nils-herrmann/clean_scirepeval huggingface dataset:
Applying machine learning methods to predict hand hygiene compliance characteristics

Increasing hospital re-admission rates due to Hospital Acquired Infections (HAIs) are a concern at many healthcare facilities. To prevent the spread of HAIs, caregivers should comply with hand hygiene guidelines, which require reliable and timely hand hygiene compliance monitoring systems. The current standard practice of monitoring compliance involves the direct observation of caregivers' hand cleaning as they enter or exit a patient room by a trained observer, which can be time-consuming, resource-intensive, and subject to bias. To alleviate tedious manual effort and reduce errors, this paper describes how we applied machine learning to study the characteristics of compliance that can later be used to (1) assist direct observation by deciding when and where to station manual auditors and (2) improve compliance by providing just-in-time alerts or recommending training materials to non-compliant staff. The paper analyzes location and handwashing station activation data from a 30-bed intensive care unit study and uses machine learning to assess if location, time-based factors, or other behavior data can determine what characteristics are predictive of handwashing non-compliance events. The results of this study show that a care provider's entry compliance is highly indicative of the same provider's exit compliance. Moreover, compliance of the most recent patient room visit can also predict entry compliance of a provider's current patient room visit.
Generative Models of Visually Grounded Imagination

It is easy for people to imagine what a man with pink hair looks like, even if they have never seen such a person before. We call the ability to create images of novel semantic concepts visually grounded imagination. In this paper, we show how we can modify variational auto-encoders to perform this task. Our method uses a novel training objective, and a novel product-of-experts inference network, which can handle partially specified (abstract) concepts in a principled and efficient way. We also propose a set of easy-to-compute evaluation metrics that capture our intuitive notions of what it means to have good visual imagination, namely correctness, coverage, and compositionality (the 3 C’s). Finally, we perform a detailed comparison of our method with two existing joint image-attribute VAE methods (the JMVAE method of (Suzuki et al., 2017) and the BiVCCA method of (Wang et al., 2016b)) by applying them to two datasets: the MNIST-with-attributes dataset (which we introduce here), and the CelebA dataset (Liu et al., 2015).
Identification of bioaccessible and uptaken phenolic compounds from strawberry fruits in in vitro digestion/Caco-2 absorption model.

Strawberry fruits are highly valued for their taste and nutritional value. However, results describing the bioaccessibility and intestinal absorption of phenolic compounds from strawberries are still scarce. In our study, a combined in vitro digestion/Caco-2 absorption model was used to mimic physiological conditions in the gastrointestinal track and identify compounds transported across intestinal epithelium. In the course of digestion, the loss of anthocyanins was noted whilst pelargonidin-3-glucoside remained the most abundant compound, amounting to nearly 12 mg per 100 g of digested strawberries. Digestion increased the amount of ellagic acid available by nearly 50%, probably due to decomposition of ellagitannins. Only trace amounts of pelargonidin-3-glucoside were found to be absorbed in the intestine model. Dihydrocoumaric acid sulphate and p-coumaric acid were identified as metabolites formed in enterocytes and released at the serosal side of the model.
The influence of Arctic amplification on mid-latitude summer circulation

Accelerated warming in the Arctic, as compared to the rest of the globe, might have profound impacts on mid-latitude weather. Most studies analyzing Arctic links to mid-latitude weather focused on winter, yet recent summers have seen strong reductions in sea-ice extent and snow cover, a weakened equator-to-pole thermal gradient and associated weakening of the mid-latitude circulation. We review the scientific evidence behind three leading hypotheses on the influence of Arctic changes on mid-latitude summer weather: Weakened storm tracks, shifted jet streams, and amplified quasi-stationary waves. We show that interactions between Arctic teleconnections and other remote and regional feedback processes could lead to more persistent hot-dry extremes in the mid-latitudes. The exact nature of these non-linear interactions is not well quantified but they provide potential high-impact risks for society. Accelerated global warming in the Arctic might have profound impacts on mid-latitude weather particularly in winter, although the evidence for an effect also in summer is also growing. Here Coumou et al. show that these interactions could lead to more persistent hot-dry extremes in mid-latitudes.
Modeling and simulation of a 24-pulse Transformer Rectifier Unit for more electric aircraft power system

This paper presents a study on a three-phase 24-pulse Transformer Rectifier Unit (TRU) for use in aircraft electric power system. Four three-phase systems with 15°, 30°, 45°, and 60° phase shifts are obtained by interconnection of conventional transformers in zig-zag configuration. The system is modeled in details using Simulink (SimPowerSystems). Simulation results are presented and the obtained performance is compared with those of a 12-pulse TRU.
Real Time Tracking of an Omnidirectional Robot - An Extended Kalman Filter Approach

This paper describes a robust localization system, similar to the used by the teams participating in the Robocup Small size league (SLL). The system, developed in Object Pascal, allows real time localization and control of an autonomous omnidirectional mobile robot. The localization algorithm is done resorting to odometry and global vision data fusion, applying an extended Kalman filter, being this method a standard approach for reducing the error in a least squares sense, using measurements from different sources.
Children's spatial thinking: does talk about the spatial world matter?

In this paper we examine the relations between parent spatial language input, children's own production of spatial language, and children's later spatial abilities. Using a longitudinal study design, we coded the use of spatial language (i.e. words describing the spatial features and properties of objects; e.g. big, tall, circle, curvy, edge) from child age 14 to 46 months in a diverse sample of 52 parent-child dyads interacting in their home settings. These same children were given three non-verbal spatial tasks, items from a Spatial Transformation task (Levine et al., 1999), the Block Design subtest from the WPPSI-III (Wechsler, 2002), and items on the Spatial Analogies subtest from Primary Test of Cognitive Skills (Huttenlocher & Levine, 1990) at 54 months of age. We find that parents vary widely in the amount of spatial language they use with their children during everyday interactions. This variability in spatial language input, in turn, predicts the amount of spatial language children produce, controlling for overall parent language input. Furthermore, children who produce more spatial language are more likely to perform better on spatial problem solving tasks at a later age.
Clinical Text Analysis Using Interactive Natural Language Processing

Natural Language Processing (NLP) systems are typically developed by informaticists skilled in machine learning techniques that are unfamiliar to end-users. Although NLP has been widely used in extracting information from clinical text, current systems generally do not provide any provisions for incorporating feedback and revising models based on input from domain experts. The goal of this research is to close this gap by building highly-usable tools suitable for the analysis of free text reports.
Land use/cover classification- An introduction review and comparison

Accurate and reliable information about land use and land cover is essential for change detection and monitoring of the specified area. It is also useful in the updating the geographical information about the area. Over the past decade, a significant amount of research has been conducted concerning the application of different classifier and image fusion technique in this area. In this paper, introductions to the land use and land cover classification techniques are given and the results from a number of different techniques are compared. It has been found that, in general fusion technique perform better than either conventional classifier or supervised/unsupervised classification.
Atypical Vancouver Type-C Periprosthetic Fracture Complicated by Nonunion: A Case Report.

In recent years, atypical femoral fractures (AFFs) associated with bisphosphonate use have increasingly been reported, but current definitions limit their diagnosis to native femora. Atypical periprosthetic fractures are rare. We present a case of a Vancouver type-C periprosthetic fracture that was recognized as an AFF following nonunion.



Bisphosphonate-associated AFFs can present as periprosthetic fractures. Delayed recognition of the role of bisphosphonates in a periprosthetic fracture may lead to a worse outcome, including a delay in diagnosis, delayed union, and failure of fixation.
Minimum Time vs Maximum Exit Velocity Path Optimization During Cornering

Numerical optimization has been used as an extension of vehicle dynamics simulation in order to reproduce trajectories and driving techniques used by expert race drivers and investigate the effects of several vehicle parameters in the stability limit operation of the vehicle. In this work we investigate how different race-driving techniques may be reproduced by considering different optimization cost functions. We introduce a bicycle model with suspension dynamics and study the role of the longitudinal load transfer in limit vehicle operation, i.e., when the tires operate at the adhesion limit. Finally we demonstrate that for certain vehicle configurations the optimal trajectory may include large slip angles (drifting), which matches the techniques used by rally-race drivers.
Enabling a Pepper Robot to provide Automated and Interactive Tours of a Robotics Laboratory

The Pepper robot has become a widely recognised face for the perceived potential of social robots to enter our homes and businesses. However, to date, commercial and research applications of the Pepper have been largely restricted to roles in which the robot is able to remain stationary. This restriction is the result of a number of technical limitations, including limited sensing capabilities, and have as a result, reduced the number of roles in which use of the robot can be explored. In this paper, we present our approach to solving these problems, with the intention of opening up new research applications for the robot. To demonstrate the applicability of our approach, we have framed this work within the context of providing interactive tours of an open-plan robotics laboratory.
Challenges to meat safety in the 21st century.

The safety of meat has been at the forefront of societal concerns in recent years, and indications exist that challenges to meat safety will continue in the future. Major meat safety issues and related challenges include the need to control traditional as well as "new," "emerging," or "evolving" pathogenic microorganisms, which may be of increased virulence and low infectious doses, or of resistance to antibiotics or food related stresses. Other microbial pathogen related concerns include cross-contamination of other foods and water with enteric pathogens of animal origin, meat animal manure treatment and disposal issues, foodborne illness surveillance and food attribution activities, and potential use of food safety programs at the farm. Other issues and challenges include food additives and chemical residues, animal identification and traceability issues, the safety and quality of organic and natural products, the need for and development of improved and rapid testing and pathogen detection methodologies for laboratory and field use, regulatory and inspection harmonization issues at the national and international level, determination of responsibilities for zoonotic diseases between animal health and regulatory public health agencies, establishment of risk assessment based food safety objectives, and complete and routine implementation of HACCP at the production and processing level on the basis of food handler training and consumer education. Viral pathogens will continue to be of concern at food service, bacterial pathogens such as Escherichia coli O157:H7, Salmonella and Campylobacter will continue affecting the safety of raw meat and poultry, while Listeria monocytogenes will be of concern in ready-to-eat processed products. These challenges become more important due to changes in animal production, product processing and distribution; increased international trade; changing consumer needs and increased preference for minimally processed products; increased worldwide meat consumption; higher numbers of consumers at-risk for infection; and, increased interest, awareness and scrutiny by consumers, news media, and consumer activist groups. Issues such as bovine sponginform encephalopathy will continue to be of interest mostly as a target for eradication, while viral agents affecting food animals, such as avian influenza, will always need attention for prevention or containment.
Do be do be do

We explore the design and implementation of Frank, a strict functional programming language with a bidirectional effect type system designed from the ground up around a novel variant of Plotkin and Pretnar's effect handler abstraction. 
 Effect handlers provide an abstraction for modular effectful programming: a handler acts as an interpreter for a collection of commands whose interfaces are statically tracked by the type system. However, Frank eliminates the need for an additional effect handling construct by generalising the basic mechanism of functional abstraction itself. A function is simply the special case of a Frank operator that interprets no commands. Moreover, Frank's operators can be multihandlers which simultaneously interpret commands from several sources at once, without disturbing the direct style of functional programming with values. 
 Effect typing in Frank employs a novel form of effect polymorphism which avoid mentioning effect variables in source code. This is achieved by propagating an ambient ability inwards, rather than accumulating unions of potential effects outwards. 
 We introduce Frank by example, and then give a formal account of the Frank type system and its semantics. We introduce Core Frank by elaborating Frank operators into functions, case expressions, and unary handlers, and then give a sound small-step operational semantics for Core Frank. 
 Programming with effects and handlers is in its infancy. We contribute an exploration of future possibilities, particularly in combination with other forms of rich type system.
Approximately Optimal Teaching of Approximately Optimal Learners

We propose a method of generating teaching policies for use in intelligent tutoring systems (ITS) for concept learning tasks <xref ref-type="bibr" rid="ref1">[1]</xref> , e.g., teaching students the meanings of words by showing images that exemplify their meanings à la Rosetta Stone <xref ref-type="bibr" rid="ref2">[2]</xref> and Duo Lingo <xref ref-type="bibr" rid="ref3">[3]</xref> . The approach is grounded in control theory and capitalizes on recent work by <xref ref-type="bibr" rid="ref4">[4] </xref> , <xref ref-type="bibr" rid="ref5">[5]</xref> that frames the “teaching” problem as that of finding approximately optimal teaching policies for approximately optimal learners (AOTAOL). Our work expands on <xref ref-type="bibr" rid="ref4">[4]</xref> , <xref ref-type="bibr" rid="ref5">[5]</xref> in several ways: (1) We develop a novel student model in which the teacher's actions can <italic>partially </italic> eliminate hypotheses about the curriculum. (2) With our student model, inference can be conducted <italic> analytically</italic> rather than numerically, thus allowing computationally efficient planning to optimize learning. (3) We develop a reinforcement learning-based hierarchical control technique that allows the teaching policy to search through <italic>deeper</italic> learning trajectories. We demonstrate our approach in a novel ITS for foreign language learning similar to Rosetta Stone and show that the automatically generated AOTAOL teaching policy performs favorably compared to two hand-crafted teaching policies.
Are test cases needed? Replicated comparison between exploratory and test-case-based software testing

Manual software testing is a widely practiced verification and validation method that is unlikely to fade away despite the advances in test automation. In the domain of manual testing, many practitioners advocate exploratory testing (ET), i.e., creative, experience-based testing without predesigned test cases, and they claim that it is more efficient than testing with detailed test cases. This paper reports a replicated experiment comparing effectiveness, efficiency, and perceived differences between ET and test-case-based testing (TCT) using 51 students as subjects, who performed manual functional testing on the jEdit text editor. Our results confirm the findings of the original study: 1) there is no difference in the defect detection effectiveness between ET and TCT, 2) ET is more efficient by requiring less design effort, and 3) TCT produces more false-positive defect reports than ET. Based on the small differences in the experimental design, we also put forward a hypothesis that the effectiveness of the TCT approach would suffer more than ET from time pressure. We also found that both approaches had distinctive issues: in TCT, the problems were related to correct abstraction levels of test cases, and the problems in ET were related to test design and logging of the test execution and results. Finally, we recognize that TCT has other benefits over ET in managing and controlling testing in large organizations.
Coverage in Wireless Sensor Networks : A Survey

Wireless Sensor Network is an emerging field which is accomplishing much importance because of its vast contribution in varieties of applications. Wireless Sensor Networks are used to monitor a given field of interest for changes in the environment. Coverage is one of the main active research interests in WSN.In this paper we aim to review the coverage problem In WSN and the strategies that are used in solving coverage problem in WSN.These strategies studied are used during deployment phase of the network. Besides this we also outlined some basic design considerations in coverage of WSN.We also provide a brief summary of various coverage issues and the various approaches for coverage in Sensor network.  Coverage; Wireless sensor networks: energy efficiency; sensor; area coverage; target Coverage.
Universal mobility-field curves for electrons and holes in MOS inversion layers

The mobility of carriers in a silicon surface inversion layer is one of the most important parameters required to accurately model and predict MOSFET device and circuit performance. It has been found that electron mobility follows a universal curve when plotted as a function of an effective normal field regardless of substrate bias, substrate doping (≤ 1017 cm-3) and nominal process variations . Although accurate modeling of p-channel MOS devices has become important due to the prevalence of CMOS technology, the existence of a universal hole mobility-field relationship has not been demonstrated. Furthermore, the effect on mobility of low-temperature and rapid high-temperature processing, which are commonly used in modern VLSI technology to control impurity diffusion, is unknown.
Tracking Multiple Vehicles Using a Variational Radar Model

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible. High-resolution radar sensors are able to resolve multiple measurements per object and therefore provide valuable information for vehicle environment perception. For instance, multiple measurements allow to infer the size of an object or to more precisely measure the object’s motion. Yet, the increased amount of data raises the demands on tracking modules: measurement models that are able to process multiple measurements for an object are necessary and measurement-toobject associations become more complex. This paper presents a new variational radar model for vehicles and demonstrates how this model can be incorporated in a Random-Finite-Setbased multi-object tracker. The measurement model is learned from actual data using variational Gaussian mixtures and avoids excessive manual engineering. In combination with the multiobject tracker, the entire process chain from the raw measurements to the resulting tracks is formulated probabilistically. The presented approach is evaluated on experimental data and it is demonstrated that data-driven measurement model outperforms a manually designed model.
Combined Nonlinear Echo Cancellation and Residual Echo Suppression

We describe a combined nonlinear acoustic echo cancellation and residual echo suppression system. The echo canceler uses parallel Hammerstein branches consisting of fixed nonlinear basis functions and linear adaptive filters. The residual echo suppressor uses an Artificial Neural Network for modeling of the residual echo spectrum from spectral features computed from the far-end signal. We show that modeling nonlinear effects both in the echo canceler and in the echo suppressor leads to an increased performance of the combined system.
Flapping wing mechanism design based on mechanical creative design theory

This research focuses on the flapping wing mechanism design for the micro air vehicle model. The paper starts with analysis the topological structure characteristics of Single-Crank Double-Rocker mechanism. Following the design procedure, all of the possible combinations of flapping mechanism which contains not more than 6 components were generated. The design procedure is based on Hong-Sen Yan's creative design theory for mechanical devices. This research designed 31 different types of mechanisms, which provide more directions for the design and fabrication of the micro air vehicle model.
Tai Chi improves pain and functional status in adults with rheumatoid arthritis: results of a pilot single-blinded randomized controlled trial.

Rheumatoid arthritis (RA) is a serious health problem resulting in significant morbidity and disability.  Chi may be beneficial to patients with RA as a result of effects on muscle strength and 'mind-body' interactions. To obtain preliminary data on the effects of Tai Chi on RA, we conducted a pilot randomized controlled trial. Twenty patients with functional class I or II RA were randomly assigned to Tai Chi or attention control in twice-weekly sessions for 12 weeks. The American College of Rheumatology (ACR) 20 response criterion, functional capacity, health-related quality of life and the depression index were assessed.



At 12 weeks, 5/10 patients (50%) randomized to Tai Chi achieved an ACR 20% response compared with 0/10 (0%) in the control (p = 0.03).  Chi had greater improvement in the disability index (p = 0.01), vitality subscale of the Medical Outcome Study Short Form 36 (p = 0.01) and the depression index (p = 0.003). Similar trends to improvement were also observed for disease activity, functional capacity and health-related quality of life. No adverse events were observed and no patients withdrew from the study.



Tai Chi appears safe and may be beneficial for functional class I or II RA. These promising results warrant further investigation into the potential complementary role of Tai Chi for treatment of RA.