Miracle-dz/UniFAR-FTUs huggingface dataset:
Recommendations for Social Skills End Points for Clinical Trials in Neurofibromatosis Type 1

Objective To review parent-report social skills measures to identify and recommend consensus outcomes for use in clinical trials of social deficit in children and adolescents (ages 6–18 years) with neurofibromatosis type 1 (NF1). Methods Searches were conducted via PubMed and ClinicalTrials.gov to identity social skills outcome measures with English language versions used in clinical trials in the past 5 years with populations with known social skills deficits, including attention-deficit/hyperactivity disorder and autism spectrum disorder (ASD). Measures were rated by the Response Evaluation in Neurofibromatosis and Schwannomatosis (REiNS) Neurocognitive Committee on patient characteristics, use in published studies, domains assessed, availability of standard scores, psychometric properties, and feasibility to determine their appropriateness for use in NF1 clinical trials. Results Two measures were ultimately recommended by the committee: the Social Responsiveness Scale–2 (SRS-2) and the Social Skills Improvement System–Rating Scale (SSIS-RS). Conclusions Each of the 2 measures assesses different aspects of social functioning. The SSIS-RS is appropriate for studies focused on broader social functioning; the SRS-2 is best for studies targeting problematic social behaviors associated with ASD. Researchers will need to consider the goals of their study when choosing a measure, and specific recommendations for their use are provided.
Characterization of micromachined cantilever valves

This paper reports the fabrication and simulation of micromachined cantilever valves. For quasi-static fluid-structural simulations, the FEM package ANSYS and the CFD package Flow3D are coupled with a control programme to yield the flow rate for the cantilever valve. The results are compared with micromachined cantilever valves. The fabrication of these valves can be subdivided into the generation of cantilevers and ducts via KOH etching and a final fusion bonding step to join them. For the release of the cantilever, toluene is used to avoid stiction while drying the chips. Agreement between measured and simulated flow rates is shown to be good and gives confidence in the use of this simulator for valve development. Dynamic simulations are established with an impact model of the cantilever sitting on top of the duct. This allows the prediction of the dynamic behaviour of cantilever valves.
Analytical Predictions and Correlation With Physical Tests for Potential Buzz, Squeak, and Rattle Regions in a Cockpit Assembly

The perceived interior noise has been one of the major driving factors in the design of automotive interior assemblies. Buzz, Squeak and Rattle (BSR) issues are one of the major contributors toward the perceived quality in a vehicle. Traditionally BSR issues have been identified and rectified through extensive hardware testing. In order to reduce the product development cycle and minimize the number of costly hardware builds, however, one must rely on engineering analysis and simulation upfront in the design cycle. In this paper, an analytical and experimental study to identify potential BSR locations in a cockpit assembly is presented. The analytical investigation utilizes a novel and practical methodology, implemented in the software tool Nhance.BSR, for identification and ranking of potential BSR issues. The emphasis here is to evaluate the software for the BSR predictions and the identification of modeling issues, rather than to evaluate the cockpit design itself for BSR issues. The methodology is based on modal and forced frequency response analysis utilizing the finite element model of the structural assembly. The analytical results are compared herein with the experimental findings for two types of load spectra and the correlation is found to be very good.
Deterioration analysis of aluminum electrolytic capacitor for DC-DC converter

Aluminum electrolytic capacitor is one of the key components that restrict the life of DC-DC converter. Studying its deterioration analysis has advanced to realizing the prognostics and health management (PHM) technology of DC-DC converter. The main deterioration modes of aluminum electrolytic capacitor include the capacitance decrease and the equivalent series resistance (ESR) increases. These cause the ripple voltage to increase and eventually lead to the DC-DC converter failure. Some parameters of DC-DC converter (such as the ripple voltage, the ripple current, etc.) are selected as the feature signals of the aluminum electrolytic capacitor deterioration. By monitoring the changes of the feature signals, the aluminum electrolytic capacitor deterioration degree can be measured indirectly. Through theoretical analysis, this paper proposed a new idea to predict the remaining useful life (RUL) of DC-DC converter, that is, establishing the curve of the ripple voltage as the aluminum electrolytic capacitor deterioration and setting a warning point in the curve. When the change rate of the ripple voltage reached the warning point, the life of the DC-DC converter will come to an end. So, the RUL of the DC-DC converter can be predicted. In this paper, the buck converter is verified by simulation and physical experiments amid good agreements with the theory.
Automating Large-scale Health Care Service Feedback Analysis: Sentiment Analysis and Topic Modeling Study

Background Obtaining patient feedback is an essential mechanism for health care service providers to assess their quality and effectiveness. Unlike assessments of clinical outcomes, feedback from patients offers insights into their lived experiences. The Department of Health and Social Care in England via National Health Service Digital operates a patient feedback web service through which patients can leave feedback of their experiences in structured and free-text report forms. Free-text feedback, compared with structured questionnaires, may be less biased by the feedback collector and, thus, more representative; however, it is harder to analyze in large quantities and challenging to derive meaningful, quantitative outcomes. Objective The aim of this study is to build a novel data analysis and interactive visualization pipeline accessible through an interactive web application to facilitate the interrogation of and provide unique insights into National Health Service patient feedback. Methods This study details the development of a text analysis tool that uses contemporary natural language processing and machine learning models to analyze free-text clinical service reviews to develop a robust classification model and interactive visualization web application. The methodology is based on the design science research paradigm and was conducted in three iterations: a sentiment analysis of the patient feedback corpus in the first iteration, topic modeling (unigram and bigram)–based analysis for topic identification in the second iteration, and nested topic modeling in the third iteration that combines sentiment analysis and topic modeling methods. An interactive data visualization web application for use by the general public was then created, presenting the data on a geographic representation of the country, making it easily accessible. Results Of the 11,103 possible clinical services that could be reviewed across England, 2030 (18.28%) different services received a combined total of 51,845 reviews between October 1, 2017, and September 30, 2019. Dominant topics were identified for the entire corpus followed by negative- and positive-sentiment topics in turn. Reviews containing high- and low-sentiment topics occurred more frequently than reviews containing less polarized topics. Time-series analysis identified trends in topic and sentiment occurrence frequency across the study period. Conclusions Using contemporary natural language processing techniques, unstructured text data were effectively characterized for further analysis and visualization. An efficient pipeline was successfully combined with a web application, making automated analysis and dissemination of large volumes of information accessible. This study represents a significant step in efforts to generate and visualize useful, actionable, and unique information from free-text patient reviews.
Efficient approximation of a neural filter for quantum noise removal in X-ray images

An efficient filter approximating the neural filter (NF) trained to remove quantum noise from X-ray images has been realized. A novel analysis method is proposed for making the characteristics of the trained NF clear. It analyses a nonlinear system with plural inputs by using its outputs when the specific input signals are fed to it. The experimental results have demonstrated that the approximate filter, which is realized by using the results of the analysis, is sufficient for approximation of the trained NF, and efficient at computational cost.
Threat Rejection Fuels Political Dehumanization

Americans disagree about many things, including what threats are most pressing. We suggest people morally condemn and dehumanize opponents when they are perceived as rejecting the existence or severity of important perceived threats. We explore perceived “threat rejection” across five studies (N = 2,404) both in the real-world COVID-19 pandemic and in novel contexts. Americans morally condemned and dehumanized policy opponents when they seemed to reject realistic group threats (e.g., threat to the physical health or resources of the group). Believing opponents rejected symbolic group threats (e.g., to collective identity) was not reliably linked to condemnation and dehumanization. Importantly, the political dehumanization caused by perceived threat rejection can be soothed with a “threat acknowledgement” intervention.
DYNAMICALLY LOCALIZED SELF-ORGANIZING MAP MODEL FOR SPEECH RECOGNITION

Dynamically localized self^rganizing map model (DLSMM) is a new speech recognition model based on the well-known self^organizing map algorithm and dynamic programming technique. The DLSMM can efficiently normalize the temporal and spatial characteristics of speech signal at the same time. Especially, the proposed model can use contextual information of speech. As experimental results on ten Korean digits recognition task, the DLSMM with contextual information has shown higher recognition rate than predictive neural network models.
Adoption and implementation of group technology classification and coding systems : insights from seven case studies

Abstract Results are reported from an empirical study of classification and coding (CC) system usage among manufacturers. The investigation, selection, justification, implementation and operation of CC systems by six user firms are presented in case study form. A case history of a former CC system user is also presented. User characteristics and experiences are compared and analysed across the seven cases. The paper concludes with managerial and research implications regarding CC system selection, justification, implementation and usage.
Chinese-Named Entity Recognition From Adverse Drug Event Records: Radical Embedding-Combined Dynamic Embedding–Based BERT in a Bidirectional Long Short-term Conditional Random Field (Bi-LSTM-CRF) Model

Background With the increasing variety of drugs, the incidence of adverse drug events (ADEs) is increasing year by year. Massive numbers of ADEs are recorded in electronic medical records and adverse drug reaction (ADR) reports, which are important sources of potential ADR information. Meanwhile, it is essential to make latent ADR information automatically available for better postmarketing drug safety reevaluation and pharmacovigilance. Objective This study describes how to identify ADR-related information from Chinese ADE reports. Methods Our study established an efficient automated tool, named BBC-Radical. BBC-Radical is a model that consists of 3 components: Bidirectional Encoder Representations from Transformers (BERT), bidirectional long short-term memory (bi-LSTM), and conditional random field (CRF). The model identifies ADR-related information from Chinese ADR reports. Token features and radical features of Chinese characters were used to represent the common meaning of a group of words. BERT and Bi-LSTM-CRF were novel models that combined these features to conduct named entity recognition (NER) tasks in the free-text section of 24,890 ADR reports from the Jiangsu Province Adverse Drug Reaction Monitoring Center from 2010 to 2016. Moreover, the man-machine comparison experiment on the ADE records from Drum Tower Hospital was designed to compare the NER performance between the BBC-Radical model and a manual method. Results The NER model achieved relatively high performance, with a precision of 96.4%, recall of 96.0%, and F1 score of 96.2%. This indicates that the performance of the BBC-Radical model (precision 87.2%, recall 85.7%, and F1 score 86.4%) is much better than that of the manual method (precision 86.1%, recall 73.8%, and F1 score 79.5%) in the recognition task of each kind of entity. Conclusions The proposed model was competitive in extracting ADR-related information from ADE reports, and the results suggest that the application of our method to extract ADR-related information is of great significance in improving the quality of ADR reports and postmarketing drug safety evaluation.
A self-decoupled three-axis force sensor for measuring the wheel force

The wheel force transducer is an important device in the automotive testing field which can measure the force or torque applied to the wheel. Because existing wheel force transducers are almost commercial products, they are too expensive and technical information about them has not been made public; this slows down the development of the wheel force transducer to a certain extent. Accordingly a three-axis wheel force transducer is presented in this paper which is self-decoupled without calculating the decoupling matrix in theory. Its elastic body has a spoke structure with eight elastic beams, which means that it is easy to fabricate. This paper first introduces the overall elastic body structure of the proposed wheel force transducer. Then the strain gauge arrangement, the principle of strain measurement, the connection modes of the bridge circuits and the rotation decoupling principle for Fx and Fz are analysed, and the self-decoupled characteristics are depicted in detail. Finally, to verify the validity of the designed wheel force transducer, three kinds of experiment are carried out. In the static experiments the static performance and the self-decoupled characteristics of the wheel force transducer are verified; in the dynamic tests, a vehicle dynamics test system is adopted to verify the accuracy of the wheel force transducer in the dynamic environment; in road tests, the sensor is installed in the vehicle to verify whether the output of the proposed wheel force transducer can reflect the variation in the force applied to the wheel in practical applications. The results shows the following: first, the maximum non-linearity error, the maximum hysteresis error and the maximum repeatability error of the proposed wheel force transducer are 0.9% of the full scale, 1.1% of the full scale and 0.5% of the full scale respectively; second, the static coupling rate is about 0.08%, which means that the designed wheel force transducer is self-decoupled in theory; third, the proposed wheel force transducer can measure Fx, Fz and My effectively in real applications.
A discussion on Bayesian analysis : Selecting Noninformative Priors

In this note, following the publication of Seaman III, Seaman Jr and Stamey(2012) we re ect on an aspect of Bayesian statistics, namely the selection of a priordensity on the parameters. In some cases Bayesian data analysis remains stable underdi erent noninformative choices of prior distributions. As discussed in [18], there maybe unintended consequences on the posterior distribution for some functions of interestof the choice of a noninformative prior and according to the authors, this is a problemthat \is often ignored in applications of Bayesian inference" (p.77). The authors focusedon four examples and analyzed each of them for several particular choices of prior. Here,we consider a new these examples and discuss the Bayesian processing of their modelsassuming di erent prior choices while the results are based on xed data sets. Theconclusion of our research leads us to infer a stability of the posterior distributions ofthe parameters and to state that the e ect of the noninformative prior is essentiallynegligible.
Dynamic Cognitive Self-Organized TDMA for Medium Access Control in Real-Time Vehicle to Vehicle Communications

The emergence of intelligent transport systems has brought out a new set of requirements on wireless communication. To cope with these requirements, several proposals are currently under discussion. In this highly mobile environment, the design of a prompt, efficient, flexible, and reliable medium access control, able to cover the specific constraints of the named real-time communications applications, is still unsolved. This paper presents the original proposal integrating Non-Cooperative Cognitive Time Division Multiple Access (NCC-TDMA) based on Cognitive Radio (CR) techniques to obtain a mechanism which complies with the requirements of real-time communications. Though the proposed MAC uses a slotted channel, it can be adapted to operate on the physical layer of different standards. The authors’ analysis considers the IEEE WAVE and 802.11p as the standards of reference. The mechanism also offers other advantages, such as avoiding signalling and the adaptation capacity to channel conditions and interferences. The solution is applied to the problem of units merging a convoy. Comparison results between NCC-TDMA and Slotted-Aloha are included.
Lodestone: An Efficient Byzantine Fault-Tolerant Protocol in Consortium Blockchains

We present Lodestone, a chain-based Byzantine fault-tolerant (BFT) state machine replication (SMR) protocol under partial synchrony. Lodestone enables replicas to achieve consensus with two phases of voting and enjoys (1) optimistic responsiveness and (2) linear communication complexity on average. Similar to the state-of-the-art chain-based BFT protocols, Lodestone can be optimized with a pipelining idea elegantly. We implement pipelined Lodestone and deploy experiments to evaluate its performance. The evaluation results demonstrate that Lodestone has a lower latency than HotStuff under various workloads.
An Exploratory Analysis of Components of Revenge Experiences

ABSTRACT Revenge refers to a retaliatory behavior following perceived harm to one’s well-being. It can include yelling, berating, and minor aggression as well as more extreme violence. Revenge has been identified as a causal factor in homicides, school shootings, and bombings. Despite the importance of understanding revenge, little is known about its different components, thus making it difficult to prevent and treat. In this study, survey data were analyzed from 458 primarily White, English-speaking, adult MTurk participants. They described a specific vengeful experience and answered follow up questions. Questions were based on rational-emotive behavior theory, a review of the literature, and clinical experience. Participants answered questions about their triggers and cognitions during the event, what they did, their emotions prior to and after engaging in revenge, the intensity of their urges, and outcomes. Triggering cognitions most associated with engaging in vengeful behavior were desires for retribution, punishment, and, unexpectedly, an accepting statement of why the transgressors engaged in their behavior. Participants reported more positive emotions and positive outcomes following engagement in revenge, challenging the bittersweet concept of revenge. Treatment implications are discussed.
CROSS-SECTIONAL THERMAL IMAGING OF A METAL-OXIDE-SEMICONDUCTOR FIELD-EFFECT TRANSISTOR

Understanding of heat generation in semiconductor devices is important in the thermal management of integrated circuits and in the analysis of the device physics. Scanning thermal microscopy was used to measure the temperature distribution of the cross-section of an operating metal-oxide-semiconductor field-effect transistor (MOSFET). The temperature distributions were measured both in DC and AC modes in order to take account of the leakage current. The location of the maximum temperature was observed to approach the drain as the drain bias was increased.
Novel Schiffman phase shifters

In a standard Schiffman phase shifter a coupled section and a uniform transmission line are used to give a differential phase shift. In order to achieve larger bandwidth it is necessary to use tight coupled sections which are difficult to realize. It is shown how different configurations of coupled lines or parallel connected coupled lines can be used together with a uniform transmission line, other coupled lines, or parallel connected coupled lines in order to obtain a differential phase shifter with loose coupled lines and the same performance as for the standard case. The measurements confirm the calculated results, leading to a more realizable structure. >
Robust Ekeland variational principles. Application to the formation and stability of partnerships

This paper has two parts. The mathematical part provides generalized versions of the robust Ekeland variational principle in terms of set-valued EVP with variable preferences, uncertain parameters and changing weights given to vectorial perturbation functions. The behavioural part that motivates our findings models the formation and stability of a partnership in a changing, uncertain and complex environment in the context of the variational rationality approach of stop, continue and go human dynamics. Our generalizations allow us to consider two very important psychological effects relative to ego depletion and goal gradient hypothesis.
First Principle Calculations for Silver Halides AgBr, AgCl, and AgF

Density functional theory (DFT) coupled with ) method are carried out to calculate the electronic structures of AgX (X; Br, Cl, and F). The effect of hybridizing between 4d orbital of Ag element and the p orbitals of the X in the valence band plays a very important role in the total density of states configuration. The electronic structure has been studied and all results were compared with the experimental and theoretical values. The importance of this work is that there is insufficient studies of silver halides corresponding the great importance of these compounds. Almost all the results were consistent with the previous studies mentioned here. We found the band gap of AgX to be 2.343 eV, 2.553 eV, and 1.677 eV for AgBr, AgCl, and AgF respectively which are in good agreement with the experimental results.
The Application of LTD-2100 GPR (Ground Penetrating Radar) in Inspection of Concrete Structures

At present, a large-scale construction of concrete structure sprout up all over china, it is imperative to inspect the concrete carefully, efficiently and accurately with portable monitoring tools as speedy bulk construction required. This paper sets out by analyzing LTD-2100 radar diagnosis waveform in concrete structure safety, and then compares the interpretation of waveform with sampling concrete examination. Eventually, the consistent result reflects the non-destructive detection method of this radar has high value, for its high resolution examination, accurate positioning defects with high efficiency and easily operates which could benefit to engineers from real-time monitoring of concrete structure quality.