Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Analysis of Informal Social Media Conversations about Autism

In today’s society, the use of social media has become a necessary daily activity. Social media is typically used for social interaction and access to news and information, and decision making. It is a valuable communication tool with others locally and worldwide, as well as to share, create, and spread information. Social media has greatly influenced many aspects of our society, particularly healthcare. Informal public speaking on social media, especially in Iran, has an influential role in the health community, such as consulting patients and their families together and sharing experiences related to symptoms, home remedies, and finding an experienced therapist or good treatment center. The virtual community of autistic patients and their families is a young but growing community. Ninisite, as the most crucial Iranian family social network, has had nearly 21.5M total visits last three Months. In this study, we first crawled the social network of interactive conversations related to autism from this forum. After preprocessing and data cleaning, the communication network between people was extracted. Then this network was studied by graph analysis methods. It was shown that this network with more than 800 members has solid and active hubs, although a fledgling and sparse network. We further showed that an auxiliary node that connects these hubs could make it much more substantial and play an essential role in managing the flow of information between the families of autistic patients.
Automotive Ethernet architecture and security: challenges and technologies

Vehicle infrastructure must address the challenges posed by today's advances toward connected and autonomous vehicles. To allow for more flexible architectures, high-bandwidth connections and scalability are needed to connect many sensors and electronic control units (ECUs). At the same time, deterministic and low latency is a critical and significant design requirement to support urgent real-time applications in autonomous vehicles. As a recent solution, the time-sensitive network (TSN) was introduced as Ethernet-based amendments in IEEE 802.1 TSN standards to meet those needs. However, it had hurdle to be overcome before it can be used effectively. This paper discusses the latest studies concerning the automotive Ethernet requirements, including transmission delay studies to improve worst-case end-to-end delay and end-to-end jitter. Also, the paper focuses on the securing Ethernet-based in-vehicle networks (IVNs) by reviewing new encryption and authentication methods and approaches.
Some Recent Results on Asymptotic Expansions of Multivariate Test Statistics for Mean Vectors Under Nonnormality

In this paper we review some recent results on asymptotic expansions of some multivariate test statistics for mean vectors under nonnormality. It is assumed that the samples are taken from a general distribution satisfying Cramér's condition. Some methods are discussed, through the derivation of asymptotic expansions of the distributions of Hotelling's T2-statistic, one-way MANOVA test statistics, and some test statistics for a multivariate linear hypothesis on regression coefficients. The results are restricted to the null distributions, but we shall see that the methods could be extended to the non-null case. Relating to the methods, asymptotic expansions are given for the distributions of the sample mean vector, the sample covariance matrix, and multivariate t-statistics. We also give some results on robustness of the test statistics for departures from normality.
Soybean Plants Exposed to Low Concentrations of Potassium Iodide Have Better Tolerance to Water Deficit through the Antioxidant Enzymatic System and Photosynthesis Modulation

Water deficit inhibits plant growth by affecting several physiological processes, which leads to the overproduction of reactive oxygen species (ROS) that may cause oxidative stress. In this regard, iodine (I) is already known to possibly enhance the antioxidant defense system of plants and promote photosynthetic improvements under adverse conditions. However, its direct effect on water deficit responses has not yet been demonstrated. To verify the efficiency of I concerning plant tolerance to water deficit, we exposed soybean plants to different concentrations of potassium iodide (KI) fed to pots with a nutrient solution and subsequently submitted them to water deficit. A decline in biomass accumulation was observed in plants under water deficit, while exposure to KI (10 and 20 μmol L−1) increased plant biomass by an average of 40%. Furthermore, exposure to KI concentrations of up to 20 μM improved gas exchange (~71%) and reduced lipid peroxidation. This is related to the higher enzymatic antioxidant activities found at 10 and 20 μM KI concentrations. However, when soybean plants were properly irrigated, KI concentrations greater than 10 μM promoted negative changes in photosynthetic efficiency, as well as in biomass accumulation and partition. In sum, exposure of soybean plants to 10 μM KI improved tolerance to water deficit, and up to this concentration, there is no evidence of phytotoxicity in plants grown under adequate irrigation.
Damage diagnosis in intelligent tires using time-domain and frequency-domain analysis

Abstract Tire durability plays an important role in road transportation safety and is taken very seriously by all tire manufacturers. Defects in tires can cause vehicle instability and create catastrophic accidents. In this article, a finite element model of the intelligent tire is developed using implicit dynamic analysis and is used for defect detection. Processing and analyzing the acceleration signals, measured at the center of the tire inner-liner, for the undamaged and damaged tires, can result in detecting the crack locations around the tire circumference. Additionally, prediction models used for damage diagnosis based on optimized number and location of sensors, was developed. Several sensors located at different locations around the circumference of the damaged tire and away from the crack surface, are used in order to assess sensor location sensitivity from the crack surface. It is observed that the radial component of the acceleration signal has the highest potential to be used as the signal of choice in defect detection as compared to circumferential acceleration signals.
A Three-Tiered Analysis of the Factors Influencing the Adoption of Forensic Accounting Field in Saudi Arabia

Purpose: The study shows how several perceptionistic, environmental, and economic aspects can be systematically assessed in advance of investment decisions to launch a proposed Master's program in Forensic Accounting. Theoretical framework: Since the final decade of the twentieth century there has been increasing global interest in adopting and applying forensic accounting, fraud detection methods, and financial fraud examination . However, there are no specialized postgraduate programs in this field at either the local (Saudi) or regional (Middle Eastern) level, despite its importance to meeting the needs of accountancy and judicial employers. Design/methodology/approach: An inductive and analytical approach evaluates the proposed program using a three-stage model that can be adopted by any higher education institution (HEIs) wishing to develop an educational program. Findings: The results show that the vast majority of the program's beneficiaries support its implementation due to its novelty both locally internationally. The program gives the University of Tabuk, its initiator, a sustainable competitive advantage over other local and regional universities through supplying the labor market with graduates qualified in financial criminal investigation. Finally, the financial analysis indicates that the program will be strong financially and have a high level of operational efficiency and expected demand. Research, Practical & Social implications: The findings are beneficial for HEIs seeking to achieve a competitive advantage over their rivals by offering attractive academic programs that meet the demands of the labor market. Originality/value: The study is the first that it uses a three-stage assessment model to show how several perceptionistic, strategic, and economic aspects can be systematically assessed in advance of investment decisions related to launching new academic programs in HEIs.
New lower bounds for approximation algorithms in the lovasz-schrijver hierarchy

Determining how well we can efficiently compute approximate solutions to NP-hard problems is of great theoretical and practical interest. Typically the famous PCP theorem is used for showing that a problem has no algorithms computing good approximations. Unfortunately, for many problem this approach has failed. Nevertheless, for such problems, we may instead be able to show that a large subclass of algorithms cannot compute good approximations. This thesis takes this approach, concentrating on subclasses of algorithms defined by the LS and LS+ Lovasz-Schrijver hierarchies. These subclasses define hierarchies of algorithms where algorithms in higher levels (also called "rounds") require more time, but may compute better approximations. Algorithms in the LS hierarchy are based on linear programming relaxations while those in the more powerful LS+ hierarchy are based on semidefinite programming relaxations. Most known approximation algorithms lie within the first two-three levels of the LS+ hierarchy, including the recent celebrated approximation algorithms of Goemans-Williamson [27] and Arora-Rao-Vazirani [7] for MAX-CUT and SPARSEST-CUT, respectively. So understanding the power of these algorithm families seems important. We obtain new lower bounds for the LS and LS + hierarchies for several important problems. In all cases the approximations we rule out in these hierarchies are not ruled out by known PCP-based arguments. Moreover, unlike PCP-based inapproximability results, all our results are unconditional and do not rely on any computational complexity assumptions. The lower bounds we prove are as follows: (1) For VERTEX COVER we show that Ω(log n) rounds of LS are needed to obtain 2 - e approximations and Ω(log 2 n) rounds are needed for 1.5 - e approximations. (2) For MAX-3SAT and SET COVER we show that Ω(n) rounds of LS + are needed for any non-trivial approximation. (3) For hypergraph VERTEX COVER on rank-k hypergraphs we show that Ω( n) rounds of LS+ are needed for k - 1 - e approximations. (4) For hypergraph VERTEX COVER on rank-k hypergraphs we show that Ω(log log n) rounds of LS are needed for k - e approximations.
Physics of unsteady thrust and flow generation by a flexible surface flapping in the absence of a free stream

Inspired by the flexible wings and fins of flying and swimming animals, we investigate the flow induced by the interaction between a flapping flexible surface and the surrounding fluid for the limiting case of Strouhal number St→∞ (zero free-stream speed). The model selected for this purpose is a two-dimensional sinusoidally pitching rigid symmetric foil to which is attached at the trailing edge a thin chordwise flexible surface (along the chord line). The flow so generated is a coherent jet aligned along the foil centreline, containing a reverse Bénard–Kármán vortex street and delivering a corresponding unidirectional thrust. We analyse the flow and thrust generation process. The measured velocity field suggests that the flow and thrust generation mainly occurs during the phases when the trailing edge is near the centreline. Flexibility of the surface is important in accelerating the near-wake flow and in transferring momentum and energy to the fluid. We present a detailed account of when and where the momentum and energy are added to the fluid. This study shows that the deformations of the flexible surface are responsible for generating a favourable pressure gradient along the jet direction, and for the observed unsteady actuator disc-type action.
Frank-Wolfe Algorithm for Exemplar Selection

In this paper, we consider the problem of selecting representatives from a data set for arbitrary supervised/unsupervised learning tasks. We identify a subset $S$ of a data set $A$ such that 1) the size of $S$ is much smaller than $A$ and 2) $S$ efficiently describes the entire data set, in a way formalized via auto-regression. The set $S$, also known as the exemplars of the data set $A$, is constructed by solving a convex auto-regressive version of dictionary learning where the dictionary and measurements are given by the data matrix. We show that in order to generate $|S| = k$ exemplars, our algorithm, Frank-Wolfe Sparse Representation (FWSR), only requires $\approx k$ iterations with a per-iteration cost that is quadratic in the size of $A$, an order of magnitude faster than state of the art methods. We test our algorithm against current methods on 4 different data sets and are able to outperform other exemplar finding methods in almost all scenarios. We also test our algorithm qualitatively by selecting exemplars from a corpus of Donald Trump and Hillary Clinton's twitter posts.
Hydrogenated Benzene in Circumstellar Environments: Insights into the Photostability of Super-hydrogenated PAHs

Polycyclic aromatic hydrocarbons (PAHs), comprised of fused benzene (C6H6) rings, emit infrared radiation (3–12 μm) due to the vibrational transitions of the C–H bonds of the aromatic rings. The 3.3 μm aromatic band is generally accompanied by the band at 3.4 μm assigned to the vibration of aliphatic C–H bonds of compounds such as PAHs with an excess of peripheral H atoms (Hn–PAHs). Herein we study the stability of fully hydrogenated benzene (or cyclohexane, C6H12) under the impact of stellar radiation in the photodissociation region (PDR) of NGC 7027. Using synchrotron radiation and time-of-flight mass spectrometry, we investigated the ionization and dissociation processes at energy ranges of UV (10–200 eV) and soft X-rays (280–310 eV). Density Functional Theory (DFT) calculations were used to determine the most stable structures and the relevant low-lying isomers of singly charged C6H12 ions. Partial Ion Yield (PIY) analysis gives evidence of the higher tendency toward dissociation of cyclohexane in comparison to benzene. However, because of the high photoabsorption cross-section of benzene at the C1s resonance edge, its photodissociation and photoionization cross-sections are enhanced, leading to a higher efficiency of dissociation of benzene in the PDR of NGC 7027. We suggest that a similar effect is experienced by PAHs in X-ray photon-rich environments, which ultimately acts as an auxiliary protection mechanism of super-hydrogenated polycyclic hydrocarbons. Finally, we propose that the single photoionization of cyclohexane could enhance the abundance of branched molecules in interstellar and circumstellar media.
SEGMENTASI PELANGGAN SALON NUII BEAUTY GLOW MENGGUNAKAN K-MEANS CLUSTERING

Persaingan dalam industri kecantikan menuntut setiap pelaku bisnis di bidang ini untuk menentukan strategi pemasaran agar manajemen tidak melakukan kesalahan dalam memberikan pelayanan kepada pelanggan. Salon Nuii Beauty Glow belum dapat mengklasifikasikan pelanggan mana yang menguntungkan bagi perusahaan. Oleh karena itu, perusahaan mengalami kesulitan untuk menentukan strategi pemasaran yang tepat bagi pelanggannya. Peneliti menggunakan model clustering data mining yang sangat efisien dalam menentukan karakteristik kelompok pelanggan yang terbentuk, dengan menggunakan algoritma K-Means yang memiliki keunggulan dalam pengelompokan. Algoritma k-means clustering merupakan salah satu teknik data mining yang dapat membagi data dalam suatu himpunan menjadi beberapa kelompok, dimana kesamaan data pada satu kelompok lebih besar dibandingkan dengan kesamaan data tersebut dengan data pada kelompok lain. Dari penelitian ini diperoleh 3 cluster pelanggan. Cluster 0 menempati jumlah pelanggan terbanyak yaitu 48 pelanggan, cluster 1 memiliki 10 pelanggan, dan cluster 3 memiliki 12 pelanggan. Ketiga cluster tersebut dikategorikan sesuai dengan karakteristik masing-masing data dengan melakukan uji indeks Davies Bouldin untuk menentukan cluster terbaik. Dan model RFM (Kebaruan, frekuensi, moneter) digunakan untuk memfasilitasi pengelompokan.
Robust Covariance Matrix Estimation and Sparse Bias Estimation for Multipath Mitigation

Multipath is an important source of error when using global navigation satellite systems (GNSS) in urban environment, leading to biased measurements and thus to false positions. This paper treats the GNSS navigation problem as the resolution of an overdetermined system, which depends on the receiver's position, velocity, clock bias, clock drift, and possible biases affecting GNSS measurements. We investigate a sparse estimation method combined with an extended Kalman filter to solve the navigation problem and estimate the multipath biases. The proposed sparse estimation method assumes that only a part of the satellites are affected by multipath, i.e., that the unknown bias vector is sparse in the sense that several of its components are equal to zero. The natural way of enforcing sparsity is to introduce an l1 regularization ensuring that the bias vector has zero components. This leads to a least absolute shrinkage and selection operator (LASSO) problem, which is solved using a reweighted-l1 algorithm. The weighting matrix of this algorithm is defined as functions of the carrier to noise density ratios and elevations of the different satellites. Moreover, the smooth variations of multipath biases versus time are enforced using a regularization based on total variation. For estimating the noise covariance matrix, we use an iterative reweighted least squares strategy based on the so-called Danish method. The performance of the proposed method is assessed via several simulations conducted on different real datasets.
Hand-worn devices for assessment and rehabilitation of motor function and their potential use in BCI protocols: a review

Introduction Various neurological conditions can impair hand function. Affected individuals cannot fully participate in activities of daily living due to the lack of fine motor control. Neurorehabilitation emphasizes repetitive movement and subjective clinical assessments that require clinical experience to administer. Methods Here, we perform a review of literature focused on the use of hand-worn devices for rehabilitation and assessment of hand function. We paid particular attention to protocols that involve brain-computer interfaces (BCIs) since BCIs are gaining ground as a means for detecting volitional signals as the basis for interactive motor training protocols to augment recovery. All devices reviewed either monitor, assist, stimulate, or support hand and finger movement. Results A majority of studies reviewed here test or validate devices through clinical trials, especially for stroke. Even though sensor gloves are the most commonly employed type of device in this domain, they have certain limitations. Many such gloves use bend or inertial sensors to monitor the movement of individual digits, but few monitor both movement and applied pressure. The use of such devices in BCI protocols is also uncommon. Discussion We conclude that hand-worn devices that monitor both flexion and grip will benefit both clinical diagnostic assessment of function during treatment and closed-loop BCI protocols aimed at rehabilitation.
Online-based Learning Management System in the Industrial Revolution 4.0 Era: Reality in Islamic Higher Education

The impact of the industrial revolution 4.0 developments with physical and internet cyber systems in the education sector is the development of computer-based teaching which then propagates to the development of online learning and the use of e-learning media. With a combined system, distance learning occurs in a learning management system with web-based assistance platforms and social media which is the result of the development of Industry 4.0 during the 21st century. The main objective of this research is to analyze and compare student perceptions in implementing eight platforms of implementing an online-based Learning Management System at the tertiary level. Then, this study links students' perceptions in implementing online-based learning management with reference to three aspects of assessment; teaching and learning aspects, lecturer competency aspects, and infrastructure aspects. A quantitative approach with a survey design has been chosen. Sampling technique was purposive sampling and involved 147 respondents. The results concluded that the Zoom, Google Classroom and Whatsapp platforms were the most frequently used distance learning media and were also liked by students. Currently, not many lecturers use Moodle because there is not enough time to learn how to use Moodle and prepare all the resources to design the desired learning, while there are many alternative platforms that are easier to learn and use in a short time. The survey on the three aspects of daring learning has been agreed in detail and the results provide positive conclusions regarding the implementation of online-based learning in the past 4 years.
Adhesion Characteristics of Tire-Asphalt Pavement Interface Based on a Proposed Tire Hydroplaning Model

In order to study the adhesion between tire and asphalt pavement, we established a finite element model of a hydroplaning, inflatable, patterned tire based on the coupled Eulerian–Lagrangian method and then validated the model’s applicability. We numerically calculated tire-pavement adhesion curves for three types of pavement: asphalt concrete (AC), stone mastic asphalt (SMA), and open-graded friction course (OGFC). In accordance with adhesion characteristic theory with regard to tires and asphalt pavements, we analyzed the influential factors that affect the adhesion characteristics of the tire-asphalt pavement interface in an antilock braking system and under damp conditions. The results show that the adhesion between tire and pavement is related to the movement of the tire. In this study, the longitudinal adhesion coefficient for the tire-pavement interface initially increased with an increase in the slip rate and then decreased. Once the slip rate was about 20 percent, the longitudinal adhesion reached its maximum value. In addition, we found that a deep surface macrotexture improved the hydroplaning speed of the tire when the water film was not too thick and the inflation pressure was high. Also, dry pavement led to better adhesion than a wet state in terms of specific mean profile depth. With the same water film thickness, the adhesion coefficient decreased with an increase in driving velocity. The OGFC pavement offered better skid resistance than both AC pavement and SMA pavement.
Recent Progress in Laboratory Astrophysics Achieved with NASA Ames’ COSmIC Facility

Abstract We describe the characteristics and the capabilities of the laboratory facility, COSmIC, that was developed at NASA Ames to generate, process and analyze interstellar, circumstellar and planetary analogs in the laboratory. COSmIC stands for ’Cosmic Simulation Chamber’ and is dedicated to the study of neutral and ionized molecules and nanoparticles under the low temperature and high vacuum conditions that are required to simulate various space environments such as diffuse interstellar clouds, circumstellar outflows and planetary atmospheres. Recent results obtained using COSmIC will be highlighted. In particular, the progress that has been achieved in the domain of the diffuse interstellar bands (DIBs) and in monitoring, in the laboratory, the formation of circumstellar dust grains and planetary atmosphere aerosols from their gas-phase molecular precursors. Plans for future laboratory experiments on interstellar and planetary molecules and grains will also be addressed, as well as the implications of the studies underway for astronomical observations and past and future space mission data analysis.