LLukas22/scidocs huggingface dataset:
Direct substrate cooling of power electronics

Liquid jet impingement can be used to efficiently generate high heat transfer coefficients for cooling. However, optimization of the jet impingement array is complicated as a large number of geometrical parameters, such as array size, jet spacing and jet diameter affect performance. In the studies described in this paper a custom designed half-bridge substrate tile, supporting two IGBT and two diode dies, is cooled using liquid jet impingement onto the underside of the active metal brazed (AMB) Aluminium Nitride substrate tile. In order to reduce redundancy in the cooling system, the impingement array is designed to directly target the hot spots on the underside of the tile. A number of jet impingement arrays are designed and compared in order to determine which impingement geometry provides the most effective cooling. The performance of each cooling array is presented as a function of temperature rise of the IGBT dies with fluid flow rate, pressure drop across the cooler and pumping power required. A 6 × 6 array of 0.5mm diameter jets spaced at 2mm is found to be the most efficient. At a pumping power requirement of 5 W the jet impingement cooler is able to maintain the IGBT dies at a temperature 22.38°C above the water temperature while dissipating 400 W of heat. Further experimental work is discussed.
Highly efficient synthesis of graphene nanocomposites.

Graphene consists of a monolayer of sp(2) bonded carbon atoms and has attracted considerable interest over recent years due to its extreme mechanical, electrical, and thermal properties. Graphene nanocomposites have naturally begun to be studied to capitalize upon these properties. A range of complex chemical and physical processing methods have been devised that achieve isolated graphene sheets that attempt to prevent aggregation. Here we demonstrate that the simple casting of a polymer solution containing dispersed graphene oxide, followed by thermal reduction, can produce well-isolated monolayer reduced-graphene oxide. The presence of single layer reduced-graphene oxide is quantitatively demonstrated through transmission electron microscopy and selected area electron diffraction studies and the reduction is verified by thermogravimetric, X-ray photoelectron spectroscopy, infrared spectrum, and electrical conductivity studies. These findings provide a simple, environmentally benign and commercially viable process to produce reduced-graphene oxide reinforced polymers without complex manufacturing, dispersion or reduction processes.
Wavelet-based nonlinear multiscale decomposition model for electricity load forecasting

We propose a wavelet multiscale decomposition based autoregressive approach for the prediction of one-hour ahead ahead load based on historical electricity load data. This approach is based on a multiple resolution decomposition of the signal using the non-decimated or redundant Haar à trous wavelet transform whose advantage is taking into account the asymmetric nature of the time-varying data. There is an additional computational advantage in that there is no need to recompute the wavelet transform (wavelet coefficients) of the full signal if the electricity data (time series) is regularly updated. We assess results produced by this multiscale autoregressive (MAR) method, in both linear and non-linear variants, with single resolution autoregression (AR), multilayer perceptron (MLP), Elman recurrent neural network (ERN) and the general regression neural network (GRNN) models. Results are based on the New South Wales (Australia) electricity load data that is provided by the National Electricity Market Management Company (NEMMCO).
Mechanisms of dyspnoea relief and improved exercise endurance after furosemide inhalation in COPD.

BACKGROUND
This study examined the effects of inhaled furosemide on the ventilatory and perceptual response to high-intensity constant-load cycle exercise in chronic obstructive pulmonary disease (COPD).


METHODS
In a randomised, double-blind, placebo-controlled, crossover study, 20 patients with COPD (mean (SD) forced expiratory volume in 1 s 45 (15)% predicted) received either nebulised furosemide 40 mg or placebo on two separate days. Thirty minutes after each treatment, patients performed pulmonary function tests and a symptom-limited cycle exercise test at 75% of their maximum incremental work rate. Changes in spirometry, plethysmographic lung volumes, dynamic operating lung volumes, ventilation, breathing pattern, cardiovascular function, dyspnoea intensity and exercise endurance time were compared between treatments.


RESULTS
Compared with placebo, treatment with furosemide resulted in a mean (SD) decrease in dyspnoea intensity at the highest equivalent exercise time (ie, isotime for each patient) of 0.9 (1.0) Borg units (p<0.01) and an increase in exercise endurance time of 1.65 (0.63) min (p<0.05). These improvements were associated with increases in dynamic inspiratory capacity, tidal volume and mean tidal expiratory flow rates at isotime (p<0.01). The eight patients whose exercise endurance time improved by >1 min had greater changes in operating lung volumes (p<0.05), submaximal oxygen pulse (p<0.05) and oxygen uptake (p = 0.05) than those in whom exercise endurance time did not improve.


CONCLUSION
Alleviation of exertional dyspnoea after single-dose furosemide inhalation in COPD is multifactorial but improvements in dynamic ventilatory mechanics are contributory in some individuals.
Adapting word2vec to Named Entity Recognition

In this paper we explore how word vectors built using word2vec can be used to improve the performance of a classifier during Named Entity Recognition. Thereby, we discuss the best integration of word embeddings into the classification problem and consider the effect of the size of the unlabelled dataset on performance, reaching the unexpected result that for this particular task increasing the amount of unlabelled data does not necessarily increase the performance of the classifier.
Analysis of anonymous pooled urine from portable urinals in central London confirms the significant use of novel psychoactive substances.

AIM
Analysis of urine samples collected across a city centre, for the detection of novel psychoactive substances (NPS).


DESIGN
Cross-sectional study of anonymized urine samples used for the analysis of classical recreational drugs, NPS and metabolites.


METHODS
Pooled urine samples collected from portable stand-alone four-person urinals across a city centre were analysed using full-scan accurate-mass high-resolution liquid chromatography coupled to tandem mass spectrometry. Data were processed against compound databases containing >1700 drug compounds and metabolites.


RESULTS
Seven established recreational drugs (3,4-methylenedioxyamphetamine, cocaine, cannabis, ketamine, 3,4-methylenedioxy-N-methylamphetamine, methamphetamine and amphetamine) and six potential NPS [hordenine (all 12 urinals), cathine (11), methylhexaneamine (9), 4-methylmethcathinone (6), methiopropamine and metabolites (2) and methoxetamine and metabolites (1)] were detected. Methylhexaneamine, methiopropamine and hordenine are currently uncontrolled in the UK, whereas methoxetamine is currently subject to a Temporary Class Drug Order. Metabolites of the anabolic steroid nandrolone were found in two urinals and trenbolone metabolites and clenbuterol in one urinal.


CONCLUSION
Analysis of pooled urine samples collected anonymously from stand-alone urinals in a large inner city can detect the use of recreational drugs, NPS and anabolic steroids. Metabolite detection indicates actual drug use, metabolism and elimination rather than simply discarded drugs in the urinals. This technique by confirming the actual drug(s) used has the potential to be additive to currently used datasets/key indicators providing more robust information for healthcare authorities, legislative and law enforcement on the drugs actually being used.
1 Capacity-approaching DNA storage

Humanity produces data at exponential rates, creating a growing demand for better storage devices. DNA molecules are an attractive medium to store digital information due to their durability and high information density. Recent studies have made large strides in developing DNA storage schemes by exploiting the advent of massive parallel synthesis of DNA oligos and the high throughput of sequencing platforms. However, most of these experiments reported small gaps and errors in the retrieved information. Here, we report a strategy to store and retrieve DNA information that is robust and approaches the theoretical maximum of information that can be stored per nucleotide. The success of our strategy lies in careful adaption of recent developments in coding theory to the domain specific constrains of DNA storage. To test our strategy, we stored an entire computer operating system, a movie, a gift card, and other computer files with a total of 2.14×10 bytes in DNA oligos. We were able to fully retrieve the information without a single error even with a sequencing throughput on the scale of a single tile of an Illumina sequencing flow cell. To further stress our strategy, we created a deep copy of the data by PCR amplifying the oligo pool in a total of nine successive reactions, reflecting one complete path of an exponential process to copy the file 218×10 times. We perfectly retrieved the original data with only five million reads. Taken together, our approach opens the possibility of highly reliable DNA-based storage that approaches the information capacity of DNA molecules and enables virtually unlimited data retrieval. . CC-BY-NC 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/074237 doi: bioRxiv preprint first posted online Sep. 9, 2016;
A Multiple Train Trajectory Optimization to Minimize Energy Consumption and Delay

In railway operations, if the journey of a preceding train is disturbed, the service interval between it and the following trains may fall below the minimum line headway distance. If this occurs, train interactions will happen, which will result in extra energy usage, knock-on delays, and penalties for the operators. This paper describes a train trajectory (driving speed curve) optimization study to consider the tradeoff between reductions in train energy usage against increases in delay penalty in a delay situation with a fixed block signaling system. The interactions between trains are considered by recalculating the behavior of the second and subsequent trains based on the performance of all trains in the network, apart from the leading train. A multitrain simulator was developed specifically for the study. Three searching methods, namely, enhanced brute force, ant colony optimization, and genetic algorithm, are implemented in order to find the optimal results quickly and efficiently. The result shows that, by using optimal train trajectories and driving styles, interactions between trains can be reduced, thereby improving performance and reducing the energy required. This also has the effect of improving safety and passenger comfort.
Are art-museum visitors different from other people? The relationship between attendance and social and political attitudes in the United States☆

Abstract Most research on aesthetic taste and activities views familiarity with and participation in the arts as a type of cultural capital and emphasizes the relationship between taste and socioeconomic achievement. By contrast, this paper examines the manner in which arts participation is embedded in larger systems of meaning, by investigating the associations between one kind of artistic participation — art-museum visiting — and individuals' responses to ninety-four questions about their social, cultural, and political values and attitudes. Using multiple classification analysis, we identified numerous significant differences between U.S. art-museum visitors and other Americans, after adjusting for the effects of age, education, income, race, and gender. Art-museum visitors are somewhat more secular, trusting, politically liberal, racially tolerant, and open to other cultures and lifestyles, and much more tolerant and interested in high culture than are comparable non-visitors. These differences represent a distinctly modern disposition, evincing, first, a faith in progress and in scientific (and artistic) authority; and, second, an open, cosmopolitan orientation to both people and cultures. Affinities and tensions between this broader set of orientations and the strategic uses of cultural capital are addressed speculatively.
Emotion recognition in human computer interaction using multiple classifier systems

Initial work on automatic emotion recognition concentrates mainly on audio-based emotion classification. Speech is the most important channel for the communication between humans and it may expected that emotional states are trans-fered though content, prosody or paralinguistic cues. Besides the audio modality, with the rapidly developing computer hardware and video-processing devices researches start exploring the video modality. Visual-based emotion recognition works focus mainly on the extraction and recognition of emotional information from the facial expressions. There are also attempts to classify emotional states from body or head gestures and to combine different visual modalities, for instance facial expressions and body gesture captured by two separate cameras [3]. Emotion recognition from psycho-physiological measurements, such as skin conductance, respiration, electro-cardiogram (ECG), electromyography (EMG), electroencephalography (EEG) is another attempt. In contrast to speech, gestures or facial expressions these biopotentials are the result of the autonomic nervous system and cannot be imitated [4]. Research activities in facial expression and speech based emotion recognition [6] are usually performed independently from each other. But in almost all practical applications people speak and exhibit facial expressions at the same time, and consequently both modalities should be used in order to perform robust affect recognition. Therefore, multimodal, and in particularly audiovisual emotion recognition has been emerging in recent times [11], for example multiple classifier systems have been widely investigated for the classification of human emotions [1, 9, 12, 14]. Combining classifiers is a promising approach to improve the overall classifier performance [13, 8]. In multiple classifier systems (MCS) it is assumed that the raw data X originates from an underlying source, but each classifier receives different subsets of (X) of the same raw input data X. Feature vector F j (X) are used as the input to the j−th classifier computing an estimate y j of the class membership of F j (X). This output y j might be a crisp class label or a vector of class memberships, e.g. estimates of posteriori probabilities. Based on the multiple classifier outputs y 1 ,. .. , y N the combiner produces the final decision y. Combiners used in this study are fixed transformations of the multiple classifier outputs y 1 ,. .. , y N. Examples of such combining rules are Voting, (weighted) Averaging, and Multiplying, just to mention the most popular types. 2 Friedhelm Schwenker In addition to a priori fixed combination rules the combiner can be a …
PaperBot: open-source web-based search and metadata organization of scientific literature

The biomedical literature is expanding at ever-increasing rates, and it has become extremely challenging for researchers to keep abreast of new data and discoveries even in their own domains of expertise. We introduce PaperBot, a configurable, modular, open-source crawler to automatically find and efficiently index peer-reviewed publications based on periodic full-text searches across publisher web portals. PaperBot may operate stand-alone or it can be easily integrated with other software platforms and knowledge bases. Without user interactions, PaperBot retrieves and stores the bibliographic information (full reference, corresponding email contact, and full-text keyword hits) based on pre-set search logic from a wide range of sources including Elsevier, Wiley, Springer, PubMed/PubMedCentral, Nature, and Google Scholar. Although different publishing sites require different search configurations, the common interface of PaperBot unifies the process from the user perspective. Once saved, all information becomes web accessible allowing efficient triage of articles based on their actual relevance and seamless annotation of suitable metadata content. The platform allows the agile reconfiguration of all key details, such as the selection of search portals, keywords, and metadata dimensions. The tool also provides a one-click option for adding articles manually via digital object identifier or PubMed ID. The microservice architecture of PaperBot implements these capabilities as a loosely coupled collection of distinct modules devised to work separately, as a whole, or to be integrated with or replaced by additional software. All metadata is stored in a schema-less NoSQL database designed to scale efficiently in clusters by minimizing the impedance mismatch between relational model and in-memory data structures. As a testbed, we deployed PaperBot to help identify and manage peer-reviewed articles pertaining to digital reconstructions of neuronal morphology in support of the NeuroMorpho.Org data repository. PaperBot enabled the custom definition of both general and neuroscience-specific metadata dimensions, such as animal species, brain region, neuron type, and digital tracing system. Since deployment, PaperBot helped NeuroMorpho.Org more than quintuple the yearly volume of processed information while maintaining a stable personnel workforce.
Displacive transformations in Fe–Ni nanophase alloys

Abstract The crystallisation behaviour and subsequent transformation of the crystalline phase of amorphous alloys in the series (Fe 100− x Ni x ) 93− y Zr 7 B y , where y =16 and x =30 or y =12 and x =40,50 have been studied. The fabrication of amorphous precursors was performed using melt-spinning. The primary crystallisation products were α (b.c.c.) for x =30 and 40 but γ (c.c.p.) in the x =50 sample. In each of the alloys, the fully crystalline structure consisted of the γ phase and a metastable boride that could be removed by annealing at elevated temperature with the result of improved ductility. Attempts have been made to induce martensitic transformation in the nanophase and nanocrystalline γ structures. No evidence of transformation on quenching to liquid nitrogen temperature has been found in any of the samples across the composition range, regardless of the degree of devitrification. Transformation was observed in the fully crystalline x =30 alloy, induced by 20 min deformation in a high velocity ball-mill, but this was not possible at higher Ni contents. The partially crystalline, c.c.p. x =50 alloy has been found to be stable against transformation. A preliminary investigation into the effects of hydrostatic pressure on the devitrification behaviour has provided evidence that pressure acts to stabilise the γ phase at lower Ni contents than is required in the vacuum-annealed samples.
Endoscopic removal of an ectopic tooth in maxillary sinus.

Ectopic teeth erupted in the maxillary sinus are rarely reported. Although the causes of eruption of a tooth into the maxillary sinus are unclear, some clinical conditions are suspected to be responsible, such as developmental disturbances (cleft palate), displacement of teeth by trauma, interventions or cyst, infection, genetic factors, crowding, and dense bone. Most cases of ectopic teeth in the maxillary sinus are asymptomatic and are occasionally diagnosed thanks to routine radiographic investigations.The aim of this article is to present and discuss the surgical management of an ectopic third molar in the roof of the maxillary sinus.
Socioeconomic status and incidence of sudden cardiac arrest.

BACKGROUND
Low socioeconomic status is associated with poor cardiovascular health. We evaluated the association between socioeconomic status and the incidence of sudden cardiac arrest, a condition that accounts for a substantial proportion of cardiovascular-related deaths, in seven large North American urban populations.


METHODS
Using a population-based registry, we collected data on out-of-hospital sudden cardiac arrests occurring at home or at a residential institution from Apr. 1, 2006, to Mar. 31, 2007. We limited the analysis to cardiac arrests in seven metropolitan areas in the United States (Dallas, Texas; Pittsburgh, Pennsylvania; Portland, Oregon; and Seattle-King County, Washington) and Canada (Ottawa and Toronto, Ontario; and Vancouver, British Columbia). Each incident was linked to a census tract; tracts were classified into quartiles of median household income.


RESULTS
A total of 9235 sudden cardiac arrests were included in the analysis. For all sites combined, the incidence of sudden cardiac arrestin the lowest socioeconomic quartile was nearly double that in the highest quartile (incidence rate ratio [IRR] 1.9, 95% confidence interval [CI] 1.8-2.0). This disparity was greater among people less than 65 years old (IRR 2.7, 95% CI 2.5-3.0) than among those 65 or older (IRR 1.3, 95% CI 1.2-1.4). After adjustment for study site and for population age structure of each census tract, the disparity across socioeconomic quartiles for all ages combined was greater in the United States (IRR 2.0, 95% CI 1.9-2.2) than in Canada (IRR 1.8, 95% CI 1.6-2.0) (p<0.001 for interaction).


INTERPRETATION
The incidence of sudden cardiac arrest at home or at a residential institution was higher in poorer neighbourhoods of the US and Canadian sites studied, although the association was attenuated in Canada. The disparity across socioeconomic quartiles was greatest among people younger than 65. The association between socioeconomic status and incidence of sudden cardiac arrest merits consideration in the development of strategies to improve survival from sudden cardiac arrest, and possibly to identify opportunities for prevention.
Postmenopausal Tuberculosis Endometritis

Tuberculosis remains a global health problem, primarily in developing countries with inadequate health services. A significant portion of tuberculosis in these settings is extrapulmonary, including tuberculosis of the genitourinary tract. Patients with genital tuberculosis are usually young women detected during work up for infertility. After menopause, tuberculosis of the endometrium is a rare possibility probably because of the decreased vascularity of the tissues. We present a case of endometrial tuberculosis with postmenopausal vaginal bleeding.
A distributed frequent itemset mining algorithm using Spark for Big Data analytics

Frequent itemset mining is an essential step in the process of association rule mining. Conventional approaches for mining frequent itemsets in big data era encounter significant challenges when computing power and memory space are limited. This paper proposes an efficient distributed frequent itemset mining algorithm (DFIMA) which can significantly reduce the amount of candidate itemsets by applying a matrix-based pruning approach. The proposed algorithm has been implemented using Spark to further improve the efficiency of iterative computation. Numeric experiment results using standard benchmark datasets by comparing the proposed algorithm with the existing algorithm, parallel FP-growth, show that DFIMA has better efficiency and scalability. In addition, a case study has been carried out to validate the feasibility of DFIMA.
A Study of Selected Social and Economic Factors in the Formation of a Religious Vocation

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