A total of 1,000 semi‐intensively managed goats belonging to two breeds—West African Dwarf (WAD) and Red Sokoto Goat (RSG) in equal proportion (500:500)—were purposively sampled across four local government areas. Six age categories (<1, 1, 2, 3, 4, and >4 years) were represented. The objective was to evaluate morphometric traits and their association with body weight in both breeds. The predominant coat colours observed in WAD goats were brown (37.4%) and black (21.0%), whereas brown coloration occurred in approximately 60% of the RSG population. Both breeds displayed varying degrees of black, brown, and white shades. Stomach girth recorded the greatest mean values among morphometric dimensions, whereas horn length showed the lowest. Overall, Red Sokoto goats exhibited superior body weights and morphometric measurements when compared to West African Dwarf goats. In WAD goats, heart girth (HTG), body length (TBL), height at withers (GHT), and stomach girth (SGT) ranged from 48.24–52.42 cm, 41.81–44.29 cm, 41.74–43.36 cm, and 57.49–68.59 cm, respectively. The corresponding ranges for RSG were 56.84–62.97 cm, 52.96–61.57 cm, 52.83–53.43 cm, and 63.76–80.12 cm, respectively. Among WAD goats, the mean body weight of young females (<1 year) and adult females (>4 years) was 2.75 kg and 17.63 kg, while males of the same age groups averaged 1.94 kg and 17.18 kg, respectively. In RSG, mean body weights for young and adult females were 3.40 kg and 19.29 kg, whereas males weighed 2.32 kg and 18.14 kg, respectively. Female goats displayed higher morphometric measurements than males, except for face length (FCL), ear length (EAL), and horn length (HRL). Phenotypic correlation coefficients ranged from 0.204 to 0.955, with all morphometric traits showing significant (p < 0.01) positive correlations with body weight in both breeds; however, correlations were generally higher in RSG than in WAD goats. Regression models indicated that stomach girth (SGT) was the strongest predictor of body weight, explaining 90.3% of variation in WAD and 91.2% in RSG. Heart girth (HTG) was the second best predictor, accounting for 83.5% and 88.8% of body weight variation in WAD and RSG, respectively.

In hybrid electric vehicles (HEVs), the electric traction motor must operate efficiently over a wide range of speeds and load conditions. The interior permanent magnet synchronous motor (IPMSM) has become a preferred choice for high-performance drive systems, particularly in traction applications, due to its high efficiency, superior torque-per-ampere ratio, and robust construction. The overall performance and energy efficiency of an IPMSM drive are largely determined by its speed and torque control strategies. However, the nonlinear behavior of rotor currents makes precise speed control a complex task. In addition, processing time and practical implementation are critical factors in the design of an effective control system. This paper proposes a Brain Emotional Learning–Based Intelligent Controller (BELBIC) to improve the dynamic and steady-state performance of IPMSM drives. BELBIC is based on a computational model inspired by emotional learning mechanisms in the human brain. The inherent feedback structure and self-tuning capability of the controller contribute to enhanced system performance. The proposed controller relies on simple algebraic operations without iterative calculations, resulting in reduced processing time and improved suitability for real-time control. BELBIC is designed to maintain machine stability under varying load conditions. To validate the effectiveness of the proposed controller, both simulation and experimental investigations were conducted on a prototype IPMSM drive under different operating scenarios. The results demonstrate superior performance in terms of stability, response speed, and robustness compared with conventional control strategies.

Aim: Chemotherapy-induced peripheral neuropathy (CIPN) is a frequent complication of cancer treatment and can significantly affect quality of life and long-term survivorship. The purpose of this study was to determine the prevalence of neuropathy in elderly patients with multiple myeloma and evaluate its relationship with chemotherapeutic exposure and survival outcomes. Method: A retrospective analysis was performed on 92 patients with multiple myeloma (53 males, 39 females) evaluated in a hematology clinic between 2009 and 2014. Demographic and clinical variables, including age, sex, performance status, chemotherapy regimen, and electromyography (EMG) findings, were recorded. The association between neuropathy and these parameters was examined. Survival analysis was conducted using Kaplan–Meier methodology to evaluate the effects of neuropathy, age, performance status, and chemotherapy type on mortality. Results: The mean age of participants was 64 ± 11.6 years, with 50% (n=46) aged ≥65 years. Patients were divided into two age groups: ≥65 years (Group I, n=46) and <65 years (Group II, n=46). Peripheral neuropathy confirmed by EMG was present in 27.2% (n=25) of patients overall, occurring in 26.1% of Group I and 28.3% of Group II. No statistically significant association was observed between age and neuropathy (p=1.00). Furthermore, neuropathy, age, performance status, and chemotherapy regimen did not show a significant impact on overall survival. Conclusion: This study represents one of the few long-term analyses with a relatively large cohort assessing the prevalence of EMG-confirmed peripheral neuropathy in elderly patients with multiple myeloma. The results indicate that increasing age does not have a significant correlation with the development of neuropathy. Larger prospective studies are warranted to further clarify risk factors and clinical implications of CIPN in this patient population. Keywords: Elderly, Electromyography, Multiple Myeloma, Neuropathy

With the advancement and expansion of technology, technical texts have gained increasing importance in modern life. Specialists across various disciplines rely on such texts to deepen their knowledge and enhance professional competencies. However, identifying accurate equivalents for technical terms remains a major challenge in translation, particularly in specialized fields. The present study aims to examine Vinay and Darbelnet’s seven translation strategies as applied to the Persian translation of Islamic banking terminology. It further seeks to determine the most and least frequently used strategies, as well as to identify the relative frequency of all seven strategies. Employing a qualitative descriptive approach, a corpus of 122 technical terms was extracted from the book Riba, Bank Interest and the Rationale of Its Prohibition and its Persian translation. Following data analysis and calculation of strategy frequency, it was found that the third strategy, literal translation, was the most frequently applied (42.6%), while the seventh strategy, adaptation, had the lowest occurrence (1.6%). The remaining strategies and their respective frequency percentages are also presented in this study.

The purpose of this study is to examine the influence of technology‐based human resource practices, with a specific focus on employee training, on organizational performance, emphasizing the mediating role of customer‐oriented employees. Drawing upon previous research in the field, the study investigates the nature and effectiveness of technology‐driven training practices within the banking industry. A random sampling technique was utilized, targeting employees from selected Islamic and conventional banks. A total of 750 questionnaires were distributed, of which 507 were returned, yielding a response rate of 67.6%. The findings indicate that technology‐based training has a strong and positive impact on the development of customer‐oriented employees. Furthermore, results reveal that such training exerts a significant positive effect on customer orientation, and that customer‐oriented employees in turn contribute substantially to enhanced organizational performance. The analysis also indicates that the influence of technology‐based training on customer orientation is more prominent in Islamic banks than in conventional banks. Overall, the study highlights the strategic importance of technology‐enabled training initiatives in shaping employee behaviour and improving organizational outcomes through increased customer orientation.

The objective of this study is to investigate key determinants of employee motivation within the banking sector. This exploratory research employs a survey strategy conducted across four major commercial banks located in seven metropolitan areas. Primary data were collected through structured questionnaires as well as in-depth, face-to-face interviews. The findings reveal that although compensation, employee benefits, and financial incentives are critical in a competitive market, non-financial factors also play a significant role in shaping employee motivation. These include job design, work environment, performance management systems, training and development, opportunities for career advancement, empowerment, and participation in organizational decision-making processes. The results underscore the importance of a comprehensive approach to employee motivation and highlight the need for senior management to reconsider existing human resource policies. Attention to both intrinsic and extrinsic motivators may contribute to enhanced employee satisfaction, commitment, and overall organizational performance.

Continual advancements in integrated circuit design have led to aggressive scaling of device dimensions toward deep and very deep submicron (DSM) technologies. As the density of system-on-chip (SoC), microprocessor, and DSP architectures increases, additional metal layers are required to support interconnection complexity. Consequently, overall system performance becomes increasingly dependent on global interconnects and on-chip buses rather than solely on gate-level performance. The efficiency of fault-tolerant on-chip data buses is significantly constrained by switching activity, energy dissipation, and crosstalk-induced delay. Improving system performance therefore requires minimizing these limiting factors. Among the available solutions, bus encoding has emerged as a promising approach for enhancing fault tolerance and optimizing interconnect performance. This paper proposes a high-performance bus encoding technique, Bus Regrouping with Hamming Distance (BRG_HD), designed to reduce switching activity, transition energy consumption, and crosstalk delay in DSM architectures. Experimental analysis demonstrates that the BRG_HD method reduces switching activity by approximately 18% to 22.5%, energy dissipation by 32.4% to 40.7%, and crosstalk delay by 35% to 41% when compared with unencoded data transmission. These improvements contribute substantially to the enhancement of overall system reliability and performance.