nils-herrmann/clean_scirepeval huggingface dataset:
Anthropometry-based approach for side-mounted desktop chairs design evaluation for university students in Ecuador

It is quite common to find side-mounted desktop chairs as main classroom furniture in Ecuadorian universities. However, there is no evidence this furniture is designed to fit the anthropometric characteristics of the students who use it. In this context, this research aims to find the ideal design parameters dimensions for mounted desktop chairs for university students in Ecuador based on relevant anthropometric information and considering the biomechanics of students in sitting position. A sample of 15 mounted desktop chair models used in 10 Ecuadorian universities was evaluated. As a result, every furniture presented mismatch in seat height, desktop height and under desktop height, as well as in the width and depth of the tablet. Students who use this furniture could be at risk to develop health issues because of their daily exposure to poor postures as a result of inadequate furniture design.
Opioid dosing trends and mortality in Washington State workers' compensation, 1996-2002.

The use of opioids for chronic non-cancer pain has increased in the United States since state laws were relaxed in the late 1990s. These policy changes occurred despite scanty scientific evidence that chronic use of opioids was safe and effective.



We examined opiate prescriptions and dosing patterns (from computerized databases, 1996 to 2002), and accidental poisoning deaths attributable to opioid use (from death certificates, 1995 to 2002), in the Washington State workers' compensation system.



Opioid prescriptions increased only modestly between 1996 and 2002. However, prescriptions for the most potent opioids (Schedule II), as a percentage of all scheduled opioid prescriptions (II, III, and IV), increased from 19.3% in 1996 to 37.2% in 2002. Among long-acting opioids, the average daily morphine equivalent dose increased by 50%, to 132 mg/day. Thirty-two deaths were definitely or probably related to accidental overdose of opioids. The majority of deaths involved men (84%) and smokers (69%).



The reasons for escalating doses of the most potent opioids are unknown, but it is possible that tolerance or opioid-induced abnormal pain sensitivity may be occurring in some workers who use opioids for chronic pain. Opioid-related deaths in this population may be preventable through use of prudent guidelines regarding opioid use for chronic pain.
Robust switching strategy for buck-boost converter

This paper presents a procedure to design a robust switching strategy for the basic Buck-Boost DC-DC converter utilizing switched systems' theory. The converter dynamic is described in the framework of linear switched systems and then sliding-mode controller is developed to ensure the asymptotic stability of the desired equilibrium point for the switched system with constant external input. The inherent robustness of the sliding-mode switching rule leads to efficient regulation of the output voltage under load variations. Simulation results are presented to demonstrate the outperformance of the proposed method compared to a rival scheme in the literature.
Heterozygosity for ARID2 loss-of-function mutations in individuals with a Coffin–Siris syndrome-like phenotype

Chromatin remodeling is a complex process shaping the nucleosome landscape, thereby regulating the accessibility of transcription factors to regulatory regions of target genes and ultimately managing gene expression. The SWI/SNF (switch/sucrose nonfermentable) complex remodels the nucleosome landscape in an ATP-dependent manner and is divided into the two major subclasses Brahma-associated factor (BAF) and Polybromo Brahma-associated factor (PBAF) complex. Somatic mutations in subunits of the SWI/SNF complex have been associated with different cancers, while germline mutations have been associated with autism spectrum disorder and the neurodevelopmental disorders Coffin–Siris (CSS) and Nicolaides–Baraitser syndromes (NCBRS). CSS is characterized by intellectual disability (ID), coarsening of the face and hypoplasia or absence of the fifth finger- and/or toenails. So far, variants in five of the SWI/SNF subunit-encoding genes ARID1B, SMARCA4, SMARCB1, ARID1A, and SMARCE1 as well as variants in the transcription factor-encoding gene SOX11 have been identified in CSS-affected individuals. ARID2 is a member of the PBAF subcomplex, which until recently had not been linked to any neurodevelopmental phenotypes. In 2015, mutations in the ARID2 gene were associated with intellectual disability. In this study, we report on two individuals with private de novo ARID2 frameshift mutations. Both individuals present with a CSS-like phenotype including ID, coarsening of facial features, other recognizable facial dysmorphisms and hypoplasia of the fifth toenails. Hence, this study identifies mutations in the ARID2 gene as a novel and rare cause for a CSS-like phenotype and enlarges the list of CSS-like genes.
Trust in Smart Contracts is a Process, As Well

Distributed ledger technologies are rising in popularity, mainly for the host of financial applications they potentially enable, through smart contracts. Several implementations of distributed ledgers have been proposed, and different languages for the development of smart contracts have been suggested. A great deal of attention is given to the practice of development, i.e. programming, of smart contracts. In this position paper, we argue that more attention should be given to the “traditional developers” of contracts, namely the lawyers, and we propose a list of requirements for a human and machine-readable contract authoring language, friendly to lawyers, serving as a common (and a specification) language, for programmers, and the parties to a contract.
Diagnostic errors in medicine: a case of neglect.

Medical diagnoses that are wrong, missed, or delayed make up a large fraction of all medical errors and cause substantial suffering and injury. Compared with other types of medical error, however, diagnostic errors receive little attention-a major factor in perpetuating unacceptable rates of diagnostic error. Diagnostic errors are fundamentally obscure, health care organizations have not viewed them as a system problem, and physicians responsible for making medical decisions seldom perceive their own error rates as problematic. The safety of modem health care can be improved if these three issues are understood and addressed.


SOLUTIONS
Opportunities to improve the visibility of diagnostic errors are evident. Diagnostic error needs to be included in the normal spectrum of quality assurance surveillance and review. The system properties that contribute to diagnostic errors need to be systematically identified and addressed, including issues related to reliable diagnostic testing processes. Even for cases entirely dependent on the skill of the clinician for accurate diagnosis, health care organizations could minimize errors by using system-level interventions to aid the clinician, such as second readings of key diagnostic tests and providing resources for clinical decision support. Physicians need to improve their calibration by getting feedback on the diagnoses they make. Finally, clinicians need to learn about overconfidence and other innate cognitive tendencies that detract from optimal reasoning and learning.



Clinicians and their health care organizations need to take active steps to discover, analyze, and prevent diagnostic errors.
Role of the aryl hydrocarbon receptor (AhR) in lung inflammation

Millions of individuals worldwide are afflicted with acute and chronic respiratory diseases, causing temporary and permanent disabilities and even death. Oftentimes, these diseases occur as a result of altered immune responses. The aryl hydrocarbon receptor (AhR), a ligand-activated transcription factor, acts as a regulator of mucosal barrier function and may influence immune responsiveness in the lungs through changes in gene expression, cell–cell adhesion, mucin production, and cytokine expression. This review updates the basic immunobiology of the AhR signaling pathway with regards to inflammatory lung diseases such as asthma, chronic obstructive pulmonary disease, and silicosis following data in rodent models and humans. Finally, we address the therapeutic potential of targeting the AhR in regulating inflammation during acute and chronic respiratory diseases.
A comparative study of control architectures in UAV/UGV-based surveillance system

The goal of this paper is to study the characteristics of various control architectures (e.g. centralized, hierarchical, distributed, and hybrid) for a team of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) in performing collaborative surveillance and crowd control. To this end, an overview of different control architectures is first provided covering their functionalities and interactions. Then, three major functional modules needed for crowd control are discussed under those architectures, including 1) crowd detection using computer vision algorithms, 2) crowd tracking using an enhanced information aggregation strategy, and 3) vehicles motion planning using a graph search algorithm. Depending on the architectures, these modules can be placed in the ground control center or embedded in each vehicle. To test and demonstrate characteristics of various control architectures, a testbed has been developed involving these modules and various hardware and software components, such as 1) assembled UAVs and UGV, 2) a real-time simulator (in Repast Simphony), 3) off-the-shelf ARM architecture computers (ODROID-U2/3), 4) autopilot units with GPS sensors, and 5) multipoint wireless networks using XBee. Experiments successfully demonstrate the pros and cons of the considered control architectures in terms of computational performance in responding to different system conditions (e.g. information sharing).
ORIGA-light: An online retinal fundus image database for glaucoma analysis and research

Retinal fundus image is an important modality to document the health of the retina and is widely used to diagnose ocular diseases such as glaucoma, diabetic retinopathy and age-related macular degeneration. However, the enormous amount of retinal data obtained nowadays mostly stored locally; and the valuable embedded clinical knowledge is not efficiently exploited. In this paper we present an online depository, ORIGA-light, which aims to share clinical groundtruth retinal images with the public; provide open access for researchers to benchmark their computer-aided segmentation algorithms. An in-house image segmentation and grading tool is developed to facilitate the construction of ORIGA-light. A quantified objective benchmarking method is proposed, focusing on optic disc and cup segmentation and Cup-to-Disc Ratio (CDR). Currently, ORIGA-light contains 650 retinal images annotated by trained professionals from Singapore Eye Research Institute. A wide collection of image signs, critical for glaucoma diagnosis, are annotated. We will update the system continuously with more clinical ground-truth images. ORIGA-light is available for online access upon request.
Pen-and-ink textures for real-time rendering

Simulation of a pen-and-ink illustration style in a realtime rendering system is a challenging computer graphics problem. Tonal art maps (TAMs) were recently suggested as a solution to this problem. Unfortunately, only the hatching aspect of pen-and-ink media was addressed thus far. We extend the TAM approach and enable representation of arbitrary textures. We generate TAM images by distributing stroke primitives according to a probability density function. This function is derived from the input image and varies depending on the TAM’s scale and tone levels. The resulting depiction of textures approximates various styles of pen-and-ink illustrations such as outlining, stippling, and hatching.
An assessment of the potential health impacts of food reformulation

Policies focused on food quality are intended to facilitate healthy choices by consumers, even those who are not fully informed about the links between food consumption and health. The goal of this paper is to evaluate the potential impact of such a food reformulation scenario on health outcomes.We first created reformulation scenarios adapted to the French characteristics of foods. After computing the changes in the nutrient intakes of representative consumers, we determined the health effects of these changes. To do so, we used the DIETRON health assessment model, which calculates the number of deaths avoided by changes in food and nutrient intakes.Depending on the reformulation scenario, the total impact of reformulation varies between 2408 and 3597 avoided deaths per year, which amounts to a 3.7–5.5% reduction in mortality linked to diseases considered in the DIETRON model. The impacts are much higher for men than for women and much higher for low-income categories than for high-income categories. These differences result from the differences in consumption patterns and initial disease prevalence among the various income categories.Even without any changes in consumers’ behaviors, realistic food reformulation may have significant health outcomes.
Discovering Higher Level Structure in Visual SLAM

In this paper, we describe a novel method for discovering and incorporating higher level map structure in a real-time visual simultaneous localization and mapping (SLAM) system. Previous approaches use sparse maps populated by isolated features such as 3-D points or edgelets. Although this facilitates efficient localization, it yields very limited scene representation and ignores the inherent redundancy among features resulting from physical structure in the scene. In this paper, higher level structure, in the form of lines and surfaces, is discovered concurrently with SLAM operation, and then, incorporated into the map in a rigorous manner, attempting to maintain important cross-covariance information and allow consistent update of the feature parameters. This is achieved by using a bottom-up process, in which subsets of low-level features are ldquofolded inrdquo to a parameterization of an associated higher level feature, thus collapsing the state space as well as building structure into the map. We demonstrate and analyze the effects of the approach for the cases of line and plane discovery, both in simulation and within a real-time system operating with a handheld camera in an office environment.
Low-Frequency Electromagnetic Modeling for Electrical and Biological Systems Using MATLAB [Book Reviews]

The role of increasingly powerful computers in the modeling and simulation domain has resulted in great advancements in the fields of wireless communications, medicine, and space technology to name a few. In The authors of this book start from the fundamental equations that govern low-frequency electromagnetic phenomenon and go through each stage of solving such problems by striking a balance between mathematical rigor and actual implementation in code. The use of MATLAB makes the advanced concepts discussed in the book immediately testable through experiments. The book pays close attention to various applications in an electrical and biological system that are of immediate relevance in today’s world. The use of state-of-the-art human phantom meshes, especially from the Visible Human Project (VHP) of the U.S. National Library of Medicine, makes this text singular in its field. The text is systematic and very well-organized in presenting the various topics on low-frequency electromagnetic. It also should be known that the first part of this text presents the mathematical theory behind low-frequency electromagnetic modeling and follows it with the topic of meshing. The text starts with the basics of meshing and builds it up in an easy-to-read manner with plenty of illustrations.
Can affective factors contribute to explain continuance intention of web-based services?

More than a decade has been passed since the birth of web-based services as novel network-based services. To explain why and how consumers are motivated to accept the web-based services, lots of technology acceptance theories such as technology acceptance model (TAM) and expectation-confirmation model (ECM) have been successfully proposed. However, the models do not fully explain why and how the consumers continue to use a specific web-based service. Meanwhile, affective factors such as intimacy have been regarded as essential factors for strengthening human relationships in consumer behavior. If a sort of relationships between consumers and web-based services has been built up due to repetitive usage, then we could assume that affective, as well as cognitive, factors may contribute to explain the consumers' continuous use. In light of this assumption, legacy ECM and human relationship-related theoretical models which include affective factors may be integrated for better explanation. Hence, the purpose of this paper is to propose an extended ECM which contains affective factors, as well as cognitive factors, related to maintaining relationship between consumers and service providers to explain why the consumers continue to use a specific information system. In this study, we mainly focus on two new constructs, familiarity and intimacy, and seek to examine how cognitive and affective factors are inter-related toward continuance intention. Moderating effects of emotion to alternatives, familiarity with alternative and intimacy with alternative, to IS continuance intention are also considered.
Corporate Financial Performance and Corporate Social Performance : Methodological Development and the Theoretical Contribution of Empirical Studies

One of the roles of accounting is to provide information on business performance, either through financial accounting indicators or otherwise. Theoretical-empirical studies on the relationship between Corporate Financial Performance (CFP) and Corporate Social Performance (CSP) have increased in recent years, indicating the development of this research field. However, the contribution to the theory by empirical studies is made in an incremental manner, given that each study normally focuses on a particular aspect of the theory. Therefore, it is periodically necessary to conduct an analysis to evaluate how the aggregation of empirical studies has contributed to the evolution of the theory. Designing such an analysis was the objective of the present study. The theoretical framework covered the following: stakeholder theory, the relationship between CSP and CFP, good management theory, and slack resource theory. This research covered a 15-year period (1996 to 2010), and the data collection employed a search tool for the following databases: Ebsco, Proquest, and ISI. The sampling process obtained a set of 58 exclusively theoretical-empirical and quantitative articles that test the CSP-CFP relationship. The main results in the theoretical field reinforce the proposed positive relationship between CSP and CFP and good management theory and demonstrate a deficiency in the explanation of the temporal lag in the causal relationship between CSP and CFP as well as deficiencies in the description of the CSP construct. These results suggest future studies to research the temporal lag in the causal relationship between CSP and CFP and the possible reasons that the positive association between CSP and CFP has not been assumed in some empirical studies.
Evaluation of neural network architectures for embedded systems

Since the emergence of Deep Neural Networks (DNNs) as a prominent technique in the field of computer vision, the ImageNet classification challenge has played a major role in advancing the state-of-the-art. While accuracy figures have steadily increased, the resource utilization of winning models has not been properly taken into account. In this work, we present a comprehensive analysis of important metrics in practical applications: accuracy, memory footprint, parameters, operations count, inference time and power consumption.  (1) power consumption is independent of batch size and architecture; (2) accuracy and inference time are in a hyperbolic relationship; (3) energy constraint is an upper bound on the maximum achievable accuracy and model complexity; (4) the number of operations is a reliable estimate of the inference time. We believe our analysis provides a compelling set of information that helps design and engineer efficient DNNs.
Self-adaptive particle swarm optimization: a review and analysis of convergence

Particle swarm optimization (PSO) is a population-based, stochastic search algorithm inspired by the flocking behaviour of birds. The PSO algorithm has been shown to be rather sensitive to its control parameters, and thus, performance may be greatly improved by employing appropriately tuned parameters. However, parameter tuning is typically a time-intensive empirical process. Furthermore, a priori parameter tuning makes the implicit assumption that the optimal parameters of the PSO algorithm are not time-dependent. To address these issues, self-adaptive particle swarm optimization (SAPSO) algorithms adapt their control parameters throughout execution. While there is a wide variety of such SAPSO algorithms in the literature, their behaviours are not well understood. Specifically, it is unknown whether these SAPSO algorithms will even exhibit convergent behaviour. This paper addresses this lack of understanding by investigating the convergence behaviours of 18 SAPSO algorithms both analytically and empirically. This paper also empirically examines whether the adapted parameters reach a stable point and whether the final parameter values adhere to a well-known convergence criterion. The results depict a grim state for SAPSO algorithms; over half of the SAPSO algorithms exhibit divergent behaviour while many others prematurely converge.
The effect of breakfast type on total daily energy intake and body mass index: results from the Third National Health and Nutrition Examination Survey (NHANES III).

The objective of this study was to investigate the relationship between breakfast type, energy intake and body mass index (BMI). We hypothesized not only that breakfast consumption itself is associated with BMI, but that the type of food eaten at breakfast also affects BMI.



Data from the Third National Health and Nutrition Examination Survey (NHANES III), a large, population-based study conducted in the United States from 1988 to 1994, were analyzed for breakfast type, total daily energy intake, and BMI. The analyzed breakfast categories were "Skippers," "Meat/eggs," "Ready-to-eat cereal (RTEC)," "Cooked cereal," "Breads," "Quick Breads," "Fruits/vegetables," "Dairy," "Fats/sweets," and "Beverages." Analysis of covariance was used to estimate adjusted mean body mass index (BMI) and energy intake (kcal) as dependent variables. Covariates included age, gender, race, smoking, alcohol intake, physical activity and poverty index ratio.



Subjects who ate RTEC, Cooked cereal, or Quick Breads for breakfast had significantly lower BMI compared to Skippers and Meat and Egg eaters (p < or = 0.01). Breakfast skippers and fruit/vegetable eaters had the lowest daily energy intake. The Meat and Eggs eaters had the highest daily energy intake and one of the highest BMIs.



This analysis provides evidence that skipping breakfast is not an effective way to manage weight. Eating cereal (ready-to-eat or cooked cereal) or quick breads for breakfast is associated with significantly lower body mass index compared to skipping breakfast or eating meats and/or eggs for breakfast.