Imipenem resistance in clinical Escherichia coli from Qom, Iran

OBJECTIVE: The emergence of metallo-\u3b2-lactamase-producing Enterobacteriaceae is a worldwide health concern. In this study, the first evaluation of MBL genes, bla IMP and bla VIM , in Escherichia coli resistant to imipenem isolated from urine and blood specimens in Qom, Iran is described. Three hundred urine and blood specimens were analysed to detect the presence of E. coli. Resistance to imipenem and other antimicrobials was determined by disk diffusion and MIC. MBL production was screened using CDDT. PCR was also carried out to determine the presence of bla IMP and bla VIM genes in imipenem-resistant isolates. RESULTS: In total, 160 E. coli isolates were collected from March to May 2016. According to disk diffusion, high-level of resistance (20%) to cefotaxime was observed, whereas the lowest (1%) was detected for tetracycline. In addition, five isolates showed resistance to imipenem with a MIC\u2009 65\u20094 \ub5g/mL. CDDT test confirmed that five isolates were MBL-producing strains, but no bla IMP and bla VIM genes were detected. Results of this study show a very low level of resistance to imipenem in our geographical area

Discrete alpha-skew-Laplace Distribution

Classical discrete distributions rarely support modelling data on the set of whole integers. In this paper, we shall introduce a flexible discrete distribution on this set, which can, in addition, cover bimodal as well as unimodal data sets. The proposed distribution can also be fitted to positive and negative skewed data. The distribution is indeed a discrete counterpart of the continuous alpha-skew-Laplace distribution recently introduced in the literature. The proposed distribution can also be viewed as a weighted version of the discrete Laplace distribution. Several distributional properties of this class such as cumulative distribution function, moment generating function, moments, modality, infinite divisibility and its truncation are studied. A simulation study is also performed. Finally, a real data set is used to show applicability of the new model comparing to several rival models, such as the discrete normal and Skellam distributions

The role of web-based promotion on the development of a relationship marketing model to enable sustainable growth

AbstractIn recent years the web-based Relationship Marketing (RM) has been receiving a great attention from e-marketing perspective. The RM is evolved as a contemporary marketing initiative, which can be applied to all types of industries. Concurrently, because of the advancement of the Information Technology, web-based promotion and market offering are considered as dominating business development tool. From this context, five grown sporting cases have been analysed to realise how web-based promotion influences RM to develop a sustainable growth model, where the cases have been utilising the RM and web-based promotion lucratively to attain and retain the key stakeholders to sustain their growth. Following the initial literature review, the websites of the cases have been scrutinised thoroughly as data collection tool. Nineteen RM indicators are identified as different RM perspectives. The cases are positioning web-based promotions and offerings underlying these RM indicators as a combined promotional effort to enhance competitive advantage. From the case analysis, the concept of stakeholder causal scope is evolved as identical with this combined promotional effort, as well as proportionate with at least one of the four identified growth strategies. Finally, the RM centred ‘Sustainable Growth Model’ has been developed through the synthesis of the impact of the web-based RM indicator focused combined promotional effort of the cases on the associated stakeholder causal scopes and their relevancy with the growth strategies. Reinforcing the model is established significantly for marketers in various industries to enhance competitive advantage aiming to sustain organisational growth

A big data approach to map the service quality of short-stay accommodation sharing

Purpose: The purpose of this paper is to map the service quality (SQ) of Airbnb, to provide additional insight for such top player of short-stay accommodation in the sharing economy context. Design/methodology/approach: A mixed-method approach is used in two phases. In the qualitative phase, 112,138 online review comments of Airbnb guests were analyzed to generate the service attributes. In the quantitative phase, an online survey (n = 814) was conducted to calculate the performance and importance values of extracted attributes to plot them in an Importance-Performance Analysis (IPA) matrix. Findings: A holistic image of the Airbnb extracted service attributes was presented through the IPA plot. Four types of SQ strategies were proposed, considering the actions priority. “Price reasonability” was the most important service attribute of Airbnb for guests, whereas “Check-in flexibility” was the best performed one. Practical implications: The results shed light on the most relevant SQ attributes of Airbnb and proposed suitable strategies that can prioritize relevant stakeholders’ actions and decisions. The study significantly contributes to all decision makers involved in the short-stay accommodation sharing industry to further understand and develop SQ. Originality/value: This research, using a comprehensive hybrid method, opens a lens to see more clearly the positioning of different attributes of Airbnb service from importance and performance viewpoints. As a contribution, the SQ of Airbnb was mapped by conducting an IPA for the first time in the literature

Absence of singular superconducting fluctuation corrections to thermal conductivity

We evaluate the superconducting fluctuation corrections to thermal conductivity in the normal state which diverge as T approaches T_c. We find zero total contribution for one, two and three-dimensional superconductors for arbitrary impurity concentration. The method used is diagrammatic many-body theory, and all contributions -- Aslamazov-Larkin (AL), Maki-Thompson (MT), and density-of-states (DOS) -- are considered. The AL contribution is convergent, whilst the divergences of the DOS and MT diagrams exactly cancel.Comment: 4 pages text; 2 figure

Deep Learning Model Based on ResNet-50 for Beef Quality Classification

Food quality measurement is one of the most essential topics in agriculture and industrial fields. To classify healthy food using computer visual inspection, a new architecture was proposed to classify beef images to specify the rancid and healthy ones. In traditional measurements, the specialists are not able to classify such images, due to the huge number of beef images required to build a deep learning model. In the present study, different images of beef including healthy and rancid cases were collected according to the analysis done by the Laboratory of Food Technology, Faculty of Agriculture, Kafrelsheikh University in January of 2020. The texture analysis of the beef surface of the enrolled images makes it difficult to distinguish between the rancid and healthy images. Moreover, a deep learning approach based on ResNet-50 was presented as a promising classifier to grade and classify the beef images. In this work, a limited number of images were used to present the research problem of image resource limitation; eight healthy images and ten rancid beef images. This number of images is not sufficient to be retrained using deep learning approaches. Thus, Generative Adversarial Network (GAN) was proposed to augment the enrolled images to produce one hundred eighty images. The results obtained based on ResNet-50 classification achieve accuracy of 96.03%, 91.67%, and 88.89% in the training, testing, and validation phases, respectively. Furthermore, a comparison of the current model (ResNet-50) with the classical and deep learning architecture is made to demonstrate the efficiency of ResNet-50, in image classification