Miracle-dz/UniFAR-FTUs huggingface dataset:
Co‐occurrence of schwannomatosis and rhabdoid tumor predisposition syndrome 1

The clinical phenotype associated with germline SMARCB1 mutations has as yet not been fully documented. It is known that germline SMARCB1 mutations may cause rhabdoid tumor predisposition syndrome (RTPS1) or schwannomatosis. However, the co‐occurrence of rhabdoid tumor and schwannomas in the same patient has not so far been reported.
The Effect of Aerobic Exercise on Different Symptoms of Depression: An Investigation of Psychological Mechanisms of Stress and Coping

Objectives: Considering the growing need for encouraging greater use of a variety of non-pharmacological methods in treating depression, the aim of this quasi experimental study was to examine the effect of aerobic exercise on triple categories of affective, cognitive and somatic symptoms of depression and to investigate its psychological mediators of perceived stress and coping strategies. Methods: Forty five female outpatients with major depressive disorder were divided into three groups including exercise + usual pharmacotherapy (n = 15), psychotherapy + usual pharmacotherapy (n = 14) and a control group receiving only usual pharmacotherapy (n = 16). The exercise used was included 36 one hour session (three sessions per week) with a low to medium intensity of 50% to 70% of the maximal heart rate. The psychotherapy used in this study was the behavioral activation treatment for depression revised. The Persian version of Beck Depression Inventory-II, Perceived Stress Scale and Coping Inventory for Stressful Situations were applied to assess the pre- and post-intervention depression, perceived stress, and coping strategies. Results: The findings indicated a significant decrease in the post-intervention scores of all three categories of affective, cognitive and somatic symptoms of depression and the perceived stress level in the adjunctive exercise and psychotherapy conditions compared with the control condition (p = 0.001), but there was no significant difference between the exercise and psychotherapy groups. In addition, no significant improvement was observed regarding the problem-centered, emotion-centered and avoidant-centered stress coping methods in the post-intervention scores of the exercise group compared with the control group. Conclusion: An adjunctive aerobic exercise program can be as effective as adding the psychotherapy to usual pharmacotherapy in further improvement in all three categories of depression symptoms especially mediated by reducing the amount of perceived stress, but not through any significant change in cognitive-behavioral coping strategies.
High Intraperitoneal Interleukin-6 Levels Predict Peritonitis in Peritoneal Dialysis Patients: A Prospective Cohort Study

Background: To evaluate the predictive value of dialysate interleukin-6 (IL-6) representing local subclinical intraperitoneal inflammation for the development of peritonitis in continuous ambulatory peritoneal dialysis (CAPD) patients. Methods: Stable prevalent CAPD patients were enrolled in this prospective study. IL-6 concentration in the overnight effluent was determined and expressed as the IL-6 appearance rate (IL-6AR). Patients were divided into 2 groups according to the median of IL-6AR and prospectively followed up until the first episode of peritonitis, cessation of PD, or the end of the study (December 30, 2017). The utility of IL-6AR in predicting peritonitis-free survival was analyzed using the Kaplan-Meier and Cox proportional hazards models. Results: A total of 149 patients were enrolled, including 72 males (48%) with mean age 52.0 ± 13.6 years and median PD duration 26 (5.9–45.5) months. During follow-up, 7,923 patient months were observed and 154 episodes of peritonitis occurred in 82 patients. Previous peritonitis episodes were significantly associated with log dialysate IL-6AR levels (β = 0.187 [0.022–0.299], p = 0.023). Patients in the high IL-6AR group showed a significantly inferior peritonitis-free survival when compared with their counterparts in the low IL-6AR group (48.8 vs. 67.7 months, p = 0.026), as well as higher treatment failure percentage of peritonitis (20.3 vs. 9.3%, p = 0.049). A multivariate Cox regression showed that high dialysate IL-6AR (hazard ratio [HR] 1.247 [1.052–1.478]; p = 0.011) and high serum C-reactive protein (HR 1.072 [1.005–1.144]; p = 0.036) were independent risk factors for inferior peritonitis-free survival. Conclusion: This prospective study suggested that the intraperitoneal inflammation marker, dialysate IL-6 level, might be a potential predictor of peritonitis development in patients undergoing PD.
Optimal Two-Stage Algorithms for Group Testing Problems

Group testing refers to the situation in which one is given a set of objects ${\cal O}$, an unknown subset ${\cal P}\subseteq {\cal O}$, and the task of determining ${\cal P}$ by asking queries of the type "does ${\cal P}$ intersect $\cal Q$? ," where $\cal Q$ is a subset of ${\cal O}$. Group testing is a basic search paradigm that occurs in a variety of situations such as quality control testing, searching in storage systems, multiple access communications, and data compression, among others. Group testing procedures have been recently applied in computational molecular biology, where they are used for screening libraries of clones with hybridization probes and sequencing by hybridization. Motivated by particular features of group testing algorithms used in biological screening, we study the efficiency of two-stage group testing procedures. Our main result is the first optimal two-stage algorithm that uses a number of tests of the same order as the information-theoretic lower bound on the problem. We also provide efficient algorithms for the case in which there is a Bernoulli probability distribution on the possible sets ${\cal P}$, and an optimal algorithm for the case in which the outcome of tests may be unreliable because of the presence of "inhibitory" items in ${\cal O}$. Our results depend on a combinatorial structure introduced in this paper. We believe that it will prove useful in other contexts, too.
Minimally Actuated Walking: Identifying Core Challenges to Economical Legged Locomotion Reveals Novel Solutions

Terrestrial organisms adept at locomotion employ strut-like legs for economical and robust movement across the substrate. Although it is relatively easy to observe and analyze details of the solutions these organic systems have arrived at, it is not as easy to identify the problems these movement strategies have solved. As such, it is useful to investigate fundamental challenges that effective legged locomotion overcomes in order to understand why the mechanisms employed by biological systems provide viable solutions to these challenges. Such insight can inform the design and development of legged robots that may eventually match or exceed animal performance. In the context of human walking, we apply control optimization as a design strategy for simple bipedal walking machines with minimal actuation. This approach is used to discuss key facilitators of energetically efficient locomotion in simple bipedal walkers. Furthermore, we extrapolate the approach to a novel application—a theoretical exoskeleton attached to the trunk of a human walker—to demonstrate how coordinated efforts between bipedal actuation and a machine oscillator can potentially alleviate a meaningful portion of energetic exertion associated with leg function during human walking.
Stochastic Gradient Descent for Stochastic Doubly-Nonconvex Composite Optimization

The stochastic gradient descent has been widely used for solving composite optimization problems in big data analyses. Many algorithms and convergence properties have been developed. The composite functions were convex primarily and gradually nonconvex composite functions have been adopted to obtain more desirable properties. The convergence properties have been investigated, but only when either of composite functions is nonconvex. There is no convergence property when both composite functions are nonconvex, which is named the \textit{doubly-nonconvex} this http URL overcome this difficulty, we assume a simple and weak condition that the penalty function is \textit{quasiconvex} and then we obtain convergence properties for the stochastic doubly-nonconvex composite optimization problem.The convergence rate obtained here is of the same order as the existing work.We deeply analyze the convergence rate with the constant step size and mini-batch size and give the optimal convergence rate with appropriate sizes, which is superior to the existing work. Experimental results illustrate that our method is superior to existing methods.
Polypyrrole increases branching and neurite extension by Neuro2A cells on PBAT ultrathin fibers

Graphical Abstract Electrospinning shows a feasible way to generate hybrid scaffolds from the combination of different materials. This work presented a successful route to prepare ultrathin fibers from hybrid solutions containing a commercial polyester, poly (butylene adipate-co-terephthalate) (PBAT) and a conductive polymer, polypyrrole (PPy). The final material (PBAT/PPy) showed an enhanced potential for neuronal differentiation when compared to neat PBAT. The PPy loading improved branching and neurite extension of Neuro2a cells, which opens a wide range of perspectives where these materials may be applied in regenerative medicine. ABSTRACT We present a methodology for production and application of electrospun hybrid materials containing commercial polyester (poly (butylene adipate-co-terephthalate; PBAT), and a conductive polymer (polypirrole; PPy) as scaffold for neuronal growth and differentiation. The physical-chemical properties of the scaffolds and optimization of the electrospinning parameters are presented. The electrospun scaffolds are biocompatible and allow proper adhesion and spread of mesenchymal stem cells (MSCs). Fibers produced with PBAT with or without PPy were used as scaffold for Neuro2a mouse neuroblastoma cells adhesion and differentiation. Neuro2a adhered to PBAT and PBAT/PPy2% scaffolds without laminin coating. However, Neuro2a failed to differentiate in PBAT when stimulated by treatment with retinoic acid (RA), but differentiated in PBAT/PPy2% fibers. We hypothesize that PBAT hydrophobicity inhibited proper spreading and further differentiation, and inhibition was overcome by coating the PBAT fibers with laminin. We conclude that fibers produced with the combination of PBAT and PPy can support neuronal differentiation.
Conditional Network Embeddings

Network Embeddings (NEs) map the nodes of a given network into $d$-dimensional Euclidean space $\mathbb{R}^d$. Ideally, this mapping is such that `similar' nodes are mapped onto nearby points, such that the NE can be used for purposes such as link prediction (if `similar' means being `more likely to be connected') or classification (if `similar' means `being more likely to have the same label'). In recent years various methods for NE have been introduced, all following a similar strategy: defining a notion of similarity between nodes (typically some distance measure within the network), a distance measure in the embedding space, and a loss function that penalizes large distances for similar nodes and small distances for dissimilar nodes. A difficulty faced by existing methods is that certain networks are fundamentally hard to embed due to their structural properties: (approximate) multipartiteness, certain degree distributions, assortativity, etc. To overcome this, we introduce a conceptual innovation to the NE literature and propose to create \emph{Conditional Network Embeddings} (CNEs); embeddings that maximally add information with respect to given structural properties (e.g. node degrees, block densities, etc.). We use a simple Bayesian approach to achieve this, and propose a block stochastic gradient descent algorithm for fitting it efficiently. We demonstrate that CNEs are superior for link prediction and multi-label classification when compared to state-of-the-art methods, and this without adding significant mathematical or computational complexity. Finally, we illustrate the potential of CNE for network visualization.
Etiology, Clinical Assessment, and Surgical Repair of Plantar Plate Tears

Abstract The plantar plate has recently gained more attention as an important structure contributing to lesser metatarsophalangeal joint stability. This has prompted a significant growth of interest in the anatomy and biomechanics of the plantar plate and in the diagnosis and treatment of its injuries. Improved understanding of plantar plate function and predictable patterns of degeneration and failure has led to the development of a clinical staging and surgical grading system of plantar plate lesions. Relatively recent innovations allow the surgeon to access and repair plantar plate tears directly with reinsertion onto the base of the proximal phalanx. The addition of direct plantar plate repair represents a significant advance in the surgical restoration of alignment and functional stability of the lesser metatarsophalangeal joint.
Childhood obesity: survey of physician assessment and treatment practices.

BACKGROUND This study examined physician experience with the 2007 Expert Committee Recommendations (ECR) on the Assessment, Prevention and Treatment of Child and Adolescent Overweight and Obesity. METHODS Pediatricians and family physicians (n = 194) practicing in the Midwest completed a survey designed to assess knowledge of, adherence to, and self-efficacy in implementing the 2007 Expert Committee recommendations. RESULTS The majority of physicians (71%) were aware of the ECR and adhered to approximately 60% of the recommendations. Adherence was significantly higher for physicians who were aware of the ECR. Differences in awareness of and adherence to the ECR were noted among physician groups by specialty and location. Self-efficacy for assessing and treating pediatric obesity was significantly positively correlated with adherence to the ECR (Pearson r = 0.46). When asked for strategies that would facilitate improved pediatric weight management, physicians most often reported desiring to learn effective methods to increase patient motivation. CONCLUSIONS Efforts to improve adherence to the Expert Committee recommendations should focus on improving physician awareness of and training in the use of the recommendations and on improved training and development of self-efficacy in pediatric weight assessment and patient counseling skills.
An Insight into the Capabilities of Professionals and Teams in Agile Software Development: A Systematic Literature Review

Background: Previous studies investigated key characteristics of software engineers and factors influencing the performance of individuals, productivity of teams and project success within agile software development (ASD). They aided in the active investigation of human aspects in ASD. However, capability measurement and prediction with respect to agile workforce, owing to its importance, is an area that needs spotlight. Objective: The objective of this paper is to present the state of the art relating to capability measurement of software engineers and teams working in ASD projects. Method: We carried out a systematic literature review (SLR) focused on identifying attributes used for measuring and predicting the capabilities of individual software engineers and teams. Results: Evidence from 16 studies showed attributes that can measure capabilities of engineers and teams, and also attributes that can be used as capability predictors. Further, different instruments used to measure those attributes were presented. Conclusions: The SLR presented a wide list of attributes that were grouped into various categories. This information can be used by project managers as, for example, a checklist to consider when allocating software engineers to teams and in turn teams to a project. Further, this study indicated the necessity for an investigation into capability prediction models.
Implementing control charts to corporate financial management

In the paper, corporate financial management using statistical process control (SPC), especially Shewhart’s control charts operating with the constant mean, control charts with non-constant mean, and process capability indices will be introduced. The center line, UCL and LCL for the control charts will be defined with the regulated process not allowed to cross the UCL and LCL boundaries. Altman’s model (the so called Z-score), the most popular corporate financial stability index, will be used. We will demonstrate benefits of SPC on two case studies: the first will focus on corporate financial flow control, the second will include six companies. Special types of control charts, i.e., CUSUM and EWMA, will be discussed due to their mean shift sensitivity and practical applications demonstrated on additional two case studies. The results prove control charts can be successfully implemented not only in manufacturing processes but in corporate financial management as well. Key–Words: Altman’s Z-score, Statistical Process Control, Shewhart’s control charts, process capability indices, EWMA control chart, CUSUM control chart
Web Services in DDoS Attack by Classify the Attacks Suji . S

A website DDoS is executed by flooding one or more of the site's web servers with so many requests that it becomes unavailable for normal use. If an innocent user makes normal page requests during a DDoS attack, the requests may fail completely, or the pages may download so slowly as to make the website unusable. DDoS attacks typically take advantage of several computers which simultaneously launch hundreds of thousands of requests at the target website. The attackers are most likely going to use noncommercial computers as attack platforms, because they are usually easier to break.To solve the problems, several defense mechanisms against DDoS attacks have been proposed in the literature. However it is not easy for a security manager to select solutions suited for his service environments. Under the respect, this is intended to classify DDoS defense systems based on the functional design method. Also various experimental results of DDoS defense systems by using our proposed classification of defense systems and performance metrics.
Superset Disassembly: Statically Rewriting x86 Binaries Without Heuristics

Static binary rewriting is a core technology for many systems and security applications, including profiling, optimization, and software fault isolation. While many static binary rewriters have been developed over the past few decades, most make various assumptions about the binary, such as requiring correct disassembly, cooperation from compilers, or access to debugging symbols or relocation entries. This paper presents MULTIVERSE, a new binary rewriter that is able to rewrite Intel CISC binaries without these assumptions. Two fundamental techniques are developed to achieve this: (1) a superset disassembly that completely disassembles the binary code into a superset of instructions in which all legal instructions fall, and (2) an instruction rewriter that is able to relocate all instructions to any other location by mediating all indirect control flow transfers and redirecting them to the correct new addresses. A prototype implementation of MULTIVERSE and evaluation on SPECint 2006 benchmarks shows that MULTIVERSE is able to rewrite all of the testing binaries with a reasonable runtime overhead for the new rewritten binaries. Simple static instrumentation using MULTIVERSE and its comparison with dynamic instrumentation shows that the approach achieves better average performance. Finally, the security applications of MULTIVERSE are exhibited by using it to implement a shadow stack.
Quantitation of Pesticide Residue in Water and Food in Louisiana, USA

Pesticides can remain in the environment for decades and contaminate surface water that is used for irrigation of produce. This study examined pesticide residues in some surface waters and foods in Louisiana. Samples of 8 foods (tomato, corn, rice, blueberry, cucumber, cabbage, wheat and melon) and 35 surface waters were studied using a QuEChERS extraction method for food samples and liquid-liquid extraction method for the water samples. Gas chromatography-mass spectrometry was used to analyze water and food samples. Nine pesticides were detected in the surface water samples and 5 in the food samples. Pesticides detected in foods were below FDA tolerance limit but 0.18 ppm cypermethrin found in tomato was within 90% of the FDA limit (0.2 ppm). Four water samples had atrazine levels that were above the FDA limit for potable water. This study suggests the need to intermittently monitor pesticide contamination in our food and water.
Cellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective

Integrating the unmanned aerial vehicles (UAVs) into the cellular network is envisioned to be a promising technology to significantly enhance the communication performance of both UAVs and existing terrestrial users. In this paper, we first provide an overview on the two main research paradigms in cellular UAV communications, namely, cellular-enabled UAV communication with UAVs as new aerial users served by the ground base stations (GBSs), and UAV-assisted cellular communication with UAVs as new aerial communication platforms serving the terrestrial users. Then, we focus on the former paradigm and study a new UAV trajectory design problem subject to practical communication connectivity constraints with the GBSs. Specifically, we consider a cellular-connected UAV in the mission of flying from an initial location to a final location that are given, during which it needs to maintain reliable communication with the cellular network by associating with one of the available GBSs at each time instant that has the best line-of-sight channel (or shortest distance) with it. We aim to minimize the UAV’s mission completion time by optimizing its trajectory, subject to a quality-of-connectivity constraint of the GBS-UAV link specified by a minimum receive signal-to-noise ratio target, which needs to be satisfied throughout its mission. To tackle this challenging non-convex optimization problem, we first propose an efficient method to verify its feasibility via checking the connectivity between two given vertices on an equivalent graph. Next, by examining the GBS-UAV association sequence over time, we obtain useful structural results on the optimal UAV trajectory, based on which two efficient methods are proposed to find high-quality approximate trajectory solutions by leveraging the techniques from graph theory and convex optimization. The proposed methods are analytically shown to be capable of achieving a flexible tradeoff between complexity and performance, and yielding a solution in polynomial time with the performance arbitrarily close to that of the optimal solution. Numerical results further validate the effectiveness of our proposed designs against benchmark schemes. Finally, we make concluding remarks and point out promising directions for future work.