Designing an effective training process a case study at Sohar Development Office Sultanate of Oman

Sohar Development Office (SDO), in the Sultanate of Oman, has invested time and resources on administrative training. Seemingly, this study explores the extent to which the seven conditions for a training process are being implemented at SDO so as to make the training effective. It specifically examines the relationship between the seven conditions which represent the independent variables and the training process. This research employed both quantitative and qualitative techniques, a questionnaire and an in-depth interview employing items that attempt to identify the respondents‘ perceptions of training. The seven conditions are needs assessment analysis (NA), readiness for training (RT), the learning environment (LE), transfer of training (TT), evaluation plan (EP), training method (TM) and monitoring and evaluation of training (ME). Based on regression analysis, NA, RT, EP, and TM are significantly related to effective training process while LE, TT and ME are not significant, thus confirming an earlier assumption that a poor traditional training design tends to thwart innovation and change. The study finally recommends an improved training process, with an action plan to overcome the deficiencies, among them include an improved job description that defines the job in terms of its purposes, key functions, and required tasks and competences that are necessary to carry it out. The study equally proposes that future research should look into the socio-cultural factors that impact training processes in the designing of effective training programmes. The investigation equally highlights the importance of on-the-job training, as a less costly and more effective alternative to off-the-job training, technical training, and e-training in matching high-end information technological tools such as modelling, instructions, and repairs

Middle East respiratory syndrome coronavirus: current situation and travel-associated concerns

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.The emergence of Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 brought back memories of the occurrence of severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002. More than 1500 MERS-CoV cases were recorded in 42 months with a case fatality rate (CFR) of 40%. Meanwhile, 8000 cases of SARS-CoV were confirmed in six months with a CFR of 10%. The clinical presentation of MERS-CoV ranges from mild and non-specific presentation to progressive and severe pneumonia. No predictive signs or symptoms exist to differentiate MERS-CoV from community-acquired pneumonia in hospitalized patients. An apparent heterogeneity was observed in transmission. Most MERS-CoV cases were secondary to large outbreaks in healthcare settings. These cases were secondary to community-acquired cases, which may also cause family outbreaks. Travel-associated MERS infection remains low. However, the virus exhibited a clear tendency to cause large outbreaks outside the Arabian Peninsula as exemplified by the outbreak in the Republic of Korea. In this review, we summarize the current knowledge about MERS-CoV and highlight travel-related issues

A bi-level multi-objective data envelopment analysis model for estimating profit and operational efficiency of bank branches

Data Envelopment Analysis (DEA) is a powerful method for analyzing the performance of decision making units (DMUs). Traditionally, DEA is applied for estimating the performance of a set of DMUs through measuring a single perspective of efficiency. However, in recent years, due to increasing competition in various industries, modern enterprises focus on enhancing their performance by measuring efficiencies in different aspects, separately or simultaneously. This paper proposes a bi-level multi-objective DEA (BLMO DEA) model which is able to assess the performance of DMUs in two different hierarchical dimensions, simultaneously. In the proposed model, we define two level efficiency scores for each DMU. The aim is to maximize these two efficiencies, simultaneously, for each DMU. Since the objective functions at both levels are fractional, a fuzzy fractional goal programming (FGP) methodology is used to solve the proposed BLMO DEA model. The capability of the proposed model is illustrated by a numerical example. Finally, to practically validate the proposed model, a real case study from 45 bank’s branches is applied. The results show that the proposed model can provide a more comprehensive measure for efficiency of each bank’s branch based on simultaneous measuring of two different efficiencies, profit and operational efficiencies, and by considering the level of their importance

An Integrated Fuzzy Clustering Cooperative Game Data Envelopment Analysis Model with application in Hospital Efficiency

Hospitals are the main sub-section of health care systems and evaluation of hospitals is one of the most important issue for health policy makers. Data Envelopment Analysis (DEA) is a nonparametric method that has recently been used for measuring efficiency and productivity of Decision Making Units (DMUs) and commonly applied for comparison of hospitals. However, one of the important assumption in DEA is that DMUs must be homogenous. The crucial issue in hospital efficiency is that hospitals are providing different services and so may not be comparable. In this paper, we propose an integrated fuzzy clustering cooperative game DEA approach. In fact, due to the lack of homogeneity among DMUs, we first propose to use a fuzzy C-means technique to cluster the DMUs. Then we apply DEA combined with the game theory where each DMU is considered as a player, using Core and Shapley value approaches within each cluster. The procedure has successfully been applied for performances measurement of 288 hospitals in 31 provinces of Iran. Finally, since the classical DEA model is not capable to distinguish between efficient DMUs, efficient hospitals within each cluster, are ranked using combined DEA model and cooperative game approach. The results show that the Core and Shapley values are suitable for fully ranking of efficient hospitals in the healthcare systems

Upwind responses of Anopheles stephensi to carbon dioxide and L-lactic acid: an olfactometer study.

Excretion of carbon dioxide and L-lactic acid through exhalation and perspiration provides olfactory signals to mosquitoes which allow them to find and bite humans; however, mosquito species differ in this regard. This study investigated upwind responses of Anopheles stephensi, mysorensis form, an important malaria vector in Asia, to carbon dioxide and L-lactic acid under laboratory conditions. While a minimal dose of carbon dioxide (90 ppm) activated the mosquitoes, 10 times this amount suppressed them. L-lactic acid alone did not produce a significant effect by itself, but addition of 6 microg/min of L-lactic acid to a range of 90 to 410 ppm carbon dioxide resulted in attraction. The results provide further support for the hypothesis that CO2 plays an important role in the host-seeking behaviour of zoophilic mosquitoes, and suggests that L-lactic acid might play a more critical role than CO2 in the attraction of An. stephensi

The Genetic Causes of Male Infertility in Iranian Population; A systematic Review

Introduction: Infertility affects an estimated 15% of couples globally and in Iran, a quarter of couples experiences primary infertility. Males are found to be individually responsible for 20-30% of infertility cases and contribute to 50% of cases totally. When assisted reproductive technologies (ARTs) are used to acquire pregnancy, a sufficient (epi) genetic diagnosis of male infertility (MI) is of main matter to consider if a genetic abnormality will be transmit-ted to offspring. Infertility centers together with Infertility research centers had been founded since 1994 in Iran and many articles from research projects have been published.Materials and Methods: This literature investigated the possible genetic causes mechanisms underlying Iranian male infertility by extensive article searches.  First, we reviewed available data from the Google Scholar, PubMed, Scopus, Web of Science, IranMedex, MEDLIB, IranDoc and Scientific Information Database were searched for articles published until 2018, using the MeSH terms for a variety of chromosome abnormalities, Y-chromosome microdeletions, gene mutations, expression and polymorphisms, Male infertility and/or Iranian, regional and international population, to provides the evidence- based and a comprehensive, up-to- date evaluation of the multifactorial factors involved in Iranian infertile men.  Results: According to the strategy adopted initially, 274 manuscripts were found. After reviewing the titles, abstracts and manuscripts entirely cited, the total of 139 articles were obtained and selected according to the eligibility criteria. The 139 studies were divided into four predetermined categories that mentioned above.  Studies have good methodological validity. The sample is quite heterogeneous, given the very different design of the studies.Conclusion: MI is a complex, multi-factorial disease and the underlying reasons frequently remain unknown. It seems that the first line of genetic diagnosis in Iranian male infertility is similar to Global One. In all investigations conducted in Iran, there are vacancies in studies such as epigenetic modification studies, RNA (lncRNA, miRNA and piRNA) abnormalities, mutation detection and polymorphism studies in other genes involved in the spermatogenesis process. At present, we have a little information for some polymorphisms (MTHFR, GST, ER, and DAZL) and mutations (mtDNA, CATSPER) which require more extensive studies. Such articles help to find a better insight into the causes of infertility in the Iranian men's community and will provide valuable visions into the development of targeted personalized treatments for patients and the ascertainment of the reasons of idiopathic infertility.

Towards a Unified Framework for Adaptable Problematic Content Detection via Continual Learning

Detecting problematic content, such as hate speech, is a multifaceted and ever-changing task, influenced by social dynamics, user populations, diversity of sources, and evolving language. There has been significant efforts, both in academia and in industry, to develop annotated resources that capture various aspects of problematic content. Due to researchers' diverse objectives, the annotations are inconsistent and hence, reports of progress on detection of problematic content are fragmented. This pattern is expected to persist unless we consolidate resources considering the dynamic nature of the problem. We propose integrating the available resources, and leveraging their dynamic nature to break this pattern. In this paper, we introduce a continual learning benchmark and framework for problematic content detection comprising over 84 related tasks encompassing 15 annotation schemas from 8 sources. Our benchmark creates a novel measure of progress: prioritizing the adaptability of classifiers to evolving tasks over excelling in specific tasks. To ensure the continuous relevance of our framework, we designed it so that new tasks can easily be integrated into the benchmark. Our baseline results demonstrate the potential of continual learning in capturing the evolving content and adapting to novel manifestations of problematic content

Surgical Technique for Femoral Intramedullary Bent Nail Removal: A Case Report and Review of the Literature

A 21-year-old male patient was admitted with a severe right thigh deformity following a car accident. He experienced a previous history of Intramedullary interlocking femoral nail three years ago.The neurovascular examination was normal. The radiologic evaluation revealed a bent nail with 105° angular deformity in the sagittal plane.With a lateral approach to the apex of the fracture site, the Bent nail was cut by an 8mm cobalt drill, two parts of nail extracted; then fixation was performed by a new intramedullary interlocking nail and autogenous cancellous graft.The fracture healed properly without any complication 6 months after corrective surgery

Global optimisation for a developed price discrimination model:A signomial geometric programming-based approach

This paper presents a price discrimination model for a manufacturer who acts in two different markets. In order to have a fair price discrimination model and compare monopoly and competitive markets, it is assumed that there is no competitor in the first market (monopoly market) and there is a strong competitor in the other market (competitive market). The manufacturer objective is to maximize the total benefit in both markets. The decision variables are selling price, lot size, marketing expenditure, customer service cost, flexibility and reliability of production process, set up costs and quality of products. The proposed model in this paper is a signomial geometric programming problem which is difficult to solve and find the globally optimal solution. So, this signomial model is converted to a posynomial geometric type and using an iterative method, the globally optimal solution is found. To illustrate the capability of the proposed model, a numerical example is solved and the sensitivity analysis is implemented under different conditions