nils-herrmann/clean_scirepeval huggingface dataset:
An Effective Via-Based Frequency Adjustment and Minimization Methodology for Single-Layered Frequency-Selective Surfaces

This paper proposes a new methodology for minimizing the size of the periodic element and tuning the resonant frequency of a single-layered frequency-selective surface (FSS). Vertical vias are introduced to the FSS design in the methodology. This via-based methodology can be applied to nearly all of the single-layered FSSs presented in the literature, which exhibit much more convenience in practice than the multilayered FSSs. Through the proposed methodology, users can easily vary the resonant frequency of the considered via-inserted FSS (VI-FSS), adding only some additional vias and without having to modify the original element pattern. In addition, the proposed methodology can be applied to minimize the element size or lower its resonant frequency. To illustrate the methodology, the well-known Jerusalem Cross (JC) FSS was first considered. A high-order equivalent circuit was suggested to model the physical mechanism of the VI-FSS with the applied methodology. A set of closed-form equations was also provided to calculate efficiently the circuit inductances and capacitances, especially those caused by the added vias. The VI-FSS prototype was fabricated and examined in a fully anechoic chamber. Favorable agreement among the proposed circuit, full-wave simulation, and measurement was achieved. For demonstrating the capability of the via-based methodology further, it was applied to two advanced applications: 1) two miniaturized-element FSSs and 2) an FSS absorber. Thus, a significant performance improvement in these applications reconfirmed the capability of the proposed methodology.
Antibody-modified T cells: CARs take the front seat for hematologic malignancies.

T cells redirected to specific antigen targets with engineered chimeric antigen receptors (CARs) are emerging as powerful therapies in hematologic malignancies. Various CAR designs, manufacturing processes, and study populations, among other variables, have been tested and reported in over 10 clinical trials. Here, we review and compare the results of the reported clinical trials and discuss the progress and key emerging factors that may play a role in effecting tumor responses. We also discuss the outlook for CAR T-cell therapies, including managing toxicities and expanding the availability of personalized cell therapy as a promising approach to all hematologic malignancies. Many questions remain in the field of CAR T cells directed to hematologic malignancies, but the encouraging response rates pave a wide road for future investigation.
Log-Free Concurrent Data Structures

Non-volatile RAM (NVRAM) makes it possible for data structures to tolerate transient failures, assuming however that programmers have designed these structures such that their consistency is preserved upon recovery. Previous approaches are typically transactional and inherently make heavy use of logging, resulting in implementations that are significantly slower than their DRAM counterparts. In this paper, we introduce a set of techniques aimed at lock-free data structures that, in the large majority of cases, remove the need for logging (and costly durable store instructions) both in the data structure algorithm and in the associated memory management scheme. Together, these generic techniques enable us to design what we call log-free concurrent data structures, which, as we illustrate on linked lists, hash tables, skip lists, and BSTs, can provide several-fold performance improvements over previous transaction-based implementations, with overheads of the order of milliseconds for recovery after a failure. We also highlight how our techniques can be integrated into practical systems, by presenting a durable version of Memcached that maintains the performance of its volatile counterpart.
GA-based Global Path Planning for Mobile Robot Employing A* Algorithm

Global path planning for mobile robot using genetic algorithm and A* algorithm is investigated in this paper. The proposed algorithm includes three steps: the MAKLINK graph theory is adopted to establish the free space model of mobile robots firstly, then Dijkstra algorithm is utilized for finding a feasible collision-free path, finally the global optimal path of mobile robots is obtained based on the hybrid algorithm of A* algorithm and genetic algorithm. Experimental results indicate that the proposed algorithm has better performance than Dijkstra algorithm in term of both solution quality and computational time, and thus it is a viable approach to mobile robot global path planning.
Ultra low-power 7T SRAM cell design based on CMOS

In his paper a 7T SRAM cell operating well in low voltages is presented. Suitable read operation structure is provided by controlling the drain induced barrier lowering (DIBL) effect and body-source voltage in the hold `1' state. The read-operation structure of the proposed cell utilizes the single transistor which leads to a larger write margin. The simulation results at 90nm TSMC CMOS demonstrate the outperforms of the proposed SRAM cell in terms of power dissipation, write margin, sensitivity to process variations as compared with the other most efficient low-voltage SRAM cells.
Optimising and enhancing human performance through nutrition

1 Introduction 545 2 Eating to optimise training 545 2.1 Energy needs for training and the ideal physique 545 2.2 Strategies to reduce mass and body fat 547 2.3 Requirements for growth and gaining lean body mass 548 3 Protein needs for muscle gain, training enhancement and repair 549 4 Fuel needs for training and recovery 550 5 Eating to minimise illness and injury 551 5.
Updates on Nutraceutical Sleep Therapeutics and Investigational Research

Approximately 50% of the population will suffer from a sleep disorder over the course of their lifetime. There is increasing interest in nutraceuticals for these conditions. The quality of the evidence for the safety and effectiveness of using these supplements to treat sleep disorders varies substantially. In this review, we discuss the data about the effectiveness and safety of six commonly used plant-based sleep therapeutics: caffeine, chamomile, cherries, kava kava, L-tryptophan, marijuana, and valerian. We explore both historical uses of each substance and the current state of the literature.
A systematic review of the neural bases of psychotherapy for anxiety and related disorders

Brain imaging studies over two decades have delineated the neural circuitry of anxiety and related disorders, particularly regions involved in fear processing and in obsessive-compulsive symptoms. The neural circuitry of fear processing involves the amygdala, anterior cingulate, and insular cortex, while cortico-striatal-thalamic circuitry plays a key role in obsessive-compulsive disorder. More recently, neuroimaging studies have examined how psychotherapy for anxiety and related disorders impacts on these neural circuits. Here we conduct a systematic review of the findings of such work, which yielded 19 functional magnetic resonance imaging studies examining the neural bases of cognitive-behavioral therapy (CBT) in 509 patients with anxiety and related disorders. We conclude that, although each of these related disorders is mediated by somewhat different neural circuitry, CBT may act in a similar way to increase prefrontal control of subcortical structures. These findings are consistent with an emphasis in cognitive-affective neuroscience on the potential therapeutic value of enhancing emotional regulation in various psychiatric conditions.
Improving oracle quality by detecting brittle assertions and unused inputs in tests

Writing oracles is challenging. As a result, developers often create oracles that check too little, resulting in tests that are unable to detect failures, or check too much, resulting in tests that are brittle and difficult to maintain. In this paper we present a new technique for automatically analyzing test oracles. The technique is based on dynamic tainting and detects both brittle assertions—assertions that depend on values that are derived from uncontrolled inputs—and unused inputs—inputs provided by the test that are not checked by an assertion. We also presented OraclePolish, an implementation of the technique that can analyze tests that are written in Java and use the JUnit testing framework. Using OraclePolish, we conducted an empirical evaluation of more than 4000 real test cases. The results of the evaluation show that OraclePolish is effective; it detected 164 tests that contain brittle assertions and 1618 tests that have unused inputs. In addition, the results also demonstrate that the costs associated with using the technique are reasonable.
Tungsten plug corrosion on B2H6-based nucleation layer induced by WCMP process

The topic of this paper is to identify tungsten plug corrosion issue at the interface of barrier metal and W bulk in W-CMP process. Two types of nucleation layers in W-CVD deposition process - SiH<sub>4</sub> and B<sub>2</sub>H<sub>6</sub> based were studied. The B<sub>2</sub>H<sub>6</sub> based nucleation W will induce W corrosion. However, SiH<sub>4</sub> based nucleation W does not have the issue. The static etch rate, electrochemical properties and removal rate (R.R.) of two types W-CMP slurries and SiH<sub>4</sub> and B<sub>2</sub>H<sub>6</sub> based nucleation W were evaluated. It has been demonstrated that the B<sub>2</sub>H<sub>6</sub> based nucleation film has much higher intensity of static etching on various W slurries. The B<sub>2</sub>H<sub>6</sub> based nucleation layer is weak than SiH<sub>4</sub> based, and it induces corrosion during W-CMP process.
What's the Risk? A simple approach for estimating adjusted risk measures from nonlinear models including logistic regression.

To develop and validate a general method (called regression risk analysis) to estimate adjusted risk measures from logistic and other nonlinear multiple regression models. We show how to estimate standard errors for these estimates. These measures could supplant various approximations (e.g., adjusted odds ratio [AOR]) that may diverge, especially when outcomes are common.



Regression risk analysis estimates were compared with internal standards as well as with Mantel-Haenszel estimates, Poisson and log-binomial regressions, and a widely used (but flawed) equation to calculate adjusted risk ratios (ARR) from AOR.



Data sets produced using Monte Carlo simulations.



Regression risk analysis accurately estimates ARR and differences directly from multiple regression models, even when confounders are continuous, distributions are skewed, outcomes are common, and effect size is large. It is statistically sound and intuitive, and has properties favoring it over other methods in many cases.



Regression risk analysis should be the new standard for presenting findings from multiple regression analysis of dichotomous outcomes for cross-sectional, cohort, and population-based case-control studies, particularly when outcomes are common or effect size is large.
Social Engineering 2.0: A Foundational Work: Invited Paper

During the past few years, social engineering has rapidly evolved and has become a mainstream technique in cybercrime and terrorism. It is used especially in targeted attacks involving complex human and technological exploits, aimed at deceiving humans and IT systems. Building on the work carried out in the DOGANA project, funded by the European Union, this paper provides an overview of the evolution and of the current landscape of social engineering, and introduces as its main contribution a theoretical model of how human exploits are built, named the Victim Communication Stack.
A novel dual-mode bandpass filter with wide stopband using the properties of microstrip open-loop resonator

A novel dual-mode microstrip square loop resonator is proposed using the slow-wave and dispersion features of the microstrip slow-wave open-loop resonator. It is shown that the designed and fabricated dual-mode microstrip filter has a wide stopband including the first spurious resonance frequency. Also, it has a size reduction of about 50% at the same center frequency, as compared with the dual-mode bandpass filters such as microstrip patch, cross-slotted patch, square loop, and ring resonator filter.
Self-biting with multiple finger amputations following spinal cord injury

We have observed mutilative self-biting leading to multiple finger amputations in two patients following C4 complete spinal cord injury (SCI). Both men were of normal intelligence without psychosis and each had a neurotic personality and history of fingernail biting. They related the self-biting to anxiety and depression. We believe these to be the first English language reports of multiple finger amputations due to self-biting following SCI.
Predictive Cruise Control of Connected and Autonomous Vehicles: An Adaptive Dynamic Programming Approach

This paper proposes a novel predictive cruise control method for a platoon of connected and autonomous vehicles. The main objective is to minimize idle time of vehicular platoon using information from the traffic lights. First, the reference velocity is determined for each vehicle in the platoon. Second, a data-driven learning strategy, named adaptive dynamic programming (ADP), is employed to develop an optimal state-feedback controller without any prior knowledge of the platooning system dynamics. This resultant controller regulates the headway, velocity and acceleration of each vehicle to accommodate both safety and trip time reduction goals. A numerical simulation is demonstrated to ascertain the effectiveness of the proposed approach.
Comparison of craniofacial characteristics of typical Chinese and Caucasian young adults.

The purpose of this study was to determine the cephalometric norms of typical Chinese young adult subjects with normal occlusions and well-balanced faces and to compare these norms with those derived from a matched Caucasian sample. Lateral cephalograms of 65 untreated Chinese adults (25 males, mean age 19.3 ± 3.0 years and 40 females, mean age 20.3 ± 3.4 years) were compared with a sample of 90 untreated Caucasian adults (30 males, mean age 24.1 ± 5.7 years and 60 females, mean age 22.9 ± 5.2 years). Each lateral cephalogram was traced and digitized, and conventional cephalometric analyses were applied. Independent sample t-tests were used to compare the values between the two ethic samples. Smaller midfaces and shorter mandibles were observed in Chinese young adults compared with those of Caucasians. The average value of lower anterior face height (ANS-Me) was longer in the Chinese females than that in the Caucasian females (P < 0.001). A greater vertical dimension also was seen in Chinese males compared with Caucasian males when evaluated by analysis of the facial axis angle (P < 0.05). The upper and lower lips were more protrusive in the Chinese, and a more convex facial profile was seen compared with the Caucasian sample. Significant differences in hard and soft tissue characteristics were found between Chinese and Caucasian young adults with normal occlusions and well-balanced faces. Gender and racial/ethnic differences must be taken into consideration during orthodontic diagnosis and treatment planning for the individual patient.
CNTFET Modeling and Reconfigurable Logic-Circuit Design

This paper examines aspects of design technology required to explore advanced logic-circuit design using carbon nanotube field-effect transistor (CNTFET) devices. An overview of current types of CNTFETs is given and highlights the salient characteristics of each. Compact modeling issues are addressed and new models are proposed implementing: 1) a physics-based calculation of energy conduction sub-band minima to allow a realistic analysis of the impact of CNT helicity and radius on the dc characteristics; 2) descriptions of ambipolar behavior in Schottky-barrier CNTFETs and ambivalence in double-gate CNTFETs (DG-CNTFETs). Using the available models, the influence of the parameters on the device characteristics were simulated and analyzed. The exploitation of properties specific to CNTFETs to build functions inaccessible to MOSFETs is also described, particularly with respect to the use of DG-CNTFETs in fine-grain reconfigurable logic.
Synthetic aperture radar signal processing in parallel using GPGPU

In this work an efficient parallel implementation of the Chirp Scaling Algorithm for Synthetic Aperture Radar processing is presented. The architecture selected for the implementation is the general purpose graphic processing unit, as it is well suited for scientific applications and real-time implementation of algorithms. The analysis of a first implementation led to several improvements which resulted in an important speed-up. Details of the issues found are explained, and the performance improvement of their correction explicitly shown.
Exploring the Reasons Behind Parental Refusal of Vaccines.

Parental refusal of vaccines is a growing a concern for the increased occurrence of vaccine preventable diseases in children. A number of studies have looked into the reasons that parents refuse, delay, or are hesitant to vaccinate their child(ren). These reasons vary widely between parents, but they can be encompassed in 4 overarching categories. The 4 categories are religious reasons, personal beliefs or philosophical reasons, safety concerns, and a desire for more information from healthcare providers. Parental concerns about vaccines in each category lead to a wide spectrum of decisions varying from parents completely refusing all vaccinations to only delaying vaccinations so that they are more spread out. A large subset of parents admits to having concerns and questions about childhood vaccinations. For this reason, it can be helpful for pharmacists and other healthcare providers to understand the cited reasons for hesitancy so they are better prepared to educate their patients' families. Education is a key player in equipping parents with the necessary information so that they can make responsible immunization decisions for their children.
Radiation characteristics of slotted waveguide array antenna for X-Band dual-polarized weather radar

This paper proposes the design of weather radar antenna on X-Band frequency with two polarizations. The antenna is built based on slotted waveguide antenna array (SWAA) with its antenna structure consists of 2 layers, first layer is a radiating waveguide and second layer is a feeder waveguide. The first layer is composed of 5 waveguides in which each of waveguide consist of 64 slots, while the second layer is a single waveguide. The simulation result shows that the key antenna parameters performace reaches the specification such as: operating frequency = 9380 MHz, S11 = -22.567, bandwidth = 51.4 MHz, 3 dB-beamwidth for H-pol = 1.2 degree, 3 dB-beamwidth for V-pol = 1.0 degree, sidelobe level for H-pol = -17.3 dB, sidelobe level for V-pol = -15.2 dB, co-pol for H-pol = 20.6 dB, co-pol for V-pol = 16.2 dB, cross-pol for H-pol = -20 dB, and cross-pol for V-pol = -20.3 dB. Therefore, the proposed antenna is suitable for use as a weather radar antenna.
Workplace stress in nursing: a literature review.

Stress perception is highly subjective, and so the complexity of nursing practice may result in variation between nurses in their identification of sources of stress, especially when the workplace and roles of nurses are changing, as is currently occurring in the United Kingdom health service. This could have implications for measures being introduced to address problems of stress in nursing.



To identify nurses' perceptions of workplace stress, consider the potential effectiveness of initiatives to reduce distress, and identify directions for future research.



A literature search from January 1985 to April 2003 was conducted using the key words nursing, stress, distress, stress management, job satisfaction, staff turnover and coping to identify research on sources of stress in adult and child care nursing. Recent (post-1997) United Kingdom Department of Health documents and literature about the views of practitioners was also consulted.



Workload, leadership/management style, professional conflict and emotional cost of caring have been the main sources of distress for nurses for many years, but there is disagreement as to the magnitude of their impact. Lack of reward and shiftworking may also now be displacing some of the other issues in order of ranking. Organizational interventions are targeted at most but not all of these sources, and their effectiveness is likely to be limited, at least in the short to medium term. Individuals must be supported better, but this is hindered by lack of understanding of how sources of stress vary between different practice areas, lack of predictive power of assessment tools, and a lack of understanding of how personal and workplace factors interact.



Stress intervention measures should focus on stress prevention for individuals as well as tackling organizational issues. Achieving this will require further comparative studies, and new tools to evaluate the intensity of individual distress.
How to Train Triplet Networks with 100K Identities?

Training triplet networks with large-scale data is challenging in face recognition. Due to the number of possible triplets explodes with the number of samples, previous studies adopt the online hard negative mining(OHNM) to handle it. However, as the number of identities becomes extremely large, the training will suffer from bad local minima because effective hard triplets are difficult to be found. To solve the problem, in this paper, we propose training triplet networks with subspace learning, which splits the space of all identities into subspaces consisting of only similar identities. Combined with the batch OHNM, hard triplets can be found much easier. Experiments on the large-scale MS-Celeb-1M challenge with 100 K identities demonstrate that the proposed method can largely improve the performance. In addition, to deal with heavy noise and large-scale retrieval, we also make some efforts on robust noise removing and efficient image retrieval, which are used jointly with the subspace learning to obtain the state-of-the-art performance on the MS-Celeb-1M competition (without external data in .
Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning

We present single-cell interpretation via multikernel learning (SIMLR), an analytic framework and software which learns a similarity measure from single-cell RNA-seq data in order to perform dimension reduction, clustering and visualization. On seven published data sets, we benchmark SIMLR against state-of-the-art methods. We show that SIMLR is scalable and greatly enhances clustering performance while improving the visualization and interpretability of single-cell sequencing data.
The Effect of the Internet of Things (IoT) on Education Business Model

The introduction of the Internet of Things (IoT) in education, which allows Internet based communications to happen between physical objects, sensors and controllers, has changed educational institutions massively. By embedding sensors in objects and integrating cloud computing, augmented reality, wearable technologies and big data in this platform, different parameters of the educational environment can be measured and analysed to provide useful information. It also has created a new interaction between people and the environment in educational organisation. In this research based on the recent IoT projects in education, we will categorize the application of IoT in education into four groups: energy management and real time ecosystem monitoring, monitoring student's healthcare, classroom access control and improving teaching and learning. We will investigate and analyse how this platform has changed the Education Business Model and added new value propositions in such organizations based on the Canvas Business Model.