Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dual-Band Filtering 4 × 4 Butler Matrix Based on SLR

In this letter, a dual-band filtering 4×4 Butler matrix (DB-F-BM) based on a stub-loaded resonator (SLR) is proposed, operating at 12 and 17 GHz. The dual-band filtering (DB-F) 180° hybrid coupler can provide power allocation, phase shifting, and frequency selection at both frequencies. Each operating band reveals a second-order bandpass filtering response. This hybrid coupler is designed based on SLR and exploits different electromagnetic coupling to realize desired phase characteristics. A DB-F-BM was built, using DB-F 180° hybrid coupler, wideband 90° coupler, and phase shifter. The DB-F 180° hybrid coupler and DB-F-BM are fabricated and measured. The measured results are in good agreement with the theoretical ones. The lower and higher frequency bandwidth of DB-F-BM is approximately 8% and 3%, respectively. It also exhibits good out-of-band suppression. Furthermore, the DB-F-BM is applied to construct a 1 × 4 antenna array and verified the designed concepts and beamforming performance.
Role of the Editor in Limiting Plagiarism or Similarity in Scholarly Journal Manuscripts

This brief communication is the outcome of the prevailing confusion and the role of editors of several prestigious journals published in India in different disciplines of science and social science including the discipline of library and information science. These journals use different Plagiarism Detection Tools (PDTs) or Plagiarism Detection Software (PDS) to assess the similarity score of the submitted manuscript. These PDTs are helpful to avoid questions raised on the academic integrity of the submitted manuscript. For every submission, the editor of the journal generates a similarity report and communicates the results of the similarity index to the scholars verbatim. It is not judicious for the editor of the journal to simply rely on the percentage of similarity index suggested by the PDT. Human intervention is required to rule out the facts by a thorough inspection of every single matching. Also, an acceptable percentage of similarity for a manuscript needs a critical analysis. Based on the set guidelines of the academic regulatory bodies, an acceptable percentage of similarity for a manuscript is considered as minor or level 0 if it is 10%. The present communication draws attention towards this malice as a lot of time of the author/scholar is devoted to incorporate small changes which do not serve any useful purpose to the manuscript and the journal.
Shifting from climate change denial to acceptance: a mixed-method, semester long case study in an undergraduate first-year experience course

Abstract Climate change denial is often treated as a binary opinion. However, an individual can express acceptance of climate change, while still denying other aspects of the field such as its causation by humans, impacts, or our ability to mitigate these impacts. Here, we conduct a semester long survey and discourse analysis of a class of first-year undergraduates as they complete a course on climate change to assess changes in their attitudes on climate denial verse acceptance across these more specific factors. Our results suggest that acceptance of the scientific facts about climate change is higher than acceptance of its impacts and solutions. However, acceptance that personal and societal changes can mitigate climate change increased throughout the term. These results can help create course curriculum with more effectively targeted content to assist in shifting perspectives on climate change in young undergraduates.
Modelling the barriers of Indian pharmaceutical supply chain using fuzzy AHP

Due to the profound discrepancy in the developing country's production, which possibly affects the quality of producing medicine, harms patient's health. The pharmaceutical supply chain has been challenged by the barriers especially in the context of developing nations like India. The identification of barriers is desired to enhance the performance of the industry. This study identifies 28 barriers under six major criteria of Indian PSC through relevant literature and expert's opinions. This paper proposes a hybrid model based on fuzzy AHP to prioritised rank barriers in PSC. This approach is best for analysing experts' judgments and uncertainty involved in the process of prioritisation. The findings and framework developed could be used by the drug industry, which helps them to destroy barriers to addressing sustainability and quality manufacturing. The results indicate that market-related barriers are the most important for Indian PSC. Further sensitivity analysis is performed to test the robustness of the proposed approach.
Recent advances of mussel-inspired materials in osteoarthritis therapy

Osteoarthritis (OA) is a common chronic joint disease that significantly affects the quality of life and can lead to disability. Oral and intra-articular administration are the main clinical treatments used to alleviate inflammation and pain. However, the therapeutic efficiency of these approaches is limited by burst drug release, poor retention time, and undesirable toxic effects. In recent years, mussel-inspired materials with strong interfacial adhesiveness have been considered as promising candidates for the treatment of OA. These materials can act as delivery platforms to enhance drug availability; moreover, they display multiple non-pharmacological pathways that alleviate OA. In this review, we introduce the pathological features of OA, summarize the fabrication methods for mussel-inspired materials, and highlight their superiority in response to recent therapeutic strategies for OA.
A Novel Approach to Assessing and Conservatively Treating Anterior Cutaneous Nerve Entrapment Syndrome: A Case Study

Anterior cutaneous nerve entrapment syndrome (ACNES) is a common source of chronic abdominal pain and is often underdiagnosed despite numerous and potentially invasive diagnostic evaluations and tests. We present a case report describing a novel, conservative, and non-invasive approach to diagnose and treat recurrent ACNES in a young and active patient. We describe a treatment-based diagnostic approach to confirm potential ACNES pain generators while recording pre- and post-treatment pain scores. After each maneuver, the patient was reassessed which allowed the working diagnosis to clinically evolve demonstrating the pathologic interrelationship between different skeletal structures and myofascial tissues contributing to irritation of the anterior cutaneous nerve. This treatment-based technique also made it possible to identify referred pain from a condition with overlapping symptoms originating from a different anatomic site. Treatment consisted of sequenced osteopathic manipulation techniques, active release techniques, instrument-assisted soft tissue mobilization, directional cupping, stretching, and strengthening exercises. The combination of sequenced treatments over the course of six physical therapy visits spanning 10 weeks resulted in 100% pain reduction and complete resolution of functional limitations. The patient was able to complete all work requirements and physical activity without pain. A sequenced treatment-based diagnostic approach to this case allowed us to more accurately identify all involved anatomic regions of pain and anatomic segments of pathology that were contributing to the abdominal pain or referring pain. No diagnostic imaging, invasive test, or injection was needed to properly diagnose and treat this case of ACNES. A proper understanding and application of osteopathic manipulation, active release techniques, instrument-assisted soft tissue mobilization, cupping, and exercises successfully resolved the contributing pain conditions and provided the patient important and useful tools and strategies to prevent recurrence.
TaSPL17s act redundantly with TaSPL14s to control spike development and their elite haplotypes may improve wheat grain yield

Wheat is a staple crop for the world’s population, and there is constant pressure to improve grain yield, which is largely determined by plant architecture. SQUAMOSA promotor-binding protein-like (SPL) genes have been widely studied in rice, including their effects on plant architecture, grain development, and grain yield. However, the function of SPL homologous genes in wheat has not been well investigated. In this study, TaSPL14s and TaSPL17s, wheat’s closest orthologous of OsSPL14, were functionally investigated using gene-editing assays, revealing that these genes redundantly influence plant height, tiller number, spike length, and thousand-grain weight (TGW). Bract outgrowth was frequently observed in the hexa-mutant, occasionally in the quintuple mutant but never in the wild type. Transcriptome analysis revealed that the expression of many spike development-associated genes was altered in taspl14taspl17 hexa-mutants compared to that in the wild type. In addition, we analyzed the sequence polymorphisms of TaSPL14s and TaSPL17s among wheat germplasm and found superior haplotypes of TaSPL17-A and TaSPL17-D with significantly higher TGW, which had been positively selected during wheat breeding. Accordingly, dCAPS and KASP markers were developed for TaSPL17-A and TaSPL17-D, respectively, providing a novel insight for molecular marker-assisted breeding in wheat. Overall, our results highlight the role of TaSPLs in regulating plant architecture and their potential application for wheat grain yield improvement through molecular breeding.
Abnormal Behavior Fish and Population Detection Method based on Deep Learning

This paper presents a detection model of fish with abnormal behavior and their number based on YOLO v8 and Deep Sort algorithm. The method firstly uses computer and acquisition system to monitor and analyze the fish behavior in real time, and can effectively detect the abnormal behavior of fish, such as abnormal swimming trajectory and abnormal residence time. The main work of this paper is to preprocess fish behavior videos, including video segmentation, data enhancement and other operations, and use data enhancement technology to improve the problem of fish occlusion in data set, which is easy to cause model false detection. Then, YOLO v8 and Deep Sort algorithm were used for multi-target tracking and target detection to extract the key information of fish behavior. Finally, through the analysis and comparison of the extracted information, the detection of fish with abnormal behavior and its quantity are realized. The experimental results show that the method proposed in this paper can effectively detect the abnormal behavior of fish, has high accuracy and real-time, and has certain application and popularization value.
Otsu Multi-Threshold Image Segmentation Based on Adaptive Double-Mutation Differential Evolution

A quick and effective way of segmenting images is the Otsu threshold method. However, the complexity of time grows exponentially as the number of thresolds rises. The aim of this study is to address the issues with the standard threshold image segmentation method’s low segmentation effect and high time complexity. The two mutations differential evolution based on adaptive control parameters is presented, and the twofold mutation approach and adaptive control parameter search mechanism are used. Superior double-mutation differential evolution views Otsu threshold picture segmentation as an optimization issue, uses the maximum interclass variance technique as the objective function, determines the ideal threshold, and then implements multi-threshold image segmentation. The experimental findings demonstrate the robustness of the enhanced double-mutation differential evolution with adaptive control parameters. Compared to other benchmark algorithms, our algorithm excels in both image segmentation accuracy and time complexity, offering superior performance.
Improved conversational recommender system based on dialog context

Conversational recommender system (CRS) needs to be seamlessly integrated between the two modules of recommendation and dialog, aiming to recommend high-quality items to users through multiple rounds of interactive dialogs. Items can typically refer to goods, movies, news, etc. Through this form of interactive dialog, users can express their preferences in real time, and the system can fully understand the user’s thoughts and recommend corresponding items. Although mainstream dialog recommendation systems have improved the performance to some extent, there are still some key issues, such as insufficient consideration of the entity’s order in the dialog, the different contributions of items in the dialog history, and the low diversity of generated responses. To address these shortcomings, we propose an improved dialog context model based on time-series features. Firstly, we augment the semantic representation of words and items using two external knowledge graphs and align the semantic space using mutual information maximization techniques. Secondly, we add a retrieval model to the dialog recommendation system to provide auxiliary information for generating replies. We then utilize a deep timing network to serialize the dialog content and more accurately learn the feature relationship between users and items for recommendation. In this paper, the dialog recommendation system is divided into two components, and different evaluation indicators are used to evaluate the performance of the dialog component and the recommendation component. Experimental results on widely used benchmarks show that the proposed method is effective.
Groupwise structural sparsity for discriminative voxels identification

This paper investigates the selection of voxels for functional Magnetic Resonance Imaging (fMRI) brain data. We aim to identify a comprehensive set of discriminative voxels associated with human learning when exposed to a neutral visual stimulus that predicts an aversive outcome. However, due to the nature of the unconditioned stimuli (typically a noxious stimulus), it is challenging to obtain sufficient sample sizes for psychological experiments, given the tolerability of the subjects and ethical considerations. We propose a stable hierarchical voting (SHV) mechanism based on stability selection to address this challenge. This mechanism enables us to evaluate the quality of spatial random sampling and minimizes the risk of false and missed detections. We assess the performance of the proposed algorithm using simulated and publicly available datasets. The experiments demonstrate that the regularization strategy choice significantly affects the results' interpretability. When applying our algorithm to our collected fMRI dataset, it successfully identifies sparse and closely related patterns across subjects and displays stable weight maps for three experimental phases under the fear conditioning paradigm. These findings strongly support the causal role of aversive conditioning in altering visual-cortical activity.
Studies on the complex Warnowiaceae (Dinophyceae) I. Lohmann’s Pouchetia parva refound and renamed Nematodinium parvum comb. nov. (= Warnowia parva)

ABSTRACT The dinoflagellate family Warnowiaceae has often been considered to include some of the most complex cells among the protists. The number of described species is around 40, but both the species and generic concepts are in need of revision. Warnowiaceans are often fragile and readily change morphology under the light microscope, and they are usually regarded to be rare. They are particularly famous for the eye-like structures, termed ocelloids. Studies on warnowiaceans are hampered by lack of cultures, and our studies are therefore based on cells obtained directly from field samples. We provide a description of Nematodinium parvum comb. nov. (syn. Pouchetia parva, Warnowia parva), based on light, scanning and transmission electron microscopy, combined with phylogenetic analyses of ribosomal genes. It was described in 1908 by Lohmann from Kieler Bay, but is often common in Danish waters, allowing observations on distribution and behaviour. Crucial conditions for finding high cell abundances were periods of warm temperatures and a calm sea. Cells were yellowish, photosynthetic, and contained a net-like chloroplast, in addition to an ocelloid, trichocysts and harpoon-like nematocysts. They divided asexually but planozygotes were also seen. Following the demonstration of nematocysts, the species, which has been known as Warnowia parva since 1928, is transferred to Nematodinium. The finding of a peduncle indicates mixotrophy but all feeding experiments failed to identify a suitable prey. The phylogenetic analyses based on single-cell PCR and sequence determinations of small and large subunit rDNA confirmed that the systematics of Nematodinium and Warnowia is in a state of flux.
Heart Failure Burden in Oman as a Mid-East Exemplar Versus Global Perspectives: An Integrative Review

Heart failure (HF), a clinical syndrome caused by a structural and functional cardiac abnormality and corroborated by elevated natriuretic peptide levels and pulmonary congestion. This study intends to investigate the state of heart failure (HF) in Oman and assess it in comparison of global trends. Ten published literatures from the past 20 years were included after a thorough search of databases (Arab World Research Source, EBSCOhost, Medline, and Google Scholar). These studies were reviewed considering the global literature. We have observed an increase in HF cases especially in older adults, over the past two decades in Oman. Acute coronary syndrome and non-compliance with medication are two factors that contribute to acute HF, according to recent research. Ischemic heart disease is the leading cause of HF in the Omani population. The mortality rate for HF patients in Oman was reported to be 25% after a one-year follow-up. The younger population that is diagnosed with HF in Oman is significantly worse than in other nations, according to these data, which are consistent with global trends. The lack of published studies and data sets hampered our understanding of heart failure (HF); yet prevalence of HF is rising and is anticipated to surge with the rise in diabetes mellitus and hypertension and other related cardiovascular precursors. Therefore, HF requires more investigation. In terms of worldwide trends, HF in Oman appears to be even worse; additional information is required to grasp the full picture on HF.
The Calculation of Roughness Uncertainty by Fitting B-Spline Filter Assessment Middle Lines

The roughness and uncertainty are important parameters of surface morphology. The least square middle line method is often used to estimate the roughness and its uncertainty. However, the roughness and its uncertainty obtained by the least square middle line method are inaccurate. This paper proposes a method to calculate exactly the roughness and its uncertainty by piecewise fitting the smooth B-spline filter assessment middle lines. A B-spline smoothing filter is selected to determine the assessment middle line of roughness. The B-spline filter can not only give the accurate roughness, but also obtain the smooth assessment middle line. The model of roughness uncertainty is proposed by piecewise fitting B-spline filter middle lines as the quadratic curves. The S-shaped test part is used to verify the model of roughness uncertainty.
Variation of Helicoverpa armigera symbionts across developmental stages and geographic locations

Cotton bollworm (Helicoverpa armigera) poses a global problem, causing substantial economic and ecological losses. Endosymbionts in insects play crucial roles in multiple insect biological processes. However, the interactions between H. armigera and its symbionts have not been well characterized to date. We investigated the symbionts of H. armigera in the whole life cycle from different geographical locations. In the whole life cycle of H. armigera, Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria were the dominant bacteria at the phylum level, while Enterococcus, Enterobacter, Glutamicibacter, and Bacillus were the four dominant bacteria at the genus level. Furthermore, high similarity in symbiotic bacterial community was observed in different stages of H. armigera, which were dominated by Enterococcus and Enterobacter. In fields, the dominant bacteria were Proteobacteria and Bacteroidetes, whereas, in the laboratory, the dominant bacteria were Proteobacteria. At the genus level, the dominant bacteria in cotton bollworm eggs of wild populations were Enterobacter, Morganella, Lactococcus, Asaia, Apibacter, and Enterococcus, and the subdominant bacteria were Bartonella, Pseudomonas, and Orbus. Moreover, the symbionts varied with geographical locations, and the closer the geographical distance, the more similar the microbial composition. Taken together, our study identifies and compares the symbiont variation along with geographical gradients and host development dynamic and reveals the high flexibility of microbiome communities in H. armigera, which probably benefits for the successful survival in a complicated changing environment.
Frequency-Selective Surfaces With Quasielliptic Bandpass Response for Filtering FRA Application

This work proposes an asymmetric antenna–filter–antenna (AFA)-based frequency-selective surface (FSS) with quasielliptic bandpass response and polarization selectivity. According to the reciprocity theorem, radiation nulls of antennas can be used to introduce transmission zeros (TZs) of AFA-based FSSs. The proposed FSS consists of two patch antennas with different slots, a ground, and a metalized via connecting two patch antennas. The antenna’s radiation nulls are generated by slots embedded in the patches, which act as a notch band and can be used to modulate the FSS frequency response with two TZs by varying the length of slots. The high-frequency selectivity performance of FSSs can be achieved without additional circuits or multilayer structures. For a potential application, we design a filtering folded reflectarray (FRA) by using the proposed FSS as its subreflectarray. The filtering characteristic of the proposed FRA, with steeper frequency response and flat gain in the passband, can be obtained. A prototype of filtering FRA is fabricated and measured. Good agreement is obtained between simulated and measured results.
Exploring the determinants of FinTech adoption and intention to use in Jordan: The impact of COVID-19

Abstract This study explores FinTech adoption in Jordan during and post-COVID-19 pandemic by integrating and extending the TAM and UTAUT theories to predict behavioral intention to use FinTech. Six predictors were hypothesized to test their impact on behavioral intention: perceived usefulness, perceived ease of use, social influence, personal innovativeness, financial risks, and privacy risks. while using COVID-19 lockdowns as a moderator. Using structural equation modeling (SEM) on a sample of 296 respondents, the data analysis results indicated that the proposed variables, including the predictors and the moderator, accounted for 38.4% of the variation in behavioral intention to use FinTech. Which clearly shows the important impact of COVID-19 on increasing the adoption of technologies and especially FinTech’s in the Jordanian context. The empirical findings revealed that perceived usefulness and personal innovativeness had the most significant impact on behavioral intention. In contrast, privacy risks had no significant impact on behavioral intention. Besides, this study empirically demonstrated the impact of COVID-19 lockdowns as a moderator. The impact of COVID-19 lockdowns significantly moderated the relationship between perceived usefulness, perceived ease of use, personal innovativeness, and financial risks with behavioral intention. The result of this study contributes to both theory and practice by adding to the existing literature on FinTech adoption using new determinants that might drive behavioral intention to use FinTech services.