Miracle-dz/UniFAR-FTUs huggingface dataset:
Physical Activity Levels of Physiotherapists across Practice Settings: A Cross-Sectional Comparison Using Self-Report Questionnaire and Accelerometer Measures.

Purpose: This article describes the physical activity of physiotherapists in British Columbia and examines differences across practice settings using self-report questionnaire and accelerometer-derived measures. Methods: Public and private practice physiotherapists aged 18-65 years were recruited through employee email lists and word of mouth to this cross-sectional study. Participants (n=98) completed the International Physical Activity Questionnaire-Long Form (IPAQ-L) online to quantify self-reported physical activity across various domains (occupational, leisure time, domestic, and transportation). Of these, 38 agreed to wear an accelerometer for 7 days to objectively measure physical activity. Descriptive statistics were used to describe self-reported and accelerometer-measured physical activity across domains, and inferential statistics were used to compare physical activity patterns across practice sites. The correlation and agreement between self-report questionnaire and accelerometer measures were also calculated. Results: Almost all (99%) of the physiotherapists self-reported meeting physical activity guidelines, and only 58% were classified as meeting guidelines when using accelerometers. Public practice physiotherapists self-reported more total, occupational, and domestic physical activity and had higher measured occupational physical activity than private practice physiotherapists. Overall, there was poor agreement between self-report questionnaires and accelerometers. Conclusions: Physiotherapists are an active group, with those in public practice reporting and participating in more physical activity than those in private practice.
Discourse Relations Detection via a Mixed Generative-Discriminative Framework

Word embeddings, which can better capture the fine-grained semantics of words, have proven to be useful for a variety of natural language processing tasks. However, because discourse structures describe the relationships between segments of discourse, word embeddings cannot be directly integrated to perform the task. In this paper, we introduce a mixed generative-discriminative framework, in which we use vector offsets between embeddings of words to represent the semantic relations between text segments and Fisher kernel framework to convert a variable number of vector offsets into a fixed length vector. In order to incorporate the weights of these offsets into the vector, we also propose the Weighted Fisher Vector. Experimental results on two different datasets show that the proposed method without using manually designed features can achieve better performance on recognizing the discourse level relations in most cases.
A phage-typing scheme for Salmonella enteritidis

SUMMARY For many years phage typing has proved invaluable in epidemiological studies on Salmonella typhi, S. paratyphi A and B, S. typhimurium and a few other serotypes. A phage-typing scheme for S. enteritidis is described. This scheme to date differentiates 27 types using 10 typing phages.
Serum components and activated Ha‐ras antagonize expression of perivenous marker genes stimulated by β‐catenin signaling in mouse hepatocytes

Hepatocytes of the periportal and perivenous zones of the liver lobule show marked differences in the contents and activities of many enzymes and other proteins. Previous studies from our and other groups have pointed towards an important role of β‐catenin‐dependent signaling in the regulation of expression of genes encoding proteins with preferential perivenous localization, whereas, in contrast, signaling through Ras‐dependent pathway(s) may induce a ‘periportal’ phenotype. We have now conducted a series of experiments to further investigate this hypothesis. In transgenic mice with scattered expression of an activated Ha‐ras (Ha‐rasG12V) mutant in liver, expression of the perivenous markers glutamine synthetase and two cytochrome P450 isoforms was completely abolished in those hepatocytes demonstrating constitutively activated extracellular signal‐regulated kinase activity, even though they were located directly adjacent to central veins. Similarly, incubation of primary hepatocytes or hepatoma cells with increasing amounts of serum caused a concentration‐dependent attenuation of expression of perivenous marker mRNAs, whereas the expression of periportal markers was increased. The inhibitory effect of high amounts of serum on the expression of perivenous markers was also observed if their expression was stimulated by activation of β‐catenin signaling, and comparable inhibitory effects were seen in cells stably transfected with a T‐cell factor/lymphoid‐enhancing factor‐driven luciferase reporter. Epidermal growth factor could partly mimic serum effects in hepatoma cells, and its effect could be blocked by an inhibitor of extracellular signal‐regulated kinase activity. These data suggest that activation of the Ras/mitogen‐activated protein kinase (extracellular signal‐regulated kinase) pathway favors periportal gene expression while simultaneously antagonizing a perivenous phenotype of hepatocytes.
Surveillance Video Synopsis in GIS

Surveillance videos contain a considerable amount of data, wherein interesting information to the user is sparsely distributed. Researchers construct video synopsis that contain key information extracted from a surveillance video for efficient browsing and analysis. Geospatial–temporal information of a surveillance video plays an important role in the efficient description of video content. Meanwhile, current approaches of video synopsis lack the introduction and analysis of geospatial-temporal information. Owing to the preceding problems mentioned, this paper proposes an approach called “surveillance video synopsis in GIS”. Based on an integration model of video moving objects and GIS, the virtual visual field and the expression model of the moving object are constructed by spatially locating and clustering the trajectory of the moving object. The subgraphs of the moving object are reconstructed frame by frame in a virtual scene. Results show that the approach described in this paper comprehensively analyzed and created fusion expression patterns between video dynamic information and geospatial–temporal information in GIS and reduced the playback time of video content.
Effects of supervised and unsupervised physical activity programmes for weight loss

Physical activity is important for weight management. However, it remains unclear what type of physical activity prescription/programme is optimal for increasing physical activity during a standard behavioural weight loss intervention. This study examined changes in physical activity after a 12‐week supervised programme prescribed in minutes per week (SUP‐PA), an unsupervised programme prescribed in minutes per week (UNSUP‐PA) and an unsupervised programme prescribed in steps per day (STEP).
Use of Antibiotic Prophylaxis for Tooth Extractions, Dental Implants, and Periodontal Surgical Procedures

Abstract Background Guidelines for antibiotics prior to dental procedures for patients with specific cardiac conditions and prosthetic joints have changed, reducing indications for antibiotic prophylaxis. In addition to guidelines focused on patient comorbidities, systematic reviews specific to dental extractions and implants support preprocedure antibiotics for all patients. However, data on dentist adherence to these recommendations are scarce. Methods This was a cross-sectional study of veterans undergoing tooth extractions, dental implants, and periodontal procedures. Patients receiving antibiotics for oral or nonoral infections were excluded. Data were collected through manual review of the health record. Results Of 183 veterans (mean age, 62 years; 94.5% male) undergoing the included procedures, 82.5% received antibiotic prophylaxis (mean duration, 7.1 ± 1.6 days). Amoxicillin (71.3% of antibiotics) and clindamycin (23.8%) were prescribed most frequently; 44.7% of patients prescribed clindamycin were not labeled as penicillin allergic. Of those who received prophylaxis, 92.1% received postprocedure antibiotics only, 2.6% received preprocedural antibiotics only, and 5.3% received pre- and postprocedure antibiotics. When prophylaxis was indicated, 87.3% of patients received an antibiotic. However, 84.9% received postprocedure antibiotics when preprocedure administration was indicated. While the majority of antibiotics were indicated, only 8.2% of patients received antibiotics appropriately. The primary reason was secondary to prolonged duration. Three months postprocedure, there were no occurrences of Clostridium difficile infection, infective endocarditis, prosthetic joint infections, or postprocedure oral infections. Conclusion The majority of patients undergoing a dental procedure received antibiotic prophylaxis as indicated. Although patients for whom antibiotic prophylaxis was indicated should have received a single preprocedure dose, most antibiotics were prescribed postprocedure. Dental stewardship efforts should ensure appropriate antibiotic timing, indication, and duration.
Identification of systems with unknown inputs using indirect input measurements

ABSTRACT A common issue with many system identification problems is that the true input to the system is unknown. This paper extends a previously presented indirect modelling framework that deals with identification of systems where the input is partially or fully unknown. In this framework, unknown inputs are eliminated by using additional measurements that directly or indirectly contain information about the unknown inputs. The resulting indirect predictor model is only dependent on known and measured signals and can be used to estimate the desired dynamics or properties. Since the input of the indirect model contains both known inputs and measurements that could all be correlated with the same disturbances as the output, estimation of the indirect model has similar challenges as a closed-loop estimation problem. In fact, due to the generality of the indirect modelling framework, it unifies a number of already existing system identification problems that are contained as special cases. For completeness, the paper is concluded with one method that can be used to estimate the indirect model as well as an experimental verification to show the applicability of the framework.
A Turkish-German Code-Switching Corpus

Bilingual communities often alternate between languages both in spoken and written communication. One such community, Germany residents of Turkish origin produce Turkish-German code-switching, by heavily mixing two languages at discourse, sentence, or word level. Code-switching in general, and Turkish-German code-switching in particular, has been studied for a long time from a linguistic perspective. Yet resources to study them from a more computational perspective are limited due to either small size or licence issues. In this work we contribute the solution of this problem with a corpus. We present a Turkish-German code-switching corpus which consists of 1029 tweets, with a majority of intra-sentential switches. We share different type of code-switching we have observed in our collection and describe our processing steps. The first step is data collection and filtering. This is followed by manual tokenisation and normalisation. And finally, we annotate data with word-level language identification information. The resulting corpus is available for research purposes.
SALM: Smartphone-Based Identity Authentication Using Lip Motion Characteristics

With rapid development and popularity, smartphones have been of importance in our daily life. Despite of its convenience in communication and computing, smartphones also lead potential security threats to users. Existing methods on smartphones for protecting user's privacy mainly depend on password or fingerprint based authentication. Most smartphone passwords are very simple and easy to guess or crack, and fingerprinting requires extra hardware and hence increases the price of smartphones. In this paper, we present a smartphone-based identity authentication method based on user's lip motion characteristics, called SALM, which can be used as an additional authentication with password. SALM extracts the feature of lip movements as the authentication token, which is unique for each user. We implement SALM using off-the-shelf smartphones and evaluate its performance via extensive experiments. The results show that the overall accuracy of user authentication using SALM (without password) is higher than 96%.
Utilization of Soluble Starch by Oleaginous Red Yeast Rhodotorula glutinis

Starch containing wastewaters from the food and feed industry have been identified as potential cheap carbon sources for the production of microbial lipids. Due to its high potential lipid content the oleaginous yeast Rhodotorula glutinis is often used for fermentations in this field. Moreover it is investigated in the context of microbial carotenoid production, which also requires a cheap source of carbon. Thus, the ability of R. glutinis (ATCC 15125TM) to degrade and utilize soluble starch for the production of lipids has been assessed in this study. While glucose and fructose were readily consumed from the medium, starch was only slightly reduced in one treatment. The yield of fatty acid methyl esters (FAME) was graduated corresponding to the initial sugar contents, with the highest FAME yield (1.5 g·L-1) at the highest initial sugar content. In the treatment that contained starch as single carbon source, no FAME production was realized. Accordingly, if starchy wastewaters should be used for microbial cultivation with R. glutinis, an enzymatic or chemical pretreatment for starch hydrolysis should be applied, to increase the availability of this carbon source.
Mining multi domain text reviews using semi-supervised approach

Opinion mining is growing area as people are sharing their views, opinions & experiences online. Automatic detection and analysis of sentiment around products, brands, political issues etc. is a challenging task. Domain adaptation is an important issue, which aims at transferring knowledge across domains or tasks. The labeling work may be time-consuming and expensive in order to build accurate opinion classifiers because of low generalization ability to new domains of supervised machine learning algorithms. Hence, domain adaptation algorithms are highly desirable to reduce domain dependency and labeling cost. The proposed approach classifies opinion words using maximum entropy and assigns weight using point wise mutual information. Results show that proposed approach performs moderately well compare to baseline method.
An Overview on Marine Sponge-Symbiotic Bacteria as Unexhausted Sources for Natural Product Discovery

Microbial symbiotic communities of marine macro-organisms carry functional metabolic profiles different to the ones found terrestrially and within surrounding marine environments. These symbiotic bacteria have increasingly been a focus of microbiologists working in marine environments due to a wide array of reported bioactive compounds of therapeutic importance resulting in various patent registrations. Revelations of symbiont-directed host specific functions and the true nature of host-symbiont interactions, combined with metagenomic advances detecting functional gene clusters, will inevitably open new avenues for identification and discovery of novel bioactive compounds of biotechnological value from marine resources. This review article provides an overview on bioactive marine symbiotic organisms with specific emphasis placed on the sponge-associated ones and invites the international scientific community to contribute towards establishment of in-depth information of the environmental parameters defining selection and acquisition of true symbionts by the host organisms.
5G beamforming implementation and trade-off investigation of cylindrical array arrangements

In this paper, we study the performance of a 5G network working at mmW range for the uplink. We consider a single base station scenario equipped with a cylindrical array and a circular array (which can be seen as a single ring cylindrical array), isotropic and directive antenna elements are taken into account and we evaluate the trade-off between antennas per ring and number of rings with fixed number of total antennas. Users are modeled as a spatial Binomial point process in a hexagonal cell. As beamforming techniques, Conventional and Capon algorithms have been considered. As main KPI to evaluate system performance, we consider average achievable per-user rate with different system configurations, such as network loading. The key result of the trade-off investigation is that, when the radius of the cell is much larger than the height of the base station, the best performance occurs when the cylindrical array degenerates in a circular array both when users lay at ground level and with random heights.
Real-Time Motor Unit Identification From High-Density Surface EMG

This study addresses online decomposition of high-density surface electromyograms (EMG) in real time. The proposed method is based on the previously published Convolution Kernel Compensation (CKC) technique and shares the same decomposition paradigm, i.e., compensation of motor unit action potentials and direct identification of motor unit (MU) discharges. In contrast to previously published version of CKC, which operates in batch mode and requires ~ 10 s of EMG signal, the real-time implementation begins with batch processing of ~ 3 s of the EMG signal in the initialization stage and continues on with iterative updating of the estimators of MU discharges as blocks of new EMG samples become available. Its detailed comparison to previously validated batch version of CKC and asymptotically Bayesian optimal linear minimum mean square error (LMMSE) estimator demonstrates high agreement in identified MU discharges among all three techniques. In the case of synthetic surface EMG with 20 dB signal-to-noise ratio, MU discharges were identified with average sensitivity of 98%. In the case of experimental EMG, real-time CKC fully converged after initial 5 s of EMG recordings and real-time and batch CKC agreed on 90% of MU discharges, on average. The real-time CKC identified slightly fewer MUs than its batch version (experimental EMG, 4 MUs versus 5 MUs identified by batch CKC, on average), but required only 0.6 s of processing time on regular personal computer for each second of multichannel surface EMG.
Role of grain boundary percolative defects and localized trap generation on the reliability statistics of high-κ gate dielectric stacks

Grain boundary (GB) microstructural defects in polycrystalline high-? dielectric thin films may cause localized non-random trap generation during the percolation breakdown (BD) process. We study the effect of this non-random trap generation on the reliability statistics of the metal gate (MG) - high-κ (HK) stack. For the first time, we propose a fundamental physics-based Kinetic Monte Carlo (KMC) model considering the thermodynamics and kinetics of bond breaking, generation of oxygen vacancy traps and simulating the trap evolution process in a dual-layer HK - interfacial layer (IL) gate stack. Our simulation model helps explain the non-Weibull distribution trends for time dependent dielectric breakdown data (TDDB) and also determine the sequence of BD which is found to be independent of the thickness ratio of (tHK : tIL) and gate voltage (Vg). Results show that the IL layer is always more susceptible to early percolation and circuit level failure may only be caused by multiple soft BD (SBD) events in the IL layer. The possibility of a sequential IL → HK breakdown is very unlikely for operating voltage conditions of Vop = 1V.
Childhood Discoid Lupus Erythematosus: A Report of Two Cases

Abstract: Discoid lupus erythematosus (DLE) is an uncommon disease in childhood. We present two patients initially diagnosed as impetigo and photosensitive eczema with impetigo, respectively, who failed to respond to topical and systemic antistaphylococcal agents and in whom a diagnosis of discoid lupus erythematosus subsequently became apparent.
Robustness of sensory-evoked excitation is increased by inhibitory inputs to distal apical tuft dendrites

Significance Even the simplest sensory stimulus activates millions of synapses across the cortex. How neurons integrate these highly specialized, but noisy synaptic input patterns to generate robust electrophysiological responses—that ultimately translate into behavior—remains elusive. Here, we provide first insight into a mechanism that may underlie the general phenomenon, observed across sensory modalities and species, that stimulation decreases variability in neuronal activity. Specifically, we show that during sensory stimulation, highly specialized inhibitory neurons provide synaptic input to distal dendrites of excitatory neurons, which reduces variability but not the mean amplitude of the response. Distal dendritic shunting may thus represent a general principle of cortex organization to ensure that noisy synaptic input patterns translate into robust sensory-evoked neuronal activity. Cortical inhibitory interneurons (INs) are subdivided into a variety of morphologically and functionally specialized cell types. How the respective specific properties translate into mechanisms that regulate sensory-evoked responses of pyramidal neurons (PNs) remains unknown. Here, we investigated how INs located in cortical layer 1 (L1) of rat barrel cortex affect whisker-evoked responses of L2 PNs. To do so we combined in vivo electrophysiology and morphological reconstructions with computational modeling. We show that whisker-evoked membrane depolarization in L2 PNs arises from highly specialized spatiotemporal synaptic input patterns. Temporally L1 INs and L2–5 PNs provide near synchronous synaptic input. Spatially synaptic contacts from L1 INs target distal apical tuft dendrites, whereas PNs primarily innervate basal and proximal apical dendrites. Simulations of such constrained synaptic input patterns predicted that inactivation of L1 INs increases trial-to-trial variability of whisker-evoked responses in L2 PNs. The in silico predictions were confirmed in vivo by L1-specific pharmacological manipulations. We present a mechanism—consistent with the theory of distal dendritic shunting—that can regulate the robustness of sensory-evoked responses in PNs without affecting response amplitude or latency.
SweetSEQer, Simple de Novo Filtering and Annotation of Glycoconjugate Mass Spectra

The past 15 years have seen significant progress in LC-MS/MS peptide sequencing, including the advent of successful de novo and database search methods; however, analysis of glycopeptide and, more generally, glycoconjugate spectra remains a much more open problem, and much annotation is still performed manually. This is partly because glycans, unlike peptides, need not be linear chains and are instead described by trees. In this study, we introduce SweetSEQer, an extremely simple open source tool for identifying potential glycopeptide MS/MS spectra. We evaluate SweetSEQer on manually curated glycoconjugate spectra and on negative controls, and we demonstrate high quality filtering that can be easily improved for specific applications. We also demonstrate a high overlap between peaks annotated by experts and peaks annotated by SweetSEQer, as well as demonstrate inferred glycan graphs consistent with canonical glycan tree motifs. This study presents a novel tool for annotating spectra and producing glycan graphs from LC-MS/MS spectra. The tool is evaluated and shown to perform similarly to an expert on manually curated data.