ANSYS will join the Edge Case Research Board of Directors.

As autonomous vehicle fleets expand into cities across the world, there remains uncertainty around the safety of this emerging technology. Edge Case is developing products and standards to allow manufacturers to gain public confidence and trust in this new technology; assuring vehicles will operate safely on public roads.

Hologram identifies “edge cases” in the perception stack. These are situations in which the deep learning algorithms at the core of autonomous vehicles fail to detect critical objects such as pedestrians, vehicles, and other road users. Hologram gives developers the information they need to retrain their algorithms to operate more reliably, addressing a critical barrier to the safe deployment of autonomous vehicles.

“I am honored to bring together an ecosystem of investors with industry expertise, and to be playing a significant role in the advancement of safe autonomous vehicles,” says Michael Wagner, CEO, Edge Case Research. “Most importantly, we’ve built an investor group that shares our mission to empower innovators to bring safe, trustworthy technologies to market. This ambitious vision is behind everything we do.”

“Self-driving technology will have a profound impact on the safety of our roads and the quality of life of communities in our cities,” said Chris Urmson, Co-founder and CEO of Aurora. “Developing and delivering self-driving technology safety is paramount, and the Edge Case team has the commitment and deep expertise for building important tools for developing this technology. I’m thrilled to see Edge Case take this next step in their mission.”

“We are excited to welcome Edge Case Research into our AV Ecosystem,” said Matt Zack, vice president of corporate marketing and business development, ANSYS. “Their unique and robust offerings complement our comprehensive autonomous solutions for safety and automatic driving scenario generation and will help make Level 5 autonomous vehicles a reality.”

Along with the development of Hologram, Edge Case is partnering with Underwriters Laboratories (UL) to provide leadership for creating the UL 4600 standard for the safety of autonomous products. UL 4600 is expected to be the first comprehensive standard to address the safe deployment of autonomous vehicles and mobile robotic products. It will specifically address ensuring the safety of autonomous products that operate without human intervention based on their current state and sensing of the operating environment. Edge Case acted as the primary subject matter experts for creating the initial draft version. Currently, the Underwriters Laboratories Standard Technical Panel (STP) is revising that draft to produce a consensus-based industry standard, with a planned completion date of late 2019.

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Pittsburgh self-driving safety firm Edge Case announces $7 million in funding

A Pittsburgh company working to make self-driving cars see better and ultimately be safer announced Thursday it raised $7 million in its first round of investment funding.

Edge Case Research, based in Lawrenceville, said the money will be used to expand its Hologram software that helps identify bugs in the software used by autonomous vehicles and will allow it to grow its staff of about 40 employees to about 60.

The investment was led by Chris Urmson, co-founder and CEO of the self-driving car company Aurora Innovation, which has offices in Pittsburgh and California, and ANSYS, a Pittsburgh-based simulation software company.

Edge Case CEO Michael Wagner said the investors are part of an “ecosystem” that together will work to advance technologies to make self-driving cars a reality.

”We’ve built an investor group that shares our mission to empower innovators to bring safe, trustworthy technologies to market. This ambitious vision is behind everything we do,” Wagner said in a statement.

Urmson said developing safe, self-driving technology is paramount. Matt Zack, vice president of corporate marketing and business development at ANSYS, said Edge Case technology will help the company move toward fully autonomous vehicles.

The investment into Edge Case comes at a time when investors appear to be returning to self-driving technology and companies are announcing a flurry of deals.

Aurora announced that it’s partnering with Fiat Chrysler Automobiles on Monday to build self-driving vehicles and shared news later in the week that it had expanded its partnership with Hyundai and Kia. The deal expands an agreement from last year. Aurora wouldn’t say how much Hyundai is putting in, but it announced in February that it had raised $530 million. So that means Hyundai-Kia and some other investors are kicking in around $70 million.

The company already has partnerships with Hyundai and Volkswagen. Volkswagen, however, confirmed that it has cut ties with Aurora. The German automaker is working on a tie-up with Ford that includes a partnership with Argo AI.

Argo AI, an autonomous vehicle company partly owned by Ford, announced Wednesday that it would expand testing to Detroit. The company already is testing vehicles in Pittsburgh, Miami, Washington, D.C., Dearborn, Michigan, and Palo Alto, California.

On Wednesday, Uber announced that it would work with Volvo Cars to build a vehicle that comes off the assembly line capable of driving autonomously. The ride-hailing company’s self-driving system will be installed in production versions of the Volvo XC90 SUV. Various sensors will allow Uber’s self-driving system to safely operate and maneuver in urban areas, the company said.

Uber and Volvo Cars partnered in September 2016. This is the third car they’ve developed together. Volvo says it plans to use a similar vehicle to introduce its own self-driving cars in the early 2020s.

Uber, Toyota and others announced a $1 billion deal in April.

The Associated Press contributed to this report.

Tom Davidson is a TribLive news editor. He has been a journalist in Western Pennsylvania for more than 25 years. He can be reached at [email protected] .

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FingerVision

• Location: Tokyo, Japan
• Founded in: 2021
• Management Team: Yuki Nono
• Investment Team: Mikuni Kimura

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FingerVision is a startup that develops technology to “estimating tactile sensation based on an image (captured by a camera).”By mounting the FingerVision sensor, which consists of a transparent soft skin (made of silicon rubber) and a small camera, on the fingertip of a robot hand, etc., it becomes possible to perceive tactile sensations (distribution of force, slippage, etc.) and realize control of a robot as if a person were handling an object using “palm” sensation.

• Founded in: 2018
• Management Team: Hiroaki Matsuoka

Reborn is developing odor sensors and data management systems based on the vision of “eliminating “somehow” smells” through scent x AI x DX. They are building a “smell data platform” that accumulates smell data from all over the world by utilizing their proprietary smell sensing devices and AI. They are using advanced sensing devices and AI analysis to identify smells, which often rely on human senses and experience, to develop and improve the quality of products for the manufacturing and food industries.

StimScience

• Location: Berkeley, CA
• Founded in: 2017
• Management Team: Aaron Bromberg
• Investment Team: Nobuhiro Seki

StimScience offers Somnee, an electronic sleep aid headband to improve sleep quality.Somnee uses non-invasive electrical stimulation to promote the natural sleep patterns of the user’s brain. After only 15 minutes of use, the overall quality of sleep is improved; Somnee customizes stimulation sessions based on individual sleep patterns and allows users to track their sleep through an app. This improves sleep quality and allows you to wake up relaxed and recharged.

Edge Case Research

• Location: Pittsburgh, Pennsylvania
• Management Team: Michael Wagner

Edge Case Research is developing Hologram, a safety simulation system for developers of automated driving technology using proprietary AI models, and nLoop, a risk analysis system for automated driving. While automated driving still requires driver intervention once every few tens of thousands of kilometers due to automated driving system failures, object misidentification, and other reasons, the company is working to achieve safe automated driving by collecting vast amounts of data and training AI models.

• Founded in: 2019
• Management Team: Akihiro Yamamoto
• Investment Team: Narimasa Makino

Ima-create develops virtual training materials for the industrial and medical fields. They call it “Active VR,” where users actively use their bodies in the virtual world instead of passively watching the content. In the “Nup Welding Training” jointly developed with KOBELCO E&M, Ima-create confirmed that people improved their welding skills more effectively in VR than in the real world. Ima-create is looking to expand its business overseas and further develop the training technology for industry and the medical field.

• Location: Shibuya-ku, Tokyo, Japan
• Founded in: 2016
• Management Team: Kosuke Shimizu (CEO)

Arblet develops a wrist-worn wearable device utilizing cuff-less blood pressure measurement technology with the aim to identify the temporal change in the user’s health condition by cross-analyzing behavioral and vital data. Utilizing the cloud analysis algorithm and the device on the wrist, it can monitor users’ health around the clock, such as blood pressure, pulse rate, body temperature, respiration rate, and other vital and behavioral data. They aim to provide a service to inform future disease risk and emergency alerts for people with or without health concerns.

• Location: Pittsburgh, PA, US
• Management Team: Navid Kazem (CEO)

Arieca is an American advanced materials start-up, spun-out of Carnegie Mellon University, that is pushing the boundaries of materials functionalities in the most demanding applications. Their proprietary and patented liquid metal embedded elastomer (LMEE) technologies allow for unprecedented performances in applications across semiconductor, aerospace, automotive, and healthcare industries. Their main products are TIMbberTM – the most adaptable thermal interface material (TIM) for high performance semiconductor devices, and Thubber® – a soft, stretchable, and thermally conductive elastomer.

ARIN Technologies

• Founded in: 2015
• Management Team: Vivek Kulkarni (CEO)

ARIN technology develops high-accuracy indoor positioning systems. This system is used in indoor places such as factories to acquire real-time 3D locations of Work In Progress (WIP). A proprietary transmitting device attached to the object measures the distance from the anchor device to calculate the XYZ location values of the device. ARIN technology also provides a solution to prevent forklift collision by applying the high-precision indoor positioning system.

• Location: Kyoto-shi, Kyoto, Japan
• Founded in: 2014
• Management Team: Kyohi Kang (CEO)

Atmoph sells smart windows along with its own high-quality landscape video contents to display on it. It has already released about 1,000 videos. It comes with 10 videos at the time of purchase and ¥590~ per video after that. The latest 27-inch model is fitted with a camera and microphone. It is cheaper than its competitors and easier to mount on the wall. Also, it can display clocks, calendars and connect to Google Assistant or Amazon Alexa. Atmoph also provide landscape videos shot by themselves all around the world for a fee. Moreover, it has partnered with Disney to stream the worlds of Disney and Star Wars.

• Location: NYC, NY, US
• Management Team: Yousef Ali (CEO)

Blast is a music streaming service that allows creators to broadcast studio-quality, live audio with a single click on their proprietary device. The streaming music will disappear in 24 hours, which gives creators the freedom to explore without worrying about copyrights. Blast Media Group launched its service in June 2021.

Brelyon Inc

• Location: San Mateo, CA, US
• Management Team: Barmak Heshmat (CEO)

BRELYON presents a new category of displays that gives immersion and high fidelity with no need for headsets. The company was founded by an MIT Media Lab graduate based on his own research. BRELYON’s displays have the immersion of VR headsets while maintaining the speed and resolution of desktop displays. BRELYONaims at places where people work with multiple displays, such as the manufacturing industry, trading rooms of financial institutions, and eventually gaming and entertainment fields as well.

• Location: Soja-shi, Okayama, Japan
• Founded in: 2012
• Management Team: Masayuki Kanehara

C-INK is engaged in producing and supplying metal nano-ink (conductive ink). Their nano-ink DryCure-Au and DryCure-Ag are made by cutting down organic impurities to a minimum compared to conventional nano-ink. As a result, they have incredibly high metal purity, minimum high-temperature sintering, stable ink condition, and reduced risk of cracking. By taking advantage of the properties of this nano-ink, it has become possible to produce wiring boards at low cost and high speed, which used to be made under complicated processes. The system for mass production is already in place and will be used for the wiring of electric circuits and LED signboards.

CleanRobotics

• Management Team: Charles Yhap (CEO)

CleanRobotics provides a solution to enable centralized management of trash cans that sort trash automatically. In the U.S., because of the lack of waste education, people can not sort waste accurately even if they want to. “Trashbot” developed by Using AI computer vision, CleanRobotics can detect if the trash is recyclable. Moreover, monitoring all Trashbots remotely simultaneously, the system can let staff know when Trashbot is getting full.

• Location: Shinjuku-ku, Tokyo, Japan
• Management Team: Kyo Nomura (CEO)

Denishindo develops a home use atmospheric pressure plasma facial skin-care device called “Un.” “Un” reduces spots by generating Plasma Air Shower. The problem of laser treatment at beauty salons, which is the most effective way to reduce spots, is that it is painful and expensive. In addition, there are no existing facial products that work on stubborn blemishes. This product opens the skin barrier and improves the penetration of toners and serums by exposing skin to plasma. It accelerates skin regeneration, and spots get reduced as a result. They are aiming to enter the Japanese and Chinese markets.

Digital Dream Labs

• Management Team: Jacob Hanchar (CEO)

Digital Dream Labs develops engaging learning robots. One of their robots, “Cozmo,” is a coding robot for kids to learn through play, while “Vector” is an interactive companion robot embedded with cutting-edge AI. Anki, the company that developed these products, sold the business to DDL in 2019 and took over the products and services.

• Location: Richmond, CA
• Management Team: Troy Helming
• Investment Team: Sabrina Sasaki , Nobuhiro Seki

EarthGrid has invented plasma tunnel boring robots that are solar-powered, use no water, have zero emissions and can bore tunnels 100x faster at 1/10th the cost of conventional techniques. They are building a network of large, underground utility tunnels that improve infrastructure and rapidly accelerate the transition to 100% clean energy by enabling underground clean energy power lines, high-speed data, water, and wastewater, H2 pipelines, e-commerce parcel transportation via pneumatic tubes, etc. They have a BOOM model (Build, Own, Operate and Manage) and intend to lease space to investment-grade utilities.

• Location: Yokohama-shi, Kanagawa, Japan
• Management Team: Yasushi Kisanuki (CEO)

EASEL is a startup developing IoT devices based on the long-range and power-saving LoRa method. Wi-Fi, 5G, RFID, and other methods have been developed due to the advanced IT trend, and various standards are being used for communication. On the other hand, the LoRa method can realize long-distance, and power-saving communication specialized for applications that require fewer data transmission charges. They are particularly focused on the LoRa method and private LoRa networks combining GPS, BlueTooth, and 3G/LTE methods. They provide planning, prototype development, and mass production development services for IoT technologies, and they are one of the best-known companies in Japan for LoRa modules.

• Location: Shibuya-ku, Tokyo, Japan/Singapore
• Management Team: Sakyasingha Dasgupta (CEO)
• Investment Team: Kazuya Tsujimoto , Nobuhiro Seki

Edge Cortix is a Singapore-based startup that provides ultra-powerful, low-latency AI inference hardware IP and software stack for edge devices. Its key customers are automotive semiconductors, industrial equipment manufacturers, and cloud servers. Their development team, including the CEO, is in Japan, while the sales force is located in Japan and the US. The market for Edge AI chips is expected to be worth USD 5 billion by 2025, and the demand for Edge AI software is expected to be worth USD 1.8 billion by 2026. 2-5x performance can be achieved on FPGAs by using the MERA compiler, and 15-20x performance can be achieved on ASICs by combining proprietary architectures. For FPGA, 2-5x performance can be achieved by using MERA compiler.

Enecoat Technologies

• Location: Kyoto, Japan
• Management Team: Naoya Kato

Enecoat Technologies develops and commercializes solar cell materials and modules for a clean environment and sustainable use of natural energy. We are a startup based on the seeds of research cultivated over several years by Prof. Atsushi Wakamiya at Kyoto University’s Institute for Chemical Research. Our goal is environmental protection and effective use of natural energy. We are creating the future of energy with ultrathin solar cell films. For next-generation solar power, perovskite solar cells are a promising emerging technology offering high efficiency not only on sunny days, but under cloudy sky and indoor light also. Perovskite solar cells are manufactured using low-cost processes and can be made flexible and lightweight. Perovskite solar cells will bring many changes to our life.

• Location: Namerikawa-shi, Toyama, Japan
• Founded in: 2013
• Management Team: Katsunori Shimomura (CEO)

Enowa is an Agri Tech startup that develops and operates “paditch,” a smart paddy field service. Paditch enables remote water management of rice fields using smartphones. It maximizes the yield of rice as well as saves labor by automatically opening and closing the sluice gates to the programmed water level and time.

ESTAT Actuation

• Management Team: Stuart Diller (CEO)

ESTAT Actuation develops cutting-edge actuators to revolutionalize industries using robots. ESTAT Actuation uses new electroadhesive clutch technology developed at Carnegie Mellon University to dramatically reduce the weight, size, and cost of actuators. In addition to selling those actuators, ESTAT’s goal is to license the clutch technology.

• Location: Cleveland, OH, US
• Management Team: Chris Wentz (CEO)

EveryKey is a startup developing security devices that can lock and unlock multiple devices without passwords or keys. For example, you can unlock your smartphone and computer at once just by getting close to them, and vice versa. The device utilizes Bluetooth technology to enable that. You can manage their passwords by using their software. In the accident of loss or theft, you can deactivate all functions remotely.

Flextrapower

• Management Team: Linh Le (CEO)

Flextrapower (formerly known as Bonbouton) is a healthcare startup from New York City that monitors the temperature and humidity of diabetic patients’ feet to help prevent severe complications such as foot amputation. Often in the US, people have to wait several days after making an appointment to see a doctor. Therefore, by the time they see a doctor, sometimes the condition is deteriorated too much, resulting in leg amputation. The company created nano-level ultra-thin sensors that fit inside the shoes’ insoles, monitored via a smartphone app. AI can read signs that could lead to severe conditions and report them to the patient and their doctor.

Hava Health

• Location: Philadelphia, PA, US
• Management Team: Josh Israel (CEO)

Hava Health is a healthcare startup tackling nicotine dependence amongst the younger generation in the U.S. due to the spread of electric cigarettes. The electric cigarette in the U.S. is different from Japanese ones because U.S. ones can be controlled to absorb liquid nicotine. Hava’s nicotine addiction treatment device uses the same mechanism as the electric cigarettes to control the nicotine dosage vis a smartphone app so that users can gradually reduce it. Hale Therapeutics plans to get medical device approval in the U.K. (MHRA) and USA (FDA)

Forest Devices

• Management Team: Tom Bumgardner (CEO)

Forest Devices is a company focused on prehospital stroke detection. The team developed AlphaStroke, a non-invasive, AI-powered device that can identify a stroke before a CT or MRI is available, improving patient outcomes by decreasing time to treatment. Forest Devices is a startup that develops a prehospital stroke detection device to automate triage so that EMTs can choose a hospital with the right equipment. Only 5% of all hospitals can treat major stroke emergencies in the USA, and only 20% can treat moderate stroke emergencies, so patients are often transferred to another hospital. 30-50% of stroke patients are misdiagnosed and transported to the wrong hospital. The device automatically measures brain waves and uses AI to determine whether or not there is a possibility and severity of the stroke. It displays the results within three minutes. A demonstration experiment is being conducted in Alberta, Canada, since May 2021.

• Management Team: Bob Fields (CEO)

HiberSense’s smart home solution enables precise climate control for each room, which was impossible with central air conditioning. The central hub controls adjustable adapters for AC vents and collects sensor data of temperature, humidity, brightness, and human presence. People in each room can set their preferences in their app, and the hub controls the climate automatically.

Hoplite Power

• Management Team: Jordan Mayerson (CEO)

Hoplite Power is a sharing economy startup that provides a mobile battery rental service for spectators at entertainment venues such as baseball stadiums, arenas, and concert venues. In the U.S., there are live social media activities during live sports games. As a result, people’s smartphones often run out of battery during the game. However, convenience stores are not widespread in the U.S., so you can not easily find a mobile battery. Hoplite Power offers a battery rental service for those spectators at the stadium.

• Location: Sunnyvale, CA, US
• Management Team: Taizo Otsuka (CEO)

Kakaxi develops solar-powered devices with cameras and sensors to monitor crops and the surrounding environment. Kakaxi can collect temperature, humidity, and insolation intensity data, which can be easily checked from a PC, tablet, or smartphone. Furthermore, the wide-angle camera makes it possible to ensure the produces’ safety and grasp the harvest timing. Kakaxi’s primary focus is data collection through the cameras so they can eventually provide a simple monitoring system with the aim to “transform the primary industry into industry 4.0.”

• Location: Austin, TX, US
• Management Team: Anand Chamarthy (CEO)

Lab 91 is an Austin, TX based company developing semiconductor processes and devices in the field of 2D materials. The company collaborates extensively with the University of Texas at Austin.2D materials like MoS2 and WS2/WSe2 are now firmly on roadmaps of major leading edge semiconductor companies; with a roadmap that starts off in Back-end-of-line/RF, Lab 91 and its partners aim to hit 2D leading edge targets for forthcoming transistor architectures

Load & Road

• Location: Chiyoda-ku, Tokyo, Japan
• Management Team: Kazunori Kawanobe (CEO)

LOAD & ROAD developed a teapot “Teplo” that automatically extracts tea in cooperation with a smartphone application and Teplo official tea leaves, and sells them in Japan and the United States. In general, when brewing the best tea, there are many factors that must be controlled, such as the amount of tea leaves, water, the extraction time, and the temperature. In order to enjoy each tea leaf in the best condition, we need to consider that these differences depending on the tea leaves. Teplo automatically controls these complex factors. In addition, normally, tea brewers adjust the tea conditions according to the behavior, facial expression, and taste preference of the drinker, and brew tea with the best taste and aroma according to the condition of the drinker at that time. LOAD & ROAD continued to do trials to reproduce craftsmanship with the latest technology, and realized the implementation of the world’s first “personalized extraction function”. 6 built-in sensors analyze the physical condition and mood of the drinker and extract the optimal tea.In Teplo’s official online shop and official app, LOAD & ROAD sell tea leaves collected by teplo as a curator, where you can enjoy the taste and the story behind it regardless of the type of tea such as Japanese tea, black tea, Chinese tea, and Taiwanese tea.

• Location: Fujisawa-shi, Kanagawa, Japan
• Founded in: 2020
• Management Team: Kenichi Nakahori (CEO)

Log Build focuses on improving the productivity and efficiency of the construction industry by visualizing the construction sites. At the moment, the quality and gross profit vary depending on the site supervisors. Also, they can not work efficiently enough to spare time to check the drawing of the building carefully. To address those issues, Log Build is creating a method of managing construction sites to reduce the number of trips to the site by 90%. Log Build develops “Logkun,” a remote monitoring system, “LogWalk,” a remote construction management system with a 360 camera, and “LogMeet” for video calling app specifically for meeting, checking, and inspection. As more and more existing industries are working on Digital Transformation(DX), the construction industry is no exception. The construction DX market is expected to grow to 791.2 billion yen in 2019 and 3.425 trillion yen in 2030.

Magic Shields

• Location: Hamamatsu-shi, Shizuoka, Japan
• Management Team: Hiroshi Shimomura (CEO)

Magic Shields develops, manufactures, and sells “Koroyawa”, a soft floor that reduces the risk of bone fractures. About 250,000 older adults fracture their femur every year. Fractures caused by falls are the third leading cause of needing nursing care, and the pain of the fracture and the life that awaits afterward can be a significant burden for the elderly themselves and their families. Magic Shilds’ “Koroyawa” is designed and manufactured based on the concept of mechanical metamaterials. Its internal “variable rigidity structure” enables it to absorb shock and reduce the risk of femur fractures by sinking significantly only when falling from a chair or bed, transferring to a wheelchair, or falling from walking.

Maxwell Labs

• Location: Minneapolis, MN, US
• Management Team: Jacob Balma (CEO)

Maxwell Labs is bringing state-of-the-art materials science to data center cooling. The company develops and manufactures thermal interface materials and intelligent radiative heatsinks with the express aim of simultaneously lowering both the operating cost and environmental impact of data centers worldwide.

Melody International

• Location: Takamatsu-shi, Kagawa, Japan
• Management Team: Yhuko Ogata (CEO)

Based on CTG(CardioTocoGram) technology developed by Tokyo University, Melody International Ltd. develops Fetal Monitor “iCTG,” which enables monitoring the health condition of an expectant mother and her fetus at any time, from anywhere. It is different from conventional CTG because of the smallness, the lightweight, the wireless system for remote examination, and the design for easy use by pregnant mothers. In addition, they offer a central monitor “Central i” and a cloud server “Melody i,” to collect data from multiple iCTGs to monitor in real-time. Right now, obstetric care is in crisis because the number of obstetrical facilities is falling, COVID is making it harder for a pregnant woman to see a doctor, and more women are carrying greater risk by having childbirths later in life. The company aims to help make the world a better place for expectant mothers by improving the safety and security of childbirths. The market size of this industry is expected to grow as the Social Insurance Medical Fee Payments law was revised in 2018 to accommodate telemedicine.

• Location: Boston, MA, US
• Management Team: Apoorva Kiran (CEO)

Connected workers  are more dedicated and productive. Mentore connects workers with employers so they can improve their training, retention, productivity, and safety. Its dedicated smartwatch combined with its AI technology are trusted by companies as Tyson, JBS, PSSI, Johnsonville, BorgWarner, Rivian, Cornell University, achieving quick results as: reduced injuries (70-80%) and less training costs (10-15%) while improving retention (15-25%) 

• Location: Los Angeles, CA, US
• Founded in: 2016 (M&A by Apple Inc.)
• Management Team: Ben Taft (CEO)

Mira is building the world’s most scalable augmented reality hardware & software platform, initially focused on industrials. We are the world’s fastest-growing augmented reality company, transforming productivity for the Global 2000 workforce and the military. We deploy the industry’s most accessible and scalable AR solutions to enhance safety and oversight in industrial environments such as in the manufacturing of chemical explosives and maintenance of military equipment. Our award-winning AR headset is safety rated, compatible with PPE, and powered by smartphones, making us 10x more affordable and 10x faster to deploy. Our convenient Mira Connect software allows see-what-I-see video calls to enable remote subject-matter experts to effectively guide frontline workers in real-time, from anywhere, without having to travel. Our Mira Flow software allows our customers to gain unparalleled insight into operational data when utilizing our hands-free Augmented Reality headsets to guide engineers and technicians through complex workflows while providing managers with macro operational trends and insights. We are backed by the world’s top VCs, including Sequoia Capital, Founder’s Fund, Greylock Partners, Marc Benioff, and others. Our headquarters are based in Los Angeles, California.　*M&A by Apple Inc.

Mitate Zepto Technica

• Management Team: Keisuke Harashima
• Investment Team: Kazuya Tsujimoto

Mitate Zepto Technica(MZT) is a venture company that achieves epoch-making acceleration of genome analysis by utilizing semiconductor technologies.With the advent of next-generation sequencers and technological innovation, DNA scan is completed in less than 10 minutes, but Data processing takes hours and hinders widespread use.MZT develops products that complete data processing within 5 minutes with our cutting-edge technology.28nm technology-powered Processor “RASEN” dedicated to Genome Analysis.Integrated 512 cores of the processing elements are activated for massively parallel computing.Custom ASIC brings by far faster-processing speed than conventional FPGA devices at low power and low cost.

• Location: Mountain View, CA, US
• Management Team: Osama Khan (CEO)

MonoLets is enabling real time supply chain globally across multi-modal trade. The company enables disposable and active digital labels for items at the price point of passives. MonoLets mesh labels provide reliable and accurate data in harsh RF environments.

• Location: Chuo-ku, Kyoto, Japan
• Management Team: Kazunori Oki (CEO)

mui Lab is a startup that develops and sells the wooden touch panel interface device “mui” and the accompanying UI/UX platform under the philosophy of “mui-shizen” (technology that blends into our daily lives). The company’s strength lies in its patent for a high-definition display on a small piece of natural wood, as well as its unique touch panel technology, which has been highly acclaimed at exhibitions and on crowdfunding. In a world full of smart devices, we can expect more technologies that blend into the environment in many different fields. They are jointly developing consumer products with Wacom and Honeywell and are in talks with smart speaker suppliers and automotive Tier 1.

• Location: Santa Clara, CA, US
• Management Team: Thuc Vu (CEO)

Ohmni Labs is a Silicon Valley startup that provides robots along with total robotics solutions. While there is high demand for robots that can communicate and guide people to tackle the labor shortage, the price of those robots is still too high. Ohmni Labs has libraries of various technologies for robot development. Combining these technologies makes it possible to develop robots quickly and inexpensively. Ohmni Labs has participated in ANA Holdings’ AVATAR project, which aims to integrate multiple exponential technologies ranging from AR/VR, robotics to AI, allowing anyone to teleport their presence to a remote location. At CEATEC 2019, Ohmni Labs and ANA jointly launched a new robot, “newme,” designed specifically for the Japanese market.

• Management Team: Yuya Kikukawa (CEO)

ORPHE (formerly known as no new folk studio) is a company that sells smart shoes called Orphe. Orphe provides smart shoes for entertainment, with LEDs inside the soles that light up, synchronizing with the music. The LEDs are programmable to specifically design for your expression. By taking more advantage of the sensor module, Orphe is now working with ASICS to develop smart shoes for sports and healthcare.

• Management Team: Kevin Li (CEO)

Playdate provides a pet toy that lets you remotely watch over your pets like dogs or cats. The ball-shaped toy has a video camera, a mic, and a speaker inside it. Pet owners can monitor and interact with their pets from their smartphones. Unlike conventional monitoring cameras, Playdate can capture the pets in the full face as it is a toy for them. In addition, Playdate is developing a new service to have vets monitor the pets’ behavior to detect indications of various diseases.

• Management Team: Naren Inukoti (CEO)

Pristeem is a portable cleaning device that can quickly steam clean small amounts of clothing such as shirts and suits. Using a special solvent, it can sterilize and stretch out the wrinkles of a couple of pieces of clothes in about 10 minutes. Pristeem aims to install their devices in apartment buildings and hotels to charge for each cleaning. They have tested in several hotels and offices and are planning to testin apartment buildings soon.

Proteus Motion

• Management Team: Sam Miller (CEO)

Proteus Motion is a startup in NY that develops the world’s first 3D resistance muscle training machine that reduces the training time to 1/3. Because Proteus can create resistance in all directions, various kinds of training can be done with just one of these.

Users can log in to the tablet on the machine to see the recommended personalized training menu as well as their training history. Furthermore, the display shows the posture in real-time, so it can be used for physical rehabilitation or improving form to play sports. The Los Angeles Dodgers and several other teams have already introduced this machine and are highly recognized by MLB baseball players.

The company receives financial support from sports players like the late David Stern, the commissioner of the National Basketball Association, David Winfield, elected to the Hall of Fame in 2001, Christopher Frank Capuano, an American former professional baseball pitcher who is Director of Operations of the MLB, and Dick Boyce, former partner of TPG investment fund and former CEO or chairman of many companies such as J.Crew, Delmonte, Burger King.

• Management Team: Takafumi Yano (CEO)

RUTILEA provides AI visual inspection solutions based on their proprietary, open-source inspection automation software called “SDTest.” The AI market for the manufacturing industry is valued at 1,300 billion yen and is expected to reach around 5,000 billion yen by 2030. Because SDTest is open source, customers can conduct PoC testing free of charge using all the disclosed testing methods and source code. So far, SDTest has been downloaded by more than 400 companies, including major manufacturers such as Toyota and STG.

Sana Health

• Location: Lafayette, CO, US
• Management Team: Richard Hanbury (CEO)

Sana Health is an American startup developing “Sana” that relieves chronic pain and improves mental well-being. Sana is a portable device that provides treatment by audiovisual. It is estimated that 50 million people in the U.S. suffer from chronic pain and 10 million suffer from fibromyalgia. Users would see low pulses of light through the closed eyelids and hear sound pulses through the headphones. It measures the heart rate on the forehead. Using a smartphone app, the user can get personalized treatment depending on the current health condition. Sana Healthaim to get FDA medical device approval by the end of 2021.

• Location: San Diego, CA, US
• Management Team: Mike Flanigan (CEO)

Seasats autonomous ocean vehicles provide remote monitoring and data collection for defense and commercial customers at a fraction of the cost, logistics, and risk compared to traditional methods.

• Location: Kearny, NJ, US
• Management Team: Aleksandar Jovicic (CEO)

Sembient, based near New York City, provides solutions to maximize the efficiency of office usage and sharing resources. Using the proprietary software, users can see and analyze the real-time and accumulated usage data of meeting rooms, offices, and shared computers, collected by the optical sensor attached to the ceiling. Users can acquire detailed analysis of usage data such as, “85% of the time the meeting room was occupied by fewer than 5 people” or “this room was never used by more than 5 people at the same time in the last 2 months.”

• Location: Kamakurashi, Kanagawa, Japan
• Management Team: Ko Kijima(CEO)

An award-winning developer of the world’s smallest IoT/Wearable module, 16Lab Inc., has gathered the best minds across the globe in order to shape a new computer-aided life for the Smart City era through our software that empowers the efficient use of sensors.

SmartShopping

• Location: Shinagawa-ku, Tokyo, Japan
• Management Team: Hidetoshi Hayashi / Takayuki Shiga (CEO)

Smart Shopping provides inventory management and an automatic order placement system with their proprietary IoT scale as well as a commodity price comparison site for businesses and consumers. In Japan’s retail market, which is over 100 trillion yen, daily necessities and food products account for 60% of the total market, and purchases via EC have been increasing in recent years in both BtoB and BtoC. Enterprises can reduce inventory management and purchase costs by simply placing consumables on the “Smart Mat,” which can be used for anything and in any location, without relying solely on purchase history in EC. In addition, as for BtoC, Smart Shopping can provide an integrated customer experience by using the “Smart Mat” as well as the existing functionalities of “Smart Shopping” such as price comparison, shopping agent, and unique catalog. Smart Shopping is applying for patents on the business model in Japan and the US.

Space Power Technologies

• Management Team: Minoru Furukawa (CEO)

Space Power Technologies is a startup for spatial transmission wireless power transfer. As IT devices become smaller and smaller, the number of devices owned continues to grow, and as the number of devices increases, the need to charge them limits economic activity. In this trend, they aim to create a genuinely wireless society with quick decision-making by a group of experts who have been exploring wireless technology.

• Location: Minato-ku, Tokyo, Japan
• Management Team: Akira Takashima (CEO)

TeamS is a startup that develops SSE, embedded software that bidirectionally links smartphones with external displays. Android accounts for about 70% of the smartphones market share. It is expected that the full adoption of 5G after 2022 and the spread of flexible sheet displays will create more demand for SSE. An SSE embedded device would only need minimum components such as image/audio processing, touch panel, communication, and battery.　Two types of mass-production models, sheet OLED and glass OLED, are under development through collaboration. TeamS keeps expanding the range of applications, such as virtual displays on the cloud, as they create the frontiers of the 5G era technologies.

• Management Team: Ken Matsui (CEO)

Ugo, formerly known as Mira Robotics, aims to solve the labor shortage through teleoperated robots. Ugo is targetting building maintenance services such as security, monitoring, cleaning. With their hybrid remote-controlled-autonomy robots, applications and UI/UX for operating and monitoring, and data storage in the cloud, Ugo seeks to create an integrated platform to eventually open up the API plugins to other robotics makers as well.

• Location: Ota-ku, Tokyo, Japan
• Management Team: Yu Kudo (CEO)

Amanogi is a startup company from Tokyo Institute of Technology that provides space cameras for satellites and space data analysis. In the current trend of utilizing big data of earth surface images taken by satellites for 24 hours a day, satellites need to control their attitude when taking photos of the earth’s surface. They are also developing technology to analyze satellite images using deep learning and make it a fundamental technology. They have recently announced a business alliance with I-NET Corporation, which provides system/subsystem design, inspection/testing, operation/evaluation analysis for many satellites.

• Location: Philadelphia, PA
• Management Team: Jon Broome (CEO & Co-Founder)

Vertiq, also known as IQ Motion Control, designs and builds high performance propulsion systems for commercial and defense drone platforms.

Vertiq spun out of the University of Pennsylvania’s robotics lab in 2017 and has since grown to be one of the leaders in the drone propulsion market.

Vertiq makes ultra compact, high performance servo motors for drone propulsion. Combining a unique hardware design (integrated motor, controller, and position sensor) and proprietary motor calibration and control software, Vertiq optimizes motor performance and controllability.

As a result, Vertiq’s products significantly increase the effectiveness of commercial and defense drones. The vehicles using Vertiq technology fly 10% longer, maneuver and stabilize 4x faster, experience 75% fewer critical failures, and have access to unique propeller positioning capabilities.

Vertiq’s mission is to bring high end motor performance to vital robotic applications, starting with drones and in the future, expanding into ground and marine mobile robotic applications.

• Management Team: Jin Nonogami (CEO)

Veldt is a Japanese startup that was ahead of many other companies to enter the growing smartwatches market. It has been producing luxury smartwatches since 2012. As a luxury brand, Veldt received high praise from prominent magazines around the world as “the most exciting smartwatch presented at BASEL WORLD 2016.” and also offer OEM, software licensing, and IoT development for corporate clients. Veldt have developed a platform called “Riiiver” to form a business and capital alliance with Citizen, a major watch manufacturer. The watches are currently sold at some large electronics retailers as luxury smartwatches. Veldt offer luxury and high quality for people who want more than just smart functionalities.

• Location: Uruma-shi, Okinawa, Japan
• Management Team: Yoshifumi Yanase (CEO)

Waqua is an Okinawa-based startup that manufactures small desalination devices under the vision of “delivering safe freshwater to the world.” Waqua has the technology to make small devices optimized for all kinds of water desalination, from pool water to seawater. Their strength is that the device is compact, inexpensive, and processes a relatively large amount of water per unit weight. Potential applications include small offshore fishing boats, coastal areas, remote islands, and construction site with no water supply infrastructure.

※Monozukuri I(Shisaku)は、 MBC Shisaku1号投資事業有限責任組合 ※Monozukuri IIは、 Monozukuri2号投資事業有限責任組合を指します

※Monozukuri I(Shisaku) refers to "MBC Shisaku 1 Limited Partnership." ※Monozukuri II refers to "Monozukuri 2 Limited Partnership."

REAL TIME VC & PRIVATE EQUITY DEALS AND NEWS

Edge Case Research Raises $7M in Funding

Chris Urmson, co-founder and CEO of Aurora, and ANSYS, the global leader in engineering simulation led the round with participation from Lockheed Martin Ventures, Liberty Mutual Strategic Ventures, Trucks VC, and Blue Tree Allied Angels. As a part of the investment, Chris Urmson and Matt Zack, vice president of corporate marketing and business development, ANSYS will join the Edge Case Research Board of Directors.

The company intends to use the funds to expand the development of Hologram.

Led by Mike Wagner, Co-Founder, and CEO, (left) and Prof. Phil Koopman, Co-Founder, and CTO (right), Edge Case Research is making Hologram, an intelligent safety assessment platform for autonomous vehicle software that operates at the speed of modern machine learning development. Hologram automatically finds scenarios in which autonomous vehicles fail to detect pedestrians, vehicles, and other important road users and gives developers the information they need to retrain their algorithms to operate more reliably.

Along with the development of Hologram, the company is partnering with Underwriters Laboratories (UL) to provide leadership for creating the UL 4600 standard for the safety of autonomous products. UL 4600 is expected to be the first comprehensive standard to address the safe deployment of autonomous vehicles and mobile robotic products. It will specifically address ensuring the safety of autonomous products that operate without human intervention based on their current state and sensing of the operating environment. Edge Case acted as the primary subject matter experts for creating the initial draft version. Currently, the Underwriters Laboratories Standard Technical Panel (STP) is revising that draft to produce a consensus-based industry standard, with a planned completion date of late 2019.

The company’s client base spans diverse markets, including automotive, aerospace, defense, consumer electronics, and industrial power systems.

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Squeezing the value out of data for AI

Data is everything — in many respects, it’s the only thing — for autonomous vehicles (AVs) vendors who depend on deep learning as the key to self-driving.

Data is the reason AV companies are racking up miles and miles of testing experience on public roads, recording and stockpiling petabytes of road lore. Waymo, for example, claimed in July more than 10 million miles in the real world and 10 billion miles in simulation.

But here’s yet another question the industry does not like to ask:

Assume that AV companies have already collected petabytes or even exabytes of data on real roads. How much of that dataset has been labeled? Perhaps more important, how accurate is the data that’s been annotated?

In a recent interview with EE Times, Phil Koopman, co-founder and CTO of Edge Case Research, asserted that “nobody can afford to label all of it.”

Data labeling: time-consuming and costly

Annotation typically requires expert human eyes to watch a short video clip, then draw and label boxes around every car, pedestrian, road sign, traffic light, or any other item possibly relevant to an autonomous driving algorithm. The process is not just time-consuming but very costly.

A recent story on Medium entitled “Data Annotation: The Billion Dollar Business Behind AI Breakthroughs” illustrates the rapid emergence of “managed data labeling services” designed to deliver domain-specific labeled data with an emphasis on quality control. The story noted:

In addition to their in-house data labeling crews, tech companies and self-driving startups also rely heavily on these managed labeling services…some self-driving companies are paying data labeling companies upwards of millions of dollars per month.

In another story from IEEE Spectrum a few years ago, Carol Reiley, cofounder and president at Drive.ai was quoted saying:

Thousands of people labeling boxes around things. For every one hour driven, it’s approximately 800 human hours to label. These teams will all struggle. We’re already magnitudes faster, and we’re constantly optimizing.

Some companies, such as Drive, are using deep learning to enhance automation for annotating data, as a way to accelerate the tedious process of data labelling.

Let’s use unlabeled data

Koopman, however, believes there is another way to “squeeze the value out of the accumulated data.” How about accomplishing this “without labeling most of the petabytes of recorded data?”

He explained that Edge Case Research “stumbled into” this, when devising a way to allow the AV industry to speed development of safer perception software. Edge Case Research calls it “Hologram,” which is in essence a “AI perception stress testing and risk analysis system” designed for AVs.

More specifically, as Koopman explained, “Hologram uses unlabeled data,” and the system runs the same unlabeled data twice.

First, it runs baseline unlabeled data on an off-the-shelf, normal perception engine. Then, with the same unlabeled data, Hologram is applied, adding a very slight perturbation — noise. By putting stress on the system, Hologram, as it turns out, can expose potential weakness of the perception in AI algorithms.

If a little grain is added to a video clip, for example, a human might perceive that “there is something there, but I don’t know what it is.”

But an AI-driven perception system, put under stress, can either totally miss an unknown object, or kick it across the threshold and put it into a different classification bin.

When AI is still learning, knowing its confidence level (as it determines what it is seeing) is useful. But when AI is applied in the world, confidence level doesn’t tell us much. AI is often “guessing” or simply “assuming.”

In other words, AI is faking it.

Hologram, by design, can “poke” the AI-driven perception software. It exposes where an AI system failed. For example, a stressed system solves its confusion by mysteriously making an object disappear from the scene.

Perhaps, more interestingly, Hologram can also identify, under noise, where AI “almost failed” but guessed right. Hologram discloses areas in a video clip where the AI-driven system otherwise “could have gone unlucky,” said Koopman.

Without labeling petabytes of data but running it twice, Hologram can provide a heads-up where things look “fishy,” and areas where “you’d better go back and look again” by either collecting more data or doing more training, said Koopman.

This, of course, is a very simplified version of Hologram, because the tool itself, in reality, “comes with a lot of secret sauces backed by a ton of engineering,” Koopman said. But if Hologram can tell users “just the good parts” that merit human review, it can result in a very efficient way to get real value out of currently locked-up data.

“Machines are amazingly good at gaming the system,” noted Koopman. Or “doing things like ‘p-hacking.’” P-hacking is a type of bias that occurs when researchers collect or select data or statistical analyses until non-significant results become significant. Machines, for example, can find correlations within data where none exist.

Open source data set

Asked if this is good news for Edge Case Research, Koopman said, “Unfortunately, these data sets are made available only for the research community. Not for the commercial use.”

Further, even if you use such a data set to run Hologram, you should use the same perception engine used to collect data, to understand areas of weakness in one’s AI system.

Hologram’s screen shot

Below is a screen shot showing how the latest commercial version of Hologram works.

By adding noise, Hologram looks for triggering conditions that made an AI system almost miss a stop sign (orange bars), or completely failed to recognize a stop sign (downward red bars).

Orange bars warn AI designers about specific areas that require AL algorithm retraining, by collecting more data. Red bars allow AI designers to explore and speculate triggering conditions: What caused AI to miss the stop sign? Was the sign too close to a pole? Was there a noisy background or not enough visible contrast? When enough examples of triggering conditions accumulate, it might be possible to identify specific triggers, explained Eben Myers, product manager of Edge Case Research.

Partnership with Ansys

Earlier this week, Ansys announced a partnership agreement with Edge Case Research . Ansys plans to integrate Hologram into its simulation software. Ansys sees the integration as a critical underlying component to design “the industry's first holistic simulation tool chain for developing AVs.” Ansys is collaborating with BMW , which has promised to deliver its first AV in 2021.

— Junko Yoshida, Global Co-Editor-In-Chief, AspenCore Media, Chief International Correspondent, EE Times

>> This article was originally published on our sister site, EE Times: “Use Unlabeled Data to See If AI Is Just Faking It .”

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Is Your Neural Net Confused? What Can You Do?

“Making autonomy safe” is perhaps one of the hardest nuts for designers of AI-based autonomous vehicles to crack.

Assume your self-driving vehicle didn’t hit a mother and a small child crossing the street. This, however, shouldn’t swell your bosom with the confidence that you’re tooling around in the safest vehicle on the road. It only means that you don’t know what exactly your neural networks recognized.

For all we know, the survival of mother and child might be sheer luck. Your AV might have identified the mother, but the neural nets might have been confused about the small object bouncing around on the end of her arm. The sensors might have thought the kid was a Prada bag.

The question becomes: Do you have a tool that can efficiently identify and fix flaws in your neural nets’ algorithms, ensuring that your AV can learn the difference between a toddler and a handbag?

Chris Urmson of Aurora and Ansys to invest in 'Hologram' Edge Case Research, a Pittsburgh-based startup founded by autonomy and safety software experts from Carnegie Mellon University, has developed a safety assessment platform called Hologram to identify ‘edge cases’ in the perception stack.

Edge Case, one of few companies tackling head-on the thorny nexus of safety and autonomy,  got a major boost this week. It secured a $7 million investment led by Chris Urmson, co-founder and CEO of self-driving vehicle startup Aurora, and Ansys, a global leader in engineering simulation for rockets, airplanes and cars.

Others joining in the round include Lockheed Martin Ventures, Liberty Mutual Strategic Ventures, Trucks VC and Blue Tree Allied Angels.

Aurora’s Urmson and Ansys’ vice president Matt Zach both will join the Edge Case Research Board of Directors. Urmson, who previously worked with Alphabet on its self-driving car project, has a background in autonomy. Ansys (Canonsburg, Penn) is known for its prowess in engineering simulation software.

Noting that his firm’s board has snagged the foremost authorities in autonomy and safety fields, Michael Wagner, CEO, Edge Case Research, said, “Our investors completely agree with us that safety of autonomous systems is paramount. We have collected investors who think a lot like what our team thinks.”

Edge Case will use the $7 million infusion– its first round of funding – to expand the development of Hologram. He called Hologram “an emerging tool for the emerging world” in which AI is playing a key role in autonomous systems. While Edge Case’s Hologram software already being tested, the company plans to deploy additional pilot programs, achieve scale, and make Hologram commercially available by the end of 2019, Wagner explained.

Edge Case Research's Hologram desktop. Hologram automatically finds scenarios in which autonomous vehicles fail to detect pedestrians, vehicles, and other important road users. This image shows an example of the kinds of scenarios that Hologram might show a user. The red bounding box on the screen shows where the objects that were not detected. The continuous risk analysis platform helps vehicle developers learn about safety hazards before accidents happen.

(Source: Edge Case Research)

Can you simulate the unknown unknowns? Simulation is widely recognized as a way for autonomous vehicle companies to build up virtual miles to see how their perception software, AI and deep learning algorithms handle situations.

The exception is Tesla. Tesla’s Elon Musk isn’t a big fan of simulations. At Tesla’s Autonomy Day in Palo Alto in April, Musk famously said: “The simulation programs engineers use to run their virtual self-driving cars through millions of ‘edge case’ scenarios to rack up billions of driving miles are good but not good enough.” He added, “We have quite a good simulation, too, but it just does not capture the long tail of weird things that happen in the real world.”

Is Musk wrong?

Edge Case’ Wagner acknowledged Musk’s point, but added that it understates the nuances of simulation.

It could take months or years for fleets of self-driving cars to build up the millions — billions, really — of miles that AV companies will need to demonstrate their systems’ safety. So, simulations are critical, said Wagner, but it’s also true that “simulation won’t be able to tell us all the unknown unknowns,” he said.

More important is the continuous monitoring and analysis of neural network reactions to real-world data, according to Wagner.

Returning to the example of the street-crossing mother and a child, Wagner explained that Hologram determined that a bounding box created by the neural nets around the mother was solid. The box assigned to the small child flickered. By showing the toddler’s box appear and disappear, Hologram helps AV developers grasp the situation’s ambiguities and see that the child is confusing to the AV system.

Wagner does not descibe Hologram as simulation software.  Instead, by leveraging every mile recorded by an AV company, Hologram acts as a tool to analyze how neural networks react to real-world data, he explained.

Today, one could presumably do the same by comparing what neural networks saw with labels assigned to each object. But that would be hard to scale, given the many objects to be labeled and compared to one another. Hologram, in contrast, offers a platform that “intelligently tests perception software against adversarial examples,” Edge Case said. AV companies can use their own sensor data, enabling Hologram to identify risks. Hologram, in essence, gives developers the information they need to retrain their algorithms to operate more reliability.

Where does Hologram run? So, where exactly does Hologram software apply? Presumably, Hologram will be integrated into a data center, said Wagner, to analyze how a given perception software reacts to real-world data. That analysis will be used for future learning.

In the long term, said Wagner, “We want to run Hologram in a camera, or inside a car itself, so that it can capture and detect whatever surprises real time.” That data will be uploaded to the data center once the AV is parked.

UL4600 Along with the development of Hologram, Edge Case is heavily involved with Underwriters Laboratories (UL) to develop the UL 4600 standard for the safety of autonomous products. Wagner said that Edge Case already crafted a 200-page draft, which is now rigorously vetted and discussed by leading industry players and UL in Chicago this week.

UL 4600 is expected to be the first comprehensive standard to address the safe deployment of autonomous vehicles and mobile robotic products.

In a previous interview with EE Times , Phil Koopman, CTO of Edge Case Research, said, “We will go after full autonomy head on.” UL 4600’s authors intend to specifically cover validation of any machine learning based functionality and other autonomy functions used in life-critical applications.

The Underwriters Laboratories Standard Technical Panel (STP) will revise the draft to produce a consensus-based industry standard, with a planned completion date of late 2019.

— Junko Yoshida, Global Co-Editor-In-Chief, AspenCore Media, Chief International Correspondent, EE Times

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My sense is, some of this is being overstated. A simple example. If a human driver sees an object, just about any object, whether he can recognize it or not, that sits, say, more than a few inches above street level, the human driver will do his level best to avoid it. Including slowing down and stopping. At night especially, you don't even expect to identify the exact nature of an object in your path. You avoid them specifically because they will most likely cause damage, no matter what they are.

Even if the object looks like a smallish cardboard box, it could be filled with cement, or nails. Or, there could be a baby inside, for that matter.

So I don't think we need to obsess too much about identifying the obstacles exactly. Human drivers don't. Instead, human drivers learn to avoid largish obstacles completely. Stationary, or moving targets, which we mantally calculate will be coming in our path.

Safety of autonomous vehicles, much like safe operation of manually piloted vehicles, depends more on making sure that the vehicle has time to take evasive action, when an unexpected obstacle appears, than it does to identify the obstacle. And here, AVs should easily beat manually driven vehicles. AVs should have better night vision, better peripheral vision, better concentration on just detecting obstacles (rather than time-sharing with texting or yelling at the kids), better calculation of trajectories, no incoherent panic reactions, and shorter reaction times.

The difference will be made by the car's ability to anticipate. If the car is strictly reactive, a human driver assisted by ADAS will be much safer.

Hi, Bert22306. Thanks for chiming in. I think the issue here is not so much whether AI recognizes the difference between a toddler and a bag (although that's what I wrote in the story). But it is more about AV designers' desire to efficiently identify and fix flaws in their neural nets' algorithms. The platform like Hologram presumably can expose the weakness of one's neural nets and create an opportunity to retrain the algorithms.

The challenge for AI is figuring out what to do with situations it has not seen before. How to deal with the baby / purse example should be simple -- don't hit either.

But what if the thing being held is indeed a child, and the parent tries to save the child by throwing the child to one side (there is simply no way of anticipating what people will do when they panic). The car, believing the item to be a purse, goes for the purse.

It's true that a human driver might not be able to react any better than an AV. It should be a reasonable assumption that an AV will react at least as well as a human, and there's at least some chance that it will get it (baby or purse?) right.

We unquestionably will get to the point where we assume an AV will react better than a human. Which means we will get less and less tolerant of this kind of ambiguity in AIs.

Identifying the child is much easier than anticipating what the parent and child will do or even anticipating that it might encounter the parent+child while factoring in many other variables that might impact the situation. The value is not in object recognition, that should be regarded as trivial and even a smartphone's camera should be able to do that and auto adjust settings. The value is in complex situational awareness that at least matches humans, you can't beat human+ADAS without it The system has to be better without human supervision than with supervision or it's just Level 2. Not being able to identify a child is the equivalent of a legally blind human but not being blind is not what makes a good driver.

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Study Suggests Genetics as a Cause, Not Just a Risk, for Some Alzheimer’s

People with two copies of the gene variant APOE4 are almost certain to get Alzheimer’s, say researchers, who proposed a framework under which such patients could be diagnosed years before symptoms.

By Pam Belluck

Scientists are proposing a new way of understanding the genetics of Alzheimer’s that would mean that up to a fifth of patients would be considered to have a genetically caused form of the disease.

Currently, the vast majority of Alzheimer’s cases do not have a clearly identified cause. The new designation, proposed in a study published Monday, could broaden the scope of efforts to develop treatments, including gene therapy, and affect the design of clinical trials.

It could also mean that hundreds of thousands of people in the United States alone could, if they chose, receive a diagnosis of Alzheimer’s before developing any symptoms of cognitive decline, although there currently are no treatments for people at that stage.

The new classification would make this type of Alzheimer’s one of the most common genetic disorders in the world, medical experts said.

“This reconceptualization that we’re proposing affects not a small minority of people,” said Dr. Juan Fortea, an author of the study and the director of the Sant Pau Memory Unit in Barcelona, Spain. “Sometimes we say that we don’t know the cause of Alzheimer’s disease,” but, he said, this would mean that about 15 to 20 percent of cases “can be tracked back to a cause, and the cause is in the genes.”

The idea involves a gene variant called APOE4. Scientists have long known that inheriting one copy of the variant increases the risk of developing Alzheimer’s, and that people with two copies, inherited from each parent, have vastly increased risk.

The new study , published in the journal Nature Medicine, analyzed data from over 500 people with two copies of APOE4, a significantly larger pool than in previous studies. The researchers found that almost all of those patients developed the biological pathology of Alzheimer’s, and the authors say that two copies of APOE4 should now be considered a cause of Alzheimer’s — not simply a risk factor.

The patients also developed Alzheimer’s pathology relatively young, the study found. By age 55, over 95 percent had biological markers associated with the disease. By 65, almost all had abnormal levels of a protein called amyloid that forms plaques in the brain, a hallmark of Alzheimer’s. And many started developing symptoms of cognitive decline at age 65, younger than most people without the APOE4 variant.

“The critical thing is that these individuals are often symptomatic 10 years earlier than other forms of Alzheimer’s disease,” said Dr. Reisa Sperling, a neurologist at Mass General Brigham in Boston and an author of the study.

She added, “By the time they are picked up and clinically diagnosed, because they’re often younger, they have more pathology.”

People with two copies, known as APOE4 homozygotes, make up 2 to 3 percent of the general population, but are an estimated 15 to 20 percent of people with Alzheimer’s dementia, experts said. People with one copy make up about 15 to 25 percent of the general population, and about 50 percent of Alzheimer’s dementia patients.

The most common variant is called APOE3, which seems to have a neutral effect on Alzheimer’s risk. About 75 percent of the general population has one copy of APOE3, and more than half of the general population has two copies.

Alzheimer’s experts not involved in the study said classifying the two-copy condition as genetically determined Alzheimer’s could have significant implications, including encouraging drug development beyond the field’s recent major focus on treatments that target and reduce amyloid.

Dr. Samuel Gandy, an Alzheimer’s researcher at Mount Sinai in New York, who was not involved in the study, said that patients with two copies of APOE4 faced much higher safety risks from anti-amyloid drugs.

When the Food and Drug Administration approved the anti-amyloid drug Leqembi last year, it required a black-box warning on the label saying that the medication can cause “serious and life-threatening events” such as swelling and bleeding in the brain, especially for people with two copies of APOE4. Some treatment centers decided not to offer Leqembi, an intravenous infusion, to such patients.

Dr. Gandy and other experts said that classifying these patients as having a distinct genetic form of Alzheimer’s would galvanize interest in developing drugs that are safe and effective for them and add urgency to current efforts to prevent cognitive decline in people who do not yet have symptoms.

“Rather than say we have nothing for you, let’s look for a trial,” Dr. Gandy said, adding that such patients should be included in trials at younger ages, given how early their pathology starts.

Besides trying to develop drugs, some researchers are exploring gene editing to transform APOE4 into a variant called APOE2, which appears to protect against Alzheimer’s. Another gene-therapy approach being studied involves injecting APOE2 into patients’ brains.

The new study had some limitations, including a lack of diversity that might make the findings less generalizable. Most patients in the study had European ancestry. While two copies of APOE4 also greatly increase Alzheimer’s risk in other ethnicities, the risk levels differ, said Dr. Michael Greicius, a neurologist at Stanford University School of Medicine who was not involved in the research.

“One important argument against their interpretation is that the risk of Alzheimer’s disease in APOE4 homozygotes varies substantially across different genetic ancestries,” said Dr. Greicius, who cowrote a study that found that white people with two copies of APOE4 had 13 times the risk of white people with two copies of APOE3, while Black people with two copies of APOE4 had 6.5 times the risk of Black people with two copies of APOE3.

“This has critical implications when counseling patients about their ancestry-informed genetic risk for Alzheimer’s disease,” he said, “and it also speaks to some yet-to-be-discovered genetics and biology that presumably drive this massive difference in risk.”

Under the current genetic understanding of Alzheimer’s, less than 2 percent of cases are considered genetically caused. Some of those patients inherited a mutation in one of three genes and can develop symptoms as early as their 30s or 40s. Others are people with Down syndrome, who have three copies of a chromosome containing a protein that often leads to what is called Down syndrome-associated Alzheimer’s disease .

Dr. Sperling said the genetic alterations in those cases are believed to fuel buildup of amyloid, while APOE4 is believed to interfere with clearing amyloid buildup.

Under the researchers’ proposal, having one copy of APOE4 would continue to be considered a risk factor, not enough to cause Alzheimer’s, Dr. Fortea said. It is unusual for diseases to follow that genetic pattern, called “semidominance,” with two copies of a variant causing the disease, but one copy only increasing risk, experts said.

The new recommendation will prompt questions about whether people should get tested to determine if they have the APOE4 variant.

Dr. Greicius said that until there were treatments for people with two copies of APOE4 or trials of therapies to prevent them from developing dementia, “My recommendation is if you don’t have symptoms, you should definitely not figure out your APOE status.”

He added, “It will only cause grief at this point.”

Finding ways to help these patients cannot come soon enough, Dr. Sperling said, adding, “These individuals are desperate, they’ve seen it in both of their parents often and really need therapies.”

Pam Belluck is a health and science reporter, covering a range of subjects, including reproductive health, long Covid, brain science, neurological disorders, mental health and genetics. More about Pam Belluck

The Fight Against Alzheimer’s Disease

Alzheimer’s is the most common form of dementia, but much remains unknown about this daunting disease..

How is Alzheimer’s diagnosed? What causes Alzheimer’s? We answered some common questions .

A study suggests that genetics can be a cause of Alzheimer’s , not just a risk, raising the prospect of diagnosis years before symptoms appear.

Determining whether someone has Alzheimer’s usually requires an extended diagnostic process . But new criteria could lead to a diagnosis on the basis of a simple blood test .

The F.D.A. has given full approval to the Alzheimer’s drug Leqembi. Here is what to know about i t.

Alzheimer’s can make communicating difficult. We asked experts for tips on how to talk to someone with the disease .

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Humanity is on the edge of self-destruction in 2024, according to these scientists

Posted: May 16, 2024 | Last updated: May 16, 2024

The Doomsday Clock continues to inch closer to the apocalypse over climate change and fears of nuclear war. The year 2024 has brought yet another dire warning issued by the Bulletin of the Atomic Scientists. But what is the Doomsday Clock, and how is it read?

To summarize, the clock was developed by scientists in 1947 to track the likelihood of mankind doing something that brings about the end of the world. The development of nuclear weapons and the rapid progression of climate change are two things that have moved the clock's hand closer to midnight, which in this case, marks Armageddon. After the end of the Cold War, the clock was 17 minutes away from midnight, but in recent years, we've gone from counting down the minutes to counting down the seconds. In 2024, the Bulletin left the clock at the same position as last year—90 seconds to midnight.

"Conflict hot spots around the world carry the threat of nuclear escalation, climate change is already causing death and destruction, and disruptive technologies like AI and biological research advance faster than their safeguards," Rachel Bronson, the Bulletin's president and CEO, told Reuters. She clarified that leaving the clock unchanged is "not an indication that the world is stable," considering how disastrously close we already are to midnight. 

Click through the gallery to learn more about the Doomsday Clock and how we've come so close to the end of the world. 

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Clock of catastrophe

The Doomsday Clock is a symbol that represents the likelihood of a man-made global catastrophe.

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Bulletin of the Atomic Scientists

It's been maintained since 1947 by the members of the Bulletin of the Atomic Scientists ,  itself founded in 1945 by Albert Einstein and University of Chicago scientists who helped develop the first atomic weapons in the Manhattan Project.

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A metaphor for threats

The clock serves as a metaphor for hazards to our world from unchecked scientific and technical advances using the imagery of apocalypse (midnight) and the contemporary idiom of nuclear explosion (countdown to zero) to convey threats to humanity and the planet.

Who sets the Doomsday Clock?

The clock is set every year by the Bulletin's Science and Security Board. It's original setting in 1947 was seven minutes to midnight. Since then its timeline has been adjusted to reflect the perceived threat from nuclear weapons, climate change, and disruptive technologies in other domains. To turn the clock back is to revisit some of the most frightening and potentially catastrophic episodes in the history of humanity.

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1949: 3 minutes to midnight (23h57)

On August 29, 1949, the Soviet Union carried out its first nuclear test, detonating an atomic bomb, the RDS-1, thus officially starting the nuclear arms race.

1953: 2 minutes to midnight (23h58)

The United States tests its first thermonuclear device, in November 1952 at Eniwetok Atoll in the Pacific Proving Ground in the Marshall Islands, as part of Operation Ivy. The USSR responds with a similar test in August 1953. This remained the clock's closest approach to midnight (tied in 2018) until 2020.

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1960: 7 minutes to midnight (23h53)

Despite a series of regional conflicts including the Suez Crisis of 1956 (pictured), the 1958 Second Taiwan Strait Crisis, and the 1958 Lebanon crisis, the clock is put back five minutes in 1960 due in part to increased scientific cooperation and public understanding of the dangers of nuclear weapons.

1963: 12 minutes to midnight (23h48)

The Partial Test Ban Treaty signed by the governments of the Soviet Union, the United Kingdom, and the United States in Moscow on August 5, 1963 set the clock back to 23h48.

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1968: 7 minutes to midnight (23h53)

The clock edges towards midnight again as involvement of the United States in the Vietnam War intensifies. The Indo-Pakistani War of 1965 and the Six-Day War in 1967 are also determining factors. Meanwhile, France and China join the nuclear arms race.

1969: 10 minutes to midnight (23h50)

Every nation in the world, with the notable exceptions of India, Israel, and Pakistan, signs the Nuclear Non-Proliferation Treaty. The treaty was negotiated by the Eighteen Nation Committee on Disarmament, a United Nations-sponsored organization based in Geneva, Switzerland. It was signed on July 1, 1968 and became effective on March 5, 1970.

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1972: 12 minutes to midnight (23h48)

A wave of renewed optimism sweeps the world as the United States and the Soviet Union sign the first Strategic Arms Limitation Treaty (SALT I) and the Anti-Ballistic Missile (ABM) Treaty. The clock drops back 120 seconds to 12 minutes before midnight as Richard Nixon and Leonid Brezhnev close the deal in Moscow.

1974: 9 minutes to midnight (23h51)

India's testing of a nuclear device and the stalling of the vital SALT II talks edges the clock forward. Pictured: a crater marks the site of the first Indian underground nuclear test conducted on May 18, 1974 at Pokhran in the desert state of Rajasthan.

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1980: 7 minutes to midnight (23h53)

The Soviet Union's invasion of Afghanistan in December 1979 sees the US Senate refuse to ratify the SALT II agreement.

1981: 4 minutes to midnight (23h56)

The world is in turmoil: rising tensions between the United States and the Soviet Union contribute to the danger of nuclear annihilation; the US pulls out of the 1980 Olympic Summer Games; the Iran hostage crisis (pictured) makes world headlines; the Iran-Iraq conflict continues; martial law is declared in Poland; apartheid in South Africa achieves new levels of brutality; and widespread human rights violations are witnessed around the globe.

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1984: 3 minutes to midnight (23h57)

Further escalation of the tensions between the United States and the Soviet Union are exemplified with the deployment in Western Europe of Pershing II medium-range ballistic missile and cruise missiles. Meanwhile, the ongoing Soviet–Afghan War only serves to intensify the Cold War. And the Soviet Union announce a boycott of the 1984 Summer Olympic Games in Los Angeles. Pictured is a banner that reads "Refuse Cruise" seen at a demonstration by the Campaign for Nuclear Disarmament (CND) against the hosting by the UK of US nuclear cruise missiles on British soil.

1988: 6 minutes to midnight (23h54)

A thaw in the Cold War sees the clock gain three minutes as Ronald Reagan and Mikhail Gorbachev sign the Intermediate-Range Nuclear Forces Treaty in Washington, D.C. on December 8, 1987, effective June 1, 1988.

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1990: 10 minutes to midnight (23h50)

The fall of the Berlin Wall on November 1990 and the Iron Curtain, along with the reunification of Germany, sees the beginning of the end of the Cold War.

1991: 17 minutes from midnight (23h43)

The dissolution of the Soviet Union on December 26, 1991 sees the hands of the Doomsday Clock set back 420 seconds to 17 minutes—to date the farthest from midnight the Doomsday Clock has been since its inception.  

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1995: 14 minutes to midnight (23h46)

Concerns mount over post-Soviet Union nuclear proliferation of weapons and brainpower. At the same time, and despite the signing of various treaties, global military spending continues at Cold War levels.

1998: 9 minutes from midnight (23h51)

Both India and Pakistan detonate nuclear weapons in underground tests: Pakistan's Chagai-I project takes place at Ras Koh Hills, while the remote Thar Desert region (pictured) serves as the location for India's Pokhran-II series of detonations.

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2002: 7 minutes from midnight (23h53)

The global nuclear disarmament initiative loses momentum and the United States, concerned about the possibility of a nuclear terrorist attack due to the amount of weapon-grade nuclear materials that are unsecured and unaccounted for worldwide, rejects a series of rams controls and treaties.

2007: 5 minutes to midnight (23h55)

The clock edges forward after North Korea tests a nuclear weapon in 2006. At the same time, Iran's nuclear ambitions become cause for concern. And in a sign of the times, after assessing the dangers posed to civilization, climate change is added to the prospect of nuclear annihilation as the greatest threats to humanity.

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2010: 6 minutes to midnight (23h54)

The Clock edges back 60 seconds after the 2009 United Nations Climate Change Conference in Copenhagen results in the developing and industrialized countries agreeing to take responsibility for carbon emissions and to limit global temperature rise to 2°C (35.6°F).

2012: 5 minutes to midnight (23h55)

The lack of global political will to address urgent global climate change issues nudges the clock another minute towards midnight. Of equal concern are nuclear weapons stockpiles, the potential for regional nuclear conflict, and nuclear power safety.

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2015: 3 minutes to midnight (23h57)

The apparent inability of governments around the world to tackle global climate change, plus the modernization of nuclear weapons in the United States and Russia, and the problem of nuclear waste, takes another 120 seconds off the clock.

2017: 2.5 minutes to midnight (23h57.30)

US President Donald Trump's alarmist rhetoric over nuclear weapons, the threat of a renewed arms race between the US and Russia, and his administration's refusal to accept scientific consensus over climate change, is enough to shave off another 90 seconds.

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2018: 2 minutes to midnight (23h58)

The clock matches its 1958 2-minute warning after the US withdraws from the 2015 Paris Agreement.

2019: 2 minutes to midnight (23h58)

In 2019, the Doomsday Clock remained at 2 minutes to midnight due to unresolved issues involving climate change and because of the threat posed by information warfare such as misuse of AI and synthetic biology, and cyberwarfare.

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2020: 100 seconds to midnight (23h58.2)

In 2020, the unit of time was announced in seconds (100) to emphasize "the most dangerous situation that humanity has ever faced," according to the Bulletin of the Atomic Scientists.

2021/2022: 100 seconds to midnight

In 2021 and 2022, the Bulletin reaffirmed the "100 seconds to midnight" time setting, reiterating the failure of world leaders to deal with the increased threats of nuclear war along with the continued neglect of climate change.

2023: 90 seconds to midnight (23h58.5)

In 2023, the clock was moved 10 seconds closer to midnight, leaving us just 90 seconds away from doomsday. This was in response to Russia's attack on Ukraine and the imminent threat of nuclear war. “We are sending a message that the situation is becoming more urgent,” said Rachel Bronson, President of the Bulletin of Atomic Scientists. "Crises are more likely to happen and have broader consequences and longer standing effects.” Other threats to humanity mentioned included "nuclear weapon proliferation in China, Iran increasing its uranium enrichment, missile tests in North Korea, future pandemics from animal diseases, pathogens from lab mistakes, “disruptive technologies,” and worsening climate change."

Sources: (BBC) (Bulletin of the Atomic Scientists) (CTBTO)

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Biology and management of wild lupine ( Lupinus perennis L.): a case study for conserving rare plants in edge habitat

• Published: 05 December 2023
• Volume 225 , pages 373–389, ( 2024 )

Cite this article

• Isabella R. Petitta 1 ,
• Margarita M. López-Uribe 1 , 2 &
• Autumn E. Sabo 1 , 3  

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Wild lupine ( Lupinus perennis ) is a perennial plant originally found primarily throughout the United States and Canada in oak savannas, which are considered an ecotone between prairie and forest. Because of primary habitat loss, this early successional plant is declining and now persists in managed edge habitats such as power line rights-of-way and roadsides across much of its range. Many edge populations of wild lupine are small and isolated, which can hinder the reproduction of this pollinator-dependent plant. Here, we synthesize current literature about the biology and management of wild lupine and associated plants and insects. We also highlight current gaps of knowledge to guide future research on wild lupine and, more generally, on savanna-like habitats. The information provided here on lupine serves as a case study for how edge habitat conserves rare plant species reliant on disturbance. Overall, habitat characteristics that seem best for wild lupine include a gradient of canopy cover from moderate to open, well-drained soils, and a low abundance of understory woody plants. Land management, including prescribed burning, mowing, and mechanical thinning, can promote the conservation of wild lupine and other forest edge plants. However, additional research in regards to ideal management regimes and intensity is needed to further plant conservation in forest edge habitat.

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Acknowledgements

We thank Kelly Sitch, Andrew Rohrbaugh, Neil Gifford, Pat McElhenny, Brian Williamson, and Roy Brubaker for their land management insights. We also thank Claire Zimmerman of Mt. Cuba Center for information about wild lupine propagation. Thank you to Grace Gutierrez and Nash Turley for guidance on figure development. Finally, we thank editor, Dr. Karen Harper, and two anonymous reviewers for their comments on our manuscript.

This work was supported by the USDA National Institute of Food and Agriculture and McIntire-Stennis Appropriations under Project #PEN04785 and Accession #1027694 and the Pennsylvania’s Department of Conservation and Natural Resources’s Wild Resources Conservation Program Grant No. 21637. IRP was supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. DGE1255832. MMLU was supported by the USDA NIFA Appropriations Projects PEN04716 and PEN04620.

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IRP, MMLU, and AES conceived the paper. MMLU and AES secured funding. IRP developed the first draft, figures, table, and compiled literature. All authors revised and approved the final manuscript.

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Petitta, I.R., López-Uribe, M.M. & Sabo, A.E. Biology and management of wild lupine ( Lupinus perennis L.): a case study for conserving rare plants in edge habitat. Plant Ecol 225 , 373–389 (2024). https://doi.org/10.1007/s11258-023-01371-9

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Received : 01 June 2023

Accepted : 21 October 2023

Published : 05 December 2023

Issue Date : April 2024

DOI : https://doi.org/10.1007/s11258-023-01371-9

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Case report: Diagnosis and Surgical Treatment of Delayed Traumatic Diaphragmatic Hernia with Hepatothorax and Enterothorax in a Small Dog Provisionally Accepted

• 1 College of Veterinary Medicine, Northeast Agricultural University, China
• 2 Heilongjiang Key Laboratory for Zoonosis, College of Veterinary Medicine, Northeast Agricultural University, China
• 3 Sichuan Provincial Key Laboratory of Quality and Innovation Research of Chinese Materia Medica, Sichuan Academy of Chinese Medicine Sciences, China

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An 8-year-old castrated male teddy bear dog presented to our clinic with a persistent cough. The sick dog suffered from vehicular trauma six months prior to the visit and had imaging and exploratory laparotomy. Imaging and exploratory laparotomy at the time showed no significant damage. We performed contrast radiography (barium gavage) on the sick dog. Based on the results of a complete contrast radiography (barium gavage), tubular shadows in the thoracic cavity were identified as the small intestine and cecum, and delayed traumatic diaphragmatic hernia with hepatothorax and enterothorax was confirmed with radiographs. Accordingly, the sick dog underwent general anesthesia, manual ventilation and diaphragmatic herniorrhaphy by standard ventral midline abdominal approach. Postoperatively, the dog were given analgesia and antibacterial treatment, and the liver biochemical indexes were monitored to prevent endotoxin. Postoperative radiographs revealed clear contours of thoracic and abdominal organs. The dog moved, ate, and urinated normally within 10 days of the surgery. This case provides a reference for a complete barium meal imaging procedure that clearly shows the position of the organs in the thoracoabdominal cavity after the occurrence of a delayed traumatic diaphragmatic hernia. This paper provides a practical reference for the diagnosis of delayed traumatic diaphragmatic hernia with hepatothorax and enterothorax.

Keywords: dog, Delayed diaphragmatic hernia, x-ray, Ultrasound examination, case report

Received: 18 Dec 2023; Accepted: 16 May 2024.

Copyright: © 2024 Shao, Liu, Tai, Liu, Han, Yang, Fei, Wang, Wang, Chen and Shi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Dr. Tiezhu Chen, Sichuan Provincial Key Laboratory of Quality and Innovation Research of Chinese Materia Medica, Sichuan Academy of Chinese Medicine Sciences, Chengdu, Sichuan Province, China Dr. Guangliang Shi, College of Veterinary Medicine, Northeast Agricultural University, Harbin, 150038, Heilongjiang Province, China

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