Miracle-dz/UniFAR-FTUs huggingface dataset:
Minor physical anomalies in adolescents at risk for substance use and early sex

Abstract Minor physical anomalies (MPAs) are associated with disruptions of fetal development. We propose that the same genetic compositions that contribute to the presence of MPAs, also predispose individuals to health-compromising behaviors, thus considering MPAs as particular endophenotypes. We developed a screening questionnaire for problematic conduct, substance abuse, and early sexual practice. A total of 108 adolescents (55 males, 50.9%) aged 11 to 19 years were recruited and further divided into case and control groups according to their answers to the questions of health behaviors mentioned above. We then measured their MPAs that included qualitative and quantitative physical features. Stepwise logistic regression and the receiver operating characteristic (ROC) analyses were used to determine the predictive values of MPAs for behavioral outcomes. The obliquity of palpebral fissure and the head MPAs were negatively associated with substance use. In the ROC analysis, the model provided an area under curve (AUC) of 0.91 with prediction indices being 0.89 for sensitivity and 0.85 for specificity. In addition, the feet MPAs and outer canthal distance were positively, whereas the obliquity of palpebral fissure and ear rotation was negatively associated with early sexual practices. The AUC for early sexual practice was 0.91 and the prediction indexes were 0.87 for sensitivity and 0.88 for specificity. Certain MPAs were associated with adolescent substance use and early sex, which suggests a neurodevelopmental etiology for behavioral outcomes
An adaptive TS fuzzy-PID controller applied to an active knee prosthesis based on Human walk

To ameliorate living conditions of people suffering from limb amputations, artificial prothesis are developed to follow Human body locomotion. This paper aims to depict and evaluate the dynamic modeling and control strategy for an Active Knee Prosthesis (APK). As a first step, the motion equations governing the APK are derived using Euler-Lagrange method. Then, human healthy leg data is used to build a knowledge based fuzzy inference system (FIS) to control the dynamic motions of the APK. An adaptive fuzzy-PID controller is designed to generate desired angles deduced from healthy leg. A conclusion finished the paper.
Bone substitutes: a review of their characteristics, clinical use, and perspectives for large bone defects management

Bone replacement might have been practiced for centuries with various materials of natural origin, but had rarely met success until the late 19th century. Nowadays, many different bone substitutes can be used. They can be either derived from biological products such as demineralized bone matrix, platelet-rich plasma, hydroxyapatite, adjunction of growth factors (like bone morphogenetic protein) or synthetic such as calcium sulfate, tri-calcium phosphate ceramics, bioactive glasses, or polymer-based substitutes. All these substitutes are not suitable for every clinical use, and they have to be chosen selectively depending on their purpose. Thus, this review aims to highlight the principal characteristics of the most commonly used bone substitutes and to give some directions concerning their clinical use, as spine fusion, open-wedge tibial osteotomy, long bone fracture, oral and maxillofacial surgery, or periodontal treatments. However, the main limitations to bone substitutes use remain the management of large defects and the lack of vascularization in their central part, which is likely to appear following their utilization. In the field of bone tissue engineering, developing porous synthetic substitutes able to support a faster and a wider vascularization within their structure seems to be a promising way of research.
Serum myoglobin, creatine kinase, and cell‐free DNA in endurance sled dogs and sled dogs with clinical rhabdomyolysis

OBJECTIVE To evaluate whether cell-free DNA (cfDNA) concentrations are increased in dogs with exertional rhabdomyolysis and whether concentrations are correlated with serum myoglobin concentration and creatine kinase activity. DESIGN Observational cohort study. SETTING Yukon Quest 1,000-mile International Sled Dog Race 2015. ANIMALS Twelve normal competitive sled dogs; 5 dogs with rhabdomyolysis. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Blood was collected from all confirmed cases of exertional rhabdomyolysis and compared to the winning team at the midrace point. Results indicate that median cfDNA did not increase, but decreased by the race finish (prerace = 314.2 ng/mL versus midrace = 283.7 ng/mL versus postrace = 249.5 ng/mL). There were no rises in median cfDNA in dogs with rhabdomyolysis (255 ng/mL) negating its potential utility as a measure of acute skeletal muscle compromise. In contrast, myoglobin concentration and creatine kinase activity at the midrace point for normal dogs were significantly lower than dogs with rhabdomyolysis. Values for myoglobin and creatine kinase were strongly positively correlated (R = 0.91). CONCLUSIONS cfDNA is not a useful biomarker for exertional rhabdomyolysis in contrast to myoglobin and creatine kinase. Further evaluation of timing and clinical signs suggests that exertional rhabdomyolysis occurs early in endurance activities. Among the dogs with rhabdomyolysis, the dog that demonstrated clinical signs had the highest serum creatine kinase activity and myoglobin concentration.
Pricing schemes for energy-efficient HPC systems: Design and exploration

Energy efficiency is of paramount importance for the sustainability of high performance computing (HPC) systems. Energy consumption limits the peak performance of supercomputers and accounts for a large share of Total Cost of Ownership (TCO). Consequently, system owners and final users have started exploring mechanisms to trade off performance for power consumption, for example, through frequency and voltage scaling. However, only a limited number of studies have been devoted to explore the economic viability of performance scaling solutions and to devise pricing mechanisms fostering a more energy-conscious usage of resources, without adversely impacting return-of-investment on the HPC facility. How to foster green-computing to take advantage of power management knobs? Would today’s accounting systems be sufficient or are novel pricing schemes needed? How to model the link between TCO and power management? To answer these questions, we present a parametrized model to analyze the impact of frequency scaling on energy consumption and to assess the potential cost benefits for the HPC facility and users. We evaluate four pricing schemes, considering both facility manager and the user perspectives. We then perform a design space exploration considering current and near-future HPC systems and technologies.
Onsite medical waste multi-objective vehicle routing problem with time windows

Healthcare services provided by hospitals generate healthcare wastes which are considered as one of the most complex types of waste generated by institutions. Although a percentage of hospital waste is considered as hazardous waste that may present various risks to humans, animals and the environment if not managed properly. This paper highlights on-site healthcare waste collection, since a proper internal collection is important in order to minimize the risk to the patients, hospital staff, visitors and the surrounding environment. We focus on determining routes for healthcare waste on-site collection from points of generation of the waste to its interim storage area, with the objective of minimizing the total traveling time, considering the disinfection time of the trolleys, and also minimizing the transportation exposure risk. This multi-objective nature of the problem makes it a special case of the vehicle routing problem with time window (VRPTW) but it is complex compared to the general VRPTW since it has several specific characteristics such as managing the trolleys' departure times and the routes ordering, also the transportation is done by a fleet of trolleys performing multiple routes during each shift thus it is related to the multi-trips vehicle routing problem (MTVRP), also each collection request is delimited by a time window and each collection request specifies the type of waste to collect which can be considered as the multi-commodity vehicle routing problem (MCVRP). We present the mathematical model that we have built for the problem, which results after an appropriate transformation of the problem into a node routing one. This specific problem was inspired by a real world application and does not appear in the literature.
Low-latency compressive active user identification over frequency-selective fading channels

This paper proposes a compressive sensing (CS) based active user identification scheme over frequency-selective fading channels. Unlike the conventional cyclic prefix (CP) based preamble transmission, our approach does not utilize CP in order to conserve signaling overhead, in turn reducing the system-wide processing latency. Our approach first estimates the multi-user channel impulse response vectors by solving a mixed ℓ2/ℓ1-norm optimization problem; then, the active users are identified via a sorting of the norms of the estimated channel vectors. By exploiting the Toeplitz channel matrix structure resulting from CP-free preamble transmission, analytic performance guarantee in term of the block restricted isometry property of the preamble matrix is given. Computer simulations are used to illustrate the performance of the proposed method.
Hypertensive Disorders of Pregnancy: ISSHP Classification, Diagnosis, and Management Recommendations for International Practice.

These recommendations from the International Society for the Study of Hypertension in Pregnancy (ISSHP) are based on available literature and expert opinion. It is intended that this be a living document, to be updated when needed as more research becomes available to influence good clinical practice. Unfortunately, there is a relative lack of high-quality randomized trials in the field of hypertension in pregnancy compared with studies in essential hypertension outside of pregnancy, and ISSHP encourages greater funding and uptake of collaborative research in this field. Accordingly, the quality of evidence for the recommendations in this document has not been graded although relevant references and explanations are provided for each recommendation. The document will be a living guideline, and we hope to be able to grade recommendations in the future. Guidelines and recommendations for management of hypertension in pregnancy are typically written for implementation in an ideal setting. It is acknowledged that in many parts of the world, it will not be possible to adopt all of these recommendations; for this reason, options for management in less-resourced settings are discussed separately in relation to diagnosis, evaluation, and treatment. This document has been endorsed by the International Society of Obstetric Medicine and the Japanese Society for the Study of Hypertension in Pregnancy. All units managing hypertensive pregnant women should maintain and review uniform departmental management protocols and conduct regular audits of maternal and fetal outcomes. The cause(s) of preeclampsia and the optimal clinical management of the hypertensive disorders of pregnancy remain uncertain; therefore, we recommend that every hypertensive pregnant woman be offered an opportunity to participate in research, clinical trials, and follow-up studies. ### Classification 1. Hypertension in pregnancy may be chronic (predating pregnancy or diagnosed before 20 weeks of pregnancy) or de novo (either preeclampsia or gestational hypertension). 2. Chronic hypertension is associated with adverse …
Genomic Contingencies and the Potential for Local Adaptation in a Hybrid Species

Hybridization is increasingly recognized as a potent evolutionary force. Although additive genetic variation and novel combinations of parental genes theoretically increase the potential for hybrid species to adapt, few empirical studies have investigated the adaptive potential within a hybrid species. Here, we address whether genomic contingencies, adaptation to climate, or diet best explain divergence in beak morphology using genomically diverged island populations of the homoploid hybrid Italian sparrow Passer italiae from Crete, Corsica, and Sicily. Populations vary significantly in beak morphology both between and within islands of origin. Temperature seasonality best explains population divergence in beak size. Interestingly, beak shape along all significant dimensions of variation was best explained by annual precipitation, genomic composition, and their interaction, suggesting a role for contingencies. Moreover, beak shape similarity to a parent species correlates with proportion of the genome inherited from that species, consistent with the presence of contingencies. In conclusion, adaptation to local conditions and genomic contingencies arising from putatively independent hybridization events jointly explain beak morphology in the Italian sparrow. Hence, hybridization may induce contingencies and restrict evolution in certain directions dependent on the genetic background.
QSNFC: Quick and secured near field communication for the Internet of Things

Near Field Communication (NFC) is used for a wide range of security-critical applications such as payment or access control. Although such applications require secured data transfer, the NFC protocol does not include transport layer security. Other protocols that are built on top of NFC, such as the NFC data exchange format (NDEF), only provide insufficient security measures. Therefore, implemented security solutions are often application specific and do not follow well-established standards. To facilitate NFC usage in the Internet of Things (IoT) where millions of devices need to be secured, an efficient and sufficiently secured NFC-based protocol needs to be developed. In this paper, we present the Quick and Secured NFC (QSNFC) protocol. Our protocol is capable of performing more efficient key agreements for recurring connections, and thus, can be used as an efficient alternative to the Transport Layer Security (TLS) protocol.
Physical exercise promotes proliferation and differentiation of endogenous neural stem cells via ERK in rats with cerebral infarction

Physical exercise is beneficial for the functional recovery of neurons after stroke. It has been suggested that exercise regulates proliferation and differentiation of endogenous neural stem cells (NSCs); however, the underlying molecular mechanisms are still largely unknown. In the present study, the aim was to investigate whether physical exercise activates the extracellular signal-regulated kinase (ERK) signaling pathway to promote proliferation and differentiation of NSCs in rats with cerebral infarction, thereby improving neurological function. Following middle cerebral artery occlusion, rats underwent physical exercise and neurological behavior was analyzed at various time points. Immunofluorescence staining was performed to detect proliferation and differentiation of NSCs, and western blotting was used to analyze cyclin-dependent kinase 4 (CDK4), Cyclin D1, retinoblastoma protein (p-Rb), P-16, phosphorylated (p)-ERK1/2 and c-Fos expression. The results indicated that physical exercise promoted proliferation and differentiation of NSCs, and led to improved neural function. In addition, the expression levels of CDK4, Cyclin D1, p-Rb, p-ERK1/2 and c-Fos were upregulated, whereas the expression of P-16 was downregulated following exercise. U0126, an inhibitor of ERK signaling, reversed the beneficial effects of exercise. Therefore, it may be hypothesized that physical exercise enhances proliferation and differentiation of endogenous NSCs in the hippocampus of rats with cerebral infarction via the ERK signaling pathway.
Montclair State University Digital Montclair State University Digital Commons Commons

— Technological advances, established best web development practices, and modern design of the 21st century have provided students, professors, researchers, etc., quasi-effortless access to academic documents encompassed within cleaner user interface and a higher level of usability. Access to and rigorous management of research publication and products is also mandated by funding agencies. Given these characteristics, we have developed an academic repository to maintain the student projects in a typical academic department. A repository of this nature is comprised of two major components: the database and the user interface. The key focus is to provide secure access to research materials (e.g. Master’s projects and the like), similar to that of a community or university library’s online catalogs, while sustaining a keen eye for contemporary front-end design. In addition to providing access to documentation, this repository uses collected data to present various citation styles, assisting users with easy composition of reference pages. Through a familiar search engine paradigm, information on projects, as well as the projects themselves, are discovered and queried using keywords and will be as if performing a Google search. The repository, while focused on single academic unit, can be expended as a campus wide tool, and provides an in house, easily expandable solution to off-the shelf repository solutions.
Homography Estimation Based on Order-Preserving Constraint and Similarity Measurement

Homography is an important concept that has been extensively applied in many computer vision applications. However, accurate estimation of the homography is still a challenging problem. The classical approaches for robust estimation of the homography are all based on the iterative RANSAC framework. In this paper, we explore the problem from a new perspective by finding four point correspondences between two images given a set of point correspondences. The approach is achieved by means of an order-preserving constraint and a similarity measurement of the quadrilateral formed by the four points. The proposed method is computationally efficient as it requires much less iterations than the RANSAC algorithm. But this method is designed for small camera motions between consecutive frames in video sequences. Extensive evaluations on both synthetic data and real images have been performed to validate the effectiveness and accuracy of the proposed approach. In the synthetic experiments, we investigated and compared the accuracy of three types of methods and the influence of the proportion of outliers and the level of noise for homography estimation. We also analyzed the computational cost of the proposed method and compared our method with the state-of-the-art approaches in real image experiments. The experimental results show that the proposed method is more robust than the RANSAC algorithm.
Maneuver and Active Vibration Suppression of Free-Flying Space Robot

This work studies the maneuver control and vibration suppression of a flexible free-flying space robot using variable-speed control moment gyros as actuators. A novel flexible space manipulator is designed. The dynamics of the flexible multibody system is derived by using Kane method. Based on the singular perturbation approach, the dynamics of the flexible manipulator is decoupled into a slow subsystem and a fast subsystem. The slow subsystem is associated with the rigid motion dynamics, and the fast subsystem is related to the link flexible dynamics. A composite control strategy is proposed as a combination of two controllers for these subsystems. An adaptive sliding mode controller is designed for the slow subsystem, and an adaptive controller is designed for the fast subsystem. Uncertainty estimation can be achieved by the adaptive terms of the composite controller. A weighted robust pseudo-inverse steering law is proposed for the variable-speed control moment gyros. Numerical results demonstrate that the proposed composite controller is robust to parameter uncertainties and external disturbances.
A Novel Early Pregnancy Risk Prediction Model for Gestational Diabetes Mellitus

Introduction: Accurate early risk prediction for gestational diabetes mellitus (GDM) would target intervention and prevention in women at the highest risk. We evaluated novel biomarker predictors to develop a first-trimester risk prediction model in a large multiethnic cohort. Methods: Maternal clinical, aneuploidy and pre-eclampsia screening markers (PAPP-A, free hCGβ, mean arterial pressure, uterine artery pulsatility index) were measured prospectively at 11–13+6 weeks’ gestation in 980 women (248 with GDM; 732 controls). Nonfasting glucose, lipids, adiponectin, leptin, lipocalin-2, and plasminogen activator inhibitor-2 were measured on banked serum. The relationship between marker multiples-of-the-median and GDM was examined with multivariate regression. Model predictive performance for early (< 24 weeks’ gestation) and overall GDM diagnosis was evaluated by receiver operating characteristic curves. Results: Glucose, triglycerides, leptin, and lipocalin-2 were higher, while adiponectin was lower, in GDM (p < 0.05). Lipocalin-2 performed best in Caucasians, and triglycerides in South Asians with GDM. Family history of diabetes, previous GDM, South/East Asian ethnicity, parity, BMI, PAPP-A, triglycerides, and lipocalin-2 were significant independent GDM predictors (all p < 0.01), achieving an area under the curve of 0.91 (95% confidence interval [CI] 0.89–0.94) overall, and 0.93 (95% CI 0.89–0.96) for early GDM, in a combined multivariate prediction model. Conclusions: A first-trimester risk prediction model, which incorporates novel maternal lipid markers, accurately identifies women at high risk of GDM, including early GDM.
Sensorless speed control of brushless doubly-fed reluctance machine for pump storage and wind power application

A sensorless speed control technique for brushless doubly-fed reluctance machine (BDFRM) drive using fictitious quantity (X = v∗s × is) based model reference adaptive system (MRAS) is proposed in the present work which is suitable for pump storage and wind power generation applications. The proposed MRAS (X-MRAS) shows stable operation in all the four quadrants of BDFRM drive. In this context, the performance analysis of the complete BDFRM drive, is done under maximum torque per inverter ampere (MTPIA) condition for both motoring and generating modes of operation using MATLAB/SIMULINK. A study on stability and sensitivity analysis of the complete drive system is also included to confirm the efficacy of the scheme.
Vehicle detection and identification in an unconstrained environment

Detection and identification of vehicles in traffic surveillance videos is very important to automate the surveillance system and also to build an intelligent transportation system. In this paper a robust method to detect and identify vehicles is proposed which deals with problem like change in illumination. Background subtraction is done using both Gaussian Mixture Model and Visual Background Extractor and supports dynamic changes in background. Vehicles are detected by finding contours in the image frame. Vehicles are tracked by assigning unique ID for each vehicles. Distance between the centroid of detected vehicle and existing vehicles is calculated. If the distance is greater than threshold value then vehicle is considered to be arrived newly and a unique ID is assigned for further tracking. Otherwise, it is the vehicle will get the same ID as in previous frame. Detected vehicle is classified using Support Vector Machine in each frame and final decision is taken when the vehicle is about to exit from the scene.