nils-herrmann/clean_scirepeval huggingface dataset:
Ultrasound-Assisted Evaluation ofthe Airway in Clinical AnesthesiaPractice: Past, Present and Future

The incidence of difficulties encountered in perioperative airway management has been reported to range from 1% to 4%. In patients with head and neck cancers, the incidence can be dramatically higher. Because of high quality of imaging, non-invasiveness and relatively low cost, ultrasonography has been utilized as a valuable adjunct to the clinical assessment of the airway. A review of the literature was conducted with the objective of summarizing the available evidence concerning the use of ultrasound (US) for assessment of the airway, with special emphasis on head and neck cancers.  A systematic search of the literature in the MEDLINE database was performed. A total of 42 manuscripts from 329 searched articles were included in this review.  Ultrasonography was found to give high-resolution images of the anatomic structures of the upper airway comparable to computed tomography and magnetic resonance imaging. Several ultrasonographic parameters (soft tissue thickness at level of hyoid bone, epiglottis and vocal cords, visibility of hyoid bone in sublingual ultrasound, hyomental distance in head-extended position and hyomental distance ratio) were found to be independent predictors of difficult laryngoscopy in obese and non-obese patients. In conjunction with elastosonography, it also provided valuable information regarding tumors, infiltration, and edema as well as fibrosis of the head and neck.  Ultrasound-assisted evaluation of the difficult airway offers many important advantages. The ready availability of US machines in anesthesiology departments, familiarity of anesthesia providers with USguided procedures and the portability of US machines allow real-time, point-of-care assessment. It will undoubtedly become more popular and will greatly contribute to improve perioperative patient safety.
Defying Unjust Authority: An Exploratory Study

This research explores the psychological factors potentially involved in fostering disobedience to an unjust authority. Our paradigm was modeled after that of the Utrecht Studies on Obedience (Meeus and Raaijmakers European Journal of Social Psychology 16:311-324, 1986) in which participants are ordered to give each of 15 increasingly hostile comments to a participant/victim whenever he fails a trial. Although 30% of our sample followed commands to insult the other participant (confederate), the majority did refuse to do so at some point in the escalating hostility sequence. Our procedure utilized conditions known from prior research to increase the ratio of disobedience to obedience: proximity of teacher to learner plus remote authority. In order to better understand some of the cognitive and affective processes that may predict such defiant behaviour, we utilized a variety of measures, among them, behavioural observations, individual difference assessments, and in depth post-experimental interviews.
Bridging Neural Machine Translation and Bilingual Dictionaries

Neural Machine Translation (NMT) has become the new state-of-the-art in several language pairs. However, it remains a challenging problem how to integrate NMT with a bilingual dictionary which mainly contains words rarely or never seen in the bilingual training data. In this paper, we propose two methods to bridge NMT and the bilingual dictionaries. The core idea behind is to design novel models that transform the bilingual dictionaries into adequate sentence pairs, so that NMT can distil latent bilingual mappings from the ample and repetitive phenomena. One method leverages a mixed word/character model and the other attempts at synthesizing parallel sentences guaranteeing massive occurrence of the translation lexicon. Extensive experiments demonstrate that the proposed methods can remarkably improve the translation quality, and most of the rare words in the test sentences can obtain correct translations if they are covered by the dictionary.
Local potassium signaling couples neuronal activity to vasodilation in the brain

The mechanisms by which active neurons, via astrocytes, rapidly signal intracerebral arterioles to dilate remain obscure. Here we show that modest elevation of extracellular potassium (K+) activated inward rectifier K+ (Kir) channels and caused membrane potential hyperpolarization in smooth muscle cells (SMCs) of intracerebral arterioles and, in cortical brain slices, induced Kir-dependent vasodilation and suppression of SMC intracellular calcium (Ca2+) oscillations. Neuronal activation induced a rapid (<2 s latency) vasodilation that was greatly reduced by Kir channel blockade and completely abrogated by concurrent cyclooxygenase inhibition. Astrocytic endfeet exhibited large-conductance, Ca2+-sensitive K+ (BK) channel currents that could be activated by neuronal stimulation. Blocking BK channels or ablating the gene encoding these channels prevented neuronally induced vasodilation and suppression of arteriolar SMC Ca2+, without affecting the astrocytic Ca2+ elevation. These results support the concept of intercellular K+ channel–to–K+ channel signaling, through which neuronal activity in the form of an astrocytic Ca2+ signal is decoded by astrocytic BK channels, which locally release K+ into the perivascular space to activate SMC Kir channels and cause vasodilation.
Dose-response relationship in music therapy for people with serious mental disorders: systematic review and meta-analysis.

Serious mental disorders have considerable individual and societal impact, and traditional treatments may show limited effects. Music therapy may be beneficial in psychosis and depression, including treatment-resistant cases. The aim of this review was to examine the benefits of music therapy for people with serious mental disorders. All existing prospective studies were combined using mixed-effects meta-analysis models, allowing to examine the influence of study design (RCT vs. CCT vs. pre-post study), type of disorder (psychotic vs. non-psychotic), and number of sessions. Results showed that music therapy, when added to standard care, has strong and significant effects on global state, general symptoms, negative symptoms, depression, anxiety, functioning, and musical engagement. Significant dose-effect relationships were identified for general, negative, and depressive symptoms, as well as functioning, with explained variance ranging from 73% to 78%. Small effect sizes for these outcomes are achieved after 3 to 10, large effects after 16 to 51 sessions. The findings suggest that music therapy is an effective treatment which helps people with psychotic and non-psychotic severe mental disorders to improve global state, symptoms, and functioning. Slight improvements can be seen with a few therapy sessions, but longer courses or more frequent sessions are needed to achieve more substantial benefits.
Creativity support for novice digital filmmaking

Machinima is a new form of creative digital filmmaking that leverages the real time graphics rendering of computer game engines. Because of the low barrier to entry, machinima has become a popular creative medium for hobbyists and novices while still retaining borrowed conventions from professional filmmaking. Can novice machinima creators benefit from creativity support tools? A preliminary study shows novices generally have difficulty adhering to cinematographic conventions. We identify and document four cinematic conventions novices typically violate. We report on a Wizard-of-Oz study showing a rule-based intelligent system that can reduce the frequency of errors that novices make by providing information about rule violations without prescribing solutions. We discuss the role of error reduction in creativity support tools.
Adaptive Comparator Bias-Current Control of 0.6 V Input Boost Converter for ReRAM Program Voltages in Low Power Embedded Applications

A novel method adaptively controls the comparator bias current in a boost converter for sensor-data storage on Resistive Random Access Memory (ReRAM). ReRAM is ideal for low-power sensors because it is faster and lower voltage than NAND flash. However, ReRAM's voltage design needs to consider program current variation due to data pattern dependency and cell reliability is sensitive to small voltage fluctuations. The proposed control method of the boost converter architecture has three proposals. First, low program voltage ripple (VRIPPLE) and high program energy efficiency is obtained with an adaptive 2 to 8 μA comparator bias-current (ICMP) control method. ICMP is adjusted depending on the number of program bits (NBITS) in the SET data. In 2 cases of NBITS = 1 and 16, and compared to a conventional scheme (ICMP = 8 μA and 2 μA), respectively, VRIPPLE decreases by 41.2% and energy efficiency improves by 6.6%, respectively. Secondly, as NBITS decrease during SET verify, ICMP also decreases, which further reduces SET energy by 8.9 pJ. Thirdly, although the conventional boost converter fails in the `SS' process condition, an additional cross-coupled charge-pump boosts the buffer circuit, which provides full functional operation over the input range of 0.6 to 1.0 V.
A Survey of Automatic Event Detection in Multi-Camera Third Generation Surveillance Systems

Third generation surveillance systems are largely requested for intelligent surveillance of different scenarios such as public areas, urban traffic control, smart homes and so on. They are based on multiple cameras and processing modules that integrate data coming from a large surveillance space. The semantic interpretation of data from a multi view context is a challenging task and requires the development of image processing methodologies that could support applications in extensive and real time contexts. This paper presents a survey of automatic event detection functionalities that have been developed for third generation surveillance systems with a particular emphasis on open problems that limit the application of computer vision methodologies to commercial multi-camera systems.
User Interface Tools for Navigation in Conditional Probability Tables and Elicitation of Probabilities in Bayesian Networks

Elicitation of probabilities is one of the most laborious tasks in building decision-theoretic models, and one that has so far received only moderate attention in decision-theoretic sys­ tems. We propose a set of user interface tools for graphical probabilistic models, fo­ cusing on two aspects of probability elici­ tation: (1) navigation through conditional probability tables and (2) interactive graph­ ical assessment of discrete probability dis­ tributions. We propose two new graphical views that aid navigation in very large condi­ tional probability tables: the CPTREE (Con­ ditional Probability Tree) and the sCPT (shrinkable Conditional Probability Table). Based on what is known about graphical pre­ sentation of quantitative data to humans, we offer several useful enhancements to probabil­ ity wheel and bar graph, including different chart styles and options that can be adapted to user preferences and needs. We present the results of a simple usability study that proves the value of the proposed tools.
Overview on electrostatic discharge protection designs for mixed-voltage I/O interfaces: design concept and circuit implementations

Electrostatic discharge (ESD) protection design for mixed-voltage I/O interfaces has been one of the key challenges of system-on-a-chip (SOC) implementation in nano-scale CMOS processes. The on-chip ESD protection circuit for mixed-voltage I/O interfaces should meet the gate-oxide reliability constraints and prevent the undesired leakage current paths. This paper presents an overview on the design concept and circuit implementations of the ESD protection designs for mixed-voltage I/O interfaces without using the additional thick gate-oxide process. The ESD design constraints in mixed-voltage I/O interfaces, the classification and analysis of ESD protection designs for mixed-voltage I/O interfaces, and the designs of high-voltage-tolerant power-rail ESD clamp circuit are presented and discussed.
TCP ex machina: computer-generated congestion control

This paper describes a new approach to end-to-end congestion control on a multi-user network. Rather than manually formulate each endpoint's reaction to congestion signals, as in traditional protocols, we developed a program called Remy that generates congestion-control algorithms to run at the endpoints.
 In this approach, the protocol designer specifies their prior knowledge or assumptions about the network and an objective that the algorithm will try to achieve, e.g., high throughput and low queueing delay. Remy then produces a distributed algorithm---the control rules for the independent endpoints---that tries to achieve this objective.
 In simulations with ns-2, Remy-generated algorithms outperformed human-designed end-to-end techniques, including TCP Cubic, Compound, and Vegas. In many cases, Remy's algorithms also outperformed methods that require intrusive in-network changes, including XCP and Cubic-over-sfqCoDel (stochastic fair queueing with CoDel for active queue management).
 Remy can generate algorithms both for networks where some parameters are known tightly a priori, e.g. datacenters, and for networks where prior knowledge is less precise, such as cellular networks. We characterize the sensitivity of the resulting performance to the specificity of the prior knowledge, and the consequences when real-world conditions contradict the assumptions supplied at design-time.
The social side of gaming: a study of interaction patterns in a massively multiplayer online game

Playing computer games has become a social experience. Hundreds of thousands of players interact in massively multiplayer online games (MMORPGs), a recent and successful genre descending from the pioneering multi-user dungeons (MUDs). These new games are purposefully designed to encourage interactions among players, but little is known about the nature and structure of these interactions. In this paper, we analyze player-to-player interactions in two locations in the game Star Wars Galaxies. We outline different patterns of interactivity, and discuss how they are affected by the structure of the game. We conclude with a series of recommendations for the design and support of social activities within multiplayer games.
Performance Optimization of a High Current Dual Active Bridge with a Wide Operating Voltage Range

The main aim of this paper is to improve the performance of high current dual active bridge converters when operated over a wide voltage range. A typical application is for fuel cell vehicles where a bi-directional interface between a 12V battery and a high voltage DC bus is required. The battery side voltage ranges from 11V to 16V while the fuel cell is operated between 220V and 447V and the required power is typically 1kW. Careful analysis shows that the high currents on the battery side cause significant design issues in order to obtain a high efficiency. The standard phase shift modulation method can result in high conduction and switching losses. This paper proposes a combined triangular and trapezoidal modulation method to reduce losses over the wide operating range. Approximately, a 2% improvement in efficiency can be expected. An experimental system is used to verify the improved performance of the dual active bridge using the proposed advanced modulation method.
Color Correction of Underwater Images for Aquatic Robot Inspection

In this paper, we consider the problem of color restoration using statistical priors. This is applied to color recovery for underwater images, using an energy minimization formulation. Underwater images present a challenge when trying to correct the blue-green monochrome look to bring out the color we know marine life has. For aquatic robot tasks, the quality of the images is crucial and needed in real-time. Our method enhances the color of the images by using a Markov Random Field (MRF) to represent the relationship between color depleted and color images. The parameters of the MRF model are learned from the training data and then the most probable color assignment for each pixel in the given color depleted image is inferred by using belief propagation (BP). This allows the system to adapt the color restoration algorithm to the current environmental conditions and also to the task requirements. Experimental results on a variety of underwater scenes demonstrate the feasibility of our method.
The biology of facial fillers.

The biologic behavior of a facial filler determines its advantages and disadvantages. The purpose of this article is to look at the relevant biology as part of a logical basis for making treatment decisions. Historical perspectives and biologic characteristics such as local tissue reaction (including phagocytosis and granulomatous inflammation) cross-linking, particle concentration, immunogenicity, biofilm formation, gel hardness, and collagen neogenesis are considered. Bovine collagen is the most immunogenic facial filler. Porcine and bioengineered human collagen implants have very low immunogenicity, but allergic reactions and elevations of IgG are possible. Cross-linking and concentration affect the longevity of collagen and hyaluronic acid fillers. Gel hardness affects how a hyaluronic acid filler flows through the syringe and needle. Calcium hydroxylapatite, poly-L-lactic acid, and polymethylmethacrylate fillers have been shown to stimulate collagen neogenesis. It appears that any facial filler can form a granuloma. Bacterial biofilms may play a role in the activation of quiescent granulomas. Various authors interpret the definition and significance of a granuloma differently.
A Compact Meander-Line UHF RFID Tag Antenna Loaded With Elements Found in Right/Left-Handed Coplanar Waveguide Structures

A new planar meander-line antenna for passive UHF radio frequency identification (RFID) tags is presented. Specifically, a meander-line antenna is loaded periodically with coplanar waveguide (CPW) LC elements traditionally found in right/left-handed waveguide structures. It is shown that by using the antenna presented in this letter in a prototype passive UHF RFID tag, effective read ranges up to 4.87 m can be achieved. Many different dielectric substrates and CPW-LC load dimensions are investigated to illustrate how the input impedance, gain, and overall dimensions of the antenna are affected by these structural differences. It is shown that the overall dimension of the meander-line antenna can be reduced by slightly more than 18% with the introduction of the CPW-LC elements to the design. Several of the simulation results are validated by comparison with measurements.
Cellular and synaptic mechanisms of nicotine addiction.

The tragic health effects of nicotine addiction highlight the importance of investigating the cellular mechanisms of this complex behavioral phenomenon. The chain of cause and effect of nicotine addiction starts with the interaction of this tobacco alkaloid with nicotinic acetylcholine receptors (nAChRs). This interaction leads to activation of reward centers in the CNS, including the mesoaccumbens DA system, which ultimately leads to behavioral reinforcement and addiction. Recent findings from a number of laboratories have provided new insights into the biologic processes that contribute to nicotine self-administration. Examination of the nAChR subtypes expressed within the reward centers has identified potential roles for these receptors in normal physiology, as well as the effects of nicotine exposure. The high nicotine sensitivity of some nAChR subtypes leads to rapid activation followed in many cases by rapid desensitization. Assessing the relative importance of these molecular phenomena in the behavioral effects of nicotine presents an exciting challenge for future research efforts.
Observing Tutorial Dialogues Collaboratively: Insights About Human Tutoring Effectiveness From Vicarious Learning

The goals of this study are to evaluate a relatively novel learning environment, as well as to seek greater understanding of why human tutoring is so effective. This alternative learning environment consists of pairs of students collaboratively observing a videotape of another student being tutored. Comparing this collaboratively observing environment to four other instructional methods-one-on-one human tutoring, observing tutoring individually, collaborating without observing, and studying alone-the results showed that students learned to solve physics problems just as effectively from observing tutoring collaboratively as the tutees who were being tutored individually. We explain the effectiveness of this learning environment by postulating that such a situation encourages learners to become active and constructive observers through interactions with a peer. In essence, collaboratively observing combines the benefit of tutoring with the benefit of collaborating. The learning outcomes of the tutees and the collaborative observers, along with the tutoring dialogues, were used to further evaluate three hypotheses explaining why human tutoring is an effective learning method. Detailed analyses of the protocols at several grain sizes suggest that tutoring is effective when tutees are independently or jointly constructing knowledge: with the tutor, but not when the tutor independently conveys knowledge.
Automated Method for Discrimination of Arrhythmias Using Time, Frequency, and Nonlinear Features of Electrocardiogram Signals

We developed an automated approach to differentiate between different types of arrhythmic episodes in electrocardiogram (ECG) signals, because, in real-life scenarios, a software application does not know in advance the type of arrhythmia a patient experiences. Our approach has four main stages: (1) Classification of ventricular fibrillation (VF) versus non-VF segments—including atrial fibrillation (AF), ventricular tachycardia (VT), normal sinus rhythm (NSR), and sinus arrhythmias, such as bigeminy, trigeminy, quadrigeminy, couplet, triplet—using four image-based phase plot features, one frequency domain feature, and the Shannon entropy index. (2) Classification of AF versus non-AF segments. (3) Premature ventricular contraction (PVC) detection on every non-AF segment, using a time domain feature, a frequency domain feature, and two features that characterize the nonlinearity of the data. (4) Determination of the PVC patterns, if present, to categorize distinct types of sinus arrhythmias and NSR. We used the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, Creighton University’s VT arrhythmia database, the MIT-BIH atrial fibrillation database, and the MIT-BIH malignant ventricular arrhythmia database to test our algorithm. Binary decision tree (BDT) and support vector machine (SVM) classifiers were used in both stage 1 and stage 3. We also compared our proposed algorithm’s performance to other published algorithms. Our VF detection algorithm was accurate, as in balanced datasets (and unbalanced, in parentheses) it provided an accuracy of 95.1% (97.1%), sensitivity of 94.5% (91.1%), and specificity of 94.2% (98.2%). The AF detection was accurate, as the sensitivity and specificity in balanced datasets (and unbalanced, in parentheses) were found to be 97.8% (98.6%) and 97.21% (97.1%), respectively. Our PVC detection algorithm was also robust, as the accuracy, sensitivity, and specificity were found to be 99% (98.1%), 98.0% (96.2%), and 98.4% (99.4%), respectively, for balanced and (unbalanced) datasets.