Variation of antibiotic resistance in Salmonella Enteritidis,Escherichia coli O157:H7, and Listeria monocytogenes after exposure to acid,salt, and cold stress

Bacteria with antibiotic-resistant could seriously threaten to human health, increasing the treatment cost for infections and negatively affecting treatment outcomes. Stress adaptation is one possible mechanism for the acquisition or enhancement of antibiotic resistance in bacteria as a result of cross-protection. In this study, the effects of acid, salt, and cold stress on the antibiotic resistance of Salmonella Enteritidis, Listeria monocytogenes, and Escherichia coli O157:H7 were investigated using the disc diffusion method. For S. Enteritidis, acidic growth conditions increased resistance to ciprofloxacin and erythromycin (p < .05), and addition of 4% NaCl to growth media decreased resistance to chloramphenicol (p < .05). Irrespective of pH and the NaCl concentration of the growth medium, refrigerated E. coli O157:H7 showed increased resistance to amoxycillin, ciprofloxacin, gentamicin, streptomycin, and erythromycin (p < .05). Acid-adapted L. monocytogenes showed decreased the resistance to amoxycillin, ampicillin, chloramphenicol, ciprofloxacin, erythromycin, gentamicin, streptomycin, and tetracycline (p < .05). In conclusion, prolonged exposure of foodborne pathogens to acid, salt, and cold stress alters their antibiotic resistance. However, the effect of acid, salt, and cold stress on bacterial antibiotic resistance depend on both the bacterial species and the specific antibiotic. Therefore, multiple factors need to be considered for a foodborne antimicrobial resistant risk assessment.     

Effect of hyperbranched poly(citric polyethylene glycol) with various polyethylene glycol chain lengths on starch plasticization and retrogradation

A series of hyperbranched poly(citric polyethylene glycol) (PCPEG) materials with varied polyethylene glycol (PEG) chain lengths as plasticizers were mixed with maize starch (MS) via cooking and film‐forming. The structure, pasting property, plasticization, aging property, moisture absorption and compatibility of plasticized starches were studied by means of Fourier transform infrared spectroscopy, X‐ray diffraction, rapid viscosity analysis, tension testing, moisture absorption measurements and scanning electron microscopy. Compared with PEG and citric acid, PCPEG was more effective in promoting starch chain movement and inhibiting the retrogradation of starch film. Also, PCPEG/MS had smaller moisture content. The longer the plasticizer chain, the better were the aging resistance and moisture resistance of starch. But with an increase of PEG chain length, mechanical properties of PCPEG/MS deteriorated and the compatibility between PCPEG and MS decreased. The hyperbranched derivative of PEG with longer chain exhibited improved plasticization and compatibility with starch. © 2019 Society of Chemical Industry     

一种基于机器视觉的表面缺陷快速检测方法

实际生产过程中,产品表面会不同程度地留下污渍和印记,这对基于机器视觉的表面缺陷识别带来严重干扰.基于图案统计分析的识别方法速度虽快,但抗干扰能力弱,出现较高的误判率.基于深度学习的人工智能识别方法计算量巨大,速度慢,难以满足生产实际的高速要求.因此介绍一种改进SIFT算法,并给出了相关参数的设置方法和经验公式,通过实际表面缺陷的检测,对比验证了SIFT算法较强的鲁棒性和抗干扰能力,以及相关参数设置方法的正确性和可行性.实验数据表明,SIFT算法在凹陷类和斑点类缺陷的检出率上具有明显优越性,在裂纹类的误检率上也具有较大优势.特别是在有噪声图像干扰情况下,检出率比神经网络提升了20％,误检率降低了3％.     

一种使用多跳事实的端到端知识库实体描述生成方法

自动化实体描述生成有助于进一步提升知识图谱的应用价值,而流畅度高是实体描述文本的重要质量指标之一。该文提出使用知识库上多跳的事实来进行实体描述生成,从而贴近人工编撰的实体描述的行文风格,提升实体描述的流畅度。该文使用编码器—解码器框架,提出了一个端到端的神经网络模型,可以编码多跳的事实,并在解码器中使用关注机制对多跳事实进行表示。该文的实验结果表明,与基线模型相比,引入多跳事实后模型的BLEU-2和ROUGE-L等自动化指标分别提升约8.9个百分点和7.3个百分点。     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

Software assurance practices for mobile applications

Mobile software applications have to cope with a particular environment that involves small size, limited resources, high autonomy requirements, competitive business models and many other challenges. To provide development guidelines that respond to these needs, several practices have been introduced; however, it is not clear how these guidelines may contribute to solve the issues present in the mobile domain. Furthermore, the rapid evolution of the mobile ecosystem challenges many of the premises upon which the proposed practices were designed. In this paper, we present a survey of the literature on software assurance practices for mobile applications, with the objective of describing them and assessing their contribution and success. We identified, organized and reviewed a body of research that spans in three levels: software development processes, software product assurance practices, and software implementation practices. By carrying out this literature survey, we reviewed the different approaches that researchers on Software Engineering have provided to address the needs that raise in the mobile software development arena. Moreover, we review the evolution of these practices, identifying how the constant changes and modernization of the mobile execution environment has impacted the methods proposed in the literature. Finally, we introduced discussion on the application of these practices in a real productive setting, opening an area for further research that may determine if practitioners have followed the proposed assurance paradigms.     

Intrinsic CFRP-metal-hybrids with rubber interface for the improvement of the damping behaviour

This paper presents an integrated passive damping approach in hybrid metal-CFRP parts for structural applications. In this concept a viscoelastic material is embedded in the joint zone of the hybrid component. To examine the connection strength single-lap-joint specimens were produced and tested and the influence of the used material combinations, different surface structures, and different process parameters i.e. the moment of cross-linking were evaluated. Afterwards, the metal-CFRP hybrids were tested in quasi-static tests to assess their connection strength and failure behaviour. Dynamic cyclic tensile tests with step-wise increased loading conditions were performed to determine the specimens damping behaviour and to estimate their fatigue performance. Finally, these results are compared to a state of the art metal-CFRP hybrid with rivets connecting both materials.     

On stochastic comparisons of finite mixtures for some semiparametric families of distributions

In this paper, we consider the classical finite mixture model, which is an effective tool for modeling lifetime distributions for random samples from heterogeneous populations. We discuss new results on stochastic comparison for two finite mixtures when each of them is drawn from one of the following semiparametric families, i.e., proportional hazards, accelerated lifetime and proportional reversed hazards.