Enabling Big Data Analytics at Manufacturing Fields of Farplas Automotive

Digitization and data-driven manufacturing process is needed for today's industry. The term Industry 4.0 stands for today industrial digitization which is defined as a new level of organization and control over the entire value chain of the life cycle of products; it is geared towards increasingly individualized customer's high-quality expectations. However, due to the increase in the number of connected devices and the variety of data, it has become difficult to store and analyze data with conventional systems. The motivation of this paper is to provide an overview of the understanding of the big data pipeline, providing a real-time on-premise data acquisition, data compression, data storage and processing with Apache Kafka and Apache Spark implementation on Apache Ha-doop cluster, and identifying the challenges and issues occurring with implementation the Farplas manufacturing company, which is one of the biggest Tier 1 automotive supplier in Turkey, to study the new trends and streams related to topics via Industry 4.0.Comment: 8 page

On the origin of the Boson peak in globular proteins

We study the Boson Peak phenomenology experimentally observed in globular proteins by means of elastic network models. These models are suitable for an analytic treatment in the framework of Euclidean Random Matrix theory, whose predictions can be numerically tested on real proteins structures. We find that the emergence of the Boson Peak is strictly related to an intrinsic mechanical instability of the protein, in close similarity to what is thought to happen in glasses. The biological implications of this conclusion are also discussed by focusing on a representative case study.Comment: Proceedings of the X International Workshop on Disordered Systems, Molveno (2006

Transcription profiling reveals potential mechanisms of dysbiosis in the oral microbiome of rhesus macaques with chronic untreated SIV infection.

A majority of individuals infected with human immunodeficiency virus (HIV) have inadequate access to antiretroviral therapy and ultimately develop debilitating oral infections that often correlate with disease progression. Due to the impracticalities of conducting host-microbe systems-based studies in HIV infected patients, we have evaluated the potential of simian immunodeficiency virus (SIV) infected rhesus macaques to serve as a non-human primate model for oral manifestations of HIV disease. We present the first description of the rhesus macaque oral microbiota and show that a mixture of human commensal bacteria and "macaque versions" of human commensals colonize the tongue dorsum and dental plaque. Our findings indicate that SIV infection results in chronic activation of antiviral and inflammatory responses in the tongue mucosa that may collectively lead to repression of epithelial development and impact the microbiome. In addition, we show that dysbiosis of the lingual microbiome in SIV infection is characterized by outgrowth of Gemella morbillorum that may result from impaired macrophage function. Finally, we provide evidence that the increased capacity of opportunistic pathogens (e.g. E. coli) to colonize the microbiome is associated with reduced production of antimicrobial peptides

Severe leukocytoclastic vasculitis secondary to the use of a naproxen and requiring amputation: a case report

<p>Abstract</p> <p>Introduction</p> <p>Leukocytoclastic vasculitis (also known as hypersensitivity vasculitis and cutaneous necrotizing vasculitis) can present with various manifestations, which often delays the diagnosis and treatment. In order to show the importance of the early recognition of leukocytoclastic vasculitis, we present a case which occurred secondary to the use of a common pharmaceutical, naproxen. We were unable to find a case of leukocytoclastic vasculitis secondary to naproxen in the literature.</p> <p>Case presentation</p> <p>We present the case of a 33-year-old African American woman with below the knee and bilateral digital gangrene from hypersensitivity vasculitis secondary to the non-steroidal anti-inflammatory medication naproxen.</p> <p>Conclusion</p> <p>This is an original case report focusing on the rheumatologic management of leukocytoclastic vasculitis. However, other specialties, such as internal medicine, dermatology, infectious disease, general surgery and pathology, can gain valuable information by reviewing this case report. Reporting a case of leukocytoclastic vasculitis secondary to treatment with naproxen will advance our understanding of this disease etiology by adding yet another non-steroidal anti-inflammatory drug to the list of potential causes of leukocytoclastic vasculitis.</p

Electrical resistance of CNT-PEEK composites under compression at different temperatures

Electrically conductive polymers reinforced with carbon nanotubes (CNTs) have generated a great deal of scientific and industrial interest in the last few years. Advanced thermoplastic composites made of three different weight percentages (8%, 9%, and 10%) of multiwalled CNTs and polyether ether ketone (PEEK) were prepared by shear mixing process. The temperature- and pressure-dependent electrical resistance of these CNT-PEEK composites have been studied and presented in this paper. It has been found that electrical resistance decreases significantly with the application of heat and pressure

Chitosan/poly vinyl alcohol/graphene oxide based ph-responsive composite hydrogel films: drug release, anti-microbial and cell viability studies

The composite hydrogels were produced using the solution casting method due to the non-toxic and biocompatible nature of chitosan (CS)/polyvinyl alcohol (PVA). The best composition was chosen and crosslinked with tetraethyl orthosilicate (TEOS), after which different amounts of graphene oxide (GO) were added to develop composite hydrogels. Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), atomic force microscopy (AFM) and contact angle was used to analyze the hydrogels. The samples were also evaluated for swelling abilities in various mediums. The drug release profile was studied in phosphate-buffered saline (PBS) at a pH of 7.4. To predict the mechanism of drug release, the data were fitted into kinetic models. Finally, antibacterial activity and cell viability data were obtained. FTIR studies revealed the successful synthesis of CS/PVA hydrogels and GO/CS/PVA in hydrogel composite. SEM showed no phase separation of the polymers, whereas AFM showed a decrease in surface roughness with an increase in GO content. 100 µL of crosslinker was the critical concentration at which the sample displayed excellent swelling and preserved its structure. Both the crosslinked and composite hydrogel showed good swelling. The most acceptable mechanism of drug release is diffusion-controlled, and it obeys Fick’s law of diffusion for drug released. The best fitting of the zero-order, Hixson-Crowell and Higuchi models supported our assumption. The GO/CS/PVA hydrogel composite showed better antibacterial and cell viability behaviors. They can be better biomaterials in biomedical applications

Impact of High Mathematics Education on the Number Sense

In adult number processing two mechanisms are commonly used: approximate estimation of quantity and exact calculation. While the former relies on the approximate number sense (ANS) which we share with animals and preverbal infants, the latter has been proposed to rely on an exact number system (ENS) which develops later in life following the acquisition of symbolic number knowledge. The current study investigated the influence of high level math education on the ANS and the ENS. Our results showed that the precision of non-symbolic quantity representation was not significantly altered by high level math education. However, performance in a symbolic number comparison task as well as the ability to map accurately between symbolic and non-symbolic quantities was significantly better the higher mathematics achievement. Our findings suggest that high level math education in adults shows little influence on their ANS, but it seems to be associated with a better anchored ENS and better mapping abilities between ENS and ANS

Prediction of conformational B-cell epitopes from 3D structures by random forests with a distance-based feature

<p>Abstract</p> <p>Background</p> <p>Antigen-antibody interactions are key events in immune system, which provide important clues to the immune processes and responses. In Antigen-antibody interactions, the specific sites on the antigens that are directly bound by the B-cell produced antibodies are well known as B-cell epitopes. The identification of epitopes is a hot topic in bioinformatics because of their potential use in the epitope-based drug design. Although most B-cell epitopes are discontinuous (or conformational), insufficient effort has been put into the conformational epitope prediction, and the performance of existing methods is far from satisfaction.</p> <p>Results</p> <p>In order to develop the high-accuracy model, we focus on some possible aspects concerning the prediction performance, including the impact of interior residues, different contributions of adjacent residues, and the imbalanced data which contain much more non-epitope residues than epitope residues. In order to address above issues, we take following strategies. Firstly, a concept of 'thick surface patch' instead of 'surface patch' is introduced to describe the local spatial context of each surface residue, which considers the impact of interior residue. The comparison between the thick surface patch and the surface patch shows that interior residues contribute to the recognition of epitopes. Secondly, statistical significance of the distance distribution difference between non-epitope patches and epitope patches is observed, thus an adjacent residue distance feature is presented, which reflects the unequal contributions of adjacent residues to the location of binding sites. Thirdly, a bootstrapping and voting procedure is adopted to deal with the imbalanced dataset. Based on the above ideas, we propose a new method to identify the B-cell conformational epitopes from 3D structures by combining conventional features and the proposed feature, and the random forest (RF) algorithm is used as the classification engine. The experiments show that our method can predict conformational B-cell epitopes with high accuracy. Evaluated by leave-one-out cross validation (LOOCV), our method achieves the mean AUC value of 0.633 for the benchmark bound dataset, and the mean AUC value of 0.654 for the benchmark unbound dataset. When compared with the state-of-the-art prediction models in the independent test, our method demonstrates comparable or better performance.</p> <p>Conclusions</p> <p>Our method is demonstrated to be effective for the prediction of conformational epitopes. Based on the study, we develop a tool to predict the conformational epitopes from 3D structures, available at <url>http://code.google.com/p/my-project-bpredictor/downloads/list</url>.</p

Self-Reported and Actual Beta-Blocker Prescribing for Heart Failure Patients: Physician Predictors

Beta-blockers reduce mortality among patients with systolic heart failure (HF), yet primary care provider prescription rates remain low.To examine the association between primary care physician characteristics and both self-reported and actual prescription of beta-blockers among patients with systolic HF.Cross-sectional survey with supplementary retrospective chart review.Primary care providers at three New York City Veterans Affairs medical centers.Main outcomes were: 1) self-reported prescribing of beta-blockers, and 2) actual prescribing of beta-blockers among HF patients. Physician HF practice patterns and confidence levels, as well as socio-demographic and clinical characteristics, were also assessed.Sixty-nine of 101 physicians (68%) completed the survey examining self-reported prescribing of beta-blockers. Physicians who served as inpatient ward attendings self-reported significantly higher rates of beta-blocker prescribing among their HF patients when compared with physicians who did not attend (78% vs. 58%; p = 0.002), as did physicians who were very confident in managing HF patients when compared with physicians who were not (82% vs. 68%; p = 0.009). Fifty-one of these 69 surveyed physicians (74%) were successfully matched to 287 HF patients for whom beta-blocker prescribing data was available. Physicians with greater self-reported rates of prescribing beta-blockers were significantly more likely to actually prescribe beta-blockers (p = 0.02); however, no other physician characteristics were significantly associated with actual prescribing of beta-blockers among HF patients.Physician teaching responsibilities and confidence levels were associated with self-reported beta-blocker prescribing among their HF patients. Educational efforts focused on improving confidence levels in HF care and increasing exposure to teaching may improve beta-blocker presciption in HF patients managed in primary care