Examining employee attitudes and behaviours towards organisational change using supervisor and peer relations

This study focuses on employee workplace and demographic predictors to know the employee attitudes and behaviours regarding organisational change. Five hundered fifty six surveys out of one thousand were returned from full time academics working in public sector universities of Pakistan. The findings indicate significant relationships between readiness for change and workplace and demographic factors. First time supervisor and peer relations predictor has been examined to readiness for change. Results indicate positive and significant relationships between readiness for change and supervisor and peer relations. However, from demographic characteristics only two i.e. number of dependents and younger employees have positive and significant relationships to readiness for change. This study contribute in the literature on change management particularly for developing countries i.e. Pakistan and assist the management and practitioners of human resources management (HRM), organisational development (OD) and change agents in assessing, designing and evaluating new or existing programs for organisational change

Impact of employees psychological and financial predictors for readiness to organizational change

This study focuses on employees’ psychological and financial predictors to know the employees reaction regarding change. One hundred forty one surveys were returned from full time teaching staff working in public sector universities of Pakistan. The findings indicate significant relationships between readiness to change and psychological and financial predictors. First time job involvement, training and skills development, pays/wages/fringe benefits and promotions predictors have been examined for readiness to change. Results indicate no relationship between readiness to change and employees’ organizational commitment. However, employees’ job involvement, training and skills development pays/wages/fringe benefits, and promotions have positive impact on readiness to change. This study may contribute in the literature on change management particularly for developing countries and may assist the management and practitioners of Human Resources Management (HRM), Human Resources Development (HRD), and Organizational Behaviour (OB) in assessing, designing and evaluating new or existing programs for organisational change

An Experiment and Detection Scheme for Cavity-based Cold Dark Matter Searches

A resonance detection scheme and some useful ideas for cavity-based searches of light cold dark matter particles (such as axions) are presented, as an effort to aid in the on-going endeavors in this direction as well as for future experiments, especially in possibly developing a table-top experiment. The scheme is based on our idea of a resonant detector, incorporating an integrated Tunnel Diode (TD) and a GaAs HEMT/HFET (High Electron Mobility Transistor/Heterogenous FET) transistor amplifier, weakly coupled to a cavity in a strong transverse magnetic field. The TD-amplifier combination is suggested as a sensitive and simple technique to facilitate resonance detection within the cavity while maintaining excellent noise performance, whereas our proposed Halbach magnet array could serve as a low-noise and permanent solution replacing the conventional electromagnets scheme. We present some preliminary test results which demonstrate resonance detection from simulated test signals in a small optimal axion mass range with superior Signal-to-Noise Ratios (SNR). Our suggested design also contains an overview of a simpler on-resonance dc signal read-out scheme replacing the complicated heterodyne readout. We believe that all these factors and our propositions could possibly improve or at least simplify the resonance detection and read-out in cavity-based DM particle detection searches (and other spectroscopy applications) and reduce the complications (and associated costs), in addition to reducing the electromagnetic interference and background.Comment: 22 pages, 7 figure

B-cell maturation antigen (BCMA) in multiple myeloma: rationale for targeting and current therapeutic approaches.

Despite considerable advances in the treatment of multiple myeloma (MM) in the last decade, a substantial proportion of patients do not respond to current therapies or have a short duration of response. Furthermore, these treatments can have notable morbidity and are not uniformly tolerated in all patients. As there is no cure for MM, patients eventually become resistant to therapies, leading to development of relapsed/refractory MM. Therefore, an unmet need exists for MM treatments with novel mechanisms of action that can provide durable responses, evade resistance to prior therapies, and/or are better tolerated. B-cell maturation antigen (BCMA) is preferentially expressed by mature B lymphocytes, and its overexpression and activation are associated with MM in preclinical models and humans, supporting its potential utility as a therapeutic target for MM. Moreover, the use of BCMA as a biomarker for MM is supported by its prognostic value, correlation with clinical status, and its ability to be used in traditionally difficult-to-monitor patient populations. Here, we review three common treatment modalities used to target BCMA in the treatment of MM: bispecific antibody constructs, antibody-drug conjugates, and chimeric antigen receptor (CAR)-modified T-cell therapy. We provide an overview of preliminary clinical data from trials using these therapies, including the BiTE® (bispecific T-cell engager) immuno-oncology therapy AMG 420, the antibody-drug conjugate GSK2857916, and several CAR T-cell therapeutic agents including bb2121, NIH CAR-BCMA, and LCAR-B38M. Notable antimyeloma activity and high minimal residual disease negativity rates have been observed with several of these treatments. These clinical data outline the potential for BCMA-targeted therapies to improve the treatment landscape for MM. Importantly, clinical results to date suggest that these therapies may hold promise for deep and durable responses and support further investigation in earlier lines of treatment, including newly diagnosed MM

THE PHYSIOLOGICAL RESPONSE OF CARDIORESPIRATORY FITNESS PARAMETERS TO EXERCISE IN PREDIABETIC POPULATION: AN EXPERIMENTAL PRE- POST DESIGN

Background: The cardiorespiratory fitness in prediabetic population at pre- and post-interventional stage after 8 weeks of moderate intensity exercise was determined. This study is part of PhD project and carried out in Physiology department, Institute of Basic Medical Sciences, Khyber Medical University, Peshawar, Pakistan. Methods: It was an experimental study design. Adult prediabetics (n=50), 22 females and 28 males of 18 to 35y age group were included in the study. Diagnosis of prediabetes was made with HbA1c falling in the range of 5.7– 6.4%, and fasting blood glucose (100-125mg/dL). Cardiorespiratory fitness parameters (Ventilation, oxygen consumed during exercise VO2, carbon dioxide exhaled VCO2, metabolic equivalents (ME), heart rate (HR), heart rate reserve (HRR), rate of carbohydrate oxidation (RCHO), fat oxidation (RFO) and energy expenditure (EE)) were determined at pre- and post-exercise intervention using breath-by-breath analyzer. The participants performed moderate exercise protocol of 30 min with HRmax% of 70 ± 5% for 5 days a week for 8 weeks during their leisure time, monitored with pedometers. Results: The results showed a significant improvement in cardiorespiratory fitness parameters at post exercise analysis.  Similar changes were observed for fasting blood glucose (P value < 0.001)  and HbA1c (P value < 0.001).Conclusion: Moderate physical activity for 8 weeks showed significant Improvement in cardiorespiratory fitness parameters and glycemic status of patients with prediabetes

MATLAB Simulink model of a photovoltaic cell

Материалы XVIII Междунар. науч.-техн. конф. студентов, аспирантов и молодых ученых, Гомель, 26–27 апр. 2018 г

Prevalence and association of obesity with self-reported comorbidity: a cross-sectional study of 1321 adult participants in Lasbela, Balochistan

Association of fatness with chronic metabolic diseases is a well-established fact, and a high prevalence of risk factors for these disorders has increasingly been reported in the third world. In order to incorporate any preventive strategies for such risk factors into clinical practice, decision-makers require objective evidence about the associated burden of disease. A cross-sectional study of 1321 adults from one of the districts of Balochistan, among the most economically challenged areas of Pakistan, was carried out for the measures of fatness and self-reported comorbidities. Body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) were measured and demographic information and self-reported comorbidities were documented.The prevalence of obesity was 4.8% (95% CI: [3.8, 6.1]) and 21.7% (95% CI: [19.5, 24.0]), as defined by the World Health Organization (WHO) international and Asia/Asia-Pacific BMI cut-offs, respectively. The proportion exhibiting comorbidity increased with increasing levels of fatness in a dose-response relationship

A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds

Most of the clustering methods used in the clustering of chemical structures such as Wards, Group Average, K- means and Jarvis-Patrick, are known as hard or crisp as they partition a dataset into strictly disjoint subsets; and thus are not suitable for the clustering of chemical structures exhibiting more than one activity. Although, fuzzy clustering algorithms such as fuzzy c-means provides an inherent mechanism for the clustering of overlapping structures (objects) but this potential of the fuzzy methods which comes from its fuzzy membership functions have not been utilized effectively. In this work a fuzzy hierarchical algorithm is developed which provides a mechanism not only to benefit from the fuzzy clustering process but also to get advantage of the multiple membership function of the fuzzy clustering. The algorithm divides each and every cluster, if its size is larger than a pre-determined threshold, into two sub clusters based on the membership values of each structure. A structure is assigned to one or both the clusters if its membership value is very high or very similar respectively. The performance of the algorithm is evaluated on two bench mark datasets and a large dataset of compound structures derived from MDL MDDR database. The results of the algorithm show significant improvement in comparison to a similar implementation of the hard c-means algorithm