Partial differential equations (PDEs) are instrumental for modeling dynamical systems in science and engineering. The advent of neural networks has initiated a significant shift in tackling these complexities though challenges in accuracy persist, especially for initial value problems. In this paper, we introduce the $\textit{Time-Evolving Natural Gradient (TENG)}$, generalizing time-dependent variational principles and optimization-based time integration, leveraging natural gradient optimization to obtain high accuracy in neural-network-based PDE solutions. Our comprehensive development includes algorithms like TENG-Euler and its high-order variants, such as TENG-Heun, tailored for enhanced precision and efficiency. TENG's effectiveness is further validated through its performance, surpassing current leading methods and achieving $\textit{machine precision}$ in step-by-step optimizations across a spectrum of PDEs, including the heat equation, Allen-Cahn equation, and Burgers' equation.

One critical bottleneck that impedes the development and deployment of autonomous transportation in open-pit mines is guaranteed robustness and trustworthiness in prohibitively extreme scenarios. In this research, a novel scenarios engineering (SE) methodology for the autonomous mining truck is proposed for open-pit mines. SE increases the trustworthiness and robustness of autonomous trucks from four key components: Scenario Feature Extractor, Intelligence & Index (I&I), Calibration & Certification (C&C), and Verification & Validation (V&V). Scenario feature extractor is a comprehensive pipeline approach that captures complex interactions and latent dependencies in complex mining scenarios. I&I effectively enhances the quality of the training dataset, thereby establishing a solid foundation for autonomous transportation in mining areas. C&C is grounded in the intrinsic regulation, capabilities, and contributions of the intelligent systems employed in autonomous transportation to align with traffic participants in the real world and ensure their performance through certification. V&V process ensures that the autonomous transportation system can be correctly implemented, while validation focuses on evaluating the ability of the well-trained model to operate efficiently in the complex and dynamic conditions of the open-pit mines. This methodology addresses the unique challenges of autonomous transportation in open-pit mining, promoting productivity, safety, and performance in mining operations.

In the era of Internet of Things, how to develop a smart sensor system with sustainable power supply, easy deployment and flexible use has become a difficult problem to be solved. The traditional power supply has problems such as frequent replacement or charging when in use, which limits the development of wearable devices. The contact-to-separate friction nanogenerator (TENG) was prepared by using polychotomy thy lene (PTFE) and aluminum (AI) foils. Human motion energy was collected by human body arrangement, and human motion posture was monitored according to the changes of output electrical signals. In 2012, Academician Wang Zhong lin and his team invented the triboelectric nanogenerator (TENG), which uses Maxwell displacement current as a driving force to directly convert mechanical stimuli into electrical signals, so it can be used as a self-driven sensor. Teng-based sensors have the advantages of simple structure and high instantaneous power density, which provides an important means for building intelligent sensor systems. At the same time, machine learning, as a technology with low cost, short development cycle, strong data processing ability and prediction ability, has a significant effect on the processing of a large number of electrical signals generated by TENG, and the combination with TENG sensors will promote the rapid development of intelligent sensor networks in the future. Therefore, this paper is based on the intelligent sound monitoring and recognition system of TENG, which has good sound recognition capability, and aims to evaluate the feasibility of the sound perception module architecture in ubiquitous sensor networks.

High-resolution radar and night vision cameras may help scientists protect bats from untimely deaths at wind farms, according to new research. Researchers are using these technologies to provide more specific details about the number of bats killed by wind turbines in Iowa. These details will improve scientists' understanding of bat activity and potentially save their lives, said Jian Teng, a graduate researcher at the University of Iowa who presented the work this week at the 2019 American Geophysical Union Fall Meeting in San Francisco. This work has broad impacts, according to Teng. "The more bats you kill, the more insects you have on farms; then, farmers will put more pesticides; and then, people will eat more pesticides," he said.

High-resolution radar and night vision cameras may help scientists protect bats from untimely deaths at wind farms, according to new research. Researchers are using these technologies to provide more specific details about the number of bats killed by wind turbines in Iowa. These details will improve scientists' understanding of bat activity and potentially save their lives, said Jing Teng, a graduate researcher at the University of Iowa who presented the work this week at the 2019 American Geophysical Union Fall Meeting in San Francisco. This work has broad impacts, according to Teng. "The more bats you kill, the more insects you have on farms; then, farmers will put more pesticides; and then, people will eat more pesticides," he said.

Facial recognition technology is likely to be among innovations on the agenda when bankers, financial regulators and officials from across Asia gather in Hong Kong on Wednesday for a landmark summit. The high-powered meeting comes as the race to regulate the fintech (financial technology) revolution is intensifying amid fears that a regulatory "vacuum" could be exploited by money launderers, fraudsters and underground bankers whose activities threaten national, regional and international financial stability. Organisers of the summit to launch the Alliance for Financial Stability with Information Technology, also known as AFS-IT, say speakers and guests will include top-level representation across the banking, financial, technology and regulatory sectors as well as government officials from China, Hong Kong, Macau, the Philippines, Thailand, Cambodia, Myanmar, Vietnam and Singapore. A key focus will be the fostering of innovation in regulation technology, or regtech, a new field in which information technology is used to enhance regulation. Innovative fintech can be used and adapted to benefit both service providers and regulators, and it includes know-your-customer facial recognition technology recently installed across the ATM network of casino hub Macau as part of an ongoing crackdown on money laundering and capital flight from China.

Summary: For your holiday reading we present this selection of robot and AI fails. We hope this brings you hope and cheer for the coming year to know that our robot overlords are not as close as some think. For your holiday reading we present this selection of robot and AI fails. We hope this brings you hope and cheer for the coming year to know that our robot overlords are not as close as some think. Alas, it seems we've got a few more years before the robots take over.

Ji\v{r}\'i Matou\v{s}ek (1963-2015) had many breakthrough contributions in mathematics and algorithm design. His milestone results are not only profound but also elegant. By going beyond the original objects --- such as Euclidean spaces or linear programs --- Jirka found the essence of the challenging mathematical/algorithmic problems as well as beautiful solutions that were natural to him, but were surprising discoveries to the field. In this short exploration article, I will first share with readers my initial encounter with Jirka and discuss one of his fundamental geometric results from the early 1990s. In the age of social and information networks, I will then turn the discussion from geometric structures to network structures, attempting to take a humble step towards the holy grail of network science, that is to understand the network essence that underlies the observed sparse-and-multifaceted network data. I will discuss a simple result which summarizes some basic algebraic properties of personalized PageRank matrices. Unlike the traditional transitive closure of binary relations, the personalized PageRank matrices take "accumulated Markovian closure" of network data. Some of these algebraic properties are known in various contexts. But I hope featuring them together in a broader context will help to illustrate the desirable properties of this Markovian completion of networks, and motivate systematic developments of a network theory for understanding vast and ubiquitous multifaceted network data.

A security company has apologized for a "freakish accident" after its crime-fighting robot hit a 16-month-old boy on the head and ran over him at a shopping mall in Palo Alto. Knightscope Inc. said attempts to reach the family haven't been successful, but the company invited them to its headquarters in Mountain View, Calif., to prevent similar incidents from happening. "Our first thoughts are for the family, and we are thankful that there were no serious injuries," said William Santana Li, the company's chairman and chief executive officer. "Our primary mission is to serve the public's overall safety, and we take any circumstances that would compromise that mission very seriously." The company said the child ran toward the robot, which veered to avoid him as it was patrolling, and the toddler then ran backward and directly into the robot.

A mall in Silicon Valley this week suspended its security robots after a collision involving one of them resulted in a toddler getting a bruised leg--a reversal from children harassing robots at the mall. The accident could reignite fears about evil robots that many robot makers have tried to overcome with cute designs. The robot company, Knightscope Inc., designed its 300-pound machine to protect against malicious humans. Children usually present the greatest risk to robots' ability to get their jobs done, previous incidents showed. Knightscope was the subject of a Wall Street Journal page one article last month.