nils-herrmann/clean_scirepeval huggingface dataset:
Improving Patient Safety through Simulation Training in Anesthesiology: Where Are We?
Venue: Anesthesiology research and practice

There have been colossal technological advances in the use of simulation in anesthesiology in the past 2 decades. Over the years, the use of simulation has gone from low fidelity to high fidelity models that mimic human responses in a startlingly realistic manner, extremely life like mannequin that breathes, generates E.K.G, and has pulses, heart sounds, and an airway that can be programmed for different degrees of obstruction. Simulation in anesthesiology is no longer a research fascination but an integral part of resident education and one of ACGME requirements for resident graduation. Simulation training has been objectively shown to increase the skill set of anesthesiologists. Anesthesiology is leading the movement in patient safety. It is rational to assume a relationship between simulation training and patient safety. Nevertheless there has not been a demonstrable improvement in patient outcomes with simulation training. Larger prospective studies that evaluate the improvement in patient outcomes are needed to justify the integration of simulation training in resident education but ample number of studies in the past 5 years do show a definite benefit of using simulation in anesthesiology training. This paper gives a brief overview of the history and evolution of use of simulation in anesthesiology and highlights some of the more recent studies that have advanced simulation based training.
Early imaging findings in germ cell tumors arising from the basal ganglia
Venue: Pediatric Radiology

BackgroundIt is difficult to diagnosis early stage germ cell tumors originating in the basal ganglia, but early recognition is important for better outcome.ObjectiveTo evaluate serial MR images of basal ganglia germ cell tumors, with emphasis on the features of early stage tumors.Materials and methodsWe retrospectively reviewed serial MR images of 15 tumors in 14 children and young adults. We categorized MR images of the tumors as follows: type I, ill defined patchy lesions <3 cm) without cyst; type II, small mass lesions <3 cm) with cyst; and type III, large lesions =3 cm) with cyst. We also assessed temporal changes of the MR images.ResultsOn the initial images, 8 of 11 (73% type I tumors progressed to types II or III, and 3 of 4 (75% type II tumors progressed to type III. The remaining 4 tumors did not change in type. All type II tumors (5/5, 100% that changed from type I had a few tiny cysts. Intratumoral hemorrhage was observed even in the type I tumor. Ipsilateral hemiatrophy was observed in most of the tumors (13/15, 87% on initial MR images. As tumors grew, cystic changes, intratumoral hemorrhage, and ipsilateral hemiatrophy became more apparent.ConclusionEarly stage basal ganglia germ cell tumors appear as ill defined small patchy hyperintense lesions without cysts on T2 weighted images, are frequently associated with ipsilateral hemiatrophy, and sometimes show microhemorrhage. Tumors develop tiny cysts at a relatively early stage.
Shared genetic effects between hepatic steatosis and fibrosis: A prospective twin study
Venue: Hepatology

Nonalcoholic fatty liver disease is associated with metabolic risk factors including hypertension and dyslipidemia and may progress to liver fibrosis. Studies have shown that hepatic steatosis and fibrosis are heritable, but whether they have a significant shared gene effect is unknown. This study examined the shared gene effects between hepatic steatosis and fibrosis and their associations with metabolic risk factors. This was a cross sectional analysis of a prospective cohort of well characterized, community dwelling twins (45 monozygotic, 20 dizygotic twin pairs, 130 total subjects) from southern California. Hepatic steatosis was assessed with magnetic resonance imaging proton density fat fraction and hepatic fibrosis with magnetic resonance elastography. A standard bivariate twin additive genetics and unique environment effects model was used to estimate the proportion of phenotypic variance between two phenotypes accounted for by additive genetic effects and individual specific environmental effects. Genetic correlations estimated from this model represent the degree to which the genetic determinants of two phenotypes overlap. Mean standard deviation) age and body mass index were 47.1 21.9) years and 26.2 5.8) kg/m2, respectively. Among the cohort, 20% (26/130) had hepatic steatosis (magnetic resonance imaging proton density fat fraction =5% and 8.2% (10/122) had hepatic fibrosis (magnetic resonance elastography =3 kPa) Blood pressure (systolic and diastolic) triglycerides, glucose, homeostatic model assessment of insulin resistance, insulin, hemoglobin A1c, and low high density lipoprotein had significant shared gene effects with hepatic steatosis. Triglycerides, glucose, homeostatic model assessment of insulin resistance, insulin, hemoglobin A1c, and low high density lipoprotein had significant shared gene effects with hepatic fibrosis. Hepatic steatosis and fibrosis had a highly significant shared gene effect of 0.756 (95% confidence interval 0.716 1, P 0.0001)  Genes involved with steatosis pathogenesis may also be involved with fibrosis pathogenesis.
Overview of glycerol reforming for hydrogen production

Hydrogen is used by the chemical industry in numerous processes, and today almost 95% is produced from raw materials based on fossil fuels, such as methane (CH4) However, catalytic reforming technologies face a number of technical and scientific challenges involving the quality of raw materials, conversion efficiency, and safety issues in the integration of systems of H2 production, purification and use, among others. Glycerol is a versatile raw material for H2 production because it is the main by product of biodiesel production, which a few years ago was consolidated in the world energy matrix and whose production continues to grow in the main consumer markets. Moreover, it has the noteworthy characteristic of decentralized production, which is directly reflected in its easy use. This paper presents a literature review on the reforming technologies applied to glycerol, the advantages of each route, and the main problems involved.
Combined Transverse Steel External FRP Confinement Model for Rectangular Reinforced Concrete Columns

Recently, the need to increase the strength of reinforced concrete members has become a subject that civil engineers are interested in tackling. Of the many proposed solutions, fiber reinforced polymer (FRP) materials have attracted attention due to their superior properties, such as high strength to weight ratio, high energy absorption and excellent corrosion resistance. FRP wrapping of concrete columns is done to enhance the ultimate strength due to the confinement effect, which is normally induced by steel ties. The existence of the two confinement systems changes the nature of the problem, thus necessitating specialized nonlinear analysis to obtain the column's ultimate capacity. Existing research focused on a single confinement system. Furthermore, very limited research on rectangular sections was found in the literature. In this work, a model to estimate the combined behavior of the two systems in rectangular columns is proposed. The calculation of the effective lateral pressure is based on the Lam and Teng model and the Mander model for FRP wraps and steel ties, respectively. The model then generates stress strain diagrams for both the concrete core and the cover. The model was developed for the analysis in extreme load events, where all possible contributions to the column's ultimate capacity should be accounted for without any margin of safety. The model was validated against experiments, and the results obtained showed good agreement with almost all of the available experimental data.
Mastering the game of Go with deep neural networks and tree search
Venue: Nature

The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses 'value networks' to evaluate board positions and 'policy networks' to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self play. Without any lookahead search, the neural networks play Go at the level of state of the art Monte Carlo tree search programs that simulate thousands of random games of self play. We also introduce a new search algorithm that combines Monte Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full sized game of Go, a feat previously thought to be at least a decade away.
Applications of Continuous Flow Photochemistry in Organic Synthesis, Material Science, and Water Treatment.
Venue: Chemical reviews

Continuous flow photochemistry in microreactors receives a lot of attention from researchers in academia and industry as this technology provides reduced reaction times, higher selectivities, straightforward scalability, and the possibility to safely use hazardous intermediates and gaseous reactants. In this review, an up to date overview is given of photochemical transformations in continuous flow reactors, including applications in organic synthesis, material science, and water treatment. In addition, the advantages of continuous flow photochemistry are pointed out and a thorough comparison with batch processing is presented.
Nutritional assessment of patients undergoing hemodialysis at dialysis centers in Belo Horizonte, MG, Brazil

This study aims to assess the nutritional status of patients undergoing he modialysis at dialysis centers in Belo Horizonte, MG, Brazil using the Subjective Global Assessment (SGA) and associate it with socioeconomic, demographic and clinical variables.  A total of 575 patients were evaluated at 12 dialysis centers in Belo Horizonte, MG, Brazil. Socioeconomic, demographic, and clinical variables were gathered through interviews using a questionnaire specifically developed for this purpose. The logistic regression model was used to determine the effect or influence of each vari able on the nutritional status.  Malnutrition was significantly prevalent (19.5% Generally, the study population had low socioeconomic status, limited access to private health services, high rate of comorbidities, and received a large number of dietary recommendations, which were not necessarily appropriate. According to multivariate analysis, the risk factors for malnutrition were age over 60 years, family income at or below one minimum wage, presence of depression, and retirement.  Malnutrition is prevalent among patients undergoing hemodialysis. Differences in socioeconomic, demographic, clinical, and general characteristics can be used to identify patients who require more attention due to the risk of malnutrition, particularly in the elderly, retirees, and those with depression and low socioeconomic status.
Common Sound Scenarios: A Context Driven Categorization of Everyday Sound Environments for Application in Hearing Device Research.
Venue: Journal of the American Academy of Audiology

Evaluation of hearing device signal processing features is performed for research and development purposes, but also in clinical settings. Most people agree that the benefit experienced in a hearing device user's daily life is most important, but laboratory tests are popular since they can be performed uniformly for all participants in a study using sensitive outcome measures. In order to design laboratory tests that have the potential of indicating real life benefit, there is a need for more information about the acoustic environments and listening situations encountered by hearing device users as well as by normal hearing people.  To investigate the acoustic environments and listening situations people encounter, and to provide a structured framework of common sound scenarios (CoSS) that can be used for instance when designing realistic laboratory tests.  A literature search was conducted. Extracted acoustic environments and listening situations were categorized using a context based approach. A set of common sound scenarios was established based on the findings from the literature.  A number of publications providing data on encountered acoustic environments and listening situations were identified. Focus was on studies including informants who reported or recorded information in field trials. Nine relevant references were found. In combination with data collected at our laboratory, 187 examples of acoustic environments or listening situations were found.  Based on the extracted data, a categorization approach based on context (intentions and tasks) was used when creating CoSS. Three intention categories, "speech communication," "focused listening," and "nonspecific" were divided into seven task categories. In each task category, two sound scenarios were described, creating in total 14 common sound scenarios. The literature search showed a general lack of studies investigating acoustic environments and listening situations, in particular studies where normal hearing informants are included and studies performed outside North America and Western Europe.  A structured framework was developed. Intentions and tasks constitute the main categories in the framework, and 14 common sound scenarios were selected and described. The framework can for instance be used when developing hearing device signal processing features, in the evaluation of such features in realistic laboratory tests, and for demonstration of feature effects to hearing device wearers.
A Clos Network Switch Architecture Based on Partially Buffered Crossbar Fabrics
Venue: 2016 IEEE 24th Annual Symposium on High Performance Interconnects (HOTI)

Modern Data Center Networks (DCNs) that scale to thousands of servers require high performance switches/routers to handle high traffic loads with minimum delays. Today's switches need be scalable, have good performance and more importantly be cost effective. This paper describes a novel three stage Clos network switching fabric with partially buffered crossbar modules and different scheduling algorithms. Compared to conventional fully buffered and buffer less switches, the proposed architecture fits a nice model between both designs and takes the best of both: i) less hardware requirements which considerably reduces both the cost and the implementation complexity, ii) the existence of few internal buffers allows for simple and high performance scheduling. Two alternative scheduling algorithms are presented. The first is scalable, it disperses the control function over multiple switching elements in the Clos network. The second is simpler. It places some control on a central scheduler to ensure an ordered packets delivery. Simulations for various switch settings and traffic profiles have shown that the proposed architecture is scalable. It maintains high throughput, low latency performance for less hardware used.
Development and Testing of a Two UAV Communication Relay System
Venue: Sensors

In the development of beyond line of sight (BLOS) Unmanned Aerial Vehicle (UAV) systems, communication between the UAVs and the ground control station (GCS) is of critical importance. The commonly used economical wireless modules are restricted by the short communication range and are easily blocked by obstacles. The use of a communication relay system provides a practical way to solve these problems, improving the performance of UAV communication in BLOS and cross obstacle operations. In this study, a communication relay system, in which a quadrotor was used to relay radio communication for another quadrotor was developed and tested. First, the UAVs used as the airborne platform were constructed, and the hardware for the communication relay system was selected and built up. Second, a set of software programs and protocol for autonomous mission control, communication relay control, and ground control were developed. Finally, the system was fully integrated into the airborne platform and tested both indoor and in flight. The Received Signal Strength Indication (RSSI) and noise value in two typical application scenarios were recorded. The test results demonstrated the ability of this system to extend the communication range and build communication over obstacles. This system also shows the feasibility to coordinate multiple UAVs' communication with the same relay structure.
Towards the automatic detection and identification of English puns

Lexical polysemy, a fundamental characteristic of all human languages, has long been regarded as a major challenge to machine translation, human computer interaction, and other applications of computational natural language processing (NLP) Traditional approaches to automatic word sense disambiguation (WSD) rest on the assumption that there exists a single, unambiguous communicative intention underlying every word in a document. However, writers sometimes intend for a word to be interpreted as simultaneously carrying multiple distinct meanings. This deliberate use of lexical ambiguity i.e. punning is a particularly common source of humour, and therefore has important implications for how NLP systems process documents and interact with users. In this paper we make a case for research into computational methods for the detection of puns in running text and for the isolation of the intended meanings. We discuss the challenges involved in adapting principles and techniques from WSD to humorously ambiguous text, and outline our plans for evaluating WSD inspired systems in a dedicated pun identification task. We describe the compilation of a large manually annotated corpus of puns and present an analysis of its properties. While our work is principally concerned with simple puns which are monolexemic and homographic (i.e. exploiting single words which have different meanings but are spelled identically) we touch on the challenges involved in processing other types
Efficient Acoustic Modeling Method for Unsupervised Speech Recognition using Multi Task Deep Neural Network

This paper proposes a method of acoustic modeling for zero resourced languages speech recognition under mismatch conditions. In those languages, very limited or no transcribed speech is available for traditional monolingual speech recognition. Conventional methods such as IPA based universal acoustic modeling has been proved to be effective under matched acoustic conditions (similar speaking styles, adjacent languages, etc. while usually poorly preformed when mismatch occurs. Since mismatch problems between languages often appears, in this paper, unsupervised acoustic modeling via cross lingual knowledge sharing has thus been proposed: first, initial acoustic models (AM) for a target zero resourced language are trained using Multi Task Deep Neural Networks (MDNN) different languages' speech mapped to the phonemes of the target language (mapped data) is jointly trained together with the same data transcribed language specifically and respectively (specific data) then, automatically transcribed target language data is used in the iterative process to train new AMs, with various auxiliary tasks. Experiment on 100 hour Japanese speech without transcripts achieved a character error rate (CER) of 57.21% 19.32% absolute improvement compared to baseline (IPA based universal acoustic modeling)
An integrated design and fabrication strategy for entirely soft, autonomous robots
Venue: Nature

Soft robots possess many attributes that are difficult, if not impossible, to achieve with conventional robots composed of rigid materials. Yet, despite recent advances, soft robots must still be tethered to hard robotic control systems and power sources. New strategies for creating completely soft robots, including soft analogues of these crucial components, are needed to realize their full potential. Here we report the untethered operation of a robot composed solely of soft materials. The robot is controlled with microfluidic logic that autonomously regulates fluid flow and, hence, catalytic decomposition of an on board monopropellant fuel supply. Gas generated from the fuel decomposition inflates fluidic networks downstream of the reaction sites, resulting in actuation. The body and microfluidic logic of the robot are fabricated using moulding and soft lithography, respectively, and the pneumatic actuator networks, on board fuel reservoirs and catalytic reaction chambers needed for movement are patterned within the body via a multi material, embedded 3D printing technique. The fluidic and elastomeric architectures required for function span several orders of magnitude from the microscale to the macroscale. Our integrated design and rapid fabrication approach enables the programmable assembly of multiple materials within this architecture, laying the foundation for completely soft, autonomous robots.
Challenges of MSMEs in India government initiatives for enhancing competitiveness of MSMEs in India.

The Micro, Small and Medium Enterprises (MSMEs) play a pivotal role in the economic and social development of the country, often acting as a nursery of entrepreneurship. They also play a key role in the development of the economy with their effective, efficient, flexible and innovative entrepreneurial spirit. The MSME sector contributes significantly to the country's manufacturing output, employment and exports and is credited with generating the highest employment growth as well as accounting for a major share of industrial production and exports. The objective of the paper is to examine the various opportunities and challenges faced by Indian MSME sector. Further, the study also focuses on evaluating the Government in policies and strategies and other measures initiated for promoting the competitiveness among the Indian MSMEs. Basically the study focused on six key challenges which the MSME sector has been facing, viz, Dearth of easy finance and credit instruments, limiting regulatory policies, unavailability of modern, affordable technology, lack of basic infrastructure facilities, absence of exclusive marketing platforms and distribution networks and inflexible labour laws and availability of affordable skilled labour. Despite the various challenges, the MSME sector has shown admirable innovativeness, adaptability and resilience to survive the recent economic downturn and contribute significantly to India's industrial growth. Finally the paper concluded with appropriate measures initiated by the government for enhancing the competitiveness of the sector.
Origin of the Anomalous Color of Egyptian and Han Blue Historical Pigments: Going beyond the Complex Approximation in Ligand Field Theory.

The complex approximation is widely used in the framework of the Ligand Field Theory for explaining the optical properties of crystalline coordination compounds. Here, we show that there are essential features of these systems that cannot be understood with the usual approximation that only considers an isolated complex at the correct equilibrium geometry. We also show that a quantitative understanding of such optical transitions cannot, in general, be reached unless the internal electric field, ER(r) created by the whole crystal on active electrons confined in the complex, is also taken into consideration. Seeking to prove the key role played by this internal field, usually ignored in crystalline transition metal compounds, we focus on the origin of the color displayed by the Egyptian Blue pigment (CaCuSi4O10) the first ever synthesized by humans. This pigment, together with Han Blue (BaCuSi4O10) are chosen as model systems because the anisotropic ER(r) field produces huge shifts, up to ~0.9 eV, in th.