Antibiotic susceptibility and high prevalence of extended spectrum beta-lactamase producing Escherichia coli in iranian broilers

Extended-spectrum β-lactamase (ESBL) producing Escherichia coli have rapidly spread worldwide and cause serious threats for public health. The study was conducted to determine the antibiotic resistance and characterization of ESBL producing E. coli strains isolated from broilers in Northern Iran. Antibiotic susceptibility test was done for a total of 100 isolates of E. coli, recovered from 240 broiler fecal samples at the slaughterhouse stage. ESBL production was screened using double-disc synergy test (DDST) and presence of four ESBL genes including blaPER, blaVEB, blaTEM and blaCTX-M was tested using PCR. Among 100 strains isolated from broilers, 53 were identified as ESBL-producing E. coli. All (100) ESBL positive isolates were typed according to the presence of one or two ESBL-associated genes. The most prevalent gene among ESBLs was CTX-M (60.3) and the PER gene was not present among isolates. All isolates in this study were resistant to colistin and nalidixic acid but were 100 sensitive to cefalexin and furazolidone. The results demonstrated the high prevalence of antibiotic resistant and ESBL producing E. coli among broilers which representing the risk of increasing these strains in human infections associated with food animals

Domain-wall excitations in the two-dimensional Ising spin glass

The Ising spin glass in two dimensions exhibits rich behavior with subtle differences in the scaling for different coupling distributions. We use recently developed mappings to graph-theoretic problems together with highly efficient implementations of combinatorial optimization algorithms to determine exact ground states for systems on square lattices with up to $10\,000\times 10\,000$ spins. While these mappings only work for planar graphs, for example for systems with periodic boundary conditions in at most one direction, we suggest here an iterative windowing technique that allows one to determine ground states for fully periodic samples up to sizes similar to those for the open-periodic case. Based on these techniques, a large number of disorder samples are used together with a careful finite-size scaling analysis to determine the stiffness exponents and domain-wall fractal dimensions with unprecedented accuracy, our best estimates being $\theta = -0.2793(3)$ and $d_\mathrm{f} = 1.273\,19(9)$ for Gaussian couplings. For bimodal disorder, a new uniform sampling algorithm allows us to study the domain-wall fractal dimension, finding $d_\mathrm{f} = 1.279(2)$. Additionally, we also investigate the distributions of ground-state energies, of domain-wall energies, and domain-wall lengths.Comment: 19 pages, 12 figures, 5 tables, accepted versio

Does the Number of Occupants in an Office Influence Individual Perceptions of Comfort and Productivity?-New Evidence from 5000 Office Workers

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Occurrence and antimicrobial resistance of emergent Arcobacter spp. isolated from cattle and sheep in Iran

This study is conducted to determine the occurrence and antimicrobial resistance of Arcobacter spp. isolated from clinically healthy food animals. A total of 308 samples from cattle (200) and sheep (108) were collected from Shiraz slaughterhouse, southern Iran to investigate the presence of the important Arcobacter spp. using cultivation and Polymerase Chain Reaction (PCR) methods. Antimicrobial susceptibility of Arcobacter isolates was determined for 18 antibiotics using disk diffusion method. Among 308 samples, 27 (8.7) and 44 (14.28) were positive for the presence of Arcobacter species with cultivation and PCR procedures, respectively. The predominant species was A. butzleri in both cattle (58.33) and sheep (55). In addition, concurrent incidence of the species was observed in 25 of the positive samples. All Arcobacter isolates were resistant to rifampicin, vancomycin, ceftriaxone, trimethoprim and cephalothin. The isolates showed high susceptibility to tetracycline, oxytetracycline, erythromycin, ciprofloxacin, kanamycin, amikacin, gentamicin and enrofloxacin. No significant difference among cattle and sheep isolates in resistance pattern was observed. The results indicate that cattle and sheep are significant intestinal carriers for Arcobacter spp. Moreover, tetracycline and aminoglycosides showed great effects on Arcobacter species in antibiogram test and can be used for treatment of human Arcobacter infections. © 2015 Elsevier Ltd

Bone mineral density is not related to angiographically diagnosed coronary artery disease

Based on data, there may exist an association between low bone mineral density (BMD) and atherosclerosis. Thisstudy aimed to investigate the association between BMD and coronary artery disease (CAD). In this study the possible association of BMD with CAD in 65 men with CAD and in 49 men with normal angiography as well as in 51 women with CAD and in 51 normal women was investigated. Both spinal and femoral BMD values for men were higher than those of women (P<0.05). Neither femoral nor spinal BMD values were different in patients with or without CAD. In addition, BMD values were not associated with the severity of CAD. Body massindex (BMI) was positively correlated with BMD both in men and women, whereas age and anti-diabetic treatment were linked with lower BMD in women. In conclusion, in this study CAD was not related to low BMD. However, BMI was an independent predictor of diminished BMD

Water degrading effects on the bond behavior in FRP-strengthened masonry

Fiber reinforced polymers are being extensively used for external strengthening of masonry structures. However, durability of this strengthening technique under environmental conditions is still under inves- tigation. Previous studies indicate that moisture plays an important role in the durability of bond between FRP and substrate. Moisture can cause degradation in the bond behavior and also in the mechan- ical properties of the constituent materials. This paper presents and discusses the results of an experi- mental investigation on the effects of moisture on the bond behavior in FRP-strengthened masonry bricks. The degradation in the bond performance has been investigated by performing pull-off and pull-out tests on the conditioned specimens. The change in the mechanical properties of the materials has also been investigated. Comparative analysis has been performed and the results are presented and critically discussed.This work was partly funded by project FP7-ENV-2009-1-244123-NIKER of the 7th Framework Program of the European Commission, which is gratefully acknowledged. The first author also acknowledges the financial support of the Portuguese Science Foundation (Fundacao de Ciencia e Tecnologia, FCT), through grant SFRH/BD/80697/2011

Data Driven and Machine Learning Based Modeling and Predictive Control of Combustion at Reactivity Controlled Compression Ignition Engines

Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), maximum pressure rise rate (MPRR), reactivity and stratification metrics as functions of fuel quantity (FQ), start of injection (SOI) timing and premixed ratio (PR) as the RCCI engine\u27s control variables. The identified model is then used for the design of a model predictive controller (MPC) to control crank angle for 50\% fuel burnt (CA50) for varying engine conditions on the actual RCCI engine. This study also established constrained multi-input multi-output (MIMO) model predictive controller (MPC) to track desired crank angle for 50\% fuel burnt and IMEP at various engine conditions. This research has demonstrated and implemented two fast and reliable method to model highly nonlinear RCCI combustion engine and develop control-oriented models for RCCI combustio

Role of the Big Data Analytic framework in Business Intelligence and its Impact: Need and Benefits

Big Data is mixed with huge, autonomous sources like decentralized and distributed control system. For organizations that use the conventional data processing mechanism to handle and archive these large data sets, these capabilities pose an extreme obstacle. A new model has to be defined and the existing framework must be re-evaluated for the analysis and management of big data. The word Business Intelligence (BI) applies to applications, technology and activities for commercial knowledge gathering, review, incorporation and presentation. Business Intelligence’s primary aim is to facilitate quicker and stronger business decision-making process.” Therefore, the strategic review of the literature must study the trend of Information System (IS) adoption factors as a well-designed strategic diagnostic tool that can be used for essential decision-making systems to enable more effective and reliable action plans. We started with discussing some frameworks required for strategic excellence by examining the potential approaches of Big Data Analytics (BDA) and Business Intelligence (BI). In the end, we would design an integrated application that functions as an organization's strategic performance management diagnostic tool. “In general, the emphasis and reach are on the corporate decision-making mechanism, there are some specifics on the analysis, but every conceivable tool and instrument is not specified, the concept is sufficiently concrete to assist in the creation of steps. This research paper therefore examines the position of the system for big data analytics and market intelligence

Threatened and Rare Ornamental Plants

The application of IUCN criteria and Red List Categories was done for ornamental plants. Main sources of the study were Glen’s book, Cultivated Plants of Southern Africa (Glen, 2002) and the Red List of Threatened Plants, IUCN (2001). About 500 threatened ornamental plants could be found and presented in respective lists. Rare ornamental plants with 209 species is the largest group followed by Vulnerable (147), Endangered (92), Indeterminate (37), Extinct (6) and finally Extinct/Endangered groups with 2 species. A weak positive correlation (r = +0.36 ) was found between the number of threatened species and the number of threatened ornamental species within the families

A Novel Detection Method for Grey Hole Attack in RPL

The Internet of Things (IoT) is a type of network that involves the Internet and things. This network consists of constrained devices that are connected through an IP protocol. In the IoT, a network with constrained devices is called 6LowPAN. RPL is a routing protocol to address the constraints and specific properties of these networks; though RPL puts the networks at risk through a large variety of attacks. The urgent need to develop secure routing solutions is required. In this paper, we investigated grey hole attacks and presented a detection method to identify and isolate the malicious node. The experiments show the proposed detection method improves PDR, Throughput and reduces PLR and E2ED in comparison with other scenarios