Miracle-dz/UniFAR-FTUs huggingface dataset:
What if the Primary Goal of the Web was to Foster Curiosity?

People go to the web to satisfy their curiosity. The web contains resources that can help: articles, videos, tutorials, online communities, and online courses, among others. In analogy to the semantic web proposal, which was motivated by a desire to structure the web to be more understandable and usable by machines [Berners-Lee, Hendler, and Lassila, 2001], we raise the question: How would we rethink the web with the primary goal of fostering and satisfying human curiosity? We propose the curiosity web, based on the intuition that the meaning of resources, such as articles, books, and videos, can be expressed in terms of the questions they address [Paritosh and Marcus, 2016]. It has three representational elements: curiosity, a semantic primitive for an abstracted question or information need with a URI and textual content in multiple languages; relationships between curiosities, such as relevant or prerequisite; relationships between curiosities and resources, such as addresses or satisfies. The goal of the curiosity web is to provide an exoskeleton for organizing information by the curiosities they address. The curiosity web is a dual of existing semantic networks and knowledge graphs [Collins and Quillian, 1972; Sowa, 2006; Hillis, 2004]. Instead of focusing on describing meaning using analytic primitives and compositions of knowledge, this approach represents meaning of resources in a holistic manner, through the curiosities it addresses.
Biometric of Intent: A New Approach Identifying Potential Threat in Highly Secured Facilities

Biometric of Intent (BoI) is a Computer Vision (CV) automation, using Artificial Intelligence (AI) techniques, which presents a new approach that extends the reach of the classic biometric identification process. It provides an efficient mechanism which deters the threats raised by unknown individuals who have deceitful intentions and who aim to deploy unlawful operations such as terrorist attacks. In this context, our proposed BoI model is based on a framework constructed upon an automated machine learning facial expression analysis system which can assist law enforcement agencies who intend to deploy a systematic preventive security approach that aims to reduce the risk of potential unlawful attacks by rogue individuals through the evaluation of their emotional state in relation to their malicious intent.
“You Have to Keep Yourself Hidden”: Perspectives From Malaysian Malay-Muslim Men Who Have Sex With Men on Policy, Network, Community, and Individual Influences on HIV Risk

ABSTRACT Malay-Muslim men who have sex with men (MSM) are marginalized and hidden in Malaysia, a predominantly Muslim country in southeast Asia. We explored the policy, network, community, and individual factors related to HIV infection among Malay-Muslim MSM through 26 in-depth interviews and one focus group discussion (n = 5) conducted in Kuala Lumpur and Kota Bharu between October 2013 and January 2014. As religion plays an important role in their lives, participants viewed homosexuality as a sin. Low risk perception and misconceptions about HIV/AIDS were common, and most participants expressed reluctance to consult a doctor unless they had symptoms. Additionally, buying condoms was embarrassing and anxiety-producing. Fear of discrimination by health care providers and community hindered participants from disclosing sexual behaviors and accessing health services. Homophobic comments and policies by the government and religious leaders were concerns of participants. A safe and enabling environment is needed to reduce HIV risks among Malay-Muslim MSM.
Hybrid Modeling of a Solar Cooling System

Abstract Solar systems are deeply affected by weather conditions and their main energy source, irradiation, cannot be manipulated. This paper describes a solar cooling system located at the University of Almeria, Spain. The system is composed by a solar collector, a gas heather, and two serial connected tanks to storage hot water. They are used as energy sources for an absorption machine whose objective is to obtain chilled water for the fan-coil system. All these components are included or excluded from the cooling system by means of switching valves and activating or deactivating signals. The switching among different configuration modes in real time increases the system challenge to be modeled or controlled, due to the mix of both discrete signals and continuous dynamics. In this paper, a model for each energy source is developed and afterwards they are integrated into one state-space model used to obtain a hybrid model. This hybrid model is able to simulate the different configuration modes of the solar cooling system. Some real tests are presented.
Application of a Multilayer AC Winding to Design Synchronous Reluctance Motors

This paper presents the design and experimental validation of a synchronous reluctance motor (SynRM) using a multilayer (ML) ac winding that meets the ultra-premium/IE5 class efficiency requirement. Compared to conventional double-layer ac windings, the ML winding yields a more sinusoidal stator magnetomotive force (MMF) with a shorter end-turn length. The ML winding is characterized using an analytical stator MMF model with verification against finite element analysis (FEA). The proposed winding configuration is optimized under a given design benchmark. The multi-barrier rotor design is also optimized based on FEA using a genetic algorithm. The performance of the designed ML-SynRM is compared against a commercial premium efficiency induction motor and a conventionally wound SynRM for the same standard frame and cooling type. Results show significant efficiency gain with SynRM designs, and also, the designed ML-SynRM yields lower torque ripple with an improved power factor compared to the conventional SynRM. The prototype ML-SynRM is built, and its simulation results are experimentally validated against the benchmark including their performances at a thermal steady state.
Technology Issues for Self-aligned Top-Gate Amorphous Metal Oxide Thin-Film Transistors

The key technology issues for fabrication of high performance self-aligned top gate amorphous metal oxide thinfilm transistors are addressed. These issues include the sputtering deposition of active layer of metal oxide, the PECVD growth of gate oxide, the plasma enabled interface treatment between the active layer and gate insulator, the doping method for low resistance source-drain regions, and the annealing process for performance enhancement. With these issues well addressed, high performance self-aligned top-gate TFTs with various amorphous oxide channel materials, like aIGZO, a-IZO and a-ZTO have been achieved.
Analysis of Distant Supervision for Relation Extraction Dataset

Deep learning techniques have been applied to relation extraction task, and demonstrated remarkable performances. However, the results of these approaches are difficult to interpret and are sometimes counter-intuitive. In this paper, we analyze the ontological and linguistic features of a relation extraction dataset and the pros and cons of existing methods for each feature type. This analysis result could help design an improved method for relation extraction by providing more insights into the dataset and models.
Double gate n-type WSe2 FETs with high-k top gate dielectric and enhanced electrostatic control

We propose and experimentally demonstrate double-gated n-type WSe2 FETs with excellent top gate high-k dielectric layer. Under back gate control, the devices behave as n-type enhancement transistors, with ON/OFF current ratios larger than 6 orders of magnitude and a ON current close to $1\ \mathbf{pA}/\mu\mathbf{m}$ under a drain bias of 100 mV. Negative top gate biases determine a much steeper turn-on of the back gated transfer characteristic and a reduction of the hysteresis. Top gated device behaves as n-type depletion FETs, exhibiting a $I_{\mathbf{ON}}/I_{\mathbf{OFF}}$ ratio larger than 106 under positive bias applied to the back gate. A minimum hysteresis of 40 mV and an average subthreshold slope close to 100 mV/dec prove the high quality of the deposited top gate dielectric. The electron mobility has been extracted using the Y-function method, obtaining 22.15 cm2V−1s−1 under a drain bias of 1 mV.
Addressing racial bias in wards

Health disparities fall along racial lines, in part, due to structural inequalities limiting health care access. The concept of race is often taught in health professions education with a clear biologic underpinning despite the significant debate in the literature as to whether race is a social or biologic construct. The teaching of race as a biologic construct, however, allows for the simplification of race as a risk factor for disease. As health care providers, it is part of our professional responsibility and duty to patients to think and talk about race in a way that is cognizant of broader historical, political, and cultural literature and context. Openly discussing the topic of race in medicine is not only uncomfortable but also difficult given its controversies and complicated context. In response, we provide several evidence-based steps to guide discussions around race in clinical settings, while also hopefully limiting the use of bias and racism in the practice of medicine.
IMPLEMENTATION OF THE STANDARD FLOATING POINT MAC USING IEEE 754 FLOATING POINT ADDER

There are two types of processors. The first category is arithmetic processors and the second category is signal processing processors. For arithmetic processors in general precision is less where as for the signal processing processors precision is high because the signal is to be reconstructed at the receiving end. In the arithmetic processors the basic building block is Arithmetic Logic Unit (ALU). In the signal processing processors the basic building block is Multiplier Accumulator Content (MAC). For the Standard floating point MAC, more precision is essential compared with the traditional fixed point MAC because the former is to be designed by the IEEE 754 floating point arithmetic and the lateral is designed with fixed-point arithmetic i.e, the precision is limited to integer. But, in general if the precision is more, the accuracy is more. Hence, to improve the performance of the traditional fixed point MAC, in this work we implemented the standard floating point MAC using IEEE 754 floating point adder. This can be used to design all floating point DSP processors through the standard floating point MAC.
A High-Gain Sub-2nW OTA for Biomedical Application using 45nm CMOS Technology

A three-stage ultra-low power and low-voltage operational transconductance amplifier (OTA) has been designed using transistors in sub-threshold region. Simulation for 45-nm CMOS technology and a supply voltage of 250 mV yields a DC gain of 66.074dB, phase margin of 64.9° and power consumption of 1.84nW showing its suitability for biomedical application.
Low-Rate PBRL-LDPC Codes for URLLC in 5G

In this letter, we propose a class of rate-compatible raptor-like protographs, which is aimed at the design of low-rate low-density parity-check (LDPC) codes with short length and fast convergence for ultra-reliable and low-latency communications in 5G. In the proposed protographs, the connection degrees can be progressively optimized by the protograph-based extrinsic information transfer analysis with a limited number of iterations. Following the protograph optimization, we construct the rate-compatible LDPC codes by a simplified error minimization progressive edge-growth algorithm and carry out simulations for performance comparisons. The simulation results show that our proposed LDPC codes have noticeable advantages over the existing low-rate LDPC codes with short length and limited numbers of decoding iterations.
Compressing and Maintaining Statistics Information about Resource Occurrences in a Distributed RDF Store

In distributed RDF stores triples are assigned to one or several storage and compute nodes. In order to perform query planning and optimization, statistical information about the occurrences of IRIs and literals on the individual storage and compute nodes is needed. In this paper, we present our novel compressed storage format for statistical information that can be updated with a single read and write operation if resources occur on few storage and compute nodes only. In our experiments this novel storage format reduced the time to collect statistical information by up to 97% and the required space by up to 99%.
Following the Shadow: Agile 3-D Beam-Steering for 60 GHz Wireless Networks

60 GHz networks, with multi-Gbps bitrate, are considered as the enabling technology for emerging applications such as wireless Virtual Reality (VR) and 4K/8K real-time Miracast. However, user motion, and even orientation change, can cause mis-alignment between 60 GHz transceivers' directional beams, thus causing severe link outage. Within the practical 3D spaces, the combination of location and orientation dynamics leads to exponential growth of beam searching complexity, which substantially exacerbates the outage and hinders fast recovery. In this paper, we first conduct an extensive measurement to analyze the impact of 3D motion on 60 GHz link performance, in the context of VR and Miracast applications. We find that 3D motion exhibits inherent non-predictability, so conventional beam steering solutions, which targets 2D scenarios with lower search space and short-term motion coherence, fail in practical 3D setup. Motivated by these observations, we propose a model-driven 3D beam-steering mechanism called Orthogonal Scanner (OScan), which can maintain high performance for mobile 60 GHz links in 3D space. OScan discovers and leverages a hidden interaction between 3D beams and the spatial channel profile of 60 GHz radios, and strategically scans the 3D space so as to reduce the search latency by more than one order of magnitude. Experiment results based on a custom-built 60 GHz platform along with a trace-driven emulator demonstrate OScan's remarkable throughput gain, up to $\mathbf{5}\times$, compared with the state-of-the-art.
The Read Amplification Analysis of NoSQL Database on Top of OSDs: A Case Study of HBase

The NoSQL database has showed a great improvement for large-scale datasets storage and compute. As for the conventional deployment architecture, they can obtain tremendously good performance as storage and compute are running in the same node. Nevertheless, many NoSQL users have their own storage pool (e.g., OSD server pool) which provides different interfaces for different NoSQL databases. Many benefits are achieved from this new application scenarios, such as higher scalability, better flexibility and data maintainability. However, the physical separation of NoSQL application and storage nodes potentially influences the system performance. To better understand the new scenario, we take HBase, a common NoSQL database, as a study. HBase exploit a layered storage architecture with two main layers, a distributed database atop a distributed file system (HDFS). We perform experiments with YCSB benchmark and a new developed benchmark to evaluate the separation deployment of RegionServer and HDFS server and verify the read amplification of network I/O between them. Based on our observations we propose a novel OSD Agent direction consisting of HBase Local Storage Scanner and HBase Local Storage Compactor to reduce the amplification by filtering out the requested data from the data block on OSD server pool. From the simulation results, the OSD Agent can reduce the network traffic amplification from 36x-92x to 1.7x for HBase read operation, 1.2x-21x to 1.2x for HBase scan with column filter operation. Moreover, the OSD Agent makes the read performance less sensitive to the network bandwidth. The OSD Agent brings in great performance improvement for NoSQL Database on top of OSDs.
Drivetrain Gearbox Fault Diagnosis: Vibration- and Current-Based Approaches

Gearboxes are widely used in rotary machines, such as wind turbines, automobiles, and helicopters. Gearbox failures contribute to a significant proportion of the total failures and downtime in these machines. Gearbox fault diagnosis is an effective means to prevent catastrophic failures, improve reliability, and reduce downtime and maintenance costs. Vibration-based approaches have been employed in most commercially available condition-monitoring systems (CMS s), while current-based approaches have received increased attention in industry and academia. This article presents a comparative study of vibration- and current-based approaches for gearbox fault diagnosis. Theoretical analysis and experimental tests are conducted to show that 1) in vibration signals, ghost frequencies appear when the gearbox is healthy and disappear when a localized gear fault occurs; 2) vibration signals of a faulty gearbox are modulated by shaft rotating frequencies; 3) in current signals, the fundamental frequency component is dominant; and 4) they are modulated by gearbox characteristic frequencies at the fundamental frequency when gear faults appear.
Contribution of psychiatric diagnoses to extent of opioid prescription in the first year post‐head and neck cancer diagnosis: A longitudinal study

The purpose of this study was to determine, within the first‐year post–head and neck cancer (HNC) diagnosis, the contribution of past and upon HNC psychiatric diagnoses (ie, substance use disorder, major depressive disorder, and anxiety disorder) to the extent (ie, cumulated dose) of opioid prescription.
Assessing the Gene-Disease Association of 19 Genes with the RASopathies using the ClinGen Gene Curation Framework

The RASopathies are a complex group of diseases regarding phenotype and genetic etiology. The ClinGen RASopathy Expert Panel assessed published and other publicly available evidence supporting the association of 19 genes with RASopathy conditions. Using the semi-quantitative literature curation method developed by the ClinGen Gene Curation Working Group, evidence for each gene was curated and scored for Noonan syndrome, Costello syndrome, cardiofaciocutaneous (CFC) syndrome, Noonan syndrome with multiple lentigines (NSML), and Noonan-like syndrome with loose anagen hair (NS/LAH). The curated evidence supporting each gene-disease relationship was then discussed and approved by the ClinGen RASopathy Expert Panel. Each association’s strength was classified as Definitive, Strong, Moderate, Limited, Disputed, or No Evidence. Eleven genes were classified as definitively associated with at least one RASopathy condition. Two genes classified as strong for association with at least one RASopathy condition while one gene was moderate and three were limited. The RAS EP also refuted the association of two genes for a RASopathy condition. Overall, our results provide a greater understanding of the different gene-disease relationships within the RASopathies and can help guide and direct clinicians, patients and researchers who are identifying variants in individuals with a suspected RASopathy GRANT NUMBERS: Research reported in this publication was supported by the National Human Genome Research Institute (NHGRI) under award number U41HG006834. MZ received support from German Federal Ministry of Education and Research (BMBF): NSEuroNet (FKZ 01GM1602A), GeNeRARe (FKZ 01GM1519A).
Closing Gaps for Aircraft Attitude Higher Order Sliding Mode Control Certification via Practical Stability Margins Identification

In this paper, the conventional aircraft control system certification approach based on phase margin (PM) and gain margin (GM) is extended to higher order sliding mode (HOSM) controllers. The proposed practical stability PM (PSPM) and the practical stability GM (PSGM) are used to quantify the HOSM control system robustness to unmodeled dynamics. The tools/algorithms for the identification of PSPM and PSGM are developed using describing function-harmonic balance method. A design algorithm of a cascade dynamic compensator for a dynamically perturbed HOSM control system is presented and can be used to satisfy required practical stability margins. The theoretical developments are illustrated and validated on controlling the attitude of an F-16 aircraft.
Convex Constrained Clustering with Graph-Laplacian Pca

In this paper, we propose a new algorithm for constrained clustering, in which a new regularizer elegantly incorporates a small amount of weakly supervisory information in the form of pair-wise constraints to regularize the similarity between the low-dimensional representations of a set of data samples. By exploring both the local and global structures of the data samples with the guidance of the supervisory information, the proposed algorithm is capable of learning the low-dimensional representations with strong separability. Technically, the proposed algorithm is formulated and relaxed as a convex optimization model, which is further efficiently solved with the global convergence guaranteed. Experimental results on multiple benchmark data sets show that our proposed model can produce higher clustering accuracy than state-of-the-art algorithms.
Adventures in Monotone Complexity and TFNP

Separations: We introduce a monotone variant of Xor-Sat and show it has exponential monotone circuit complexity. Since Xor-Sat is in NC^2, this improves qualitatively on the monotone vs. non-monotone separation of Tardos (1988). We also show that monotone span programs over R can be exponentially more powerful than over finite fields. These results can be interpreted as separating subclasses of TFNP in communication complexity. Characterizations: We show that the communication (resp. query) analogue of PPA (subclass of TFNP) captures span programs over F_2 (resp. Nullstellensatz degree over F_2). Previously, it was known that communication FP captures formulas (Karchmer - Wigderson, 1988) and that communication PLS captures circuits (Razborov, 1995).
Opinion paper: poor response to treatment of depression in people in high occupational levels

Abstract The working environment may have a significant effect on response to treatment of depression and this issue has not yet been sufficiently addressed in the scientific literature. There is evidence showing that being engaged in high-level positions can be an obstacle to the success of treatment. This article discusses the few evidence in the literature and some of the possible mechanisms involved. Specific personality attributes and difficulties in adapting to depression may delay access to care and may also reduce treatment compliance. The presence of stress in jobs that require high cognitive function and lack of social support may be elements that hinder the recovery process. Residual symptoms that impact on cognitive functions may undermine adherence to treatment and adversely affect the response. The implications of these issues are potentially relevant for clinical practice in the treatment of depression and for future research.