Miracle-dz/UniFAR-FTUs huggingface dataset:
Diffusion Approximations for a Class of Sequential Experimentation Problems

A decision maker (DM) must choose an action in order to maximize a reward function that depends on the DM’s action as well as on an unknown parameter Θ. The DM can delay taking the action in order to experiment and gather additional information on Θ. We model the problem using a Bayesian sequential experimentation framework and use dynamic programming and diffusion-asymptotic analysis to solve it. For that, we consider environments in which the average number of experiments that is conducted per unit of time is large and the informativeness of each individual experiment is low. Under such regimes, we derive a diffusion approximation for the sequential experimentation problem, which provides a number of important insights about the nature of the problem and its solution. First, it reveals that the problems of (i) selecting the optimal sequence of experiments to use and (ii) deciding the optimal time when to stop experimenting decouple and can be solved independently. Second, it shows that an optimal experimentation policy is one that chooses the experiment that maximizes the instantaneous volatility of the belief process. Third, the diffusion approximation provides a more mathematically malleable formulation that we can solve in closed form and suggests efficient heuristics for the nonasympototic regime. Our solution method also shows that the complexity of the problem grows only quadratically with the cardinality of the set of actions from which the decision maker can choose. We illustrate our methodology and results using a concrete application in the context of assortment selection and new product introduction. Specifically, we study the problem of a seller who wants to select an optimal assortment of products to launch into the marketplace and is uncertain about consumers’ preferences. Motivated by emerging practices in e-commerce, we assume that the seller is able to use a crowd voting system to learn these preferences before a final assortment decision is made. In this context, we undertake an extensive numerical analysis to assess the value of learning and demonstrate the effectiveness and robustness of the heuristics derived from the diffusion approximation. This paper was accepted by Omar Besbes, revenue management and market analytics.
Percutaneous Patent Foramen Ovale Closure versus Medical Therapy in Cryptogenic Stroke: An Update Meta-Analysis of Randomized Controlled Trials

Objectives: Concerns regarding the real efficacy of transcatheter patent foramen ovale (PFO) closure versus medical therapy in patients with cryptogenic stroke remained unresolved. We performed a meta-analysis using the randomized controlled trials on the efficacy and safety of transcatheter PFO closure in patients with cryptogenic stroke. Methods: Web of Science, EMBASE, PubMed, and the Cochrane Library were searched for relevant randomized controlled trials (RCTs). The primary outcome was recurrent stroke and transient-ischemic attack (TIA). Original data, hazard ratio (HR) with 95% confidence interval (95% CI) were abstracted to calculate a pooled effect size. Results: Our meta-analysis showed benefit with device closure when compared with medical therapy with an HR of 0.54 (95% CI: 0.39 - 0.74, P = 0.108) in the intention-to-treat cohort, 0.44 (95% CI: 0.24 - 0.82, P = 0.103) in the per-protocol populations, and 0.43 (95% CI: 0.31 - 0.60, P = 0.019) in the as-treated populations. There was a significantly higher incidence of new-onset atrial fibrillation in PFO closure patients (OR = 4.53, 95% CI: 2.58 - 7.97, P = 0.094). PFO Patients with an atrial septal aneurysm benefit from device closure (OR = 0.39, 95% CI: 0.22 - 0.69, P = 0.053). Patients with a substantial PFO shunt benefit the greatest with device closure with a pooled OR of 0.27 (95% CI: 0.14 - 0.56, P = 0.525). Conclusions: The meta-analysis concluded that PFO closure was associated with significantly lower risk of recurrent stroke in PFO patients with cryptogenic stroke than with medical therapy alone. The benefit of PFO closure was greater in patients with a substantial shunt and atrial septal aneurysm. PFO closure was associated with higher rates of new-onset atrial fibrillation.
Progressive transmission and display of static images

Progressive image transmission has been studied for some time in association with image displays connected to remote image sources, by communications channels of insufficient data rate to give subjectively near instantaneous transmission. Part of the work presented in this thesis addresses the progressive transmission problem constrained that the final displayed image is exactly identical to the source image with no redundant data transmitted. The remainder of the work presented is concerned with producing the subjectively best image for display from the information transmitted throughout the progression. Quad-tree and binary-tree based progressive transmission techniques are reviewed, especially an exactly invertible table based binary-tree technique. An algorithm is presented that replaces the table look-up in this technique, typically reducing implementation cost, and results are presented for the subjective improvement using interpolation of the display images. The relevance of the interpolation technique to focusing the progressive sequence on some part of the image is also discussed. Some aspects of transform coding for progressive transmission are reviewed, intermediate image resolution and most importantly problems associated with the coding being exactly invertible. Starting with the two-dimensional case, an algorithm is developed, that judged by the progressive display image can mimic the behaviour of a linear transform while also being exactly invertible (no quantisation). This leads to a mean/difference transform similar to the binary-tree technique. The mimic algorithm is developed to operate on n-dimensions and used to mimic an eight-dimensional cosine transform. Photographic and numerical results of the application of this algorithm to image data are presented. An area transform, interpolation to disguise block boundaries and bit allocation to coefficients, based on the cosine mimic transform are developed and results presented.
Optimizing resource sharing in node-capacitated overlay networks

A frequently occurring problem in the field of distributed systems is to determine an allocation of a generic resource so that the demand of every node in the system is fulfilled. Node-capacitated graphs, i.e. graphs where the weight of a node corresponds to the amount of resources it can give to the system, provide an appealing model that can be readily applied to real-world applications, such as peer-to-peer and grid-based systems. In this paper, we propose a model for this problem and show that it can be reduced to a problem of maximizing a flow in a bipartite network. We then describe a distributed fault-tolerant algorithm which allows each peer to compute the allocation of its resources using only local knowledge. Finally, we show that computing the maximal flow in a bounded-degree graph is NP-complete, which means that optimizing resource sharing in bounded-degree overlays is still an open problem.
Physicochemical and phytochemical screening of Convolvulus pluricaulis collected from Bagalkot, Karnataka

Aim: The present study aim was to analyze quantitatively and qualitatively the phytochemicals as well as to investigate the physicochemical and phytochemical screening of Convolvulus pluricaulis and its chloroform and ethanol extracts. Materials and Methods: In this, the physicochemical evaluation; ash values, namely total ash, acid-insoluble ash, water-soluble ash, and sulfated ash; extractive values, namely alcohol soluble extractive value, water-soluble extractive, and chloroform soluble extractive value; and loss on drying were determined. Preliminary phytochemical screening was done for the presence of carbohydrates, proteins, amino acids, glycosides, alkaloids, phytosteroids, flavonoids, saponins, tannins, and phenolic compounds, and total phenolic content was estimated by Folin–Ciocalteu method, and total flavonoid content was measured with the aluminum chloride colorimetric assay. Results: In results, it was found that the seed containing various phytochemicals were present in its ethanol and chloroform extracts. The total phenolic content in the ethanol and chloroform extracts was found 13.7 ± 0.4187 and 7.367 ± 0.2987 mg of gallic acid equivalent weight/g of extract, respectively, and the concentration of flavonoids in plant ethanol and chloroform extracts of Cassia hirsuta was found 114.6 ± 13.33 and 99.56 ± 11.6 mg of quercetin equivalent weight/g of extract, respectively. Conclusion: The present study concludes that the C. pluricaulis has the potential to act as a source of useful drugs because of the presence of various phytochemical constituents and high concentration of phenolic and flavonoid compounds.
Predicting the next location: A self‐attention and recurrent neural network model with temporal context

Nowadays, the popularity of mobile devices and location‐based services have generated a large amount of geographic data. It provides the opportunity for researchers to employ techniques to predict the next location. However, predicting the next location is difficult because it depends on temporal and spatial factors, and it is closely related to the historical behavior of users. In this article, we first analyze the geographic data of users and discover the potential behavior patterns of users. Then, we mine the relationship between user's movement behavior and temporal feature. Hence, we propose a method based on a recurrent neural network and self‐attention mechanism to predict the next location where users may visit. Our model can explore sequence regularity and extract temporal features according to historical trajectories information. Experimental results on a real‐world dataset demonstrate the effectiveness of our proposed model.
Local Feature Detection using Neural Networks

Feature detectors and descriptors have been successfully used for various computer vision tasks, such as image stitching and content-based image retrieval. Many methods use image gradients in different stages of the detection-description pipeline to describe local image structures. Recently, some of these stages have been replaced by convolutional neural networks, in order to increase their performance. Replacing orientation estimators and descriptors is a relatively straightforward task, mapping a single image patch to a single output. A detector, however, is defined as a selection problem, which makes it more challenging to implement as a neural network. They are therefore generally defined as regressors, converting input images to score maps. Keypoints can be then be selected from this map by applying non-maximum suppression. This thesis discusses several methods that use neural networks and defines different metrics to determine their performance. Experiments are performed on a selection of conventional methods, as well as a detector network that is trained from scratch, a pre-trained image classifier that is used to generate feature descriptors and a method that replaces the complete pipeline with three separate networks. In addition to qualitative measures defined on keypoints and descriptors, the bag-of-words model is used to implement an image retrieval application, in order to determine how the methods perform in practice. The results show that, in some cases, neural networks can outperform traditional methods.
Condition-based Maintenance of High-speed Train Wheels Through Trackside Monitoring

Condition-based maintenance (CBM) is a promising strategy in reducing the operating cost for modern high-speed rail (HSR), especially for train wheelsets. This paper presents a research effort on wheel defect detection in high-speed trains by devising a fiber Bragg grating (FBG)-based online monitoring system deployed on rail tracks to detect both wheel local defect and wheel polygonization during the passage of in-service high-speed trains. A diagnostic algorithm is developed using the online monitoring rail response to automatically identify both potential wheel local defects and polygonal wears. The devised monitoring system is then deployed on a test track to experimentally verify its capability to detect wheel defects. Two blind tests are conducted by running a train with potential wheel local defects and wheel polygonization on the instrumented rail, respectively. Results indicate that both local defects and polygonal wears can be identified with high fidelity, with the identified results being in good agreement with the results of radius deviation measurement later conducted offline in a depot.
Gradient Error Compensation in SC-MDACs

High speed data converter architectures such as pipelined analog-to-digital-converters (ADCs) typically consist of large capacitor arrays that are highly susceptible to systematic errors. Although significant efforts have been made in the literature to compensate linear and parabolic errors, the rotated parabolic components are less explored. These rotated parabolic components are responsible for spurious harmonics at the output of the converter, thereby degrading the linearity. In this article, we have investigated the origin of these rotated components, their impact on conversion linearity and discussed strategies to mitigate them. A placement technique along with one track routing solution, is proposed for complete compensation of the systematic errors. An algorithm is also provided to extend this technique to higher resolutions. The proposed technique is verified on the model of pipelined ADC, as well as current steering DAC. The incorporation of such technique results in near ideal linearity performance.
Anthropometric measurement of the hand

The hand is presented in a large area in cerebral cortex and controlled by a rich nerve network and it is like a psychologic, physicologic and aesthetic extention of the brain. The hand has a number of important functions like perception, management and self expression (1). With its nerve and vessel packages, channels and tunnels and musculosceletal components like ligaments, tendons and facias the hand has a unique biomechanic and architectural design (2). That the hand gets injured in 1/3 of industrial accidents reflects its functional importance. Besides; permanent damages occur in half of accidents. Some anthropologists believe that the hand causes the inconceivable development of the brain. In fact; the hand has been of great help for the formation of civilization, and to humankind for effectively changing his environment. The hand is open to traumas and gets widely affected in the course of diseases. 31% of all injuries affect upper extremity and 1/3 of these end up with an anatomic or a functional loss of the hand. (3,4,5,6). Besides all these clinical significances the hand helps draw a roadmap for gender and height prediction of people.
Step 1 Advice Booklet

Author(s): Satterfield, Kellie | Abstract: The purpose of the Step 1 Advice Survey was to collect anonymous information from current UCSD medical students who had completed the USMLE Step 1 examination. The survey aimed to ascertain various Step 1 study habits and resulting trends for the purposes of medical education quality improvement. The goal was to help better inform future medical studies on what study tools/habits have been used in teh past and what had worked for students, and to highlight any discovered correlations or significant findings. This survey will also help to inform the adminstration on student needs.
Microbiome predictors of dysbiosis and VRE decolonization in patients with recurrent C. difficile infections in a multi-center retrospective study

The gastrointestinal microbiome is intrinsically linked to the spread of antibiotic resistance. Antibiotic treatment puts patients at risk for colonization by opportunistic pathogens like vancomycin resistant Enterococcus and Clostridioides difficile by destroying the colonization resistance provided by the commensal microbiota. Once colonized, the host is at a much higher risk for infection by that pathogen. Furthermore, we know that microbiome community differences are associated with disease states, but we do not have a good understanding of how we can use these changes to classify different patient populations. To that end, we have performed a multicenter retrospective analysis on patients who received fecal microbiota transplants to treat recurrent Clostridioides difficile infection. We performed 16S rRNA gene sequencing on fecal samples collected as part of this study and used these data to develop a microbiome disruption index. Our microbiome disruption index is a simple index that is predictive across cohorts, indications, and batch effects. We are able to classify pre-fecal transplant vs post-fecal transplant samples in patients with recurrent C. difficile infection, and we are able to predict, using previously-published data from a cohort of patients receiving hematopoietic stem cell transplants, which patients would go on to develop bloodstream infections. Finally, we also identified patients in this cohort that were initially colonized with vancomycin resistant Enterococcus and that 92% (11/12) were decolonized after the transplant, but the microbiome disruption index was unable to predict such decolonization. We, however, were able to compare the relative abundance of different taxa between the two groups, and we found that increased abundance of Enterobacteriaceae predicts whether patients were colonized with vancomycin resistant Enterococcus. This work is an early step towards a better understanding of how microbiome predictors can be used to help improve patient care and patient outcomes.
Design of learning modules writing factual text based on discovery learning by using mobile devices

Innovation and development of language teaching materials that are appropriate to the development of science and technology need to be done. At present, the development of knowledge and technology has an impact on changing generations. The use of technological devices, such as digital media, mobile applications, websites, etc., has resulted in a change in needs that allows all activities to move faster, one of which is information and knowledge. That has a big impact on education. One teaching material that can be developed is a learning module. At this time, the learning module developed can be done using a variety of digital devices, one of which is mobile. By using a mobile device, practical learning modules are used and can be equipped with various media. The module developed is a learning module writing factual text on the basis of Discovery Learning. This research is R & D (research & development) using a 4-D model (define, design, develop, and dessiminate). Based on the results of validation and trials it was concluded that the learning module is valid, practical, and effective in learning Indonesian.
Estudos moleculares em pacientes com fibrose cística do sul do Brasil

Cystic Fibrosis (CF) is the most common genetic disease among Caucasians. The CF gene, named cystic fibrosis transmembrane conductance regulator (CFTR), codifies a protein that acts as a channel through the epithelial membrane. The present work aimed (1) to detect sequence alterations in the nucleotide binding regions and at the membrane spanning domain of the CFTR gene, and (2) to detect the following frequent mutations R347P, R347H, R334W and Q359K (located in exon 7), ∆F508 (located in exon 10), G542X, G551D, R553X and S549N (located in exon 11), W1282X (located in exon 20) and N1303K (located in exon 21). Seventy seven unrelated CF patients were analyzed, who were previously diagnosed and currently under treatment at the Pneumology Service of our hospital. Regions of interest were amplified by PCR using specific primers. Each sample was analyzed by a non-radioactive singlestranded conformational polymorphism (SSCP) analysis technique and restriction enzyme digestion. The ∆F508 mutation was found in 48.7% of the alleles. Frequencies of G542X, R334W, R553X and W1282X mutations in our population were 3.25%, 1.3%, 0.65% and 0.65%, respectively. No alleles were found to carry mutations G551D, R334W, R347P, R347H, Q359K, S549N and N1303K, which were included in the screening protocol. This study allowed the characterization of 84 out of 154 CF mutant alleles (54.5%). The incidence of main CF mutations analyzed was similar to that of the South European population. Mutation data presented here will be useful for designing new DNA testing strategies for CF in South Brazil.
Adopsi Website Quality Evaluation Method (WebQem) dan Iso 9126 untuk Mengukur Service Quality pada Ujian Online

Ujian merupakan salah satu cara untuk mengevaluasi proses belajar. PalComTech merupakan lembaga pendidikan yang mengembangkan berbagai sistem dan aplikasi pembelajaran. Computer Best Test (CBT) yang digunakan PalComTech terdiri dari ujian online pada sistem euniversity dan CBT lainnya. Itu dikenal dengan nama Qualitiva.id. Qualitiva.id dikembangkan oleh R&D PalComTech dan sudah digunakan selama 2 tahun di PalComTech. Tujuan penelitian ini adalah mengadopsi Website Quality Evaluation Method (WebQEM) dan ISO 9126 untuk mengukur service quality ujian online, sehingga dapat memberikan masukan kepada PalComTech mengenai proses pengembangan Qualitiva.id. Metode dalam penelitian ini adalah deskriptif dengan pendekatan kuantitatif. Pengujian dilakukan dengan analisis regresi berganda untuk mengetahui pengaruh variabel high level quality, yaitu: Usability, Functionality, Reliability dan Efficiency. Hasil penelitian adalah kesimpulan bahwa variabel usability, functionality, reliability, dan efficiency berpengaruh terhadap WebQEM, Nilai yang didapat sebesar 0,743 atau 74.3%. Variabel functionality dan reliability berpengaruh signifikan terhadap kualitas web qualitiva.id dan variabel usability dan efficiency tidak berpengaruh signifikan terhadap kualitas web qualitiva.id. Luaran penelitian ini memberikan masukkan/rekomendasi kepada pihak Palcomtech R&D sebagai pengembang, untuk melakukan perbaikan sesuai analisis kebutuhan user dari sisi usability dan efficiency. Kata kunci- website, ISO 9126, Ujian Online, Service Quality
EPS phenotype and genotype in Streptococcus thermophilus strains of dairy origin

The aim of this work was to evaluate EPS production and the organisation of the eps gene cluster in 43 Streptococcus thermophilus strains of dairy origin. The EPS production was evaluated in M17 medium using glucose or lactose as the carbon source and the total sugar content was determined using the phenol-sulphate method. The amount of EPS produced using glucose as the carbon source ranged between 24 and 662 mg l -1 (glucose equivalents) and between 16 and 570 mg l -1 using lactose. PCR experiments showed that epsA, epsB, epsC, epsD, epsE and epsF genes were the most conserved and widespread in the exopolysaccharide locus, while few PCR positive signals were detected for epsG, epsH, epsJ and epsK genes. Results from the PCR cluster analysis allowed the identification of seventeen genotypes among the 44 analysed strains. The genetic polymorphism of the eps locus was further demonstrated by sequencing the epsCD genes of some representative strains. The EPS phenotype is widely distributed among S. thermophilus strains, but only few strains produce an amount of EPS of potential industrial interest. The spreading of the eps genes could be used as a genetic tool for S. thermophilus strains typing since, in some cases, the genotype was related to EPS production. The characterisation of the EPS phenotype and genotype of S. thermophilus strains should expand the knowledge of this biotechnological feature and help in the genetic characterisation of strains of potential industrial interest.