nils-herrmann/clean_scirepeval huggingface dataset:
Plantar pressure relief under the metatarsal heads: therapeutic insole design using three-dimensional finite element model of the foot.

Therapeutic footwear with specially-made insoles is often used in people with diabetes and rheumatoid arthritis to relieve ulcer risks and pain due to high pressures from areas beneath bony prominences of the foot, in particular to the metatarsal heads (MTHs). In a three-dimensional finite element study of the foot and footwear with sensitivity analysis, effects of geometrical variations of a therapeutic insole, in terms of insole thicknesses and metatarsal pad (MP) placements, on local peak plantar pressure under MTHs and stress/strain states within various forefoot tissues, were determined. A validated musculoskeletal finite element model of the human foot was employed. Analyses were performed in a simulated muscle-demanding instant in gait. For many design combinations, increasing insole thicknesses consistently reduce peak pressures and internal tissue strain under MTHs, but the effects reach a plateau when insole becomes very thick (e.g., a value of 12.7mm or greater). Altering MP placements, however, showed a proximally- and a distally-placed MP could result in reverse effects on MTH pressure-relief. The unsuccessful outcome due to a distally-placed MP may attribute to the way it interacts with plantar tissue (e.g., plantar fascia) adjacent to the MTH. A uniform pattern of tissue compression under metatarsal shaft is necessary for a most favorable pressure-relief under MTHs. The designated functions of an insole design can best be achieved when the insole is very thick, and when the MP can achieve a uniform tissue compression pattern adjacent to the MTH.
Efficient Physics-Based Implementation for Realistic Hand-Object Interaction in Virtual Reality

We propose an efficient physics-based method for dexterous ‘real hand’ - ‘virtual object’ interaction in Virtual Reality environments. Our method is based on the Coulomb friction model, and we show how to efficiently implement it in a commodity VR engine for realtime performance. This model enables very convincing simulations of many types of actions such as pushing, pulling, grasping, or even dexterous manipulations such as spinning objects between fingers without restrictions on the objects' shapes or hand poses. Because it is an analytic model, we do not require any prerecorded data, in contrast to previous methods. For the evaluation of our method, we conduction a pilot study that shows that our method is perceived more realistic and natural, and allows for more diverse interactions. Further, we evaluate the computational complexity of our method to show real-time performance in VR environments.
Interpretation of coal gasification modeling in commercial process analysis simulation codes †

The purpose of this study is to recognize modeling methods for coal combustion and gasification in commercial process analysis codes. Many users have appreciated the reliability of commercial process analysis simulation codes; however, it is necessary to understand the physical meaning and limitations of the modeling results. Modeling of coal gasification phenomena has been embodied in commercial process analysis simulators such as Aspen. Commercial code deals with modeling of the gasification system with a number of reactor blocks supported by the specific code, not as a coal gasifier. However, the primary purpose of using process analysis simulation code is to interpret the whole plant cycle rather than an individual unit such as a gasifier. Equilibrium models of a coal gasifier are generally adopted in the commercial codes, where the method of Gibbs free energy minimization of chemical species is applied at the given temperature and pressure. The equilibrium model of the coal gasifier, RGibbs, in commercial codes provides users with helpful information, such as exit syngas temperature, composition, flow rate, performance of coal gasifier model, etc. with various input and operating conditions. This simulation code is being used to generate simple and fast response of results. Limitations and uncertainties are interpreted in the view of the gasification process, chemical reaction, char reactivity, and reactor geometry. In addition, case studies are introduced with examples. Finally, a way to improve the coal gasifier model is indicated, and a kinetically modified model considering reaction rate is proposed.
The mediating effects of team and self-efficacy on the relationship between transformational leadership, and job satisfaction and psychological well-being in healthcare professionals: a cross-sectional questionnaire survey.

The importance of transformational leadership for the health and well-being of staff in the healthcare sector is increasingly acknowledged, however, there is less knowledge about the mechanisms that may explain the links between transformational leaders and employee health and well-being.



To examine two possible psychological mechanisms that link transformational leadership behaviours to employee job satisfaction and well-being.



Cross-sectional study design.



The study took place in two elderly care centers in large Danish local government. Staff were predominantly healthcare assistants but also nurses and other healthcare-related professions participated in the study.



274 elderly care employees completed the questionnaire. Surveys were sent to all employees working at the centers. 91% were female, the average age was 45 years.



A questionnaire was distributed to all members of staff in the elderly care centers and where employees were asked to rate their line manager's leadership style and were asked to evaluate their own level of self-efficacy as well as the level of efficacy in their team (team efficacy) and their job satisfaction and psychological well-being.



Both team and self-efficacy were found to act as mediators, however, their effects differed. Self-efficacy was found to fully mediate the relationship between transformational leadership and well-being and team efficacy was found to partially mediate the relationship between transformational leadership and job satisfaction and fully mediate the relationship between transformational leadership and well-being.



Within the pressurised environment faced by employees in the healthcare sector today transformational leaders may help ensure employees' job satisfaction and psychological well-being. They do so through the establishment of a sense of being in control as individuals but also as being part of a competent group.
Feasibility and Efficacy of an mHealth Game for Managing Anxiety: "Flowy" Randomized Controlled Pilot Trial and Design Evaluation.

Meeting the complex needs of patients with chronic common mental health disorders (CMHDs) may be the greatest challenge facing organized medical practice. On the basis of a well-established and proven theoretical foundation for controlled respiration as a behavioral intervention for CMHDs, as well as preliminary evidence that gamification can improve health outcomes through increasing patient engagement, this randomized controlled pilot study evaluated the feasibility and clinical efficacy of a mobile health game called "Flowy" ( www.flowygame.com ) that digitally delivered breathing retraining exercises for anxiety, panic, and hyperventilation symptom management.



We designed an unblinded, Web-based, parallel-group randomized controlled trial focusing on feasibility, clinical efficacy, and design proof of concept. In the intervention condition (n = 31), participants received free access to "Flowy" for 4 weeks. In the control condition (n = 32), participants were placed on a waitlist for 4 weeks before being offered free access to "Flowy." Online measurements using psychological self-report questionnaires were made at 2 and 4 weeks post-baseline.



At trial conclusion, participants found "Flowy" acceptable as an anxiety management intervention. "Flowy" engaged participants sufficiently to endorse proactive gameplay. Intent-to-treat analysis revealed a reduction in anxiety, panic, and self-report hyperventilation scores in both trial arms, with the intervention arm experiencing greater quality of life. Participants perceived "Flowy" as a fun and useful intervention, proactively used "Flowy" as part of their care, and would recommend "Flowy" to family and friends.



Our results suggest that a digital delivery of breathing retraining exercises through a mobile health game can manage anxiety, panic, and hyperventilation symptoms associated with CMHDs.
Quality Control in Crowdsourcing Systems: Issues and Directions

As a new distributed computing model, crowdsourcing lets people leverage the crowd's intelligence and wisdom toward solving problems. This article proposes a framework for characterizing various dimensions of quality control in crowdsourcing systems, a critical issue. The authors briefly review existing quality-control approaches, identify open issues, and look to future research directions. In the Web extra, the authors discuss both design-time and runtime approaches in more detail.
Software Defined networking based routing firewall

A router's main function is to allow communication between different networks as quickly as possible and in efficient manner. The communication can be between LAN or between LAN and WAN. A firewall's function is to restrict unwanted traffic. In big networks, routers and firewall tasks are performed by different network devices. But in small networks, we want both functions on same device i.e. one single device performing both routing and firewalling. We call these devices as routing firewall. In Traditional networks, the devices are already available. But the next generation networks will be powered by Software Defined Networks. For wide adoption of SDN, we need northbound SDN applications such as routers, load balancers, firewalls, proxy servers, Deep packet inspection devices, routing firewalls running on OpenFlow based physical and virtual switches. But the SDN is still in early stage, so still there is very less availability of these applications. There already exist simple L3 Learning application which provides very elementary router function and also simple stateful firewalls providing basic access control. In this paper, we are implementing one SDN Routing Firewall Application which will perform both the routing and firewall function.
A Comparison of Global Search Algorithms for Continuous Black Box Optimization

Four methods for global numerical black box optimization with origins in the mathematical programming community are described and experimentally compared with the state of the art evolutionary method, BIPOP-CMA-ES. The methods chosen for the comparison exhibit various features that are potentially interesting for the evolutionary computation community: systematic sampling of the search space (DIRECT, MCS) possibly combined with a local search method (MCS), or a multi-start approach (NEWUOA, GLOBAL) possibly equipped with a careful selection of points to run a local optimizer from (GLOBAL). The recently proposed “comparing continuous optimizers” (COCO) methodology was adopted as the basis for the comparison. Based on the results, we draw suggestions about which algorithm should be used depending on the available budget of function evaluations, and we propose several possibilities for hybridizing evolutionary algorithms (EAs) with features of the other compared algorithms.
Application of active disturbance rejection control in tank gun control system

The problem of position tracking for a tank gun control system with inertia uncertainty and external disturbance is investigated in this paper. The tank gun control system, demanding high tracking precision and stabilization precision, is a nonlinear system. Classical control methods are commonly used in the actual system, which is difficult to ensure high precision and high disturbance rejection capability. An active disturbance rejection control (ADRC) scheme is applied to guarantee the state variables of the closed loop system to converge to the reference state with the help of the extended state observer by estimating the inertia uncertainty and external disturbance. The basic theory of the ADRC is introduced here. According to the mathematical model, the parameters of ADRC is designed. Also, simulation results show that ADRC controller has advantages of high precision and high disturbance rejection ability. A comparison between ADRC and PID is also presented, to show the effectiveness of the ADRC control strategy.
Learning to Act Using Real-Time Dynamic Programming

Learning methods based on dynamic programming (DP) are receiving increasing attention in arti cial intelligence. Researchers have argued that DP provides the appropriate basis for compiling planning results into reactive strategies for real-time control, as well as for learning such strategies when the system being controlled is incompletely known. We introduce an algorithm based on DP, which we call Real-Time DP (RTDP), by which an embedded system can improve its performance with experience. RTDP generalizes Korf's Learning-Real-Time-A* algorithm to problems involving uncertainty. We invoke results from the theory of asynchronous DP to prove that RTDP achieves optimal behavior in several di erent classes of problems. We also use the theory of asynchronous DP to illuminate aspects of other DP-based reinforcement learning methods such as Watkins' Q-Learning algorithm. A secondary aim of this article is to provide a bridge between AI research on real-time planning and learning and relevant concepts and algorithms from control theory.
Blue fluorescent emitters: design tactics and applications in organic light-emitting diodes.

Organic light-emitting diodes (OLEDs) are competitive candidates for the next generation flat-panel displays and solid state lighting sources. Efficient blue-emitting materials have been one of the most important prerequisites to kick off the commercialization of OLEDs. This tutorial review focuses on the design of blue fluorescent emitters and their applications in OLEDs. At first, some typical blue fluorescent materials as dopants are briefly introduced. Then nondoped blue emitters of hydrocarbon compounds are presented. Finally, the nondoped blue emitters endowed with hole-, electron- and bipolar-transporting abilities are comprehensively reviewed. The key issues on suppressing close-packing, achieving pure blue chromaticity, improving thermal and morphological stabilities, manipulating charge transporting abilities, simplifying device structures and the applications in panchromatic OLEDs are discussed.
Reinforcement Learning in Large Discrete Action Spaces

Being able to reason in an environment with a large number of discrete actions is essential to bringing reinforcement learning to a larger class of problems. Recommender systems, industrial plants and language models are only some of the many real-world tasks involving large numbers of discrete actions for which current methods can be difficult or even impossible to apply. An ability to generalize over the set of actions as well as sub-linear complexity relative to the size of the set are both necessary to handle such tasks. Current approaches are not able to provide both of these, which motivates the work in this paper. Our proposed approach leverages prior information about the actions to embed them in a continuous space upon which it can generalize. Additionally, approximate nearest-neighbor methods allow for logarithmic-time lookup complexity relative to the number of actions, which is necessary for time-wise tractable training. This combined approach allows reinforcement learning methods to be applied to large-scale learning problems previously intractable with current methods. We demonstrate our algorithm’s abilities on a series of tasks having up to one million actions.
Anatomy of a Personalized Livestreaming System

With smartphones making video recording easier than ever, new apps like Periscope and Meerkat brought personalized interactive video streaming to millions. With a touch, viewers can switch between first person perspectives across the globe, and interact in real-time with broadcasters. Unlike traditional video streaming, these services require low-latency video delivery to support high interactivity between broadcasters and audiences.
 We perform a detailed analysis into the design and performance of Periscope, the most popular personal livestreaming service with 20 million users. Using detailed measurements of Periscope (3 months, 19M streams, 705M views) and Meerkat (1 month, 164K streams, 3.8M views), we ask the critical question: ``Can personalized livestreams continue to scale, while allowing their audiences to experience desired levels of interactivity?' We analyze the network path of each stream and break down components of its end-to-end delay. We find that much of each stream's delay is the direct result of decisions to improve scalability, from chunking video sequences to selective polling for reduced server load. Our results show a strong link between volume of broadcasts and stream delivery latency. Finally, we discovered a critical security flaw during our study, and shared it along with a scalable solution with Periscope and Meerkat management.
5G cellular: key enabling technologies and research challenges

The evolving fifth generation (5G) cellular wireless networks are envisioned to provide higher data rates, enhance end-user quality-of-experience (QoE), reduce end-to-end latency, and lower energy consumption. This article presents several emerging technologies which could enable and define future 5G mobile communication standards and cellular networks. We highlight the key ideas for each technology and the major open research challenges related to measurement, testing and validating the performance of 5G system components. Then, we highlight the fundamental research challenges for resource management in 5G systems.
Planning future electric vehicle central charging stations connected to low-voltage distribution networks

A great interest is recently paid to Electric Vehicles (EV) and their integration into electricity grids. EV can potentially play an important role in power system operation, however, the EV charging infrastructures have been only partly defined, considering them as limited to individual charging points, randomly distributed into the networks. This paper addresses the planning of public central charging stations (CCS) that can be integrated in low-voltage (LV) networks for EV parallel charging. The concepts of AC and DC architectures of CCS are proposed and a comparison is given on their investment cost. Investigation on location and size of CCS is conducted, analyzing two LV grids of different capacity. The results enlighten that a public CCS should be preferably located in the range of 100 m from the transformer. The AC charging levels of 11 kW and 22 kW have the highest potential in LV grids. The option of DC fast-charging is only possible in the larger capacity grids, withstanding the parallel charge of one or two vehicles.
Using synthetic data to train neural networks is model-based reasoning

We draw a formal connection between using synthetic training data to optimize neural network parameters and approximate, Bayesian, model-based reasoning. In particular, training a neural network using synthetic data can be viewed as learning a proposal distribution generator for approximate inference in the synthetic-data generative model. We demonstrate this connection in a recognition task where we develop a novel Captcha-breaking architecture and train it using synthetic data, demonstrating both state-of-the-art performance and a way of computing task-specific posterior uncertainty. Using a neural network trained this way, we also demonstrate successful breaking of real-world Captchas currently used by Facebook and Wikipedia. Reasoning from these empirical results and drawing connections with Bayesian modeling, we discuss the robustness of synthetic data results and suggest important considerations for ensuring good neural network generalization when training with synthetic data.
Cancer-associated cachexia

Cancer-associated cachexia is a disorder characterized by loss of body weight with specific losses of skeletal muscle and adipose tissue. Cachexia is driven by a variable combination of reduced food intake and metabolic changes, including elevated energy expenditure, excess catabolism and inflammation. Cachexia is highly associated with cancers of the pancreas, oesophagus, stomach, lung, liver and bowel; this group of malignancies is responsible for half of all cancer deaths worldwide. Cachexia involves diverse mediators derived from the cancer cells and cells within the tumour microenvironment, including inflammatory and immune cells. In addition, endocrine, metabolic and central nervous system perturbations combine with these mediators to elicit catabolic changes in skeletal and cardiac muscle and adipose tissue. At the tissue level, mechanisms include activation of inflammation, proteolysis, autophagy and lipolysis. Cachexia associates with a multitude of morbidities encompassing functional, metabolic and immune disorders as well as aggravated toxicity and complications of cancer therapy. Patients experience impaired quality of life, reduced physical, emotional and social well-being and increased use of healthcare resources. To date, no effective medical intervention completely reverses cachexia and there are no approved drug therapies. Adequate nutritional support remains a mainstay of cachexia therapy, whereas drugs that target overactivation of catabolic processes, cell injury and inflammation are currently under investigation.
Hoare logic for Java in Isabelle/HOL

This article presents a Hoare-style calculus for a substantial subset of Java Card, which we call Java . In particular, the language includes side-effecting expressions, mutual recursion, dynamic method binding, full exception handling, and static class initialization. The Hoare logic of partial correctness is proved not only sound (w.r.t. our operational semantics of Java, described in detail elsewhere) but even complete. It is the first logic for an object-oriented language that is provably complete. The completeness proof uses a refinement of the Most General Formula approach. The proof of soundness gives new insights into the role of type safety. Further by-products of this work are a new general methodology for handling side-effecting expressions and their results, the discovery of the strongest possible rule of consequence, and a flexible Call rule for mutual recursion. We also give a small but non-trivial application example. All definitions and proofs have been done formally with the interactive theorem prover Isabelle/HOL. This guarantees not only rigorous definitions, but also gives maximal confidence in the results obtained.
Realization and Measurement of Broadside Beam Modulated Metasurface Antennas

Realizations and measurements of broadside-beam circularly polarized anisotropic metasurface antennas are presented. The validity of the design methodology proposed in a previous paper is here experimentally demonstrated by developing a 28-dBi transmitting antenna and a 22-dBi receiving antenna for space-to-ground links at X-band. High polarization purity is obtained by using a simple vertical (i.e., linearly polarized) monopole as feeder, thus providing experimental evidence of the fact that anisotropic surface increases aperture efficiency with respect to isotropic surface implementation. Both the realized antennas are 1.5 mm thick and do not require a beamforming network as they only incorporate the feeding monopole in the same substrate.