The study focused on investigating the effects of varying levels of HA (HA1 = 0, HA2 = 25, HA3 = 50, HA4 = 75, and HA5 = 100) on Red Dragon, Red Prince, and Red Meat varieties of red radish. This analysis aimed to unravel the relationship between different levels of HA and their impact on the growth and productivity of red radish genotypes. The findings revealed that the Red Prince genotype attained the utmost plant height of 24.00 cm, an average of 7.50 leaves per plant, a leaf area of 23.11 cm2, a canopy cover of 26.76%, a leaf chlorophyll content of 54.60%, a leaf fresh weight of 41.16 g, a leaf dry weight of 8.20 g, a root length measuring 9.73 cm, a root diameter of 3.19 mm, a root fresh weight of 27.60 g, a root dry weight of 6.75 g, and a remarkable total yield of 17.93 tons per hectare. The implications of this study are poised to benefit farmers within the Dera Ismail Khan Region, specifically in the plain areas of Pakistan, by promoting the cultivation of the Red Prince variety.
Among contemporary computational techniques, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to tackle non-linear modelling and complex stochastic datasets. Nondeterministic models involve some computational intricacies when deciphering real-life problems but always yield better outcomes. For the first time, this study utilized the ANN and ANFIS models for modelling power generation/electric power output (EPO) from databases generated in a combined cycle power plant (CCPP). The study presents a comparative study between ANNs and ANFIS to estimate the power output generation of a combined cycle power plant in Turkey. The inputs of the ANN and ANFIS models are ambient temperature (AT), ambient pressure (AP), relative humidity (RH), and exhaust vacuum (V), correlated with electric power output. Several models were developed to achieve the best architecture as the number of hidden neurons varied for the ANNs, while the training process was conducted for the ANFIS model. A comparison of the developed hybrid models was completed using statistical criteria such as the coefficient of determination (R2), mean average error (MAE), and average absolute deviation (AAD). The R2 of 0.945, MAE of 3.001%, and AAD of 3.722% for the ANN model were compared to those of R2 of 0.9499, MAE of 2.843% and AAD of 2.842% for the ANFIS model. Even though both ANN and ANFIS are relevant in estimating and predicting power production, the ANFIS model exhibits higher superiority compared to the ANN model in accurately estimating the EPO of the CCPP located in Turkey and its environment.
In a time of a growingly age-diverse workforce, modern organizations are facing the challenge of simultaneously maintaining job satisfaction for both younger and older workers. In that regard, this study aims to analyse and further explore the difference in job expectations of employees from the IT industry who belong to different age groups. Based on the extant literature, an appropriate research model was designed, which was subsequently tested using the data gathered through the surveys conducted over the past fourteen years. The research results show that the main difference between younger and older employees within the IT industry is related to professional and personal growth. Specifically, younger employees primarily look for personal development and rapid professional advancement, which are of minor importance to their older counterparts. Intriguingly, the obtained results showed no difference between the younger and older employees regarding the work environment, including its competitiveness.
This study investigates the relationship between Corporate Social Responsibility (CSR) dimensions and employees’ satisfaction and retention for sustainability in banks. Four components (economic, legal, ethical, and philanthropic) are analyzed CSR activities and their effects on employee’s satisfaction and retention in the company. Purposive and convenient sampling method was used to get the information from 221 participants. The entire form of the dataset is utilized to execute regression and correlation analysis using SPSS. In order to find out the relationship between economic, legal, ethical, and philanthropic factors and employee’s satisfaction and retention, regression beta coefficient and correlation were used to analyze. This study also examines the relationship between job satisfaction and intentions to retain with an organization. The findings demonstrate that the CSR aspects of ethical and philanthropic have a considerable and favorable influence on employee’s satisfaction. The outcome also demonstrates a good and prominent influence of legal CSR on the satisfaction of employee’s to retain with the firm. Moreover, this study demonstrates that economic aspect of CSR has no significant impact on employee’s retention and satisfaction. Correlation analysis depicts that economic CSR is positively and significantly connected with employee’s retention and satisfaction. This research came to the conclusion that enhancing employees view regarding CSR activities such as economic, legal, ethical, and philanthropic will increase employee’s satisfaction. Therefore, executives and managers in the banks should take steps to influence how employees see CSR areas in order to raise employee’s satisfaction and retention in the banks for sustainability.
In this work, the structural transformations of a suboxide vacuum-deposited film of SiO1.3 composition annealed in an inert atmosphere in a wide temperature range of 100 °C–1100 °C were characterized by the reflection-transmission spectroscopy technique. The experimental spectroscopic data were used to obtain the spectra of the absorption coefficient α(hν) in the absorption edge region of the film. Based on their processing, the dependences of Urbach energy EU and optical (Tauc) bandgap Eo on the annealing temperature were obtained. An assessment of the electronic band gap (mobility gap) Eg was also carried out. Analysis of these dependences allowed us to trace dynamics of thermally stimulated disproportionation of the suboxide film and the features of the formation of nanocomposites consisting of amorphous and/or crystalline silicon nanoparticles in an oxide matrix.
Introduction: the presence of anti-CCP is an important prognostic tool for rheumatoid arthritis (RA), but its relationship with the activity of the disease and functional capacity is still being investigated. Objectives: to study the relationship between anti-CCP and the indices of disease activity, functional capacity and structural damage, by means of conventional radiography (CR) and magnetic resonance imaging (MRI), in stabilized RA. Methods: cross-sectional study of RA patients with one to 10 years of disease. The participants were subjected to clinical evaluation with anti-CCP screening. Disease activity was assessed by means of the Clinical Disease Activity Index (CDAI) and functional capacity by means of the Health Assessment Questionnaire (HAQ). CR was analyzed by the Sharp van der Heijde index (SmvH) and MRI by the Rheumatoid Arthritis Magnetic Resonance Image Scoring System (RAMRIS). Results: 56 patients were evaluated, with median (IIq) of 55 (47.5–60.0) years, 50 (89.3%) were female among whom 37 (66.1%) were positive for anti-CCP. The median (IIq) of CDAI, HAQ, SmvH and RAMRIS were 14.75 (5.42–24.97), 1.06 (0.28–1.75), 2 (0–8) and 15 (7–35), respectively. There was no association between anti-CCP and CDAI, HAQ, SmvH and RAMRIS. Conclusion: our results did not establish the association of anti-CCP with the severity of the disease. So far, we cannot corroborate the anti-CCP as a prognostic tool in RA established.
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