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关键词： Capital punishment   Death sentence   Mental damage   State compensation   Wrongful conviction   Wrongful execution  

摘要： In 1994, China passed its first State Compensation Law (SCL) for wrongfully convicted individuals who can file claims for loss of life or freedom, physical injury, and property loss due to illegal state actions in administrative and criminal cases. The 2010 amended SCL added mental damage compensation and mandated and prioritized a negotiation procedure. The current study used 144 capital exonerees to examine whether and how state compensation was claimed by and/or awarded to these exonerees in China. Our analyses revealed that almost all of the state compensation claims received compensation, and the amount claimed and the amount awarded had increased exponentially over time. In addition, after mental damage compensation was permitted in 2010, capital exonerees had successfully obtained such awards. However, despite of the increased compensation amounts over the years, the winning rates across almost all categories (e.g., mental damage, life/physical injury claims) decreased over time, and the standard of national daily average salary played a more important role on the increased amounts claimed and awarded than the SCL based on results of multivariate analyses. Policy recommendations were discussed to help improve the state compensation system in China.

关键词： Diagram understanding   topology   Computer Science  

摘要： Diagram is a special form of visual expression for representing complex concepts, logic, and knowledge, which widely appears in educational scenes such as textbooks, blogs, and encyclopedias. Current research on diagrams preliminarily focuses on natural disciplines such as Biology and Geography, whose expressions are still similar to natural images. In this article, we construct the first novel geometric type of diagrams dataset in Computer Science field, which has more abstract expressions and complex logical relations. The dataset has exhaustive annotations of objects and relations for about 1,300 diagrams and 3,500 question-answer pairs. We introduce the tasks of diagram classification (DC) and diagram question answering (DQA) based on the new dataset, and propose the Diagram Paring Net (DPN) that focuses on analyzing the topological structure and text information of diagrams. We use DPN-based models to solve DC and DQA tasks, and compare the performances to well-known natural images classification models and visual question answering models. Our experiments show the effectiveness of the proposed DPN-based models on diagram understanding tasks, also indicate that our dataset is more complex compared to previous natural image understanding datasets. The presented dataset opens new challenges for research in diagram understanding, and the DPN method provides a novel perspective for studying such data. Our dataset can be available from https://***/ WayneWong97/CSDia.

关键词： Computational methods   Atomistic models   Method development   Computer science   Scientific data  

摘要： Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials. Graph neural networks (GNNs) are one of the fastest growing classes of machine learning models. They are of particular relevance for chemistry and materials science, as they directly work on a graph or structural representation of molecules and materials and therefore have full access to all relevant information required to characterize materials. In this Review, we provide an overview of the basic principles of GNNs, widely used datasets, and state-of-the-art architectures, followed by a discussion of a wide range of recent applications of GNNs in chemistry and materials science, and concluding with a road-map for the further development and application of GNNs. Graph neural networks are machine learning models that directly access the structural representation of molecules and materials. This Review discusses state-of-the-art architectures and applications of graph neural networks in materials science and chemistry, indicating a possible road-map for their further development.

关键词： Computational neuroscience   Computer science   Neural circuits  

摘要： TractoInferno is the world's largest open-source multi-site tractography database, including both research- and clinical-like human acquisitions, aimed specifically at machine learning tractography approaches and related ML algorithms. It provides 284 samples acquired from 3 T scanners across 6 different sites. Available data includes T1-weighted images, single-shell diffusion MRI (dMRI) acquisitions, spherical harmonics fitted to the dMRI signal, fiber ODFs, and reference streamlines for 30 delineated bundles generated using 4 tractography algorithms, as well as masks needed to run tractography algorithms. Manual quality control was additionally performed at multiple steps of the pipeline. We showcase TractoInferno by benchmarking the learn2track algorithm and 5 variations of the same recurrent neural network architecture. Creating the TractoInferno database required approximately 20,000 CPU-hours of processing power, 200 man-hours of manual QC, 3,000 GPU-hours of training baseline models, and 4 Tb of storage, to produce a final database of 350 Gb. By providing a standardized training dataset and evaluation protocol, TractoInferno is an excellent tool to address common issues in machine learning tractography.

关键词： Civil engineering   Computer science  

摘要： This study combined crash reports, land use, real-time traffic, and weather data to form an integrated database to analyze the severity of crashes taking place on rural highways. As the traffic cameras are placed at fixed locations, there is a wide range of measured distances between crashes and the selected nearest camera for extracting traffic variables. This may change the significance of traffic variables. For the first time, spacing was introduced as the distance around the detectors in which traffic characteristics are inferred to crashes. Classification and Regression Tree (CART) was employed as an interpretable tool to explore how spacing affects model performance and the significance of traffic variables. Twelve spacing scenarios from 250 to 3000 m were evaluated. Except for short spacings suffering from the low sample size issue, each model has a good predictive performance based on overall accuracy and F-2 score in the 1000-3000 m spacings. In this range, three dominant rules emerged: (1) high deviations of speed on the roads surrounded by wastelands are associated with severe crashes;(2) faded markings in residential zones increase the likelihood of severe outcomes;(3) installation of barriers decrease the probability of severe crashes. Comparing the Variable Importance Measure (VIM) reveals that the total importance of traffic variables reduces as the spacing increases. Also, results indicate that average speed is significant until 1750 m;but speed deviation, traffic flow, and percent of heavy vehicles are more stable variables for further spacings. In conclusion, for the first time, spacing scenarios were evaluated systematically and proved that they have a remarkable impact on the significance of variables. This novel research provides guidance not only on the spacing but also on which real-time traffic variables have a greater impact on crash severity, along with design, land use, and environmental variables.

关键词： Aerospace engineering   Electrical and electronic engineering   Applied mathematics   Computer science   Information technology  

摘要： Considering the limited communication resources and slow convergence speed of multi-unmanned aerial vehicle (UAV) systems, this paper presents a finite-time even-triggered control framework for multi-UAV systems to achieve formation-containment tracking control. First, a virtual leader with time-varying output is introduced so that the trajectory of the whole system can be manipulated in real time. Second, the finite-time control enables that the systematic error converge to a small neighborhood of origin in finite time. Third, in order to save communication resources, an event-triggering function is developed to generate the control event sequences, which avoids continuous update of the controller. Rigorous proof shows the finite-time stability of the proposed control algorithm, and Zeno behavior is strictly excluded for each UAV. Finally, some numerical simulations are given to verify the effectiveness of the proposed controllers.

关键词： Mechanical engineering   Aerospace engineering   Electrical and electronic engineering   Computer science  

摘要： Modular robotic systems built of reconfigurable components offer an efficient and versatile alternative to traditional monolithic robots. However, as modular systems scale up, construction efficiency is compromised due to an increase in travel time and path planning complexity. Here we introduce a discrete modular material-robot system that is capable of serial, recursive (making more robots), and hierarchical (making larger robots) assembly. This is accomplished by discretizing the construction into a feedstock of simple primitive building blocks which can be re-configured to create a wide range of functionality. The discretization significantly simplifies the swarm's navigation, error correction, and coordination. The component composition is supported by an algorithm to compile the building blocks into swarms and plan the optimal construction path. Our approach challenges the convention that larger constructions need larger machines to build them, and could be applied in areas that today either require substantial capital investments for fixed infrastructure or are altogether unfeasible.

ISBN: (纸本)9781450397117

关键词： Virtual reality  

摘要： Due to the corona pandemic, numerous courses were held using digital solutions in order to be able to continue teaching. Conventional collaboration tools (Zoom, Big Blue Button, etc.) were used in particular to digitally map a synchronous session for teaching and learning purposes. While these conventional collaboration tools offer a solid basis for communication between learners and teachers, aspects such as presence or a realistic type of interaction are neglected. In this work, we report on the experiences from a computer science seminar where virtual reality (VR) technology was used as an alternative solution for teaching and group work. The benefits of VR compared to conventional collaboration tools were examined using questionnaires and interviews with the participants. On the one hand, the results show the high potential of VR to increase the clarity and experienceability of learning content and to promote cooperation through social presence. On the other hand, the use of VR brings with it some technical and organizational difficulties that should be taken into account in the didactic implementation. © 2022, CC BY.