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Assessment of Muscle Fatigue Progression Based on Surface Electromyograph Sensor: A Pilot Study
No full textSurface muscle fatigue (MF) is an important area to study especially in medicine and sport. One way to detect and process muscle fatigue is by the use of surface electromyography (sEMG). This study presents a real-time sEMG signal acquisition and processing system designed to detect muscle fatigue during. The study included four participants that performed isometric contractions until muscle fatigue was reached, during which sEMG signals were continually monitored. The acquired sEMG data underwent systematic processing, including filtering, rectification, and feature extraction. Four features were extracted: Root Mean Square (RMS), Mean Absolute Value (MAV), Mean Frequency (MNF), and Median Frequency (MDF). The results show that MNF is the clearest indicator of fatigue in the suggested system. Moreover, RMS and MAV can be helpful in indicating the early signs of fatigue. The selected method is useful for real-time muscle fatigue monitoring without the need for complex algorithms. These results offer a basis for the next research focusing on enhancing real-time sEMG signal processing techniques using industrial sensors
Effect of Sisal and Steel Fibers on the Properties of Lightweight Concrete
No full textThe research examined how sisal natural fibers combined with steel fibers with hooked ends influence the mechanical and physical properties of lightweight concrete. The lightweight quality of pumice made it a suitable alternative to regular aggregates, which supported environmental initiatives through insulation applications and partition panels. 70% of natural sand grains were substituted with fine and coarse pumice stock. The testing process separated the pumice into two fractions: the coarse elements stayed on the 12.5 mm screen while the fine pumice material fit through a 4.75 mm screen. Tensile and compressive strength evaluations were performed as well as flexural strength, modulus of elasticity, and dry density testing. The experimental samples included various volume combinations of sisal fibers at 0.25%, 0.5%, and 0.75% together with steel fibers at 1%, 1.25%, and 1.5% levels. The combination of sisal at 0.5% content delivered elevated tensile and flexural strength results, and performance declined due to increased porosity levels. 1.5% steel fibers exhibited the best performance in terms of compressive and flexural strength, which demonstrates their powerful reinforcement properties. Compressive strength decreased because sisal fibers did not bond well with the cement matrix and created additional holes inside the material. When 0.5% sisal particles were added to concrete instead of the standard mix, the tensile strength went up by 5.1% and the flexural strength went up by 7.8%. Concrete reinforced with 1.5% steel fibers showed strength gains of 10.5% and 26.9%, with minor decreases in workability and density. The experimental outcomes identified the best fiber-to-concrete ratio, offering an ideal combination of strength improvement and environmentally friendly practices in lightweight concrete.
Automated Liver Disease Classification Via Modified ResNet-50 Architecture on CT Images
No full textThe classification of liver diseases is fundamental for the prompt identification and management of hepatic illnesses. In recent years, many computer-aided diagnostic systems for liver lesions have been developed based on deep learning techniques. This paper describes the design and assessment of the Automated classification of liver diseases with the use of Computed tomography (CT) imaging using a Modified residual convolutional neural network (ResNet-50) model. The dataset comprised many classifications of liver tissues, including cirrhosis, benign tumors, malignant tumors, and normal liver cells. The model performed training, validation, and testing, attaining excellent results with a training accuracy of 99.1%, validation accuracy of 96.4%, and test accuracy of 99.3%. This precision surpasses that of several leading approaches. The findings achieved with the proposed framework illustrate the effective execution of the experiment for practical application in liver tumor screening. By augmenting the accuracy of diagnostics, this research addresses Goal 3: Good Health and Well Being. It also encourages new developments in AI technologies and medical imaging, which shifts the focus to the integration of AI powered systems within health care for achieving Goal 9: Industry, Innovation and Infrastructure and subsequently, the development of medical technology and healthcare globally
Diagnosing the Reality of Cleaner Production Dimensions: An Exploratory Study of the Opinions of a Sample of Functional Staff at the Ready-Made Garments Factory in Mosul
No full textThe current research aims to diagnose the dimensions of cleaner production, represented by (substituting raw materials, modifying technology and equipment, recycling waste, and good managerial practices) in the ready-made garment factory in Mosul. The study is based on a research problem that emerged from diagnosing the extent to which the surveyed organization adopts a cleaner production policy through its dimensions. The research hypothesis states that the ready-made garment factory in Mosul adopts cleaner production at a comprehensive level and in terms of its specific dimensions.A questionnaire was used as the primary tool for data collection, and the statistical program (SPSS V24) was employed to analyze the data from the surveyed sample, which consisted of 165 respondents from the organization’s workforce. Using a five-point Likert scale, the study concluded with several findings confirming the presence of these dimensions at varying levels within the surveyed organization. Additionally, the study presented key recommendations, most notably the necessity of focusing more precisely on the cleaner production approach and its dimensions to achieve the organization’s objective
The Role of Cleaner Production in Enhancing Enlightened Marketing: An Exploratory Study of the Opinions of a Sample of Employees in the Ready-Made Garments Factory in Mosul
No full textThe current research aims to study the correlation and impact relationship between cleaner production (independent variable) and enlightened marketing (dependent variable) in the ready-made garments factory in Mosul. This is in light of a research problem centered on the environmental challenges that impose the need for the factory to adopt a marketing policy that preserves the environment while ensuring societal well-being. Such an approach guarantees the factory’s continuity in a competitive environment where customers demand sustainability across various operations. A questionnaire was adopted as the primary tool for data collection from a sample of 165 employees in the factory, with a 91% response rate. The study relied on a five-point Likert scale and used SPSS V24 and AMOS V24 for data analysis and hypothesis testing. The findings revealed a statistically significant correlation and impact of cleaner production on enlightened marketing. Additionally, the study presents several recommendations, the most important of which is the necessity for the factory to focus on adopting cleaner production practices and enlightened marketing policies to achieve sustainable goals for society as a whole
Leadership Influence Methods and Their Reflections on Sustainable Development A Study of the Opinions of a Sample of Administrative Leaders at Al-HadbaUniversity College
No full textThe current study aimed to identify the reflections of leadership influence methodsnamely,(enthusiasm stimulation, adaptation of work conditions, emotional involvement, and expertise-based influence)—on sustainable development, represented by its dimensions (economic, social, and environmental) The study adopted several hypotheses, the most prominent of which stated that there are no correlation or impact relationships between leadership influence methods and sustainable development at the investigated university A descriptive-analytical approach was employed to test the hypotheses, with a questionnaire as the primary tool for data collection from a random sample of 40 administrative leaders at Al-Hadba University College. Several statistical methods were used for hypothesis testing, relying on SPSS V.26 for analysis .The study reached several conclusions, including the widespread application of various leadership influence methods and the prominent indicators of sustainable development, which collectively contributed to the existence of correlation and impact relationships between them at both the overall and partial levels within Al-Hadba University College
Self-efficacy of Administrative Leadership and Its Reflections on Sustainable Development: An Exploratory Study of the Opinions of a Sample of Administrative Leaders in the Presidency of the Nineveh Health Department
No full textThe present study aimed to examine the reflections of administrative leadership self-efficacy on sustainable development in the Presidency of the Nineveh Health Department through its dimensions (self-confidence, task accomplishment ability, self-awareness, and control) as an independent variable and to determine its correlation and impact on sustainable development as a dependent variable.
The research problem was defined by the question: What are the reflections of administrative leadership self-efficacy on sustainable development? The study adopted a hypothetical model indicating the relationship and influence, employing a descriptive approach. Data was collected through a questionnaire distributed to a sample of 50 individuals and analysed using the SPSS statistical program.
The study reached several findings, most notably the availability of self-efficacy dimensions among administrative leaders and the presence of sustainable development dimensions. The results also confirmed a relationship between these two variables
The Correlations Between Antibiotics Resistance and Biofilm Formation of Acinetobacter baumannii isolated from Burned Wound Patients
Get PDFOne hundred and fifty samples from burned wound swabs and from both genders and different ages were included in this study. They were collected from patients in Baquba teaching hospital, Khanaqin general hospital, and outpatient clinics between the beginning of September 2023 and February 2024. Identification of A. baumannii by manual biochemical tests that used Gram staining, catalase test, oxidase test, urease test, indole test, Kligler iron agar (KIA) test, and Simmon citrate test, as well as growth at 44°C. The VITEK2 compact system includes biochemical testing for final validation. The biofilm formation capacity of the A. baumannii isolate was determined using a microtiter plate assay. ESBLs and MBLs were detected using phenotypic methods. Antibiotic susceptibility testing was performed to determine the probable resistance of A. baumannii isolates to 14 antibiotics from various classes. The results indicated that the highest incidence of infection with A. baumannii occurred in the 1-40-year-old age group, with 55 cases representing 36.7% and 36.6%. A. baumannii isolates produced 17/30 (57%) strong biofilms, 9/30 (30%) moderate biofilms, and 4/30 (13%) non-biofilms. Our results indicate that A. baumannii exhibits crucial antibiotic resistance. The recent findings indicated that all A. baumannii isolates displayed 100% MBL production, but none of the 30 isolates produced ESBL enzymes, and there was a connection between biofilm production and antibiotic resistance in these isolates. A. baumannii isolates resistant to aminoglycosides, carbapenems, and sulfonamides show a positive correlation between biofilm production and antibiotic resistance
Latest developments in NO2 gas sensors based on PEDOT:PSS nanocomposites and metal oxides: A comprehensive review
Get PDFNNitrogen dioxide (NO?) is a toxic atmospheric contaminant having serious impacts on human health and the environment. The low concentration detection of NO? in high accuracy and high sensitivity is still one? of the difficult points in air quality monitoring. Recently, hybrid gas sensors based on the conducting polymer PEDOT:PSS and metal oxide semiconductors have been proposed as potential candidates for what? high-performance NO sensing. Using the p-type polymer and n-type or p-type metal oxides in nanocomposites can lead to what? a synergetic effect in terms of improved charge transport, sensitivity, and operation at lower temperatures. Recent developments in the area of PEDOT:PSS/metal oxide nanocomposite-based NO? sensing are reviewed with what? a critical look at the structural and electronic nature of PEDOT:PSS, the gas-sensing mechanism of conventional metal oxides, and the importance of interface engineering for device performance. It also highlights eco-friendly synthesis techniques, e.g., water-based processing and green synthesis of metal oxides, contributing to sustainable production practices for the sensors developed. Major previous works are summarized and discussed on the basis of important performance largeness, such as the detection limit, response/recovery time/temperature/humidity, and environment-friendly processing conditions. Although these hybrid systems present obvious opportunities compared with pure sensors, the issues of long-term stability and selectivity under mixed gas environments and reproducibility of the fabrication approaches are still challenging. In general, PEDOT:PSS/metal oxide nanocomposites offer a viable and sustainable platform for the next-generation NO? gas sensors with lavish sensing performance, eco-compatibility, and prospects to be scaled up for cost-effective fabrication
Embedded MPPT for Photovoltaic Systems: Low-Cost Microcontrollers, P&O and Incremental Conductance Algorithms, and IoT-Based Monitoring - A Systematic Review
No full text This survey offers an embedded-oriented view of MPPT applied to PV systems, with specific attention devoted to low-cost microcontroller-based implementations and classical P&O and INC algorithms for application in IoT-supervised smart PV infrastructures. This paper synthesizes 83 recent peer-reviewed articles published from 2023 to 2025. It highlights how embedded MPPT controllers are increasingly implemented using low-cost hardware, such as Arduino , ESP32 and STM32, that support real-time duty-cycle control, remote monitoring, and PV supervision at a large scale. These results confirm that although classical P&O and INC dominate lower-memory embedded hardware, they are inherently limited by steady-state oscillations, poor adaptability to rapid irradiance transitions, and practical constraints such as finite ADC resolution and sampling delays. To address these limitations, robust and hybrid strategies for enhancement (among which Active Disturbance Rejection Control – ADRC/LADRC, sliding-mode-and super-twisting Sliding-mode or Super-twisting controllers controllers, as well as hybrid approaches such as INC–SMC and LADRC– metaheuristic optimization) always tend to outperform conventional ones by reducing ripple magnitude , decreasing the settling time while guaranteeing a higher tracking efficiency under conditions of partial shading ranging from partially clouded to dynamic operating conditions. Additionally, enables embedded MPPT systems with intelligent cyber-physical infrastructures and with predictively supervised, adaptively operated systems, using secured wireless IoT monitoring layers (WiFi, LoRaWAN, XBee, MQTT). There are still important research gaps, such as the lack of an end-to-end, unified, IoT-robust co-design, insufficient real-time resilience, and insufficient cybersecurity integration. Thus, this review suggests that the secure cyber-physical embedded MPPT model, based on ESP32 edge control, is adopted with ADRC-based stability improvement and secure IoT communication, for highly relevant PV farm installations in harsh Iraqi weather, such as Basra and desert areas