Miracle-dz/UniFAR-FTUs huggingface dataset:
Personality Type and Chronic Pain: The Relationship between Personality Profile and Chronic Low Back Pain Using Eysenck’s Personality Inventory

Background: Personality type plays a key role in how individuals respond to a variety of stimuli; however, it is unclear if there is a significant influence on pain perception. While pain is associated with many conditions, chronic low back pain (cLBP) is one of the most prevalent and debilitating problems in modern society. Treating this condition can be a challenge and clinicians must understand all factors that can influence pain perception. Purpose: The present study investigated the relationship between personality type and pain experience in patients experiencing cLBP. Methods: One hundred twenty-four participants completed the Eysenck Personality Inventory (EPI), which identifies two major components of the human personality, neuroticism, and extraversion. Participants also completed the Oswestry Disability Index (ODI), the Tampa Scale for Kinesiophobia (TSK), the Numeric Pain Rating Scale (NPRS), and the Pain Catastrophizing Scale (PCS). The association between pain and personality was determined with a Spearman Rank Correlation Coefficient. A hierarchical cluster analysis with Ward’s clustering method examined for subgroups of individuals based on these variables. Results: The neuroticism score (EPI-N) was found to have a statistically significant relationship with all pain outcome measures. This suggests that people exhibiting a neurotic personality type are likely to have more fear of movement (p = 0.001), greater catastrophizing behavior (p < 0.001), higher self-reported levels of disability (p < 0.001), and higher overall reported levels of pain (p = 0.046) than those with other, more stable personality types. Three clusters were derived with varying levels of pain-related factors and personality. Conclusions: Personality type appears to have an influence on many of the attributes associated with cLBP and may be a useful determinate in both prognosis and interventions.
Opportunities and challenges in integrating 2D materials with inorganic 1D and 0D layered nanostructures

The birth of nanoscience more than 50 years ago fueled the renaissance in layered materials research leading to many materials discoveries with unprecedented scientific and technological impacts. Following the early reports on carbon fullerenes and nanotubes, the discovery of inorganic one-dimensional (1D) nanotubes and zero-dimensional (0D) fullerenes created a major playground for new physicochemical observations. The meteoric rise of two-dimensional (2D) materials in concert set off outstanding advances in the synthesis and manipulation of layered materials with atomic precision. This review identifies new directions in materials science that emerge through integrating the two layered systems—2D with inorganic 1D and 0D. Summarizing the key developments in the two distinct nanomaterials families, we highlight preliminary instances of integrating them into functional nanostructures. A few gedankenexperiments regarding prospective applications of the integrated system are then introduced to stimulate further experimental and theoretical investigations that can potentially result in unforeseen scientific observations. Graphical abstract
COMPARISON OF THE FINANCIAL CONDITION OF MILK PROCESSING ENTERPRISES IN POLAND AND UKRAINE

The study aimed to compare and evaluate the effectiveness of enterprises processing and trading dairy products in Poland and Ukraine. Milk processing is an important sector of food production. Milk and milk products account for about 14% of world trade in agricultural products. The five largest companies from Poland and Ukraine were selected for the study. Evaluation of the effectiveness of dairy enterprises required the adoption of appropriate indices. Therefore, the research considered, above all, the indices characterizing the profitability of the surveyed companies as the basic ones in the evaluation of the financial condition of enterprises. In addition, the evaluation included the surveyed enterprises’ return on sales, assets, and equity. The analyses were performed based on data available in the EMIS database for 2016-2020. In Poland, the milk processing sector was in a relatively good financial condition, although the profitability ratios were not too high. Profitability ratios have long been lower than the food industry average and have fallen even further in recent years. The data show that the return on equity slightly exceeded the interest rate on bank deposits and treasury bonds. In Ukrainian enterprises, the return on equity, assets, and sales was much higher, but it was also characterized by high volatility.
Weapons against Themselves: Identification and Use of Quorum Sensing Volatile Molecules to Control Plant Pathogenic Fungi Growth

Quorum sensing (QS) is often defined as a mechanism of microbial communication that can regulate microbial behaviors in accordance with population density. Much is known about QS mechanisms in bacteria, but fungal QS research is still in its infancy. In this study, the molecules constituting the volatolomes of the plant pathogenic fungi Fusarium culmorum and Cochliobolus sativus have been identified during culture conditions involving low and high spore concentrations, with the high concentration imitating overpopulation conditions (for QS stimulation). We determined that volatolomes emitted by these species in conditions of overpopulation have a negative impact on their mycelial growth, with some of the emitted molecules possibly acting as QSM. Candidate VOCs related to QS have then been identified by testing the effect of individual volatile organic compounds (VOCs) on mycelial growth of their emitting species. The antifungal effect observed for the volatolome of F. culmorum in the overpopulation condition could be attributed to ethyl acetate, 2-methylpropan-1-ol, 3-methylbutyl ethanoate, 3-methylbutan-1-ol, and pentan-1-ol, while it could be attributed to longifolene, 3-methylbutan-1-ol, 2-methylpropan-1-ol, and ethyl acetate for C. sativus in the overpopulation condition. This work could pave the way to a sustainable alternative to chemical fungicides.
Utilitarian motivations to engage with travel websites: an interactive technology adoption model

Purpose This study aims to investigate perceptions about interactive travel websites. The researchers hypothesize that engaging content, the quality of information and source credibility have a significant effect on the consumers’ utilitarian motivations to continue using them in the future. Design/methodology/approach A structured survey questionnaire was used to gather data from 1,287 online users, who were members of two popular social media groups. The methodology relied on a partial least squares approach to analyze the causal relationships within an extended information adoption model (IAM). Findings The findings reveal that the research participants perceive the utility of interactive travel websites and are willing to continue using them, particularly the responsive ones. The research participants suggest that these sites are easy to use, capture their attention and offer them useful information on various tourism services. The results also indicate that they appreciate their source credibility (in terms of their trustworthiness and expertise of their curators) as well as their quality content. Research limitations/implications This study integrates key measures from the IAM with a perceived interactivity construct, to better understand the individuals’ acceptance and use of interactive websites. Practical implications This research implies that service businesses ought to have engaging websites that respond to consumer queries in a timely manner. Hence, they should offer a seamless experience to their visitors to encourage loyal behaviors and revisit intentions to their online domains. Originality/value To the best of the authors’ knowledge, there are no other studies that incorporated an interactive engagement construct with key constructs from IAM and from the technology acceptance model (TAM). This contribution underlines the importance of measuring the individuals’ perceptions about the engagement capabilities of interactive media when investigating information and/or technology adoption.
Hydrogenation Effects on the Hot-Carrier Endurance of Metal Induced Laterally Crystallized n-Type Polycrystalline Silicon Thin Film Transistors

Hydrogenation effects on the performance and hot-carrier (HC) stability of n-type metal induced laterally crystallized (MILC) polycrystalline silicon thin-film transistors (TFTs) are systematically investigated using statistics. It is demonstrated for the first time that plasma hydrogenation not only largely improves device performance before stress, but also significantly enhances its HC endurance and tightens the distribution of its degradation data. The improvement of HC reliability is attributed to the reduced Si–H bond breaking mechanism, and the suppression of impact ionization in hydrogenated MILC TFTs.
A hybrid model for high spatial and temporal resolution population distribution prediction

ABSTRACT The accurate prediction of population distribution is crucial for numerous applications, from urban planning to epidemiological modelling. Using one-week data collected from open and multiple sources, including telecommunication activity, weather, point of interest, buildings, roads, and land use in Milan, Italy, we develop a hybrid method combining cellular automata (CA) and long short-term memory (LSTM) to predict population distribution with fine temporal and spatial granularity. Specifically, the convolutional autoencoder and LightGBM are applied to identify missing building types based on the pedestrian shed. The LSTM learns the transition rules of CA and Shapley additive explanations value is used for variable importance analysis. Results demonstrate that the combination of convolutional autoencoder and LightGBM is effective in building type prediction. The proposed model for population distribution prediction outperforms LSTM, the combination of CA and neural network, and the combination of CA and LightGBM by at least 5–10%. A variable importance analysis reveals that temporal variables are the most significant for prediction, followed by spatial and natural variables. The order of hour, housing-related variables, and types of precipitation are the most important variables in each category.
Metode sosialisasi SMA dalam pengenalan kampus di era pandemi

Penelitian ini bertujuan untuk (1) mengetahui metode yang dipergunakan guru kepada siswanya dalam memperkenalkan kampus kepada siswa di masa pandemi, (2) menghasilkan pengetahuan yang tepat mengenai kampus kepada siswa. Penelitian ini menggunakan pendekatan kualitatif dengan melakukan wawancara mendalam pada 9 orang guru sebagai informan yang merupakan perwakilan guru dari 9 sekolah, dengan ketentuan sekolah 3 SMA di Provinsi DIY, 3 SMA di Pulau Jawa (luar DIY) dan 3 SMA di luar Pulau Jawa. Dengan penentuan sampel penelitian dengan cara mengambil data dari sekolah yang paling banyak diterima siswanya di kampus UNY dan yang pernah melakukan kunjungan ke UNY. Sekolah yang dijadikan sampel adalah sekolah negeri. Analisis data dalam penelitian ini menggunakan teknik penarikan purposive sampling, atau disebut juga judgmental sampling yang digunakan dengan menentukan kriteria khusus terhadap sampel, terutama yang dianggap ahli. Adapun target yang diharapkan dari penelitian ini adalah hasil analisis untuk mengetahui dari interaksi yang dilakukan oleh pihak sekolah dengan siswa khususnya kelas XII, metode seperti apa yang dipilih agar pemahaman para siswa mengenai informasi tentang perguruan tinggi sebagai tempat untuk studi lanjut bisa diterima dengan baik sesuai dengan target. Selain itu, penelitian ini juga bertujuan untuk mengetahui sejauh mana para guru menginformasikan UNY kepada para siswa dan mengetahui sejauh mana minat para siswa untuk studi lanjut di UNY.The research aims at (1) finding out the methods used by teachers to their students in introducing campuses to students during the pandemic, (2) producing appropriate knowledge about campuses to students. This study used qualitative approach by conducting in-depth interviews with 9 representative teachers as informants from 9 schools, with the provisions of 3 high schools in Yogyakarta Special Region (DIY) Province, 3 high schools in Java Island (outside DIY) and 3 high schools outside Java Island. By determining the research samples by taking data from the schools that most students are accepted in Universitas Negeri Yogyakarta (UNY) campus and they have visited UNY. The schools that were sampled were state schools. Data analysis in this research used purposive sampling technique, or also called judgmental sampling used to determine specific criteria for the samples, especially those considered as experts. The expected target of this research is the results of the analysis to find out from the interactions done by the school with students, especially Grade XII, what kind of method is chosen so that students' understanding on the information about higher education as a place for further study can be well received in accordance with target. In addition, this research also aims to determine the extent to which teachers inform UNY to students and find out the extent to which students are interested in further studies at UNY.
BARRN: A Blind Image Compression Artifact Reduction Network for Industrial IoT Systems

Most industrial Internet of Things (IoT) devices reduce the capture image size using high-ratio joint photographic experts group (JPEG) compression, saving storage space, and transmission bandwidth consumption. However, the resulting compression artifacts considerably affect the accuracy of subsequent tasks. Most artifact reduction algorithms do not consider the limitations of storage space and computing power of edge devices. In this study, a blind artifact reduction recurrent network (BARRN), which can reduce compression artifacts when the quality factors are unknown, is proposed. First, a structure based on recurrent convolution is designed for the specific requirements of industrial IoT image acquisition devices; the network can be scaled according to system resource constraints. Second, a more efficient convolution group, capable of adaptively processing different degradation levels, is proposed for optimal use of the limited computational resources. The experimental results demonstrate that the proposed BARRN can meet the needs of industrial systems with high computational efficiency.
The Relationship Between Paternal Postpartum Depression and Psychosocial Variables: A longitudinal Study in Iran

Objective: This study aimed to investigate and identify the psychosocial factors that are associated with paternal postpartum depression. Materials and methods: A longitudinal correlation study with 150 fathers was performed with three time frames (late pregnancy, postpartum, and four weeks postpartum). The Edinburgh Postnatal Depression Scale assessed those with depression (38.7%; n=58) and those without depressive symptoms (61.3%; n=92). Psychological variables related to paternal depression were also assessed through questionnaires. Results: Psychological variables such as marital adjustment and stress had a significant relationship with paternal depression. In addition, depressed fathers experienced less marital compatibility and more tension than non-depressed fathers. Conclusion: These findings emphasize the importance of considering the psychosocial variables that affect paternal psychological health. Mental health professionals may be able to reduce mental disorders, stress, psychological distress, and marital maladjustment in fathers with appropriate psychological interventions.
Reproductive outcomes of neonatal exposure to betamethasone in male and female rats

Betamethasone (BM) is the drug of choice for antenatal corticosteroid therapy for women at risk of preterm delivery because it induces fetal lung maturation and enhances survival after birth. However, our group reported evidence of fetal programming and impaired reproductive development and function in rats exposed during the critical window of genital system development. Therefore, we aimed to investigate the effects of BM on the sexual development of rats in the period that corresponds to antenatal corticosteroid therapy in humans. Male and female rats were exposed subcutaneously to BM at 0.1 μg/g of pups' body weight or to a NaCl 0.9% solution (control) on postnatal days 1–3. It was observed that neonatal exposure to BM decreased body weight and weight gain in male and female rats during treatment. The estrous cycle was deregulated and LH level was decreased in female rats. In male rats, the sperm concentration in the caput–corpus of the epididymis was decreased, whereas the sperm transit time and sperm concentration in the cauda of the epididymis were increased. Our results demonstrated that neonatal exposure to BM impaired body growth of male and female rats, deregulated the estrous cycle of female rats, and altered sperm quality of male rats. Therefore, BM exposure from postnatal days 1 to 3 corroborated results previously observed after prenatal exposure to this drug. Despite the recognized importance of human antenatal corticosteroid therapy, the findings of this study should encourage further studies in order to minimize possible adverse postnatal effects.
Non-perturbative models of intermittency in drift-wave turbulence: towards a probabilistic theory of anomalous transport

Two examples of non-perturbative models of intermittency in drift-wave (DW) turbulence are presented. The first is a calculation of the probability distribution function (PDF) of ion heat flux due to structures in ion temperature gradient turbulence. The instanton calculus predicts the PDF to be a stretched exponential. The second is a derivation of a bi-variate Burgers equation for the evolution of the DW population density in the presence of radially extended streamer flows. The PDF of fluctuation intensity avalanches is determined. The relation of this to turbulence spreading, observed in simulations, is discussed.
Examining Pareto Law across department store shoppers

Department stores invest in loyalty strategies that largely focus on retaining current high value customers in response to increasing competition in retail shopping. In this study, we examine the contribution of the top 20% customers for transaction frequency and value (“heavy buyers”) to the total sales, and the consistency of this contribution across departments within a store. We also investigate the heavy buyer stability over time across 3 years, from over 550 million transactions from a department store chain in East Asia. The results show that the Pareto ratio of the top 20% spenders account for 71% of revenue (and 52% of the total transactions), and the top 20% transactors represent 58% of revenue (and 62% of total transactions), which may signal the role of such heavy buyers to overall stores sales. At each department level, the heavy buyers (by value) contribute from 65% to 86% of the department revenue. Despite this, the stability of the top 20% segment over time varies greatly by department from 11% to 74%. Finally, whether high value customers in one department store also translate across departments, depends mainly on the department size in terms of its shopper penetration. The research furthers our knowledge on Pareto Law, with important implications for customer retention strategies and loyalty programs especially for retailers.
Reception of a block of symbols in the presence of a timing offset

The theory of hidden Markov models is used to formulate an iterative method for the joint estimation of timing phase offset and the detection of symbols carried by a time-unsynchronized PAM signal block. Timing phase offset estimation is based on the maximum likelihood criterion. Posterior probabilities of symbols are calculated and used to perform symbol-by-symbol decisions minimizing the symbol error probability. <<ETX>>
A broadband stable gain antenna using nonuniform hexagonal-Slot metasurface

ABSTRACT This paper demonstrates a broadband metasurface antenna with stable gain. A 4 × 4 square patches metasurface loaded with nonuniform hexagonal slots is proposed. To achieve stable radiation performance in broadband range, two characteristic modes with the same current direction are selected as operating modes of the metasurface. A slot antenna is employed to excite the metasurface. By combining the resonant modes of metasurface and slot antenna, the broadband is obtained. The measured results show that, the −10 dB impedance bandwidth of the proposed antenna is 4.36–8.21 GHz (61.2%), the 2 dB gain bandwidth is 4.36–7.2 GHz (49.1%), and the peak gain value reaches 10.6 dBi.
Pengenalan Lirik Lagu Otomatis Pada Video Lagu Indonesia Menggunakan Hidden Markov Model Yang Dilengkapi Music Removal

Video sangat penting untuk membuat informasi berupa suara dalam video agar dapat dipahami oleh semua kalangan masyarakat, dan orang-orang yang memiliki masalah pendengaran yaitu dengan cara paling alami terletak pada penggunaan subtitle. Oleh karena itu, peneliti membuat pengenalan lirik lagu otomatis pada video lagu Indonesia menggunakan Hidden Markov Model yang dilengkapi music removal. Dalam pengenalan suara lebih akurat dilakukan dengan menggunakan model HMM yang dilengkapi oleh MFCC (kata yang cocok 81% dan WER 19%) dibandingkan dengan model LDA + MFCC (kata yang cocok 71% dan WER 29%) dan DWT + MFCC (kata yang cocok 61% dan WER 39%). Jumlah kata dan sample suara pada library Bahasa Indonesia yang digunakan cukup sangat mempengaruhi MFCC dan CMU Sphinx-4, Nada pada inputan lagu yang akan diproses CMU Sphinx-4 juga sangat berpengaruh pada tingkat keberhasilan, dikarenakan CMU Sphinx-4 sangat sensitif dengan nada yang terlalu tinggi dan noise yang ada pada inputan lagu tersebut sehingga peneliti menambahkan fitur ekstraksi pada suara yaitu menggunakan MFCC. Dalam hal ini menggunakan dataset kecil terlebih dahulu untuk memastikan metode Hidden Markov Model yang dilengkapi MFCC dan CMU Sphinx-4 dapat berjalan dengan baik, Dari penelitian beberapa peneliti sebelumnya, maka hasil akhir yang diperoleh dengan menggunakan metode HMM yang dilengkapi oleh MFCC dan CMU Sphinx-4 dalam penelitian ini mendapatkan hasil akurasi training 78% dan testing 81% kecocokan kata pada video lagu.
THEORY AND APPLICATIONS OF OPTIMAL CONTROL PROBLEMS WITH MULTIPLE TIME-DELAYS

In this paper we study optimal control problems with multiple time delays in control and state and mixed type control-state constraints. We derive necessary optimality conditions in the form of a Pontryagin type Minimum Principle. A discretization method is presented by which the delayed control problem is transformed into a nonlinear programming problem. It is shown that the associated Lagrange multipliers provide a consistent numerical approximation for the adjoint variables of the delayed optimal control problem. We illustrate the theory and numerical approach on an analytical example and an optimal control model from immunology.