Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Garlic (Allium sativum) Supplementation on Premenstrual Disorders: A Randomized, Double-Blind, Placebo-Controlled Trial

Background Premenstrual disorders involve physical, behavioral, and mood variations that affect women of childbearing age and interfere with family relationships, household responsibilities, professional duties, and social activities. Objectives Considering the side effects of conventional medications, their use is not recommended except in severe cases of premenstrual disorders. Nowadays, there is a tendency to use traditional and complementary medicine that offers various treatments. The purpose of the current study was to investigate the impacts of garlic as a herbal medicine on the severity of premenstrual symptoms. Methods This study was a double-blind, randomized, controlled trial. After identification of participants with moderate-to-severe PMS through the premenstrual symptoms screening tools questionnaire (PSST), they were randomly assigned to placebo (n = 64) or garlic (n = 65) groups. Each participant received one tablet daily for three consecutive cycles and logged the severity of their symptoms in the PSST questionnaire during the intervention period. Results There was no significant difference between the two groups in the baseline level of premenstrual symptoms before the intervention. After treatment with garlic for three consecutive cycles, the total score of the severity of premenstrual symptoms significantly (P < 0.001) reduced from 34.09 ± 7.31 to 11.21 ± 7.17. In the placebo group, this score changed from 33.35 ± 7.96 to 24.28 ± 7.22. The difference between mean changes in the two groups was 13.78, with a 95% Confidence Interval (CI) of 11.23–16.33. No serious side effects were observed in either group. Conclusion Our findings highlight the potential effect of garlic in reducing the severity of premenstrual symptoms; therefore, the use of garlic can be considered as an alternative therapy in the prevention and treatment of premenstrual disorders.
Exciting Circular TM11 Mode Using Symmetric Probes Based on Ridge Gap Waveguide

This article proposes a method to excite the TM11 mode in circular waveguides. The principle of synthesizing a circular TM mode is deduced based on the electric dipole moment theory first, and the output mode and its purity are analyzed theoretically. Then, a mode conversion scheme to convert the rectangular TE10 into circular TM11 mode via a pair of out-of-phase quasi-TEM mode is proposed. In order to achieve the broadband excitation in a compact size, the ridge gap waveguide is used as a medium between the rectangular and cylindrical waveguide. Simulation results present that the proposed exciter has a propagation bandwidth up to 10 GHz in Ka-band with a mode purity over 98%. A prototype is manufactured and measured, and the presence of TM11 mode and the mode purity are confirmed by a port radiation pattern measurement. The mode exciter features high mode purity, broad bandwidth, and a compact size, which provides a low-power generator for the research of novel gyrobackward-wave devices and devices in the high-power transmission line.
Post-Traumatic Epilepsy (PTE) and Quality of Life after Traumatic Brain Injury (TBI)

Traumatic Brain Injury (TBI), a complex neurotrauma worldwide, commonly occurs in social life and shows several symptoms, longterm neuropsychological disability, and also causes mortality [1]. The prevalence of TBI is 10 million individuals per year and is one of the major causes of death amid young adults [2,3]. TBI damages brain in two ways: 10 brain damage, the damage which occurs at the time of insult, and 20 brain damage, the damage that develops few time after the injury [4]. TBI is classified into 3 categories i.e. mild, moderate, and severe based on the 15-point Glasgow Coma Scale (GCS), commonly used for rating the severity of brain insult [5]. The common areas which are injured during TBI are contusion, focal shear injury, edema, vascular compromise, Diffuse Axonal Injury (DAI), and excitotoxic reaction, along with diffuse brain injury (DBI) [6]. PostTraumatic Epilepsy (PTE) is one of the common prognosis of TBI but the mechanisms are not known and followed by PTE. Epileptogenesis refers to the latent period followed by brain damaging injury in which the brain experiences molecular and cellular modifications, causes its excitability then leads to the occurrence of repeated spontaneous seizures. Post-traumatic epileptogenic components linked with severe TBI, enhance seizure susceptibility and lead to PTE. The categories of epilepsy which are associated with TBI are symptomatic, partial seizure with consciousness and without consciousness and generalized seizures. Absence seizures are not associated with head trauma [7]. TBI is believed to be a ‘silent epidemic,’ as individuals are mostly unaware of this problem [8]. It also decreases the quality of life (QoL) of the affected patients. Patients become unacceptable to the society which leads to their social boycott, sometimes leads to suicidal attempt. It interferes with the normal brain function also [9]. The important factors which affect QoL are memory disorders [10], fatigue [11], self-awareness deficits, feeling, emotions etc [12].
Aplicación y uso del Modelo de Resonancia o Customer-Based Brand Equity (CBBE). Estudio de la lealtad de marca a través de la figura del influencer

Los avances tecnológicos provocan un desafío para los formatos publicitarios tradicionales que presentan cierta dificultad a la hora desconectar con el público. La sobreexposición publicitaria provoca que los canales promocionales tradicionales pierdan su eficacia y los esfuerzos de comunicación se dirijan hacia la búsqueda de nuevos formatos para alcanzar a los consumidores de un modo no intrusivo como es el escenario del social media. En este contexto, y como punto de partida, cobra fuerza la figura del influencer, una herramienta estratégica que viene siendo utilizada por las marcas y que ha generado un gran impacto económico en ámbitos como la moda. El objetivo es, pues, profundizar en la influencia que estos persuasores ejercen sobre los consumidores en la elección de marcas de moda. La metodología empleada parte del triple enfoque e incluye varias técnicas de investigación, cualitativas y cuantitativas, y atiende tanto a consumidores como a influencers. Así, apoyado en el Modelo de Resonancia de Keller, se realizaron 9 entrevistas en profundidad a influencers en Instagram y se obtuvieron 1080 respuestas a una encuesta a seguidores. Los resultados indican que la lealtad de marca se ve ampliada gracias a la resonancia a la que contribuyen los influencers con sus acciones de colaboración con las marcas.
Determination of Extracellular Hydrolytic Enzyme Production Capabilities of Acidithiobacillus Bacteria Isolated from Awasppi River in Sulaymaniyah, Iraq and 16S rDNA Analysis

In this study, the 16S rDNA gene regions’ phylogenetic positions based on the sequence analysis were determined by examining some hydrolytic extracellular enzyme activities of the Acidithiobacillus bacteria isolated from the water and mud samples obtained from the Awasspi River in Sulaymaniyah province, northern Iraq and from the Darzilais sulphur cave in Sangaw district. While the catalase activity of the isolates was positive; lipase, protease, xylanase, and amylase activities were found to be negative. Genomic DNAs of the isolates were isolated and 16S rDNA gene region was realized with PCR amplification. To determine the distance between the species, Maximum Likelihood algorithm was used to form a phylogenetic tree. It was observed that gene strands belonging to Acidithiobacillus species acquired from NCBI and 2 isolates we used in our study clustered with a strong homology and their genetic positions were revealed.
Edukasi Diversifikasi Pangan Skala Rumah Tangga pada Masa Pandemi Bagi Masyarakat Di Lingkungan Kevikepan Daerah Istimewa Yogyakarta

Selama masa pandemi, terjadi peningkatan aktivitas budidaya tanaman sayur mayur dan ikan lele yang dilakukan secara mandiri oleh masyarakat di lingkungan Kevikepan Daerah Istimewa Yogyakarta (DIY). Hal tersebut menyebabkan tingginya hasil panen di lingkup rumah tangga. Diversifikasi pangan menjadi solusi yang dapat dilakukan untuk mengolah hasil panen secara optimal, sehingga akan tercipta ketahanan pangan bagi masing-masing keluarga. Edukasi diversifikasi pangan bertujuan meningkatkan pengetahuan masyarakat terhadap ragam pangan yang dapat dikembangkan dengan mudah di rumah, serta trik teknologi pengolahan pangan tersebut. Edukasi berupa kegiatan penyuluhan dilakukan secara daring dan dihadiri 27 peserta yang merupakan masyarakat di lingkungan Kevikepan DIY. Teknik pengolahan produk pangan didemonstrasikan melalui video pengolahan sayuran hijau menjadi sayur fermentasi, cabai menjadi bubuk cabai, dan ikan lele menjadi sambal ikan lele. Tingkat pengetahuan peserta diukur melalui pengerjaan pretest dan post test berdasarkan pertanyaan yang sama. Hasil analisis uji Wilcoxon Signed Ranks membuktikan bahwa terdapat peningkatan skor yang signifikan setelah mengikuti kegiatan penyuluhan (p=0,004).
Enhancing Comprehension of Informational Text by Young Children With Autism Spectrum Disorders

144 YOUNG EXCEPTIONAL CHILDREN Vol. 26, No. 3, September 2023 https://doi.org/10.1177/10962506211056026 DOI: 10.1177/10962506211056026 journals.sagepub.com/home/yec Article reuse guidelines: sagepub.com/journals-permissions © 2021 Division for Early Childhood Ms. Charlotte’s inclusive kindergarten classroom is bright and inviting. She uses evidence-based and developmentally appropriate practices to create a well-rounded and effective educational experience. She understands the importance of children learning from informational text (IT). With the assistance of her paraprofessional, Ms. Tam, Ms. Charlotte uses a variety of instructional approaches to enhance her students’ abilities to understand IT. However, one of her students, Mark, who has autism spectrum disorders and uses an augmentative and alternative communication (AAC) system on an iPad, has been struggling to understand IT. Ms. Charlotte has decided to modify her instructional strategies to better support Mark’s learning from IT. Informational text (IT) is a type of nonfiction designed to convey information about the natural or social world. Reading IT with young children increases knowledge of content area vocabulary and concepts and helps children build the background knowledge for success with future reading (Pentimonti et al., 2010). However, similar to Mark, children with autism spectrum disorder (ASD) may struggle to understand IT (Marsh, 2015). Therefore, the purpose of this article is to discuss how young children with ASD can be supported to comprehend IT. Instructional 1056026 YECXXX10.1177/10962506211056026YOUNG EXCEPTIONAL CHILDRENComprehension of Informational Text / Jackson et al. research-article2021
Interaction of CD147 and human epididymis protein 4 promotes invasion and metastasis of ovarian cancer

Background: Ovarian cancer is one of the most common malignant tumors in female reproductive system. The expression of CD147 and human epididymis protein 4 (HE4) are both upregulated and associated with malignant progression in ovarian cancer. However, the important role of interaction between CD147 and HE4 in the invasion and metastasis of ovarian cancer remains unclear. Methods: The co-expression and co-localization of CD147 and HE4 in cells and tissues of ovarian cancer were detected by co-immunoprecipitation, immunohistochemistry and immunocytochemistry, double-labeling immunofluorescence method. The interaction between CD147 and annexin A2 (ANXA2) was also investigated. Furthermore, we detect the regulatory relationship between CD147 and HE4 by Western blot. Transwell assay and scratch test were conducted to explore the effect of CD147-HE4 interaction on migration and invasion of ovarian cancer. Results: The protein CD147 and HE4 were co-immunoprecipitated and co-located in the cytoplasm and membrane of ovarian cancer tissues and cells. Both of two proteins were highly expressed and positively associated with advanced FIGO stages, poor differentiation degree and poor prognosis of ovarian cancer, and HE4 was confirmed as an independent risk factor for CD147 in ovarian cancer tissues. What's more, AXNA2 was also identified as a CD147 interacting protein in ovarian cancer. It is further confirmed that interaction between CD147 and HE4 can affect the invasion and metastasis of ovarian cancer. Conclusion: This study demonstrated that HE4 and ANXA2 were both CD147 interacting proteins, the expression of CD147 and HE4 can affect each other, and HE4 could promote the invasion and metastasis of ovarian cancer by regulating the expression of CD147, which may provide novel thought for early diagnosis and therapeutic target of ovarian cancer.
From Social Gaze to Indirect Speech Constructions: How to Induce the Impression That Your Companion Robot Is a Conscious Creature

We implemented different modes of social gaze behavior in our companion robot, F-2, to evaluate the impression of the gaze behaviors on humans in three symmetric communicative situations: (a) the robot telling a story, (b) the person telling a story to the robot, and (c) both parties communicating about objects in the real world while solving a Tangram puzzle. In all the situations the robot localized the human’s eyes and directed its gaze between the human, the environment, and the object of interest in the problem space (if it existed). We examined the balance between different gaze directions as the novel key element to maintaining a feeling of social connection with the robot in humans. We extended the computer model of the robot in order to simulate realistic gaze behavior in the robot and create the impression of the robot changing its internal cognitive states. Other novel results include the implicit, rather than explicit, character of the robot gaze perception for many of our subjects and the role of individual differences, especially the level of emotional intelligence, in terms of human sensitivity to the robotic gaze. Therefore, in this study, we used an iterative approach, extending the applied cognitive architecture in order to simulate the balance between different behavioral reactions and to test it in the experiments. In such a way, we came to a description of the key behavioral cues that suggest to a person that the particular robot can be perceived as an emotional and even conscious creature.
A Planar Multi-coil Transmitter for Visible Magnetic Field Shaping in Wireless Power Transfer

The wireless power transfer (WPT) systems operating at MHz are known to be advantageous thanks to their small size and a high tolerance for coil misalignment. Magnetic field (B-field) shaping technology in WPT enables control of the magnetic flux at a particular location, thereby further improving positional freedom with high coil efficiency. Most WPT systems with magnetic field shaping technology use a 3D transmitting coil structure. Besides, current research work lacks a simple, intuitive, and low-cost method to show the magnetic field shaping effect. This paper proposes a planar multi-coil transmitter for visible 3D magnetic field shaping but without a 3D transmitting coil structure. An LED receiver array realizes the magnetic field visualization by displaying the magnetic field in different positions and directions through the LED brightness. Based on the time domain modeling of the B-field generated by the multi-coil transmitter, the phasor domain modeling paves a new way to establish a time-invariant magnetic field model. The analysis of the magnetic field generated by a 2D coil array provides insights into the three degrees of freedom (DoF) WPT. Final experiments validate the modeling and analysis via a magnetic field visualization system. Experimental results match well with theoretical analysis. Thus, the proposed planar multicoil transmitter can shape 3D magnetic field.
Parameter Tuned Machine Learning based Decision Support System for Bank Telemarketing

In banking sectors, telemarketing is the major support of selling the products or services. Banking advertisement and marketing are mainly depending upon the comprehensive knowledge of objective data regarding the market and the actual client requirements for the bank gainful way. Decision Support Systems (DSS) play a vital part in telemarketing sector, which determines a specific class of automized facts to assist the company to make decisions. Machine learning (ML) is commonly used in the DSS which integrates the data and computer application for precise prediction of results. This paper presents an effective parameter tuned ML based DSS (PTML-DSS) for bank telemarketing sector. The proposed PTML-DSS technique follows a three-level process namely preprocessing, classification, and parameter optimization. Initially, the marketing data is preprocessed to get rid of unwanted information. In addition, gradient boosting decision tree (GBDT) based classifier model is used to classify the data. Besides, firefly algorithm (FFA) is applied for tuning the parameters involved in the GBDT model. In order to verify the improved performance of the PTML-DSS technique, a series of simulations were performed, and the results are inspected under varying aspects. The resultant values reported the improved performance of the PTML-DSS technique over the other techniques.
Application of Gradient Boosting Machine Learning Algorithms to Predict Uniaxial Compressive Strength of Soft Sedimentary Rocks at Thar Coalfield

The uniaxial compressive strength (UCS) of rock is one of the essential data in engineering planning and design. Correctly testing UCS of rock to ensure its accuracy and authenticity is a prerequisite for assuring the design of any rock engineering project. UCS of rock has a broad range of applications in mining, geotechnical, petroleum, geomechanics, and other fields of engineering. The application of the gradient boosting machine learning algorithms has been rarely used, especially for UCS prediction, and has performed well, based on the relevant literature of the study. In this study, four gradient boosting machine learning algorithms, namely, gradient boosted regression (GBR), Catboost, light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost), were developed to predict the UCS in MPa of soft sedimentary rocks of the Block-IX at Thar Coalfield, Pakistan, using four input variables such as wet density (ρw) in g/cm3; moisture in %; dry density (ρd) in g/cm3; and Brazilian tensile strength (BTS) in MPa. Then, 106-point dataset was allocated identically for each algorithm into 70% for the training phase and 30% for the testing phase. According to the results, the XGBoost algorithm outperformed the GBR, Catboost, and LightGBM with coefficient of correlation (R2) = 0.99, mean absolute error (MAE) = 0.00062, mean square error (MSE) = 0.0000006, and root mean square error (RMSE) = 0.00079 in the training phase and R2 = 0.99, MAE = 0.00054, MSE = 0.0000005, and RMSE = 0.00069 in the testing phase. The sensitivity analysis showed that BTS and ρw are positively correlated, and the moisture and ρd are negatively correlated with the UCS. Therefore, in this study, the XGBoost algorithm was shown to be the most accurate algorithm among all the investigated four algorithms for UCS prediction of soft sedimentary rocks of the Block-IX at Thar Coalfield, Pakistan.
Prediction of Shield Machine Attitude Based on Various Artificial Intelligence Technologies

The shield machine attitude (SMA) is the most important parameter in the process of tunnel construction. To prevent the shield machine from deviating from the design axis (DTA) of the tunnel, it is of great significance to accurately predict the dynamic characteristics of SMA. We establish eight SMA prediction models based on the data of five earth pressure balance (EPB) shield machines. The algorithms adopted in the models are four machine learning (ML) algorithms (KNN, SVR, RF, AdaBoost) and four deep learning (DL) algorithms (BPNN, CNN, LSTM, GRU). This paper obtains the hyperparameters of the models by utilizing grid search and K-fold cross-validation techniques and uses EVS and RMSE to verify and evaluate the prediction performances of the models. The prediction results reveal that the two best algorithms are the LSTM and GRU with EVS > 0.98 and RMSE < 1.5. Then, integrating ML algorithms and DL algorithms, we design a warning predictor for SMA. Through the historical 5-cycle data, the predictor can give a warning in advance if the SMA deviates significantly from DTA. This study indicates that AI technologies have considerable promise in the field of SMA dynamic prediction.
Oxidative Stability, Carcass Traits, and Muscle Fatty Acid and Amino Acid Profiles in Heat-Stressed Broiler Chickens

The objective was to elucidate the effects of chronic heat stress on carcass traits, muscle oxidative stability, muscle fatty acids and amino acid profiles in broiler chickens. A total of 100-day-old male Ross broiler chicks were divided into two equal groups of five replicates. The control group (TN) was maintained on a thermoneutral condition, while the experimental group (HS) was subjected to 8 h of heat stress (34 °C). The HS group showed lower dressing percentage and breast yield compared with the TN group (p = 0.040 and 0.042, respectively). Meanwhile, heat stress significantly increased the percentage of abdominal fat in broiler chickens (p = 0.001). The HS group showed significantly lower levels of PUFA (linoleic, docosahexaenoic and eicosapentaenoic) in the breast (p = 0.003, 0.002 and 0.001, respectively) and thigh (p = 0.001, 0.009 and 0.003, respectively) muscles than did the TN group. The levels of α-lenolinec acid in the breast and thigh muscles did not differ between both experimental groups (p = 0.818 and 0.060, respectively). With exception of threonine, tyrosine and phenylalanine, the levels of essential AA in the breast muscles were significantly (p ˂ 0.05) reduced in the HS group. The HS group showed significantly higher concentration of malondialdehyde (MDA) in the breast muscles (p = 0.032). Meanwhile, the concentration of MDA in the thigh muscles did not differ between both experimental groups (p = 0.149). Furthermore, the HS group showed significantly lower superoxide dismutase and catalase in heart tissues (p = 0.005 and 0.001, respectively). In conclusion, chronic thermal stress deteriorates carcass yield and the oxidative stability of breast muscles, as well as the levels of PUFA and essential AA in broiler chickens. However, the oxidative stability of thigh muscles was not affected.
Nonlinear Nonlocal Algorithm for Video Filtering

Video sequences are frequently contaminated by noise throughout the acquisition process, resulting in considerable degradation of video display quality. In this paper, we present a novel method of video fi ltering. The proposed fi lter is developed from an optimization problem in which a Bayesian term and a noisy video sequence prior distribution are combined. The method begins by segmenting the video sequence into space-time blocks and then substituting each noisy block by a weighted average of non-local neighbor blocks. Gradient-based weights are used to dynamically adjust the edge preservation and smoothness of the reference block. The obtained formulation enables nonlinear fi ltering and, hence, preserving key features such as edges and corners while using the intrinsic Bayesian fi ltering framework. Experiments on diff erent video sequences with varying degrees of noise show that the proposed method performs better than state-of-the-art video fi ltering approaches.