Miracle-dz/UniFAR-FTUs huggingface dataset:
Therapeutic Potential of Buprenorphine in Depression: A Meta-Analysis of Current Evidence

Background Emerging research indicates buprenorphine, used in management of opioid use disorder, has attracted interest for its potential in treating a variety of psychiatric conditions. This meta-analysis aimed to determine the efficacy of buprenorphine in treating symptoms of depression. Methods Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a search was conducted of several databases until April 25, 2022, for English language articles related to buprenorphine and its use in treating various mental health conditions. Standardized mean differences (SMDs) and its 95% confidence intervals (CIs) were reported for the Hamilton Rating Scale for Depression (HAM-D) and the Montgomery-Asberg Depression Rating Scale (MADRS) scores. Statistical analyses were performed using Cochrane RevMan 5. Results Of the 1,347 identified studies, six clinical trials were included. MADRS-10 least square mean difference (LSMD) inter-group assessment favored buprenorphine over placebo, but it lacked statistical significance. Similarly, MADRS scores as well as HAM-D inter-group assessment were in favor of buprenorphine, however, were not statistically significant. These findings suggest a potential therapeutic role for buprenorphine in treating depression, albeit with caution due to the observed lack of statistical significance and the potential for confounding factors. Conclusions Preliminary evidence suggests potential efficacy of buprenorphine at lower doses in improving improving outcomes specifically related to depression. However, due to limitations in statistical significance and possible confounding factors, entail cautious interpretation. Further rigorous research is needed to investigate the long-term effects, optimal dosing, and determine the role of adjuvant drug therapy.
Comparison of the Transmembrane Mucins MUC1 and MUC16 in Epithelial Barrier Function

Membrane-anchored mucins are present in the apical surface glycocalyx of mucosal epithelial cells, each mucosal epithelium having at least two of the mucins. The mucins have been ascribed barrier functions, but direct comparisons of their functions within the same epithelium have not been done. In an epithelial cell line that expresses the membrane-anchored mucins, MUC1 and MUC16, the mucins were independently and stably knocked down using shRNA. Barrier functions tested included dye penetrance, bacterial adherence and invasion, transepithelial resistance, tight junction formation, and apical surface size. Knockdown of MUC16 decreased all barrier functions tested, causing increased dye penetrance and bacterial invasion, decreased transepithelial resistance, surprisingly, disruption of tight junctions, and greater apical surface cell area. Knockdown of MUC1 did not decrease barrier function, in fact, barrier to dye penetrance and bacterial invasion increased significantly. These data suggest that barrier functions of membrane-anchored mucins vary in the context of other membrane mucins, and MUC16 provides a major barrier when present.
T Cell-Dependence of Lassa Fever Pathogenesis

Lassa virus (LASV), the causative agent of Lassa fever (LF), is endemic in West Africa, accounting for substantial morbidity and mortality. In spite of ongoing research efforts, LF pathogenesis and mechanisms of LASV immune control remain poorly understood. While normal laboratory mice are resistant to LASV, we report that mice expressing humanized instead of murine MHC class I (MHC-I) failed to control LASV infection and develop severe LF. Infection of MHC-I knockout mice confirmed a key role for MHC-I-restricted T cell responses in controlling LASV. Intriguingly we found that T cell depletion in LASV-infected HHD mice prevented disease, irrespective of high-level viremia. Widespread activation of monocyte/macrophage lineage cells, manifest through inducible NO synthase expression, and elevated IL-12p40 serum levels indicated a systemic inflammatory condition. The absence of extensive monocyte/macrophage activation in T cell-depleted mice suggested that T cell responses contribute to deleterious innate inflammatory reactions and LF pathogenesis. Our observations in mice indicate a dual role for T cells, not only protecting from LASV, but also enhancing LF pathogenesis. The possibility of T cell-driven enhancement and immunopathogenesis should be given consideration in future LF vaccine development.
Feature Correlation Attack on Biometric Privacy Protection Schemes

Privacy protection techniques are an important supplementary of biometric systems. Their main purpose is to prevent security leakages in common biometric systems and to preserve the user's privacy. However, when cryptographic functions are used in the algorithms, randomness of biometric features is strictly required from the security point of view. This randomness is hard to achieve in many feature extraction algorithms, especially for those using the local information of biometric modality. In this paper we discuss privacy protection based on a fuzzy extractor. We show that the security of the algorithm is strongly reduced when statistical properties of biometric features as well as the details of the algorithm are known. An attack exploiting feature correlation is demonstrated.
Functional Relationships between Capacitation-dependent Cell Signaling and Compartmentalized Metabolic Pathways in Murine Spermatozoa*

Spermatozoa are highly polarized cells with specific metabolic pathways compartmentalized in different regions. Previously, we hypothesized that glycolysis is organized in the fibrous sheath of the flagellum to provide ATP to dynein ATPases that generate motility and to protein kinases that regulate motility. Although a recent report suggested that glucose is not essential for murine sperm capacitation, we demonstrated that glucose (but not lactate or pyruvate) was necessary and sufficient to support the protein tyrosine phosphorylation events associated with capacitation. The effect of glucose on this signaling pathway was downstream of cAMP, and appeared to arise indirectly as a consequence of metabolism as opposed to a direct signaling effect. Moreover, the phosphorylation events were not affected by uncouplers of oxidative respiration, inhibitors of electron transfer, or by a lack of substrates for oxidative respiration in the medium. Further experiments aimed at identifying potential regulators of sperm glycolysis focused on a germ cell-specific isoform of hexokinase, HK1-SC, which localizes to the fibrous sheath. HK1-SC activity and biochemical localization did not change during sperm capacitation, suggesting that glycolysis in sperm is regulated either at the level of substrate availability or by downstream enzymes. These data support the hypothesis that ATP specifically produced by a compartmentalized glycolytic pathway in the principal piece of the flagellum, as opposed to ATP generated by mitochondria in the mid-piece, is strictly required for protein tyrosine phosphorylation events that take place during sperm capacitation. The relationship between these pathways suggests that spermatozoa offer a model system for the study of integration of compartmentalized metabolic and signaling pathways.
Role of sigma H in expression of the fumarase gene (citG) in vegetative cells of Bacillus subtilis 168

The fumarase gene (citG) of Bacillus subtilis is transcribed from two promoter regions, citGp1 and citGp2 (P1 and P2); the P2 promoter is used by the E sigma H form of RNA polymerase. In order to study the role of P1 and P2 in citG expression, the promoter region and various deletion derivatives that effectively separate P1 and P2 were fused to the Escherichia coli beta-galactosidase gene (lacZ) and introduced into the chromosome in single copy at the amyE locus. P1 functioned to provide a relatively low and stable basal level of fumarase activity throughout growth. In contrast, P2 activity was found to vary over at least a 50-fold range and was responsible for regulating fumarase activity during growth and sporulation in a rich medium and in response to changes in carbon source. To further investigate the role of sigma H in fumarase regulation, citGp2-lacZ fusions were introduced into a strain in which the expression of the chromosomal spoOH gene was under the control of the isopropylthiogalactopyranoside-inducible spac promoter. Induction of pspac did not lead to P2 induction, suggesting that citG expression is not regulated at the level of spoOH transcription.
Effect of Variations in Long-Duration Rainfall Intensity on Unsaturated Slope Stability

In recent years, many scientific methods have been used to prove that the Earth’s climate is changing. Climate change can affect rainfall patterns, which can in turn affect slope safety. Therefore, this study analyzed the effects of climate change on rainfall patterns from the perspective of rainfall intensity. This analysis was combined with numerical model analysis to examine the rainfall patterns of the Zengwen reservoir catchment area and its effects on slope stability. In this study, the Mann–Kendall test and the Theil–Sen estimator were used to analyze the rainfall records of rainfall stations at Da-Dong-Shan, Ma-To-Shan, and San-Jiao-Nan-Shan. The rainfall intensity of the Zengwen reservoir catchment area showed an increasing trend from 1990–2016. In addition, the analysis results of rainfall intensity trends were used for qualitative analysis of seepage and slope stability. The trend analysis result showed that in the future, from 2017–2100, if the amount of rainfall per hour continues to rise at about 0.1 mm per year, the amount of seepage will increase at the slope surface boundary and significantly change pore water pressure in the soil. As a result, the time of the occurrence of slope instability after the start of rainfall will decrease from 20 to 13 h, and the reduction in the safety coefficient will increase from 32 to 41%. Therefore, to decrease the effects of slope disasters on the safety of the Zengwen reservoir and its surrounding areas, changes in rainfall intensity trends should be considered for slope safety in this region. However, the results of trend analyses were weak and future research is needed using a wider range of precipitation data and detailed hydrological analysis to better predict rainfall pattern variations.
Towards a Common Air Traffic Control Simulation Scenario Development

Although the importance of scenarios in Air Traffic Control (ATC) training and simulation has long been well known, there still exists a lack of common understanding and standardized practices in scenario development in this domain. It is an extensive process beginning with the stakeholders’ descriptions of the scenario and finishing with the generation of the corresponding executable specifications. The purpose of developing an ATC Scenario Language is to implement a standard scenario specification that will lead to a common mechanism for specifying, verifying and executing ATC scenarios, effective sharing of scenarios among various simulation and training environments, improve the consistency among different training modules, and enable the reuse of scenario specifications. The proposed ATC Scenario Language is built as an extension to the newly published Aviation Scenario Definition Language (ASDL), complementing ASDL to support ATC scenario specification.
Self-reported health parameters compared with clinician measurements: methods in practice-based research.

CONTEXT Self-reported health data are used by health insurance companies to assess risk. Most studies show underreporting compared with clinical measurements. OBJECTIVE To compare self-reported height, weight, blood pressure, waist circumference, and dietary intake with registered dietitian's (RD's) measures of the same parameters. DESIGN This is a secondary analysis of data collected in a larger study on the benefits of Medical Nutrition Therapy from an RD for overweight and obese patients when provided free of charge through an insurance benefit. SETTING Participants completed a health risk assessment survey at home, from which the self-reported measures were extracted. The clinical measurements were taken by an RD in the office during a visit for Medical Nutrition Therapy. PARTICIPANTS Participants were 81.4% female, with a mean body mass index of 35.0. All were insured and had a least 1 visit with an RD. MAIN OUTCOME MEASURE(S) Main outcomes were correlation between self-reported and RD-measured height, weight, body mass index, blood pressure, and waist circumference. Blood pressure was categorized as normal or high and the κ statistic was used to examine category agreement between the 2 measures. Servings of food groups were compared between the 2 measures by examining cumulative percent within 0, 1, or 2 servings of the RD-measured value. RESULTS The 2 measures of height and weight were highly correlated (0.974 and 0.986, respectively). Blood pressure was more weakly correlated and when categorized had low κ scores, as did servings of food groups. CONCLUSIONS Height and weight were more closely correlated than in previous studies. In an insured population enrolled in a weight management program, self-reported measures may be accurate for determining program impact. Blood pressure may be better collected categorically than continuously. The necessity of food intake assessment on a risk assessment should be reconsidered.
Characterisation of the Transcriptomes of Genetically Diverse Listeria monocytogenes Exposed to Hyperosmotic and Low Temperature Conditions Reveal Global Stress-Adaptation Mechanisms

The ability of Listeria monocytogenes to adapt to various food and food- processing environments has been attributed to its robustness, persistence and prevalence in the food supply chain. To improve the present understanding of molecular mechanisms involved in hyperosmotic and low-temperature stress adaptation of L. monocytogenes, we undertook transcriptomics analysis on three strains adapted to sub-lethal levels of these stress stimuli and assessed functional gene response. Adaptation to hyperosmotic and cold-temperature stress has revealed many parallels in terms of gene expression profiles in strains possessing different levels of stress tolerance. Gene sets associated with ribosomes and translation, transcription, cell division as well as fatty acid biosynthesis and peptide transport showed activation in cells adapted to either cold or hyperosmotic stress. Repression of genes associated with carbohydrate metabolism and transport as well as flagella was evident in stressed cells, likely linked to activation of CodY regulon and consequential cellular energy conservation.
FST-based recognition techniques for multi-lingual and multi-domain spontaneous speech

In this paper we present techniques for building multi-domain and multi-lingual recognizers within a finite-state transducer (FST) framework. The fle xibility of the FST approach is also demonstrated on the task of incorporating networks modeling different types of non-speech events into an existing word lattice network. The ability to create robust multi-domain and/or multi-lingual recognizers for spontaneous speech will enable a conversational system to switch seamlessly and automatically among different domains and/or languages. Preliminary results using a bi-domain recognizer exhibit only small recognition accuracy degradation in comparison to domain-dependent recognition. Similarly promising results were observed using a bilingual recognizer which performs simultaneous language identification and recognition. When using the FST techniques to add non-speech models to the recognizer, experiments show a 10% reduction in word error rate across all utterances and a 30% reduction on utterances containing non-speech events.
Execution-based prediction using speculative slices

A relatively small set of static instructions has significant leverage on program execution performance. These problem instructions contribute a disproportionate number of cache misses and branch mispredictions because their behavior cannot be accurately anticipated using existing prefetching or branch prediction mechanisms. The behavior of many problem instructions can be predicted by executing a small code fragment called a speculative slice. If a speculative slice is executed before the corresponding problem instructions are fetched then the problem instructions can move smoothly through the pipeline because the slice has tolerated the latency of the memory hierarchy (for loads) or the pipeline (for branches). This technique results in speedups up to 43 percent over an aggressive baseline machine. To benefit from branch predictions generated by speculative slices, the predictions must be bound to specific dynamic branch instances. We present a technique that invalidates predictions when it can be determined (by monitoring the program's execution path) that they will not be used. This enables the remaining predictions to be correctly correlated.
SAR Image Despeckling Based on Local Homogeneous-Region Segmentation by Using Pixel-Relativity Measurement

This paper provides a novel pointwise-adaptive speckle filter based on local homogeneous-region segmentation with pixel-relativity measurement. A ratio distance is proposed to measure the distance between two speckled-image patches. The theoretical proofs indicate that the ratio distance is valid for multiplicative speckle, while the traditional Euclidean distance failed in this case. The probability density function of the ratio distance is deduced to map the distance into a relativity value. This new relativity-measurement method is free of parameter setting and more functional compared with the Gaussian kernel-projection-based ones. The new measurement method is successfully applied to segment a local shape-adaptive homogeneous region for each pixel, and a simplified strategy for the segmentation implementation is given in this paper. After segmentation, the maximum likelihood rule is introduced to estimate the true signal within every homogeneous region. A novel evaluation metric of edge-preservation degree based on ratio of average is also provided for more precise quantitative assessment. The visual and numerical experimental results show that the proposed filter outperforms the existing state-of-the-art despeckling filters.
Extracting Patterns of Urban Activity from Geotagged Social Data

Data generated on location-based social networks provide rich information on the whereabouts of urban dwellers. Specifically, such data reveal who spends time where, when, and on what type of activity (e.g., shopping at a mall, or dining at a restaurant). That information can, in turn, be used to describe city regions in terms of activity that takes place therein. For example, the data might reveal that citizens visit one region mainly for shopping in the morning, while another for dining in the evening. Furthermore, once such a description is available, one can ask more elaborate questions: What are the features that distinguish one region from another -- is it simply the type of venues they host or is it the visitors they attract? What regions are similar across cities? In this paper, we attempt to answer these questions using publicly shared Foursquare data. In contrast with previous work, our method makes use of a probabilistic model with minimal assumptions about the data and thus relieves us from having to make arbitrary decisions in our analysis (e.g., regarding the granularity of discovered regions or the importance of different features). We perform an empirical comparison with previous work and discuss insights obtained through our findings.
Macro-action Discovery Based on Change Point Detection and Boosting

We present a novel approach to automatic macroaction discovery and its application to a complex goal-planning task. The problem of macro-action discovery is framed as one of multiple change point detection and is addressed with the help of the Dynamic Programming Boosting algorithm. The procedure is then employed to solve a complex goal-planning problem which entails an avatar navigating a 3D environment. By using DPBoost to decompose the problem into a number of simpler ones, we are able to successfully address both the complexity and partial observability of the environment.
Continuous Speech Recognition Using Segmental Neural Nets

The authors present the concept of a 'segmental neural net' (SNN) for phonetic modeling in continuous speech recognition (CSR) and show how this can be used, together with a hidden Markov model (HMM) system, to improve continuous speech recognition (CSR). The SNN is a segment-based model that uses a neural network to correlate features of the speech signal throughout the duration of a phonetic segment. The problem of handling phonetic segments of varying length is solved by applying a warping function which provides the neural network inputs with a fixed-length representation of the segment. This method of modeling speech differs from that of HMMs, which assume that speech frames are conditionally independent. To take advantage of the training and decoding speed of HMMs, a hybrid SNN/HMM system has been developed to combine the advantages of both types of approaches. In this hybrid system, use is made of the N-best paradigm to generate likely phonetic segmentations, which are then scored by the SNN. The HMM and SNN scores are then combined to optimize performance. <<ETX>>
CrowdWatch: pedestrian safety assistance with mobile crowd sensing

Pedestrians distracted by smartphones are easy to meet with various dangers when crossing or walking on the street. To help them, we propose CrowdWatch, a system that leverages crowd-powered smartphone sensing to make fine-grained characterization of the sensing field and provides context-aware alerts to pedestrians for their safety. The crowd data including acceleration, orientation, and GPS reflects the behavior of the crowd in three different situations: crossing roads, waiting traffic lights, and encountering obstacles. We present details about applying the behavior of the crowd into the system in this paper. What's more, under different contexts/situations, different reminders are delivered. Experiment results indicate that CrowdWatch is effective in safety dynamics detection.
AN investigation into features for multi-view lipreading

For the first time in this paper we present results showing the effect of speaker head pose angle on automatic lip-reading performance over a wide range of closely spaced angles. We analyse the effect head pose has upon the features themselves and show that by selecting coefficients with minimum variance w.r. t. pose angle, recognition performance can be improved when train-test pose angles differ. Experiments are conducted using the initial phase of a unique multi view Audio-Visual database designed specifically for research and development of pose-invariant lip-reading systems. We firstly show that it is the higher order horizontal spatial frequency components that become most detrimental as the pose deviates. Secondly we assess the performance of different feature selection masks across a range of pose angles including a new mask based on Minimum Cross-Pose Variance coefficients. We report a relative improvement of 50% in Word Error Rate when using our selection mask over a common energy based selection during profile view lip-reading.
Design of Power FETs Based on Coupled Electro-Thermal-Electromagnetic Modeling

A comprehensive modeling approach is applied to the study of pHEMT transistors for microwave power amplifier applications. This approach combines physical, electromagnetic and thermal simulations to model large power transistors used in these applications, allowing both the individual finger contribution and the global performance to be investigated in an efficient manner, which can be used with commercial CAD tools. In this way the design of the transistor structure contributes to the optimization of the RF performances of the complete amplifier. Discrete transistor and MMIC designs are investigated using this work with validation based on infra-read and microwave measurements.