The Importance Of Accurate Performance Appraisals For Creating Ethical Organizations

Improving the day-to-day ethical judgments of employees within an organization remains a challenge. This study examined how employees’ job performance outcomes influence how others judge the employees’ ethical performance. The research found that respondents judged employees with successful job performance outcomes to have exhibited more ethical behaviors than employees with unsuccessful job performance outcomes. This pattern of results was consistent regardless of the respondent’s ethical beliefs. We discuss implications of these results for research and for practice, particularly in terms of improving judgments of ethical behavior in organizations

Synthesis, Growth and Spectroscopic Studies of L-Alanine Hydrogen Chloride(Lahc) Crystals

L-alanine Hydrogen Chloride (LAHC) salt was synthesized by taking L-alanine and hydrochloric acid in 1:1 molar ratio and the solubility of the synthesized salt in deionized water was determined at different temperatures. Single crystals of  L-alanine  Hydrogen Chloride (LAHC) were grown by solution method with slow evaporation technique. The grown crystals were characterized by single crystal X-ray diffraction (XRD) analysis, FTIR studies and UV-visible transmittance studies and the NLO activity of the grown crystal has been checked by Second Harmonic Generation (SHG) test.ÂÂ

Work–Family Conflict and Counterproductive Work Behaviors: Moderating Role of Regulatory Focus and Mediating Role of Affect

Evidence suggests work–family conflict can lead to numerous negative consequences in the workplace, including behaviors detrimental to the organization and its members, such as counterproductive work behaviors (CWBs). Yet relatively little research has addressed the relationship between work–family conflict and CWBs. This study builds on the structural model of stress and regulatory focus theory to addresses this major gap in the literature. Our model proposes that negative affect and self-regulation can help us understand how and why work–family conflict may be related to CWBs. We hypothesize that work–family conflict is positively related to negative affect, which in turn is positively related to CWBs, and regulatory focus moderates the relationship between work–family conflict and CWBs. A survey of 332 employees shows work–family conflict is directly related to CWBs, indirectly related to CWBs via negative affect, and the relationship is moderated by regulatory prevention focus. We discuss implications for theory and practice

SL-RI: Integration of supervised learning in robots for industry 5.0 automated application monitoring

Robotic technology holds a significant role within the realm of smart industries, wherein all functionalities are executed within real-time systems. The verification of robot operations is a crucial aspect in the context of Industry 5.0. To address this requirement, a distinctive design methodology known as SL-RI is proposed. This article aims to establish the significance of incorporating robots in the Industry 5.0 framework through analytical representations. In the context of this industrial monitoring system, the implementation of a supplementary algorithm is essential for effective management, as it enables the robots to acquire knowledge through the analysis and adaptation of restructured commands. The analytical model of robots is designed to accurately monitor the precise position and accelerations of robots, resulting in full-scale representations with minimal error conditions. The uniqueness of the proposed method in robotic monitoring system is related to the application process that is directly applied in Industry 5.0 by using various parametric cases where active movement of robots are monitored with rotational matrix representations. In this type of representations the significance relies in the way to understand the full movement of robots across various machines and its data handling characteristics that provides low loss and error factors

Surface acoustic wave distribution and acousto-optic interaction in proton exchanged LiNbO<SUB>3</SUB> waveguides

The efficiency of acoustooptic (AO) interaction in YZ-cut proton exchanged (PE) LiNbO3 waveguides is theoretically analysed by determining the overlap between the optical and acoustic field distributions. The present analysis takes into account the perturbed SAW field distribution due to the presence of the PE layer on the LiNbO3 substrate determined by the rigorous layered medium approach. The overlap is found to be significant upto very high acoustic frequencies of the order of 5 GHz, whereas in the earlier analysis by vonHelmolt and Schaffer [6] for diffused waveguides, it was shown that the overlap integral rolls down to nearly zero at this high frequency range

Ensemble Machine Learning Framework for Predicting Maternal Health Risk during Pregnancy

Maternal health risks can cause a range of complications for women during pregnancy. High blood pressure, abnormal glucose levels, depression, anxiety, and other maternal health conditions can all lead to pregnancy complications. Proper identification and monitoring of risk factors can assist to reduce pregnancy complications. The primary goal of this research is to use real-world datasets to identify and predict Maternal Health Risk (MHR) factors. As a result, we developed and implemented the Quad-Ensemble Machine Learning framework to predict Maternal Health Risk Classification (QEML-MHRC). The methodology used a variety of Machine Learning (ML) models, which then integrated with four ensemble ML techniques to improve prediction. The dataset collected from various maternity hospitals and clinics subjected to nineteen training and testing tests. According to the exploratory data analysis, the most significant risk factors for pregnant women include high blood pressure, low blood pressure, and high blood sugar levels. The study proposed a novel approach to dealing with high-risk factors linked to maternal health. Dealing with class-specific performance elaborated further to properly un-derstand the distinction between high, low, and medium risks. All tests yielded outstanding results when pre-dicting the amount of risk during pregnancy. In terms of class performance, the dataset associated with the "HR" class outperformed the others, predicting 90% correctly. GBT with ensemble stacking outperformed and demonstrated remarkable performance for all evaluation measure (0.86) across all classes in the dataset. The key success of the models used in this work is the ability to measure model performance using a class-wise distribution. The proposed approach can help medical experts assess maternal health risks, saving lives and preventing complications throughout pregnancy. The prediction approach presented in this study can detect high-risk pregnancies early on, allowing for timely intervention and treatment. This study’s development and findings have the potential to raise public awareness of maternal health issues

Piloting a scale-up platform for high-quality human T-cells production

Copyright \ua9 2024 Selvarajan, Teo, Chang, Ng, Cheong, Sivalingam, Khoo, Wong and Loo. Cell and gene therapies are an innovative solution to various severe diseases and unfulfilled needs. Adoptive cell therapy (ACT), a form of cellular immunotherapies, has been favored in recent years due to the approval of chimeric antigen receptor CAR-T products. Market research indicates that the industry’s value is predicted to reach USD 24.4 billion by 2030, with a compound annual growth rate (CAGR) of 21.5%. More importantly, ACT is recognized as the hope and future of effective, personalized cancer treatment for healthcare practitioners and patients worldwide. The significant global momentum of this therapeutic approach underscores the urgent need to establish it as a practical and standardized method. It is essential to understand how cell culture conditions affect the expansion and differentiation of T-cells. However, there are ongoing challenges in ensuring the robustness and reproducibility of the manufacturing process. The current study evaluated various adoptive T-cell culture platforms to achieve large-scale production of several billion cells and high-quality cellular output with minimal cell death. It examined factors such as bioreactor parameters, media, supplements and stimulation. This research addresses the fundamental challenges of scalability and reproducibility in manufacturing, which are essential for making adoptive T-cell therapy an accessible and powerful new class of cancer therapeutics