Does the Suitability of National Culture Matters in the Adoption of Six Sigma?

The concept and methodology of Six Sigma was developed by the American companies within the local culture of America. Therefore it is grounded on the standards, ethics and behaviours represented by America. The present study proposes that implementing Six Sigma in other countries with different cultures, norms and behaviours may have adjustment problems, as the required culture, values and behaviours for Six Sigma do not match with the local cultures of countries. A conceptual model is proposed which would utilize the Hofstede’s cultural dimensions to determine the effect of national culture at each phase of Six Sigma process

A Study on Work Design and Country Values

The performance of an organization is dependent on the work design or in other words, the job design. It includes the elements of work included in the job as well as the work environment. With the creation of multinational companies operating in different countries, the cultural element has been added to the organization entity. The question has been whether work design of an MNC, which was originated in the country of origin of the MNC, can also be exported to other countries resulting in the same efficiency of work. This study through literature review looks into major work designs developed in various countries and regions of the world to answer the above given question i.e. whether culture is the moderating factor between job design and the performance

The Relationship between Organizational Conduct and National Culture

This paper puts forwards different existing theories on classifying cultures of different countries. The first theory it introduces is of Hofstede’s cultural aspects, then the Hall’s Method of classifying culture into low and high context, and lastly the model of cultural differences by Trompenaars. Following that is the discussion on the interaction between organizational behaviour and the national culture. The focus would be the influence of culture on employee motivation, communication, organizational changes and conflict resolution

Diabetes Diagnosis through Machine Learning: An Analysis of Classification Algorithms

Diabetes is a serious and chronic disease characterized by high levels of sugar in the blood. If left untreated, it can lead to numerous complications. In the past, diagnosing diabetes required a visit to a diagnostic center and consultation with a doctor. However, the use of machine learning can help to identify the disease earlier and more accurately. This study aimed to create a model that can accurately predict the likelihood of diabetes in patients using three machine learning classification algorithms: Logistic Regression (LR), Decision Tree (DT), and Naive Bayes (NB). The model was tested on the Pima Indians Diabetes Database (PIDD) from the UCI machine learning repository and the performance of the algorithms was evaluated using various metrics such as accuracy, precision, F-measure, and recall. The results showed that Logistic Regression had the highest accuracy at 71.39% outperforming the other algorithms

Effects of Polyethylene Glycol Spacer Length and Ligand Density on Folate Receptor Targeting of Liposomal Doxorubicin In Vitro

The folate receptor is an attractive target for selective tumor delivery of liposomal doxorubicin (DXR) because it is abundantly expressed in a large percentage of tumors. This study examined the effect of polyethylene glycol (PEG) spacer length and folate ligand density on the targeting ability of folate-modified liposomes. Liposomes were modified with folate-derivatized PEG-distearoylphosphatidylethanolamine with PEG molecular weights of 2000, 3400, or 5000. The association of DXR-loaded liposomes with KB cells, which overexpress the folate receptor, was evaluated by flow cytometry at various ratios of folate modification. A low ratio of folate modification with a sufficiently long PEG chain showed the highest folate receptor-mediated association with the cells, but did not show the highest in vitro cytotoxicity. DXR release from folate-modified liposomes in endosomes might be different. These findings will be useful for designing folate receptor-targeting carriers

Prevalence of Black Quarter in Association with Patho-Morphological Alterations in Affected Tissues at Different Zones of Punjab-Pakistan

Background: Blackleg or Black Quarter (BQ) is a serious bacterial disease caused by Clostridium chauvoei. It causes edematous and gaseous changes in skeletal muscles of animals. The study was designed to find prevalence of BQ in 6 districts of Punjab, Pakistan from June 2018 to June 2019.Methods: Animals were randomly monitored, and selected in each union council regardless of age, sex and species, but lameness and hyperthermia were the selection parameters. A proforma was used to record the experimental readings of each animal. A total of 1500 swab samples from bovines (cattle and buffaloes) were processed through conventional PCR and culture sensitivity tests to examine the comparative diagnostic efficacy and suitability of the test.Results: Sensitivity and specificity of culture tests were 87.6% and 34.19% respectively, whereas PCR demonstrated 81% and 47.3% results for the said aspects, respectively. Alpha toxin gene (Ccta) was amplified at 52.2oC yielding an amplicon size of 1400 base pairs. Area wise and season wise prevalence of each animal was also determined. The prevalence of BQ in cattle was significantly higher (P 0.05) in Lahore (0%) and Nankana Sahib (8%) which belonged to the canal irrigated zones.Conclusion: There was higher prevalence of BQ in different areas of Punjab, Pakistan that show the higher risk of disease transmission. A systematic surveillance system is essential to regularly monitor the disease incidence and prevalence in these areas of Pakistan.Keywords: Black Quarter; Prevalence; Pathological; Ruminants;  Zone

FEDRP Based Model Implementation of Intelligent Energy Management Scheme for a Residential Community in Smart Grids Network

ABSTRACT In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy management has forced power supplying agencies to become globally competitive. Demand Response (DR) Programs in context with smart energy network have influenced prosumers and consumers towards it. In this paper Fair Emergency Demand Response Program (FEDRP) is integrated for managing the loads intelligently by using the platform of Smart Grids for Residential Setup. The paper also provides detailed modeling and analysis of respective demands of residential consumers in relation with economic load model for FEDRP. Due to increased customer's partaking in this program the load on the utility is reduced and managed intelligently during emergency hours by providing fair and attractive incentives to residential clients, thus shifting peak load to off peak hours. The numerical and graphical results are matched for intelligent energy management scenario

In-vitro Antagonistic Potential of Different Fungi Against Fusarium oxysporum f. sp. Capsici

The current research was conducted in Lab. to assess an antagonistic effect of various fungi against Fusarium oxysporum f. sp. capsici. In the present research, each treatment (Trichoderma viride, T. harzianum and T. Koningii) with three concentrations viz.