Miracle-dz/UniFAR-FTUs huggingface dataset:
HighTech and

Businesses globally heavily invest in Enterprise Resource Planning (ERP) implementation to meet high customer demands and maintain competitiveness. Despite significant investments, underutilization hampers reaping the system's full benefits, leading to stagnant or adverse performance. Hence, this study aims to uncover reasons for the lack of end-user adoption of ERP systems. It focuses on the correlation between performance expectancy, effort expectancy, social influence, and organizational support in determining ERP system acceptance by end users. This study utilized a quantitative methodology. Data were collected from 392 respondents within a Malaysian shared service center. Multiple regression analysis was conducted employing the UTAUT model and perceived organizational support theory to evaluate and interpret the collected data. The study’s key findings include the significant positive association between performance expectancy and ERP system adoption, reinforcing the influence of effort expectancy on technology adoption. Despite its positive effects, social influence had little effect on end-user adoption. Additionally, it was observed that ERP system adoption was consistently facilitated by organizational support. This study confirms the essential factors that drive the adoption of ERP systems by end-users. It emphasizes the crucial role of leadership in prioritizing these elements for organizations to enhance user acceptance and ensure the successful implementation of ERP systems.
Insect Localization and Detection using Object Detection Techniques

In recent years, the precise localization and detection of insects within images have become increasingly imperative across various domains, including agriculture, entomology, and biodiversity monitoring. Traditional methods for insect identification have heavily relied on manual labor and intricate feature engineering, leading to sub-optimal performance and constrained scalability. Confronted with these formidable challenges, our research paper embarks on an exhaustive investigation into the application of cutting-edge object detection techniques for insect localization and detection. Our specific focus is directed towards the IP102 dataset, a comprehensive and widely acclaimed resource within the field of insect image analysis. The evolution of object detection techniques, particularly those rooted in deep learning, has revolutionized the landscape of computer vision tasks by enabling the simultaneous identification and precise localization of objects within images. Deep learning models, in particular, have demonstrated their prowess in automating insect detection processes and delivering a significant boost in accuracy. Among the plethora of object detection architectures at our disposal, this research harnesses the power various iterations of the YOLO (You Only Look Once) framework, with the results consistently highlighting the superior performance of YOLO versions 5 and 8 in comparison to other models. Further, the incorporation of class activation map (CAM) has played a pivotal role in explaining the exceptional performance of these models.
5G V2X Misbehavior Detection as Edge Core Network Function Based on AI/ML

As 5G Cellular Vehicle-to-Everything (C-V2X) technology takes the lead in V2X communication, it opens the possibility for telecommunication service providers to offer Vehicle-to-Network (V2N) services using their existing 5G network infrastructure. To enhance the security of 5G V2N services, in this paper we propose a novel collaborative V2X misbehavior detection system. This system would safeguard the V2X application servers (V2X ASs), deployed in the 5G edge network, from any malicious V2X position manipulation attacks. Our proposal includes two enhanced machine learning models. The first model utilizes historical data to conduct On-Road Plausibility Checks (ORPC), while the second model builds upon the first by enabling collaboration among edge detection nodes through the sharing of attack ratios for each vehicle. Our proposed models were tested using extensive 5G core-network emulations, yielding excellent results. The first model achieved a notable accuracy improvement from 73% to 91%, while the second model further enhanced the accuracy to an impressive 95%.
Organizational resilience factors in Bogotá-based businesses during the Covid-19 pandemic

This article reports on descriptive case studies, and researched the factors of improvisation in organizational resilience in the context of the Covid-19 health emergency. A total of 23 businesses in the city of Bogotá, from different economic activities, participated in this study. Participants were managers, owners, legal representatives, or executives from those businesses. The research type is descriptive with a qualitative approach, aimed at identifying qualitative attributes based on responses or ratings using the Likert scale. A Likert-type questionnaire was used, rating seven resilience factors, whose indicators were defined by reviewing the literature on the subject. It was found that among the resilience factors, those with the lowest performance were the components of sustainability, corporate culture, and innovative ecosystem; the determinants of coping skills and leadership were the best performing; meanwhile, human talent and the elements of flexibility and adaptation played an intermediate role in sustaining the business amid the health emergency. The study corroborates the previously existing theory and shows the possible variation in the influence of improvisation factors depending on the size of the company, its structure and organization. This study may serve as an input for future research related to the determining factors in organizational resilience and the behavior of companies in the face of different types of crises.
Multilevel Code Designs for mmWave Networks

Millimeter-wave (mmWave) networks support a large variety of applications, particularly delay-sensitive applications by providing high-speed communication. A well-recognized challenge in mmWave communications is that mmWave links are susceptible to blockage and thus, communication may get disrupted. In this paper, we design and evaluate low-complexity proactive transmission mechanisms for mmWave networks that are resilient to such disruptions. Our mechanisms build on the multipath environment and on the existence of accurate models for link blockage probabilities in mmWave networks. We propose the deployment of symmetric multilevel codes across paths to achieve an attractive trade-off between the average information rate and a graceful performance degradation. Our numerical evaluations show that our proposed coding schemes indeed provide a graceful performance degradation compared to alternative schemes (such as erasure correcting codes), while significantly reducing the code complexity compared to traditional multilevel code designs.
Towards an ecosystem-based approach to assess non-target tropical reef fishes

An ecosystem-based approach integrating ontogenetic habitat uses and population dynamics was developed to assess population risks from exploitation and environmental changes on non-target reef fishes. The method employed a combination of fisheries and ecological theory, and a suite of simulation techniques to study South Florida parrotfishes. Recommended steps in this systems approach are: (1) analysis of information gaps for the stocks (or taxon) under consideration, including systematics, biogeography, population dynamics, reproductive ecology, trophodynamics, habitat use, and fisheries catch and fleet dynamics; (2) determination of primary objectives from prioritization of information gap analyses of Step 1; (3) determination of essential fish habitats from integration of stratified sampling design for fisheries-independent surveys and habitat selection theory-based analyses. These length-based analyses include ontogenetic shifts, migrations, and connections between reefs and adjacent habitats subject to fisheries, gear selectivity and catchability; (4) refined estimation of population dynamics and fisheries-specific parameters encompassing life history demographics from empirical data or comparisons to theoretical expectations adapted to local conditions; (5) simulation modeling of a realistic range of fishing scenarios and demographic characteristics using REEFS (Reef fish Equilibrium Exploitation Fisheries Simulator) and sizebased mortality estimation (LBAR) to evaluate the efficacy of potential traditional fisheries (e.g., size/bag limits) and spatial (e.g., marine protected areas) management strategies. An example application to the Florida Keys coral reef ecosystem is presented.
Genotypic Variation in Physico-Chemical Properties of Avocado at Dailekh

This study was conducted to analyze the physical and chemical properties of the fruits in 16 avocado genotypes in 2020. Fruits were harvested at physiological maturity stage from seed propagated plants and analyzed their physical (fruit weight, fruit length, fruit diameter, pulp weight, pulp/fruit ratio, and seed/fruit ratio) and chemical properties (moisture content, reducing sugar, total soluble solids, crude protein, total ash, phosphorous, iron, calcium, crude fat and crude fiber). The analysis of one-way variance of the data revealed highly significant variation in physico-chemical properties among avocado genotypes. Genotypes HRSDAV05, HRSDAV07, HRSDAV06 and HRDAV03 displayed the lowest seed/fruit ratio of 10.0, 13.5, 14.6 and 16.8%, respectively. Total soluble solid (TSS) content was the highest in HRSDAV08 (6.7 °Brix), HRSDAV03 (6.0 °Brix), HRSDAV07 (6.0 °Brix) and HRSDAV012 (6.0 °Brix). Crude protein was the highest in HRSDAV07 (19.2%), HRSDAV09 (17.8%) and HRSDAV014 (17.4%). HRSDAV03 and HRSDAV012 had the highest total ash content of 6.4% and 5.1%, respectively. Phosphorus content was the highest in HRSDAV03 (235.2 mg/100 g), but iron content was the highest in HRSDAV07 (2.5 mg/100 g). Crude fat and crude fiber were the highest in HRSDAV013 (63.0%) and HRSDAV03 (48.4%), respectively. The analysis of physico-chemical characters of avocado fruits identified HRSDAV03, HRSDAV05, HRSDAV06, HRSDAV07, HRSDAV08, HRSDAV09 and HRSDAV013 as potential parental genotypes for developing new cultivars.
Plasma Treatment of Large-Area Polymer Substrates for the Enhanced Adhesion of UV–Digital Printing

UV–digital printing belongs to the commonly used method for custom large-area substrate decoration. Despite low surface energy and adhesion, transparent polymer materials, such as polymethylmethacrylate (PMMA) and polycarbonate (PC), represent an ideal substrate for such purposes. The diffuse coplanar surface barrier discharge (DCSBD) in a novel compact configuration was used for substrate activation to improve ink adhesion to the polymer surface. This industrially applicable version of DCSBD was prepared, tested, and successfully implemented for the UV–digital printing process. Furthermore, wettability and surface free energy measurement, X-ray photoelectron spectroscopy, atomic force, and scanning electron microscopy evaluated the surface chemistry and morphology changes. The changes in the adhesion of the surface and of ink were analyzed by a peel-force and a crosscut test, respectively. A short plasma treatment (1–5 s) enhanced the substrate’s properties of PMMA and PC while providing the pre-treatment suitable for further in-line UV–digital printing. Furthermore, we did not observe damage of or significant change in roughness affecting the substrate’s initial transparency.
Effect of Damaged Starch and Wheat-Bran Arabinoxylans on Wheat Starch and Wheat Starch–Gluten Systems

This study investigated the impact of damaged starch and arabinoxylans on the thermal and pasting behavior of mixtures containing starch and gluten. The mixtures containing starch, arabinoxylans, and gluten were dispersed in water and a 50% sucrose solution. When arabinoxylans were added to native starch in water, it did not modify the viscosity profiles. An increase in viscosity parameters was observed due to the addition of arabinoxylans to starch with a higher level of damage. Gluten did not influence the effects caused by arabinoxylans. In the sucrose solution, arabinoxylans caused an increase in the viscosity parameters of native starch and starch with higher damage content dispersions. Gluten caused greater viscosity increases when arabinoxylans were added. In water, the addition of arabinoxylans to native starch caused a decrease in the enthalpy of gelatinization and an increase in the onset temperature. Adding arabinoxylans to starch with a higher level of damage caused the opposite effects. In the presence of sucrose, arabinoxylans caused a decrease in the enthalpy of gelatinization. These results lay the foundations for studying the influence of damaged starch and arabinoxylans in water-rich systems characterized by the presence of substantial proportions of sucrose, such as batter formulations.
A Nanowatt Low Voltage Subthreshold CMOS Voltage Reference Based On 2-T

This article presents the design and implementation of a nanowatt CMOS voltage reference circuit capable of operating with a low supply voltage and functioning over a wide temperature range for Io T and biomedical applications. The core of the proposed voltage reference circuit is based on a two-transistor structure. By utilizing the PMOS leakage current biasing technique, the circuit achieves ultra-low voltage operation. This method does not rely on on-chip resistors or operational amplifiers (opamps), thereby reducing complexity and improving reliability. The design is implemented using 0.18-$\mu$m CMOS technology. The circuit consumes approximately 69 nA from a minimum supply voltage of 0.9 V at room temperature. The untrimmed output voltage is 560 mV, exhibiting an average temperature coefficient (TC) of 43.4 ppm/°C over the temperature range of −40°C to 85°C. The line-voltage sensitivity (LS) is measured 0.303%/V when the input supply voltage varies from 0.9 V to 1.8 V. Finally the DC power supply rejection ratio (PSRR) at 100 Hz is −81.5 dB.
Sex-Biased Expression and Response of microRNAs in Neurological Diseases and Neurotrauma

Neurological diseases and neurotrauma manifest significant sex differences in prevalence, progression, outcome, and therapeutic responses. Genetic predisposition, sex hormones, inflammation, and environmental exposures are among many physiological and pathological factors that impact the sex disparity in neurological diseases. MicroRNAs (miRNAs) are a powerful class of gene expression regulator that are extensively involved in mediating biological pathways. Emerging evidence demonstrates that miRNAs play a crucial role in the sex dimorphism observed in various human diseases, including neurological diseases. Understanding the sex differences in miRNA expression and response is believed to have important implications for assessing the risk of neurological disease, defining therapeutic intervention strategies, and advancing both basic research and clinical investigations. However, there is limited research exploring the extent to which miRNAs contribute to the sex disparities observed in various neurological diseases. Here, we review the current state of knowledge related to the sexual dimorphism in miRNAs in neurological diseases and neurotrauma research. We also discuss how sex chromosomes may contribute to the miRNA sexual dimorphism phenomenon. We attempt to emphasize the significance of sexual dimorphism in miRNA biology in human diseases and to advocate a gender/sex-balanced science.
A Hydrologic Drying Bias in Water‐Resource Impact Analyses of Anthropogenic Climate Change

For water‐resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (Ep) as inputs. Because Ep is not a climate‐model output, an intermediary model of Ep must be introduced to connect the climate model to the hydrologic model. Several Ep methods are used. The suitability of each can be assessed by noting a credible Ep method for offline analyses should be able to reproduce climate models’ ACC‐driven changes in actual evapotranspiration in regions and seasons of negligible water stress (Ew). We quantified this ability for seven commonly used Ep methods and for a simple proportionality with available energy (“energy‐only” method). With the exception of the energy‐only method, all methods tend to overestimate substantially the increase in Ep associated with ACC. In an offline hydrologic model, the Ep‐change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC‐induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water‐resource impact analyses.
Adenocortical carcinoma: A rare malignant tumor

Adrenocortical adenocarcinoma (ACA) is a rare malignancy that develops at the expense of the adrenal cortex. The key to its treatment lies in surgery, with complete resection of a localized form offering the best chance of cure. This article presents the case of a 68-year-old man treated for adrenocortical adenocarcinoma at the Hassan 2 University Hospital in Fez. The patient, with no notable pathological history, consulted for dizziness and abdominal pain, leading to the discovery of a malignant adrenal mass on radiological evaluation. A successful left laparotomy adrenalectomy was performed, confirming, by pathological analysis, a Weiss score 4 adenocarcinoma. Immunohistochemical results showed expression of cytokeratin AE1/AE3, while other markers were absent. The article highlights the efficacy of surgery in the treatment of localized forms of this rare tumor, while highlighting diagnostic challenges and the need for international coordination in adrenocortical adenocarcinoma research and care.
The Cardioprotective Role of Nitrate-Rich Vegetables

Nitric oxide (NO) is an inorganic radical produced by both the non-enzymatic nitrate (NO3−)—nitrite (NO2−)—NO pathway and enzymatic reactions catalyzed by nitric oxide synthase (NOS). Also, as nitrate and nitrite from dietary and other endogenous sources can be reduced back to nitric oxide in vivo, the endogenous NO level can be increased through the consumption of nitrate–rich vegetables. Ingestion of dietary NO3− has beneficial effects which have been attributed to a subsequent increase in NO: a signaling molecule that may regulate various systems, including the cardiovascular system. A diet rich in NO3− from green leafy and root vegetables has cardioprotective effects, with beetroot products being particularly good sources of NO3−. For example, various studies have demonstrated a significant increase in nitrite levels (regarded as markers of NO) in plasma after the intake of beetroot juice. The present review describes the current literature concerning the role of nitrate-rich vegetables (especially beetroot products) in the prophylaxis and treatment of cardiovascular diseases (CVDs). This review is based on studies identified in electronic databases, including PubMed, ScienceDirect, Web of Knowledge, Sci Finder, Web of Science, and SCOPUS.
Dietary Diversity Score and Associated Factors among High School Adolescent Girls in Gurage Zone, Southwest Ethiopia

Introduction: Dietary diversity and the amount of animal source foods that an individual consume are two commonly used measures for dietary quality. Healthy growth and development essentially need a balanced diet of nutrients which includes a variety of foods from different food groups such as vegetables, fruits, grains and animal source. Objective: To assess dietary diversity and associated factors among high school adolescent girls in Gurage zone, southwest Ethiopia. Methodology: School based quantitative cross sectional study was conducted. The study included 634 adolescent girls. The sample was recruited using multistage cluster sampling technique. A dietary diversity score (DDS) and anthropometric of girls were measured. Bi-variable analysis was done to identify candidate variables for multivariable logistic regression and those variables having a p <0.25 was entered in multivariable logistic regression model. The results were reported by using Odds Ratio and 95% CI. P-value less than 0.05 were considered as statistically significant. Results: The mean dietary diversity score was 4.69±1.46. The prevalence of adolescents consuming less than or equal to three food groups was 20% and those consumed 3-4 food groups was 53.2% and those consumed greater than or equal to six food groups from nine food groups was 26.8%. Mother’s education (AOR=3.44, 95% CI=1.04-7.29, P=0.24), monthly income of the household (AOR=1.56, 95% CI=1.28-1.9, P=0.001) and residence (AOR=0.8, 95% CI=0.1-0.9, P=0.21) were significantly associated with dietary diversity score. Conclusion: Dietary diversity score of high school adolescent girls was low in the study area.
The Use of Electronic Resources by Postgraduate Students of the University of Cape Coast

Developments in Information and Communication Technologies (ICT) have radically taken over every sphere of activity in university libraries. Academic libraries owe it a key duty to keep pace with technological advancement in order to cope with users’ continual sophisticated information requirements. The main purpose of this study was to examine the use of electronic resources by postgraduate students of the University of Cape Coast, and with a view of giving recommendations based on findings. The major objectives of the study are: (1) To determine postgraduate students’ awareness of electronic resources in the library. (2) To find out the frequency of usage of e-resources by students. (3) To determine the computer literacy level of postgraduate students. And (4) To identify the likely problems in the utilization of electronic resources by postgraduate students. The findings revealed that most of the postgraduate students were aware of the e-resources in the library. The findings of this study also revealed that most postgraduate students rather preferred to access information from Google scholar, and other web based databases more frequently than the databases in the library. The respondents identified poor internet connection as the most significant constrained for ineffective access e-resources.