Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Autistic Traits Between Iranian Students With Different Ethnic Backgrounds: A Cross-Cultural Study

Autistic traits (ATs) include symptoms associated with autism spectrum conditions (ASCs), which are assumed to be continuously distributed across the general population. Studies have indicated the cultural differences in the expression of ATs. Notwithstanding, our literature review indicated that studies on cross-cultural differences in the expression of ATs included samples from different countries. This is the first study designed to compare the expression of ATs between different ethnicities from the same country. Using the Autism-spectrum Quotient (AQ-28), we examined the possible cultural differences in the expression of autistic traits from four groups of students with different ethnic backgrounds, including Turkish (n = 262), Persian (n = 290), Kurdish (n = 300), and Luri (n = 307) students. Behaviors associated with autistic traits were reported overall higher for males than females. Also, significant cultural differences in autistic traits were found that were different for males and females. Furthermore, while the medical sciences student group scored significantly higher than the humanities group in the Imagination dimension, the humanities group had significantly higher scores in Number/Pattern dimensions than the engineering and medical sciences groups. Altogether, our results provide further support for the idea that the expression of ATs is significantly influenced by culture. A significant limitation of the current study was that groups were not matched with respect to age, percentage of male participants, and fields of studies and that these variables may influence the AQ scores.
Altruistic Preference Models of Low-Carbon E-Commerce Supply Chain

With the gradual popularity of online sales and the enhancement of consumers’ low-carbon awareness, the low-carbon e-commerce supply chain (LCECSC) has developed rapidly. However, most of the current research on LCECSC assumes that the decision-making body is rational, and there is less research on the irrational behavior of the e-platform altruistic preference. Therefore, aiming at the LCECSC composed of a single e-platform and a single manufacturer, this paper establishes two basic models with or without altruistic preference. Additionally, this paper combines the characteristics of online sales and assumes that altruistic preference is a proportional function of commission, then establishes a commission-based extended model with altruistic preference to further explore the influence of commission on its altruistic preference. The current literature does not consider this point, nor does it analyze the influence of other parameters on the degree of altruism preference. By comparing the optimal decisions and numerical analysis among the models, the following conclusions can be drawn that: (1) different from the traditional offline supply chain, the profit of the dominator e-platform is lower than the profit of the follower manufacturer; (2) when the consumers’ carbon emission reduction elasticity coefficient increases, service level, sales price, carbon emission reduction, sales, supply chain members profits, and system profit increase, ultimately improving economic and environmental performances; (3) the altruistic preference behavior of the e-platform is a behavior of ‘profit transferring’. The moderate altruistic preference is conducive to the stable operation and long-term development of LCECSC.
PENTINGNYA FINANCIAL LITERACY DALAM TATA KELOLA KEUANGAN PRIBADI (SUATU STUDI PUSTAKA)

Tujuan pengelolaan keuangan ini adalah agar kita terhindar dari kondisi lebih banyak hutang daripada pemasukan. Literasi keuangan adalah kemampuan (kecakapan) seseorangan dalam membuat keputusan yang efektif berhubungan dengan keuangannya. Literasi keuangan membantu individu terhindar dari masalah keuangan terutama yang terjadi akibat kesalahan pengelolaan keuangan. Pentingnya literasi keuangan dalam bentuk semua aspek keuangan pribadi bukan karena untuk mempersulit dalam menggunakan uang yang mereka miliki, tetapi diharapkan individu dapat menikmati hidup dengan menggunakan sumber daya keuangan yang dimiliki dengan tepat. Dengan pengelolaan keuangan yang tepat yang ditunjang dengan literasi keuangan yang baik, maka taraf hidup masyarakat diharapkan akan meningkat, karena walau bagaimanapun tingginya tingkat penghasilan seseorang tapi tanpa pengelolaan keuangan yang tepat, keamanan finansial pasti akan sulit tercapai. Literasi keuangan yang baik dapat melindungi masyarakat dari berbagai modus tindak penipuan keuangan. Dengan memahami dan melaksanakan manajemen keuangan pribadi, maka kita telah mengetahui tujuan tertinggi dan bagaimana mencapainya. Pengelolaan keuangan pribadi sangat membantu untuk menjalani aktivitas secara terencana secara finansial. Literasi keuangan dalam bentuk pemahaman terhadap semua aspek keuangan pribadi bukan ditujukan untuk mempersulit atau mengekang orang dalam menikmati hidup, tetapi justru dengan literasi keuangan, individu atau keluarga dapat menikmati hidup dengan mendayagunakan sumberdaya keuangannya dengan tepat dalam rangka mencapai tujuan keuangan pribadinya.
Effects of Passive Haptic Learning in Music-Supported Therapy on Sensorimotor Performance in Older Adult Hands: A Randomized Crossover Trial

Background: Music-supported therapy (MST), a type of biofeedback therapy with multi-sensory information input, has been proposed as an effective approach to improving motor control in people with sensorimotor deficits. However, currently, MST training is restricted to being extensively applied for patients with various levels of defects in fine motor skills and cognitive functions. Therefore, the integration of passive haptic learning (PHL) with MST has been adopted as a motor training strategy intended to enhance “motor memory” learning through the use of vibration stimuli. The current study was designed to investigate differences in the sensorimotor performance of older adults’ hands under baseline, a single session of standard MST, and PHL-based MST conditions. Methods: Thirty healthy older adults were recruited and randomized to receive either the single session of 30-minutes of PHL-based MST or 30-minutes of standard MST at the beginning of the experiment. After a one-week washout period, they switched their treatment programs and then were assessed to study the training effects of both approaches through measuring precision pinch performance, hand function, and sensory status. Results: The results of the Pinch-Holding-Up Activity test revealed a statistically significant difference in the FRpeak parameter (F = 14.37, p < 0.001, η² = 0.507) under the PHL-based MST condition compared to the baseline and standard MST conditions. In addition, significant beneficial effects were found on the results of the barognosis (F = 19.126, p < 0.001, η² = 0. 577) and roughness differentiation subtests (F = 15.036, p < 0.001, η² = 0.518) in the Manual Tactile Test for the participants in the PHL-based MST group. In addition, the participants under both the standard MST and PHL-based MST conditions exhibited better performance in the three subtests of the Purdue Pegboard Test as compared to under the baseline condition (p < 0.016). Conclusions: The findings indicated that PHL-based MST potentially improves the precision pinch performance of hands in healthy older adults. In addition, the add-on effect of vibrotactile stimulation to the MST condition provides beneficial effects on the sensory functions of the upper extremities. Clinical Trial Registration: NCT04802564
Surface Characterization of Sulfated Iron Oxide and Its Synthesis of Biodiesel Under Microwave Radiation

Abstract The solid acid catalysts SO42−/Fe2O3 were prepared by impregnation technique, and the preparation conditions were different in calcination temperature, concentration of impregnation solution of H2SO4 and impregnation time. The characterization was performed by using Fourier transform infrared spectrometer (FTIR), X-ray diffraction (XRD), Temperature programed desorption of NH3 (NH3‒TPD), N2‒BET and microwave absorbing test. As shown by FTIR spectra, the S=O functional group existed in the sample, which was essential for the strong acidity of the SO42‒/MxOy type solid acids. The XRD results indicated that when the calcination temperature exceeded 400℃, iron in SO42‒/Fe2O3 transformed from amorphous to crystalline phase. The results from NH3-TPD showed that the prepared sample possessed strong acid and superacid sites. As shown by N2-BET results, the BET surface area of the samples was up to 200m2/g, and their pore size distributions essentially belonged to mesoporous characteristic distribution. The SO42−/Fe2O3 solid acid catalysts were used for the transesterification of castor oil under microwave radiation to produce biodiesel. The amounts of FAME in the product were analyzed by high-performance liquid chromatography. The highest yield of product was 65.3 wt. % when the reaction temperature was 65 ℃, alcohol/oil molar ratio was 30/1, catalyst loading was 20 wt. %, the reaction time was 3 h and the power of microwave was 300 w. Furthermore, the reaction results showed that SO42‒/Fe2O3 had better catalytic activity under microwave radiation than under conventional heating condition.
O uso de Data Mart para apoio à tomada de decisão na Gestão de Pessoas em uma Instituição Federal de Ensino

Business Intelligence (BI) é composto por um banco de dados multidimensional, orientado por assunto, não volátil, histórico, decisório e variável em relação ao tempo. Ao aplicar o uso do Data Mart para uma Instituição Federal de Ensino no setor de gestão de pessoas, essa pesquisa trabalhou com os dados para desenvolver indicadores para a tomada de decisão. Questões como falta de sinergia entre as bases de dados existentes, qualidade dos dados fornecidos e impossibilidade da emissão de relatórios gerenciais em tempo hábil, foram tratados nesse estudo. Concluiu-se que a aplicação e implantação de BI através de Data Mart pode gerar dados precisos, solucionar os problemas e fornecer indicadores de desempenho.
Effect of TritonX-100 on the aggregation behavior of SDS in water

ABSTRACT The phase behavior patterns and microstructures of surfactant systems containing sodium dodecyl sulfate (SDS)/TritonX-100/H2O were investigated under a polarizing microscope. Ternary mixtures of SDS/TritonX-100/H2O form two types of well-ordered lyotropic liquid crystals: a hexagonal phase linked to the SDS/water axis and a lamellar phase located at the corner of their phase diagram. Surface tension measurements were conducted for TritonX-100 in the SDS solutions. In the SDS/TritonX-100/H2O system, transition points were found in the surface tension concentration curves at different quality ratios. On the basis of the critical micelle concentration values, the thermodynamic parameters of the aggregate formation, namely, , , and , were estimated. Results show that the addition of TritonX-100 is beneficial to the formation of surfactant aggregates, and thermodynamic data indicate that the micellization of binary mixture of SDS/TritonX-100 in aqueous solution is an entropy-driven spontaneous process. Therefore, the addition of TritonX-100 in SDS aqueous solutions may have potential applications in nanomaterial preparation.
Soft Exoskeletons: Development, Requirements, and Challenges of the Last Decade

In this article, various investigations on soft exoskeletons are presented and their functional and structural characteristics are analyzed. The present work is oriented to the studies of the last decade and covers the upper and lower joints, specifically the shoulder, elbow, wrist, hand, hip, knee, and ankle. Its functionality, applicability, and main characteristics are exposed, such as degrees of freedom, force, actuators, power transmission methods, control systems, and sensors. The purpose of this work is to show the current trend in the development of soft exoskeletons, in addition to specifying the essential characteristics that must be considered in its design and the challenges that its construction implies.
Perbandingan Efektivitas Virgin Coconut Oil dan Triamcinolon Acetonide dalam Pencegahan Adhesi Intraperitoneal pada Hewan Percobaan Tikus

Latar belakang: Adhesi peritoneal sering terjadi setelah operasi abdomen, dimana adhesi kemudian menjadi sumber morbiditas. Adanya perlekatan menimbulkan keluhan seperti nyeri perut, mempersulit pembedahan berikutnya, sampai terjadinya obstruksi usus. Pemakaian obat-obatan farmakologik sebagai ajuvan telah banyak dilakukan untuk pencegahan adhesi paska operasi. Pada penelitian ini diteliti perbandingan efektivitas antara penggunaan Virgin Coconut Oil (VCO) dan Triamcinolone Acetonide (TCA) dalam mencegah terbentuknya adhesi intraperitoneal paska laparatomi Metode: Penelitian eksperimen dengan pengukuran perbandingan derajat adhesi secara makroskopik dan mikroskopik pada 30 tikus jantan Rattus norvegicus strain Wistar. Subjek dibagi dalam tiga kelompok. Satu kelompok diberikan VCO pada caecum yang telah diabrasi, satu kelompok diberikan TCA, dan kelompok yang lain menjadi kontrol. Hasil: Tampak bahwa sebagian hewan-hewan tersebut (n = 14, atau 47%) tidak menunjukkan adanya adhesi secara makroskopik dan mikroskopik. Pada 16 tikus dengan fibrosis pun, semuanya berkategori ringan dan tipis (tingkat 1) menurut klasifikasi Yilmaz. Dalam pembagian gambaran makroskopik Zuhlke, tiga perempat (n = 12) dari tikus-tikus dengan adhesi tergolong tingkat 1 ataupun 2. Diskusi: Penggunaan preparat TCA dan VCO terbukti membantu mengurangi angka kejadian adhesi intraperitoneal sesuai kepustakaan dan penelitian sebelumnya, yang mengungkapkan bahwa TCA dan VCO mengandung zat-zat yang secara langsung berfungsi mencegah adhesi baik secara lokal maupun sistemik karena kinerjanya dalam proses inflamasi. Simpulan: Penggunaan TCA dan VCO memiliki efektivitas yang bermakna dalam pencegahan adhesi intraperitoneal dibandingkan dengan kelompok kontrol, namun dalam perbandingan antara kedua preparat yaitu TCA dan VCO, tidak ditemukan perbedaan efektivitas yang bermakna.
Metric Learning via Cross-Validation

In this paper, we propose a cross-validation metric learning approach to learn a distance metric for dimension reduction in the multiple-index model. We minimize a leaveone-out cross-validation-type loss function, where the unknown link function is approximated by a metric-based kernel-smoothing function. To the best of our knowledge, we are the first to reduce the dimensionality of multiple-index models in a framework of metric learning. The resulting metric contains crucial information on both the central mean subspace and the optimal kernel-smoothing bandwidth. Under weak assumptions on the design of the predictors, we establish asymptotic theories for the consistency and convergence rate of the estimated directions, as well as the optimal rate of the bandwidth. Furthermore, we develop a novel estimation procedure to determine the structural dimension of the central mean subspace. The proposed approach is relatively easy to implement numerically by employing fast gradient-based algorithms. Various empirical studies illustrate its advantages over other existing methods. Statistica Sinica: Preprint doi:10.5705/ss.202020. 0398
Parkinson sEMG signal prediction and generation with Neural Networks

Parkinson’s Disease (PD) is a neurodegenerative disorder characterized by symptoms like resting and action tremors, which cause severe impairments to the patient’s life. Recently, many assistance techniques have been proposed to minimize the disease’s impact on patients’ life. However, most of these methods depend on data from PD’s surface electromyography (sEMG), which is scarce. In this work, we propose the first methods, based on Neural Networks, for predicting, generating, and transferring the style of patient-specific PD sEMG tremor signals. This dissertation contributes to the area by i) comparing different NN models for predicting PD sEMG signals to anticipate resting tremor patterns ii) proposing the first approach based on Deep Convolutional Generative Adversarial Networks (DCGANs) to generate PD’s sEMG tremor signals; iii) applying Style Transfer (ST) for augmenting PD’s sEMG signals with publicly available datasets of non-PD subjects; iv) proposing metrics for evaluating the PD’s signal characterization in sEMG signals. These new data created by our methods could validate treatment approaches on different movement scenarios, contributing to the development of new techniques for tremor suppression in patients.
Probing Lipid Diffusion in Curved and Planar Membranes with Fluorescence Microscopy

Diffusion is the most important transport mechanism in biological membranes and essential for processes such as signalling or trafficking. Many different techniques have given insight into this matter, most of which are based on fluorescence microscopy. Applying these to synaptic vesicles or nanoscopic membrane domains, which are much smaller than the diffraction-limited resolution of a light microscope, is an ambitious task. In this thesis, two methods based on fluorescence correlation spectroscopy (FCS) are presented which circumvent the resolution limit and enable diffusion coefficient estimations in vesicles less than 200 nm in diameter. At this scale, the influence of membrane curvature on viscosity, diffusion speed, or lipid composition becomes dominant. The first approach, dynamicMIET, exploits the interaction energy transfer of a fluorescent lipid in close proximity to a thin metal sheet. The resulting fluctuation in fluorescence intensity strongly depends on their distance to each other, which can in turn be obtained by FCS, making it possible to extract the membrane diffusion coefficient of a surface-tethered vesicle of arbitrary size. A robust and highly specific binding assay has been developed, but the organic dyes used for labelling were neither bright nor stable enough to obtain proper correlation curves. A detailed analysis revealed drastically increased dark state transitions and photo-bleaching of the lipid-conjugated dyes compared to their free counterparts. The second technique is based on measuring the polarisation-resolved rotational diffusion of a fluorescent lipid within a vesicle bilayer. By fixing the dye-to-membrane orientation, rotational and translational diffusion components can be measured and extracted separately. A 3D diffusion model incorporating the vesicle size distribution fits the correlation curves very well, but the obtained diffusion coefficients are biased towards higher values, especially for larger liposomes. However, the fluorophore used in these experiments was found to have excellent photo-physical characteristics which could help to resolve the issues encountered in the dynamicMIET measurements. To handle the data evaluation for many of the control experiments, I developed TrackNTrace, an open-source framework for fluorescence microscopy image analysis. TNT was originally designed as a localisation microscopy and particle tracking tool, but is extendible through a simple plugin system. It provides many state-of-the-art implementations of important algorithms and is aimed at novices as well as experienced researchers. An extensive visual feedback mechanism allows inspecting the program's output at all times, facilitating parameter optimisation and error recognition. These concepts were validated by comparing TrackNTrace against similar programs. The software has been a great help in analysing many of the experiments presented in this thesis and will hopefully turn out to be similarly beneficial for other scientists.
Path tracking control of an autonomous vehicle with model-free adaptive dynamic programming and RBF neural network disturbance compensation

The performance of the model-based controller is always affected by the uncertainty and nonlinearity of the model parameters in the vehicle path tracking process. To address this issue, a novel path tracking controller based on model-free adaptive dynamic programming (ADP) is proposed for autonomous vehicles in this paper. To be specific, the proposed controller obtains information from the online state and front-wheel angle input data which are repeatedly used to calculate the controller gain iteratively. So, this controller features not requiring accurate knowledge of vehicle model parameters for controller development. Meanwhile, the path tracking performance of the autonomous vehicle will be inevitably disturbed by unknown nonlinear external disturbance. To approximate this disturbance, the learning characteristics of Radial Basis Function Neural Network (RBFNN) are applied to generate compensation for the front-wheel angle. Afterward, the weight updating law of RBFNN is derived by Lyapunov function to ensure the stability and convergence of the whole system. Finally, Hardware in the loop (HIL) test results demonstrate that the proposed ADP-RBF controller can improve the comprehensive performance of the vehicle path tracking control system and achieve the balance between path tracking accuracy and minimum sideslip angle.
The Correlation Between Annual Reports’ Narratives and Business Performance: A Retrospective Analysis

This article investigates the extant literature on the correlation between narratives in corporate annual reports and corporate performance. Prior studies are reviewed for overall characteristics, research topics, theoretical foundations, and methods. Articles published between 2000 and 2018 were analyzed using the content analysis method. The results demonstrated that prior studies generally show an increasing trend with salient interdisciplinarity. Mapping and predictability between annual reports’ narratives and business performance have been the prevailing topics. The impression management and agency theories are the most frequent theoretical references. More importantly, complexity of research methods was found in data, analytical approaches, and variables. The emphasis on narratives in prior research proves the necessity of contextualizing narratives in business communication. Future work would benefit from a “narrative framework” that incorporates linguistic, socio-cultural, and organizational perspectives into the correlation study. The article presents the first study to investigate the correlation studies through content analysis.
An Online Map Matching Algorithm Based on Second-Order Hidden Markov Model

Map matching is a key preprocess of trajectory data which recently have become a major data source for various transport applications and location-based services. In this paper, an online map matching algorithm based on the second-order hidden Markov model (HMM) is proposed for processing trajectory data in complex urban road networks such as parallel road segments and various road intersections. Several factors such as driver’s travel preference, network topology, road level, and vehicle heading are well considered. An extended Viterbi algorithm and a self-adaptive sliding window mechanism are adopted to solve the map matching problem efficiently. To demonstrate the effectiveness of the proposed algorithm, a case study is carried out using a massive taxi trajectory dataset in Nanjing, China. Case study results show that the accuracy of the proposed algorithm outperforms the baseline algorithm built on the first-order HMM in various testing experiments.