Miracle-dz/UniFAR-FTUs huggingface dataset:
TGF‐β Control of Adaptive Immune Tolerance: A Break From Treg Cells

The vertebrate adaptive immune system has well defined functions in maintaining tolerance to self‐tissues. Suppression of autoreactive T cells is dependent on the regulatory cytokine transforming growth factor‐β (TGF‐β) and regulatory T (Treg) cells, a distinct T cell lineage specified by the transcription factor Foxp3. Although TGF‐β promotes thymic Treg (tTreg) cell development by repressing T cell clonal deletion and peripheral Treg cell differentiation by inducing Foxp3 expression, a recent study shows that TGF‐β suppresses autoreactive T cells independent of Foxp3+ Treg cells. These findings imply that as an ancestral growth factor family member, TGF‐β may have been co‐opted as a T cell‐intrinsic mechanism of self‐tolerance control to assist the evolutionary transition of vertebrate adaptive immunity. Later, perhaps in placental mammals upon their acquisition of a TGF‐β regulatory element in the Foxp3 locus, the TGF‐β pathway is further engaged to induce peripheral Treg cell differentiation and expand the scope of T cell tolerance control to innocuous foreign antigens.
Fault Diagnosis of Power Systems Using Intuitionistic Fuzzy Spiking Neural P Systems

In this paper, intuitionistic fuzzy spiking neural P (IFSNP) systems as a variant are proposed by integrating intuitionistic fuzzy logic into original spiking neural P systems. Compared with a common fuzzy set, intuitionistic fuzzy set can more finely describe the uncertainty due to its membership and non-membership degrees. Therefore, IFSNP systems are very suitable to deal with fault diagnosis of power systems, specially with incomplete and uncertain alarm messages. The fault modeling method and fuzzy reasoning algorithm based on IFSNP systems are discussed. Two examples are used to demonstrate the availability and effectiveness of IFSNP systems for fault diagnosis of power systems. Case studies involve single fault, complex fault, and multiple faults with protection device failures and incorrect tripping signals.
Modification of Tracking Algorithm Struck by the Application of the Scale Estimation Method

The article considers work of visual object tracking algorithm “Struck”, scales estimation algorithm based on the correlation filter and their cooperative work. The results of the experiments showed that the combination of these algorithms allows achievement of gain in precision of visual object tracking in different variations of sizes of tracked object, compared to the original version of “Struck”. The average gain is equal from 30% and depends on the number of scales in tested video sequences. The features of these sequences: increasing and decreasing of object sizes in 3 - 30 times. The localization accuracy of the object degrades the accuracy of the estimation of the object size. Performance is decreased by 5 - 8 frames per second on averages in comparison to the original algorithm of the “Struck”. However, our proposed method provides real-time working.
Comparison of Clinical Instructors' Teaching Behaviors as Perceived by Themselves with Those Assessed by their Students in the Clinical Setting

The clinical education is considered as the heart of the nursing education. It remains the single most important resource in the development of competent, capable, and caring nurses. It prepares the students for their professional role and provides them with opportunity to apply knowledge, skills, and concepts in the clinical settings. Most importantly, clinical instructors' behaviors in the clinical area play an important part in the learning process of the student. There are few studies that determine and evaluate what constitutes effective teaching behaviors of clinical instructors in the clinical area. Hence, the present study aimed at comparing clinical instructors' teaching behaviors as perceived by themselves with those assessed by their students and also using qualitative analysis to determine positive and negative students' comments for clinical instructor behaviors in the clinical setting. The study was conducted at Faculty of Nursing at Mansoura University. Two groups of subjects were included in the present study; clinical instructors group (n=62) and nursing students group (n=120). Two questionnaire sheets were used for data collection; clinical instructors' questionnaire and student's questionnaire that were developed by researcher based on reviewing literature. The third part of student's questionnaire included open ended questions to establish positive and negative clinical instructors' as perceived by student encountered in clinical training. A major finding of this study was that there was a statistical significance difference between clinical instructors' teaching behaviors as perceived by themselves with those assessed by their students in the clinical setting. At the end of the study, recommendations were given that clinical instructor should offer information and positive feedback in the directions of students, being accessible and also encourage student's creative thinking and freedom in discussion.
Constrained Optimal End-Effector Positioning Using Pseudo-Inversion and B-Splines: Numerical Simulation on the One Link Flexible Manipulator Linearized Model

This paper investigates the potential possibility offered by the recently proposed pseudo inversion approach as a novel solution to the optimal output transition problem in the end-effector positioning task under saturation constraints on the control effort. Exact positioning and high precision tracking of the end-effector along a given path are key requirements. Due to flexibility and non minimum phase nature of the system, achieving high level performances is a challenging problem. To this purpose a two degrees of freedom control scheme is proposed: a feedforward action, denoted by r (t), is applied to the stable closed loop system Σf,c, given by the feedback connection of the flexible arm with a stabilizing controller. The recently proposed pseudo inversion approach is adopted to compute r(t) yielding an actual end-effector transient trajectory which is the best approximation of the desired transient one. The optimal r(t) is assumed to be given by a B-spline function, and, to take into account saturating actuators, the actual control input u(t) forcing the flexible arm is optimally approximated by a B-spline u(t), whose control points u(t) are chosen in such a way to satisfy the saturation constraints on u(t). If u(t) is a sufficiently accurate approximation of u(t), the exact fulfillment of saturation constraints by u(t) are transferred to u(t). The main advantage of the approach is its generality: the method can be directly applied to the linear dynamic model of any multilink flexible arm.
Parenteral phenobarbital in status epilepticus revisited: Mayo Clinic experience

Despite phenobarbital (PB) being a key component in status epilepticus (SE) treatment algorithms for decades, it has fallen out of favor compared to newer nonsedating medications due to potential for respiratory suppression and prolonged sedation. We retrospectively analyzed all nonintubated patients with refractory SE treated with parenteral PB. Forty patients were identified as having received PB in the neurologic intensive care unit at Mayo Clinic over a 7‐year period through our pharmacy dispensing database. Patients who received PB for maintenance therapy, those replenishing subtherapeutic levels, those who were already intubated, and those receiving PB for a non‐SE indication were excluded. Clinical data, prior treatments, therapeutic response, and outcome were reviewed. Eight patients were identified. Ages ranged from 24 to 77 years (median = 64 years); all had focal SE, and none was comatose. Seizure activity improved acutely following PB administration in seven and stopped in six. Dosages ranged from 5 to 19.8 mg/kg (median = 10.1 mg/kg); none required intubation, and one received supplemental oxygen. Patients received a median of four antiepileptic drugs prior to PB. Median interval between first drug and PB was 23.5 hours. Glasgow Coma Scale score did not change following PB administration. One patient required intervention for hypotension. Moderate‐dose parenteral PB was effective in attaining seizure control in a significant proportion of noncomatose refractory SE patients. None required ventilatory support. PB dosages below those in recent guidelines may be sufficient to stop SE without clinically significant cardiopulmonary complications.
Path Planning for Automation of Surgery Robot based on Probabilistic Roadmap and Reinforcement Learning

Laparoscopic robotic surgery is a new surgical method performed by inserting several surgical tools and a laparoscope through an umbilical incision [12]. Compared with conventional laparoscopic surgery minimizes patient pain with minimally invasive surgery and has many advantages in terms of beauty. However, medical doctor's fatigue due to repetitive operations such as tissue resection and suturing still remains a problem to be improved. To solve this problem, there are a lot of automation researches on surgical robots [1], [7]–[10]. Especially in cutting automaton, for high accuracy, optimal path planning is essential factor. Probabilistic Roadmap (PRM) is a popular method for path planning. It creates path from static environment to desired point without collision. However, this does not show great performance in a dynamic environment. Reinforcement Learning (RL) shows strong performance in an unspecified probabilistic environment and it is widely applied to robot motion learning because learning data is not needed before [4]. In this paper, we suggest a collision avoidance path planning for automation of surgery robot by using PRM and RL in dynamic situation. We found the collision avoidance path through PRM and RL, and used mapping algorithm of coordination system from pixel to world coordination and transformed the coordination system from cartesian space to joint space using inverse kinematics. Finally, we apply it to the APOLLON laparoscopic surgery robotic system developed by KAIST in V-rep simulator. As a result, we confirmed a possible of collision avoidance path planning for automation of resection task for surgery robot.
Feature Selection for Anomaly Detection in Vehicular Ad Hoc Networks

An emerging trend to improve automotive safety is the development of Vehicle-to-Vehicle (V2V) safety applications. These applications use information gathered from the vehicle's sensors and from surrounding vehicles to detect and prevent imminent crashes. Vehicles have been equipped with external communication interfaces to make these applications possible, but this also exposes them to security threats. If an attacker is able to feed safety applications with incorrect data, they might actually cause accidents rather than prevent them. In this paper, we investigate the application of white-box anomaly detection to detect such attacks. A key step in applying such an approach is the selection of the “right” behavioral features, i.e. features that allow the detection of attacks and provide an understanding of the raised alerts. By finding meaningful features and building accurate models of normal behavior, this work makes a first step towards the design of effective anomaly detection engines for V2V communication.
An Adaptive Importance Sampling Method for Spinning Reserve Risk Evaluation of Generating Systems Incorporating Virtual Power Plants

The concept of virtual power plant (VPP) has been proposed to manage distributed renewable energy sources as packaging to engage in the energy and reserve planning on contemporary generating portfolios. In this context, an efficient tool is needed to support analysis of generating flexibility of conventional units in combination with VPPs to cooperatively counterbalance the fluctuation of net demand. In this paper, an adaptive importance sampling method is proposed, intentionally for efficiently evaluating specific indices capturing the possibility and severity of rare inadequate spinning reserve events of a deployed unit comment schedule for a generating system incorporating VPPs, in terms of short-term stochastic unit failures and power fluctuation of VPPs. The proposed method is based on the standard cross-entropy (CE) method, which newly introduces a mathematical transformation aiming at diverting evaluations of customized risk indices to a generic rare-event probability estimation problem. A Markov chain Monte Carlo method is employed to train the proposal density, to efficiently gain on the best, owing to avoiding the iterative parameter-updating mechanism of the standard CE method. The efficacy of the proposed method is tested on a modified RTS-96 generating system emulating a portfolio of conventional and renewable generating sources modeled as VPPs.
Analytical Modeling, Simulation, and Fabrication of a MEMS Rectangular Paddle Piezo-Resistive Micro-Cantilever-Based Wind Speed Sensor

In this paper, fabrication of a rectangular paddle micro-cantilever-based wind speed sensor along with its analytical model has been presented. The analytical model uses the closed-form solution to the bending stress caused by static deflection. Simulations of the device were done using finite-element analysis. The simulation, analytical, and experimental results have been compared for a better insight into the sensor behavior. Piezo-resistive deflection detection mechanism has been utilized to measure the wind speed. The experimental results show that the fabricated sensor can detect wind speed up to 29 ms−1 and has a sensitivity of 0.071 mV/ms−1 – V.
Collaborative Visual Area Coverage by Aerial Agents Under Positioning Uncertainty

In this article a control scheme for the coverage of a convex region by a team of Mobile Aerial Agents (MAAs) is presented. Each MAA is outfitted with a downwards facing camera, the sensed area of which is dependent on the MAA's altitude. Additionally, the MAAs' footprints are assumed to be known with a certain degree of uncertainty. In order to take into account the MAAs' positioning uncertainty as well as their varying sensed areas, an Additively Weighted Guaranteed Voronoi (AWGV) partitioning of the region is utilized. Based on this partitioning scheme, a gradient-based algorithm is derived in order to guarantee monotonic increase of an area coverage metric, while also constraining the MAAs' altitudes and it is extended to offer collision avoidance. The proposed scheme is evaluated through simulation studies.
Psychosocial factors at work and inflammatory markers: protocol for a systematic review and meta-analysis

Introduction Chronic inflammation may be a mediator for the development of cardiovascular disease (CVD), metabolic diseases and psychotic and neurodegenerative disorders. Meta-analytic associations between work-related psychosocial factors and inflammatory markers have shown that work-related psychosocial factors could affect the flexibility and balance of the immune system. However, few systematic reviews or meta-analyses have investigated the association between work-related psychosocial factors and inflammatory markers. Based on prospective studies, the present investigation will conduct a comprehensive systematic review and meta-analysis of the association between work-related psychosocial factors and inflammatory markers. Methods and analysis The systematic review and meta-analysis will include published studies identified from electronic databases (PubMed, EMBASE, PsycINFO, PsycARTICLES, Web of Science and Japan Medical Abstracts Society) according to recommendations of the Meta-analysis of Observational Studies in Epidemiology guideline. Inclusion criteria are studies that: examined associations between work-related psychosocial factors and increased inflammatory markers; used longitudinal or prospective cohort designs; were conducted among workers; provided sufficient data for calculating ORs or relative risk with 95% CIs; were published as original articles in English or Japanese; and were published up to the end of 2017. Study selection, data extraction, quality assessment and statistical syntheses will be conducted by 14 investigators. Any inconsistencies or disagreements will be resolved through discussion. The quality of studies will be evaluated using the Risk of Bias Assessment Tool for Non-randomized Studies. Ethics and dissemination The investigation study will be based on published studies, so ethics approval is not required. The results of this study will be submitted for publication in a scientific peer-reviewed journal. The findings may be useful for assessing risk factors for increased inflammatory markers in the workplace and determining future approaches for preventing CVD, metabolic diseases and psychotic and neurodegenerative disorders. PROSPERO registration number CRD42018081553.
Analysis of Half Circular F Slot Multiband Microstrip Antenna with Defected Ground Structure

A half circular F slot multiband microstrip patch antenna (MSA) with defected ground structure (DGS) presented through this paper. The dimension of proposed antenna is 39.6 × 24.6 × 1.6 mm3 for two different substrate materials (Fr-4 andTeflon). The performance analysis of proposed antenna characteristics such as return loss, VSWR and radiation pattern has simulated using ANSoft HFSS. This antenna has resonated at frequencies 3.4 GHz, 6GHz and 8.25 GHz with impedance bandwidth 2.35%,2.58% and 3.15% respectively lies in S, C and X band for Teflon base substrate, and resonated at frequencies 2.5 GHz, 4.45 GHz, 5.15 GHz and 6.15 GHz operated with impedance bandwidth3.2%, 4.26%, 2.52% and 3.98% in S and C bands respectively for Fr-4 substrate.
Theoretical Security Evaluation of the Human Semantic Authentication Protocol

Using a secret password or a PIN (Personal Identification Number) code is a common way to authenticate a user. Unfortunately this protection does not resist an attacker that can eavesdrop on the user (shoulder surfing attack). The Human Semantic Authentication (HSA) protocol proposes a solution against this attack. The main idea is to have concept passwords and to propose images that the user must correctly select in order to authenticate. A concept can be represented by different pictures, so one observation is not enough to retrieve the secret. In this paper, the security/efficiency trade-off in the HSA protocol is evaluated. A probabilistic approach is used. Under the assumption that the picture/concept database is known to the attacker, we show that HSA is barely more resistant to shoulder surfing attacks than a PIN code. More precisely we show that the probability to retrieve the secret concept password increases rapidly with the number of observations. Moreover the constraints on the size of the picture/concept database are very difficult to satisfy in practice.
Virtualization: Past and Present Challenges

Virtualization plays an important role in cloud computing by providing the capability of running multiple operating systems and applications on top of the same underlying hardware. However, there are limitations in current virtualization technologies, which are inherited by cloud computing. For example, performance, security and dependability. While these challenges remain, the adoption of virtualization in the different fields will be limited. This paper presents a survey in the past and open virtualization challenges, such as nested virtualization, reliability and security.
Wide-Area Monitoring of Power Systems Using Principal Component Analysis and  $k$-Nearest Neighbor Analysis

Wide-area monitoring of power systems is important for system security and stability. It involves the detection and localization of power system disturbances. However, the oscillatory trends and noise in electrical measurements often mask disturbances, making wide-area monitoring a challenging task. This paper presents a wide-area monitoring method to detect and locate power system disturbances by combining multivariate analysis known as Principal Component Analysis (PCA) and time series analysis known as <inline-formula><tex-math notation="LaTeX">$k$</tex-math> </inline-formula>-Nearest Neighbor (<inline-formula><tex-math notation="LaTeX">$k{\text{NN}}$</tex-math> </inline-formula>) analysis. Advantages of this method are that it can not only analyze a large number of wide-area variables in real time but also can reduce the masking effect of the oscillatory trends and noise on disturbances. Case studies conducted on data from a four-variable numerical model and the New England power system model demonstrate the effectiveness of this method.
Registration of Inconsistent Point Cloud Maps with Large Scale Persistent Features

Accurate point cloud registration techniques such as Iterative Closest Point matching have been developed to produce large scale 3D maps of the environment. Typically they iteratively register point clouds captured from adjacent sensor scans resulting in point clouds which are largely consistent. However, merging two seperate point cloud maps constructed at different times can lead to significant inconsistencies between the point clouds. Existing point based registration techniques can be sensitive to local minima caused by such inconsistencies. Feature based approaches can overcome local minimum but are typically less accurate, and can still suffer from correspondence errors. We introduce Large Scale Persistent Features (LSPFs), sub regions of point clouds that have orthogonal planar regions that are consistent and persist over a large spatial area. Each LSPF is used to calculate an individual transformation estimate using traditional registration techniques. Sampling Consensus is then used to select the best transform which is used for registration, avoiding local minima. LSPF registration is applied to simulated point cloud maps with known inconsistencies and shown to perform with more accuracy and lower computation time than other popular approaches. In addition, real world registration results are presented which demonstrate LSPF registration between MMS maps and low cost sensor maps captured 6 months apart.
Optical Wireless Communication Channel Measurements and Models

Optical wireless communications (OWCs) refer to wireless communication technologies which utilize optical carriers in infrared, visible light, or ultraviolet bands of electromagnetic spectrum. For the sake of an OWC link design and performance evaluation, a comprehensive understanding and an accurate prediction of link behavior are indispensable. Therefore, accurate and efficient channel models are crucial for the OWC link design. This paper first provides a brief history of OWCs. It also considers OWC channel scenarios and their utilization trade-off in terms of optical carrier, range, mobility, and power efficiency. Furthermore, the main optical channel characteristics that affect the OWC link performance are investigated. A comprehensive overview of the most important OWCs channel measurement campaigns and channel models, primarily for wireless infrared communications and visible light communications, are presented. OWCs channel models are further compared in terms of computation speed, complexity, and accuracy. The survey considers indoor, outdoor, underground, and underwater communication environments. Finally, future research directions in OWCs channel measurements and models are addressed.