Miracle-dz/UniFAR-FTUs huggingface dataset:
Halal blockchain: Bibliometric analysis for mapping research

Purpose – The main purpose of this study is to identify patterns and directions of halal blockchain research and find out the development of halal blockchain research trends.Methodology – This study used data from various articles in the Google Scholar database with the publication year limited from 2011 to 2022. Data collection used Harzing's Publish or Perish software. There were 353 articles that matched the keyword and they were processed by bibliometric analysis. Findings – This study found the basic pattern in halal blockchain research, trends in halal blockchain research, the relationship among research, research gaps, researchers who research a lot on halal Blockchain and the most published publications.Implications – This study contributes an overview of bibliometric studies in the halal blockchain literature, which can widen the previous literature and show more focused study topics by examining the abstracts and content of published articles. Findings related to evaluative and relational techniques can be helpful information for researchers, especially those new to this field of study. This bibliometric approach can be invaluable, especially for graduate students in supply chain management, logistics management, and industrial engineering.Originality – The originality offered by this research is to process research documents based on halal blockchain journals on Google Scholar. Thus, a lot of information and knowledge about halal Blockchain over the last 10th years can be useful for further research.
E4orf1 Prevents Progression of Fatty Liver Disease in Mice on High Fat Diet

Non-alcoholic fatty liver disease (NAFLD) covers a broad spectrum of liver diseases ranging from steatosis to cirrhosis. There are limited data on prevention of hepatic steatosis or its progression to liver disease. Here, we tested if either transgenic (Tg) doxycycline-induced expression in adipose tissue of E4orf1 (E4), an adenoviral protein, or dietary fat restriction attenuated hepatic steatosis or its progression in mice. Twelve to fourteen-week-old TgE4 mice (E4 group) and control mice were exposed to a 60% (Kcal) high fat diet (HFD) for 20 weeks, while another group of mice on HFD for 10 weeks were switched to a chow diet (chow group) for another 10 weeks. Glycemic control was determined at weeks 10 and 20. Tissues were collected for gene and protein analysis at sacrifice. Compared to control, diet reversal significantly reduced body weight in the chow group, whereas E4 expression attenuated weight gain, despite HFD. E4 mice evinced significantly improved glucose clearance, lower endogenous insulin secretion, reduced serum triglycerides, attenuated hepatic steatosis and inflammation. Interestingly, in spite of weight loss and lower liver fat, chow mice showed significant upregulation of hepatic genes involved in lipid metabolism. Despite HFD, E4 prevents hepatic lipid accumulation and progression of hepatic steatosis, while diet reversal maintains hepatic health, but is unable to improve molecular changes.
Determining the Amount of Iodine in Edible Salts Obtained from Markets and District Bazaars in İstanbul

Objective: Iodine is an element that is rarely found in water and soil in nature. Iodine is a component of thyroid gland hormones and is an essential element for human life. Iodine deficiency disease (IDD) is an important public health problem all over the world, which occurs as a result of iodine deficiency. Visible symptoms of iodine deficiency are defined as goiter. On the other hand, excessive intake of iodine into the body may disrupt thyroid hormone secretion and result in iodine deficiency. Methods: In this study, the iodine amounts of 26 edible salt samples collected from markets and district bazaars in Istanbul were analyzed according to the method “Determination of Iodine in Iodized Salts with Iodized Ion” in TS 933 Edible Salt Standard, and the compliance of salts sold in the market with the Turkish Food Codex Salt Communiqué was investigated. Results: Thirteen of 26 salt samples were appropriate at the level of 28.0-39.8 mg/kg (50%), high at the level of 44.0-52.9 mg/kg (27%) in 7 samples and low at the level of 2.0-20.0 (23%) in 6 samples have been found. Conclusion: It has been determined that the amount of iodine in 50% of the salt samples was not appropriate. Iodine deficiency detected in salts in the market increases the risk of IDD, and excess iodine increases the risk of goiter. In this case, it is important that the sustainability of food control and inspection by administrative authorities is effective for the protection of public health.
Learning-Based Sparse Recovery for Joint Activity Detection and Channel Estimation in Massive Random Access Systems

We consider the problem of joint activity detection and channel estimation in massive random access. When the receiver has multiple antennas, this is a joint sparse recovery problem with multiple measurement vectors (MMV). For the general setting where the channels could be correlated across antennas, we first develop a modified minimum mean squared error (MMSE) shrinkage function to be used in the Trainable Iterative Soft Thresholding Algorithm (TISTA). Then, we learn this MMSE shrinkage function using a model-based neural network. In the simulation results, the proposed learning-based method, L-MMSE-MMV-TISTA, offers a 30-40% reduction in preamble length requirement compared to TISTA. We also compare L-MMSE-MMV-TISTA with the state-of-the-art MMV sparse Bayesian learning (M-SBL) method. While M-SBL can provide better performance at the cost of higher complexity in highly measurement-constrained settings, LMMSE-MMV-TISTA provides a significant complexity advantage when only a slightly larger number of measurements are available.
Impact of Employee Perception Shaped by Despotic Leadership on the Job Performance of Employees: Investigating the Mediating Role of Work Engagement and the Moderating Role of Social Climate of Friendship Groups

The effect of employee perception of despotic leadership on employee job performance is an active area of research. The current study used the conservation of resource (COR) theory to investigate the mediating impact of employee work engagement and the moderating role of social climate of friendship groups. For this purpose, a proportionate sampling technique was used. Data was collected from 423 employees of pharmaceutical companies listed on Pakistan Stock Exchange (PSX) by utilizing a dyad approach with predictors (self-reports) and employees’ performance (supervisor-reports). The hypotheses were tested through Hayes Process (2012) and regression analysis. The study results showed that employee perception of despotic leadership is inversely associated with employee job performance and work engagement. Furthermore, this study identified that the impact of this association decreases under the conditions created by the social climate of strong friendship groups. This research explores this broad area and adds to the body of knowledge on dark leadership. The findings of the study have significance for both theory and organizational practice.
Packet Classification with Segregated Cross-Producting

Packet classification, which performs multidimensional point location upon fields in packet headers, is the key technology for enabling software-defined networking (SDN). It categorizes incoming packets into multiple forwarding classes based on pre-defined rules. This categorization also enables quality of service or network security. In this work, we propose an algorithm, Segregated Cross-producting, to improve the scalability of cross-producting in term of storage. The performance of our scheme was evaluated with rule sets of varying sizes and characteristics. The experimental results show that our scheme achieves good and stable performance in terms of speed and space.
Analysis of Floral Organ Development and Sex Determination in Schisandra chinensis by Scanning Electron Microscopy and RNA-Sequencing

S. chinensis is a typical monoecious plant, and the number and development of female flowers determines the yield of S. chinensis. Due to a lack of genetic information, the molecular mechanism of sex differentiation in S. chinensis remains unclear. In this study, the combination of scanning electron microscopy (SEM) and RNA sequencing (RNA-seq) was used to understand the way of sex differentiation of S. chinensis and to mine the related genes of sex determination. The result shows the development of male and female S. chinensis flowers was completed at the same time, the unisexual S. chinensis flowers did not undergo a transition stage between sexes, and sex may have been determined at an early stage in flower development. The results of the gene function analysis of the plant hormone signaling pathway and sucrose metabolism pathway suggest that auxin and JA could be the key hormones for sex differentiation in S. chinensis, and sucrose may promote pollen maturation at the later stage of male flower development. Two AGAMOUS (GAG) genes, 10 AGAMOUS-like MADS-box (AGLs) genes, and the MYB, NAC, WRKY, bHLH, and Trihelix transcription factor families may play important roles in sex determination in S. chinensis. Taken together, the present findings provide valuable genetic information on flower development and sex determination in S. chinensis.
Efficient Clustering of Genetic Entities

The paper proposes a novel application of a highly efficient method for comparing symbol sequences based on convolution. The technique utilizes Fast Fourier Transform (FFT) to compare long symbol sequences achieving practical results using commodity PC hardware. While the main focus is on bioinformatics, the proposed approach is general and can work beyond genetic sequences. One of the main advantages of the proposed method is the robustness to insertion/deletion. Also, unlike standard alignment algorithms, the proposed method is parameter-free. The paper shows that the FFT-based comparison allows for efficient clustering of long sequences in bioinformatics as a practical application. Exploration of coronaviruses offers an illustration of the proposed clustering techniques.
F-TPE: Flexible Thumbnail-Preserving Encryption Based on Multi-Pixel Sum-Preserving Encryption

People are accustomed to utilizing mobile phones to capture images and uploading them to the cloud due to various incomparable advantages such as saving the storage space on the device. In this context, privacy concerns are raised since images may contain some sensitive information. Encrypting images by traditional schemes can alleviate privacy leak, but the usability is often deprived since it is tough to browse them on the cloud. Recently, Tajik et al. proposed an ideal thumbnail-preserving encryption (TPE) scheme to achieve the balance of usability and privacy by leveraging a two-pixel substitution encryption method while the Markov chain is utilized to prove the security. However, the connectivity of Markov chain in this scheme is weak since the length of pixel groups in the encryption process is only two, leading to a long mixing time of achieving the stationary distribution of Markov chain. To this end, we firstly propose a method of multi-pixel sum-preserving encryption (MP-SPE) that realizes the encipherment of vectors of arbitrary length. Then, with the help of MP-SPE, a novel flexible ideal TPE scheme (F-TPE) is designed and the connection of Markov chain is improved. The experiments have demonstrated that the proposed scheme can effectively attain the balance between usability and privacy. In addition, F-TPE takes much less time in encrypting compared with the existing work.
Computational fluid dynamics of gassed-stirred fermenters

The current understanding of the transport phenomena involved in the operation of industrial fermenters is not sufficient. This is reflected by the limitations seen in their design and operation. A better insight in the local processes taking place (hydrodynamics, gas dispersion, mixing, microbial kinetics) is required to be able to make a step change in the design of those reactors. At the scale of industrially relevant fermenters, experimental methods become quickly limited when detailed information is needed. It was the aim of this research to provide a framework where such information could be gained by means of Computational Fluid Dynamics (CFD) simulations with a manageable computational burden so that it could readily be used by the industrial practitioners. The main focus of this thesis is on the hydrodynamics of bubbly flows in stirred reactors, although, scalar mixing and substrate uptake kinetics studies were also conducted. Because the literature on the standard configured lab/pilot scale single-impeller reactors is vast and the experimental data is abundant, we chose to start with such a system first and, with the learnings gained, moved ultimately to realistic industrial scale multi-impeller fermenters. We also limited ourselves to Rushton type radial pumping disk turbine systems, again on the basis of available data for validation, and also due to time limitations.
mRNA and Viral Vector COVID-19 Vaccines Do Not Affect Male Fertility: A Prospective Study

Purpose To assess whether mRNA and viral vector coronavirus disease 2019 (COVID-19) vaccines detrimentally affected semen parameters. Materials and Methods In this prospective study, we enrolled 101 men vaccinated for COVID-19 (76% received mRNA vaccines, 20% viral vector vaccines, 2% a mixed formulation, and for 2 men no information about vaccine xlink:type was available) in 2021 and with a previous semen analysis. For each man we compared semen parameters before and after vaccination. Results Post-vaccine samples were obtained at a median of 2.3±1.5 months after the second dose. After vaccination, the median sample volume significantly decreased (from 3.0 to 2.6 mL, p=0.036), whereas the median sperm concentration, the progressive motility, and total motile sperm count increased (from 25.0 to 43.0 million/mL, p<0.0001; from 50% to 56%, p=0.022; from 34.8 to 54.6 million, p<0.0001, respectively). Thirty-four patients were oligospermic before the vaccine, and also in these patients we observed a significant increase of sperm parameters after vaccine. Finally, we confirmed the aforementioned results in men who received a mRNA or a viral vector vaccine. Conclusions The semen parameters following COVID-19 vaccination did not reflect any causative detrimental effect from vaccination, and for the first time we demonstrated that this applies to both mRNA and viral-vector vaccines. The known individual variation in semen and the reduced abstinence time before the post-vaccine sample collection may explain the increases in sperm parameters.
Respiratory sinus arrhythmia moderates the interpersonal consequences of brooding rumination

Brooding rumination is an intrapersonal emotion regulation strategy associated with negative interpersonal consequences. Resting respiratory sinus arrhythmia (RSA), a psychophysiological marker of self-regulatory capacity, may buffer the association between maladaptive emotion regulation and negative interpersonal behaviors. The current work examines the moderating effect of RSA on the association between brooding rumination and different negative interpersonal consequences. Across three convenience samples, individuals with lower RSA showed a stronger association between brooding rumination and more negative interpersonal behaviors as well as less perception of received instrumental social support (Study 1; n = 154), higher levels of interviewer-rated interpersonal stress (Study 2; n = 42) and a stronger indirect association between brooding rumination and depressive symptoms via daily interpersonal stress (Study 3; n = 222). These findings highlight the negative interpersonal consequences of brooding rumination, particularly among individuals with lower RSA.
Virtual teaching assistants: A survey of a novel teaching technology

This study centers around virtual teaching assistants (“VTA”) and the potential application of VTAs to reduce the burden on teachers across secondary schools in China exacerbated by the Double Reduction Policy. It seeks to understand how VTAs could be implemented in the classroom while ensuring student and teacher well-being, success, and happiness. Through interviews with fourteen different experts spanning industry, academia, and education, combined with extensive review of the existing literature and ecosystem of VTAs, research shows that VTAs are potentially a major aid in the context of exam review, after school tutoring, automated grading, and student performance reporting. However, they need to be created carefully with an attentive eye towards student support to ensure that the learning experience is not diminished. It must be clearly communicated to all stakeholders that the goal of a VTA is not to replace teachers, but rather to support them such that they can spend more time with students and less time on mundane tasks.
Intelligent computational design of scalene-faceted flat-foldable tessellations

Origami tessellations can be folded from a given planar pattern into a three-dimensional object with specific geometric properties, inspiring developments in various fields of science and engineering such as deployable structures, energy absorption devices, reconfigurable robots, and metamaterials. However, the range of existing origami patterns with functional properties such as flat-foldability is rather scant, as analytical solutions to constraint equations arising in the design process are generally highly complicated. In this paper, we tackle the challenging problem of automated design of scalene-faceted flat-foldable origami tessellations using an efficient metaheuristic algorithm. To this end, this study establishes constraint curves based on compatibility conditions for all six-fold (i.e. degree-6) vertices. Subsequently, a graphical method and a particle swarm optimization (PSO) method are adopted to produce optimal origami patterns. Moreover, mountain-valley assignments for the obtained geometric designs are determined using a computational approach based on mixed-integer linear programming (MILP). It turns out that the flat-foldable internal vertices of each C2-symmetric unit fragment (UF) exist as C2-symmetric pairs about the centroid of the UF. Furthermore, numerical experiments are carried out to examine the feasibility and compare the accuracy, computational efficiency, and global convergence of the proposed methods. The results of numerical experiments demonstrated that, in comparison with the graphical method, the proposed PSO method has not only a higher accuracy but also a significantly lower computational cost, enabling us to develop an intelligent computational platform to efficiently design scalene-faceted flat-foldable origami tessellations.
Effect of Nano Zinc Oxide and Traditional Zinc (Oxide and Sulphate) Sources on Performance, Bone Characteristics and Physiological Parameters of Broiler Chicks

Zinc is one of the most importance trace minerals in poultry nutrition. Therefore, the objective of this study is to investigate the influence of nano zinc oxide (green and chemical) and traditional zinc (Oxide and Sulphate) on broiler performance, bone characteristics and some biochemical parameters from 1-35 day of age. A total of 240 a-day-old male chicks (Arbor Acres) were assigned at random into 4 treatments. Treatments 1 and 2 contained zinc in traditional form as zinc oxide (ZnO) and zinc sulphate (Zn SO4) and treatments 3 and 4 contain zinc in nano form; green synthesized zinc oxide nanoparticles (GZnO NPs) and chemically synthesized zinc oxide nanoparticles (CZnO NPs); respectively. The results showed that the birds fed diet treated with nano-Zn sources (GZnO NPs and CZnO NPs) showed the best results (P<0.01) in weight gain and feed conversion ratio. There were no statistical differences between the two sources of zinc in the traditional form as well as between the two sources of zinc in the nano form. In addition, chicks fed nano zinc sources gave the best values in bone mineral density and bone mineral concentration compared to those fed traditional sources of zinc. These results reflect the values obtained for tibia length, width, breaking strength and ash since the dietary GZnO NPs and CZnO NPs were recorded for the highest values compared with the other traditional form. Non-significant differences were detected in the metabolic hormones (T3, T4) levels and their ratio T3/T4 among different dietary treatments. The results of the liver function (ALT, AST and albumin), the kidney function (creatinine) and alkaline phosphatase were within the normal range in all treatments. From the current results it can be suggested that using zinc in nano form instead of traditional form enhances performance and bone parameters of broiler chicks.
Gene Correlation Network Analysis to Identify Biomarkers of Peri-Implantitis

Background and Objectives: The histopathological and clinical conditions for transforming peri-implant mucositis into peri-implantitis (PI) are not fully clarified. We aim to uncover molecular mechanisms and new potential biomarkers of PI. Materials and Methods: Raw GSE33774 and GSE57631 datasets were obtained from the Gene Expression Omnibus (GEO) database. The linear models for microarray data (LIMMA) package in R software completes differentially expressed genes (DEGs). We conducted a weighted gene co-expression network analysis (WGCNA) on the top 25% of altered genes and identified the key modules associated with the clinical features of PI. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the R software. We constructed a protein–protein interaction (PPI) network through the STRING database. After that we used Cytohubba plug-ins of Cytoscape to screen out the potential hub genes, which were subsequently verified via receiver operating characteristic (ROC) curves in another dataset, GSE178351, and revalidation of genes through the DisGeNET database. Results: We discovered 632 DEGs (570 upregulated genes and 62 downregulated genes). A total of eight modules were screened by WGCNA, among which the turquoise module was most correlated with PI. The Cytohubba plug-ins were used for filtering hub genes, which are highly linked with PI development, from the candidate genes in the protein–protein interaction (PPI) network. Conclusions: We found five key genes from PI using WGCNA. Among them, ICAM1, CXCL1, and JUN are worthy of further study of new target genes, providing the theoretical basis for further exploration of the occurrence and development mechanism of PI.
Grey wolf optimizer-based machine learning algorithm to predict electric vehicle charging duration time

ABSTRACT Precise charging time prediction can effectively mitigate the inconvenience to drivers induced by inevitable charging behavior throughout trips. Although the effectiveness of the machine learning (ML) algorithm in predicting future outcomes has been established in a variety of applications (transportation sector), the investigation into electric vehicle (EV) charging time prediction is almost new. This calls for the investigation of the ML algorithm to predict EV charging time. The study developed an EV charging time prediction model based on two years of charging event data collected from 500 EVs in Japan. To predict EV charging time, this paper employed three ML algorithms: extreme learning machine (ELM), feed-forward neural network (FFNN), and support vector regression (SVR). Furthermore, ML algorithms parameters are optimized by a metaheuristic techniques: the gray wolf optimizer (GWO), particle swarm optimizer (PSO), and genetic algorithm (GA) to achieve higher accuracy and robustness. The prediction results reveal that GWO-based ML models yielded better results compared to other models.