Sensors data collection framework using mobile identification with secure data sharing model

Sensors are the modules or electronic devices that are used to measure and get environmental events and send the captured data to other devices, usually computer processors allocated on the cloud. One of the most recent challenges is to protect and save the privacy issues of those sensors data on the cloud sharing. In this paper, sensors data collection framework is proposed using mobile identification and proxy re-encryption model for data sharing. The proposed framework includes: identity broker server, sensors managing and monitoring applications, messages queuing sever and data repository server. Finally, the experimental results show that the proposed proxy re-encryption model can work in real time

Who are the Users of Speed Regulation Assistance? Comparing Driver Characteristics of Casual and Intensive System Users

Speed regulation assistance can contribute to road safety provided that drivers use the systems on a regular basis. With the objective to gain knowledge about drivers who use Cruise Control and the Speed Limiter, a comparison of the characteristics of casual and intensive users was performed with survey data. The results show that gender and annual mileage play a role for the usage frequency of Cruise Control, whereas the usage frequency of the Speed Limiter depends on age. Consistent effects of the car use for business matters and the use of other invehicle technologies were found on the usage frequency of both systems. The predominant motive to reduce speeding found for both systems corresponds with the objective of speed regulation assistance as a safety measure. It was complemented with a comfort benefit perceived by Cruise Control users

Porous beta titanium alloy coated with a therapeutic biopolymeric composite to improve tribomechanical and biofunctional balance

Tooth loss is common in patients struggling with dental cavities, periodontal diseases, and tumors, as well as those who abuse tobacco or drugs. In this scenario, dental implants have become the primary treatment option for complete or partial tooth loss. Dental implant failure can be caused by stress shielding phenomenon, poor osseointegration, or to bacterial infections. In the present study, a joint solution to these limitations is proposed using a variety of porous β-titanium substrates using powder Ti35Nb7Zr5Ta alloy and employing the spacer-holder approach (ammonium bicarbonate) to obtain a variety of porosity percentage (30, 40, and 50 vol%), and pore diameters in 100–200 μm, that has been characterized in terms of its size distribution, density, morphology, chemical composition, compaction ability and Vickers micro-hardness. Furthermore, porosity, microstructure (Archimedes and image analysis) and tribomechanical behavior (P-h curves and scratch tests) experiments were performed to study and characterize the porous substrates. Polyvinyl alcohol (PVA)/poly-ε-caprolactone (PCL) containing silver nanoparticles (AgNPs), as antibacterial composite, was employed to infiltrate β-Ti disks. Scanning electron microscopy was used to determine the coating morphology, thickness, and infiltration of the porous substrates. Wettability and SBF experiments were also carried out to investigate hydrophobicity and potential biofunctionality. The results suggested how the porosity of the β-Ti alloy affects the mechanical characteristics and the wettability of the substrate that was successfully infiltrated to exert an antimicrobial behavior

Applications and multidisciplinary perspective on 3D printing techniques: Recent developments and future trends

In industries as diverse as automotive, aerospace, medical, energy, construction, electronics, and food, the engineering technology known as 3D printing or additive manufacturing facilitates the fabrication of rapid prototypes and the delivery of customized parts. This article explores recent advancements and emerging trends in 3D printing from a novel multidisciplinary perspective. It also provides a clear overview of the various 3D printing techniques used for producing parts and components in three dimensions. The application of these techniques in bioprinting and an up-to-date comprehensive review of their positive and negative aspects are covered, as well as the variety of materials used, with an emphasis on composites, hybrids, and smart materials. This article also provides an updated overview of 4D bioprinting technology, including biomaterial functions, bioprinting materials, and a targeted approach to various tissue engineering and regenerative medicine (TERM) applications. As a foundation for anticipated developments for TERM applications that could be useful for their successful usage in clinical settings, this article also examines present challenges and obstacles in 4D bioprinting technology. Finally, the article also outlines future regulations that will assist researchers in the manufacture of complex products and in the exploration of potential solutions to technological issues

CSI-OMIM - Clinical Synopsis Search in OMIM

<p>Abstract</p> <p>Background</p> <p>The OMIM database is a tool used daily by geneticists. Syndrome pages include a Clinical Synopsis section containing a list of known phenotypes comprising a clinical syndrome. The phenotypes are in free text and different phrases are often used to describe the same phenotype, the differences originating in spelling variations or typing errors, varying sentence structures and terminological variants.</p> <p>These variations hinder searching for syndromes or using the large amount of phenotypic information for research purposes. In addition, negation forms also create false positives when searching the textual description of phenotypes and induce noise in text mining applications.</p> <p>Description</p> <p>Our method allows efficient and complete search of OMIM phenotypes as well as improved data-mining of the OMIM phenome. Applying natural language processing, each phrase is tagged with additional semantic information using UMLS and MESH. Using a grammar based method, annotated phrases are clustered into groups denoting similar phenotypes. These groups of synonymous expressions enable precise search, as query terms can be matched with the many variations that appear in OMIM, while avoiding over-matching expressions that include the query term in a negative context. On the basis of these clusters, we computed pair-wise similarity among syndromes in OMIM. Using this new similarity measure, we identified 79,770 new connections between syndromes, an average of 16 new connections per syndrome. Our project is Web-based and available at <url>http://fohs.bgu.ac.il/s2g/csiomim</url></p> <p>Conclusions</p> <p>The resulting enhanced search functionality provides clinicians with an efficient tool for diagnosis. This search application is also used for finding similar syndromes for the candidate gene prioritization tool S2G.</p> <p>The enhanced OMIM database we produced can be further used for bioinformatics purposes such as linking phenotypes and genes based on syndrome similarities and the known genes in Morbidmap.</p

Making effective use of healthcare data using data-to-text technology

Healthcare organizations are in a continuous effort to improve health outcomes, reduce costs and enhance patient experience of care. Data is essential to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text is an important medium to make data accessible. Financial reports are produced to assess healthcare organizations on some key performance indicators to steer their healthcare delivery. Similarly, at a clinical level, data on patient status is conveyed by means of textual descriptions to facilitate patient review, shift handover and care transitions. Likewise, patients are informed about data on their health status and treatments via text, in the form of reports or via ehealth platforms by their doctors. Unfortunately, such text is the outcome of a highly labour-intensive process if it is done by healthcare professionals. It is also prone to incompleteness, subjectivity and hard to scale up to different domains, wider audiences and varying communication purposes. Data-to-text is a recent breakthrough technology in artificial intelligence which automatically generates natural language in the form of text or speech from data. This chapter provides a survey of data-to-text technology, with a focus on how it can be deployed in a healthcare setting. It will (1) give an up-to-date synthesis of data-to-text approaches, (2) give a categorized overview of use cases in healthcare, (3) seek to make a strong case for evaluating and implementing data-to-text in a healthcare setting, and (4) highlight recent research challenges.Comment: 27 pages, 2 figures, book chapte

Circulating Monocyte Chemoattractant Protein-1 and Risk of Stroke: A Meta-Analysis of Population-Based Studies Involving 17,180 Individuals.

RATIONALE: Pro-inflammatory cytokines have been identified as potential targets for lowering vascular risk. Experimental evidence and Mendelian randomization suggest a role of monocyte-chemoattractant protein-1 (MCP-1) in atherosclerosis and stroke. However, data from large-scale observational studies are lacking. OBJECTIVE: To determine whether circulating levels of MCP-1 are associated with risk of incident stroke in the general population. METHODS AND RESULTS: We used previously unpublished data on 17,180 stroke-free individuals (mean age 56.7{plus minus}8.1 years; 48.8% males) from six population-based prospective cohort studies and explored associations between baseline circulating MCP-1 levels and risk of any stroke, ischemic stroke, and hemorrhagic stroke over a mean follow-up interval of 16.3 years (280,522 person-years at risk; 1,435 incident stroke events). We applied Cox proportional hazard models and pooled hazard ratios (HR) using random-effects meta-analyses. Following adjustments for age, sex, race, and vascular risk factors, higher MCP-1 levels were associated with increased risk of any stroke (HR per 1 SD increment in ln-transformed MCP-1: 1.07, 95%CI: 1.01-1.14). Focusing on stroke subtypes, we found a significant association between baseline MCP-1 levels and higher risk of ischemic stroke (HR: 1.11, [1.02-1.21]), but not hemorrhagic stroke (HR: 1.02, [0.82-1.29]). The results followed a dose-response pattern with a higher risk of ischemic stroke among individuals in the upper quartiles of MCP-1 levels as compared to the 1st quartile (HRs: 2nd quartile: 1.19 [1.00-1.42]; 3rd quartile: 1.35, [1.14-1.59]; 4th quartile: 1.38, [1.07-1.77]). There was no indication for heterogeneity across studies and in a sub-sample of four studies (12,516 individuals) the risk estimates were stable after additional adjustments for circulating levels of interleukin-6 and high-sensitivity C-reactive protein. CONCLUSIONS: Higher circulating levels of MCP-1 are associated with increased long-term risk of stroke. Our findings along with genetic and experimental evidence suggest that MCP-1-signaling might represent a therapeutic target to lower stroke risk.M. Georgakis is funded by scholarships from the German Academic Exchange Service (DAAD) and Onassis Foundation. The ARIC study has been funded in whole or in part with Federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, Department of Health and Human Services, under Contract nos. (HHSN268201700001I, HHSN268201700002I, HHSN268201700003I, HHSN268201700005I, HHSN268201700004I). The DHS study was funded by a grant from the Donald W. Reynolds Foundation. The EPIC-Norfolk study is funded by grants from the Medical Research Council UK (G9502233, G0401527) and Cancer Research UK (C864/A8257, C864/A2883). FHS is supported by the National Heart, Lung and Blood Institute’s Framingham Heart Study (Contract No. N01-HC-25195 and No. HHSN268201500001I and 75N92019D00031), received funding by grants from the National Institute of Aging (R01s AG054076, AG049607, AG059421, U01-AG049505, AG058589 and AG052409) and the National Institute of Neurological Disorders and Stroke (R01 NS017950, UH2 NS100605), as well as grants for the MCP-1 measurements by NIH (1RO1 HL64753, R01 HL076784, 1 R01 AG028321). The KORA study was initiated and financed by the Helmholtz Zentrum München – German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of Bavaria. Furthermore, KORA research was supported within the Munich Center of Health Sciences (MC-Health), Ludwig-Maximilians-Universität, as part of LMUinnovativ. The MDCS-CV study has been supported with funding from the Swedish Research Council, Swedish Heart and Lung Foundations, and the Swedish Foundation for Strategic Research. This project has received funding from the European Union’s Horizon 2020 research and innovation programme (No 666881), SVDs@target (to M. Dichgans) and No 667375, CoSTREAM (to M. Dichgans); the DFG as part of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy – ID 390857198) and the CRC 1123 (B3) (to M. Dichgans); the Corona Foundation (to M. Dichgans); the Fondation Leducq (Transatlantic Network of Excellence on the Pathogenesis of Small Vessel Disease of the Brain)(to M. Dichgans); the e:Med program (e:AtheroSysMed) (to M. Dichgans) and the FP7/2007-2103 European Union project CVgenes@target (grant agreement number Health-F2-2013-601456) (to M. Dichgans)

Self-reported use of complementary and alternative medicine (CAM) products in topical treatment of diabetic foot disorders by diabetic patients in Jeddah, Western Saudi Arabia

<p>Abstract</p> <p>Background</p> <p>There is little published on current Saudi diabetic patients' practices when they are exposed to foot disorders such as open wound, ulcer, and skin cracks. These factors are usually influenced by local culture and communities beliefs. The aim of the current study was to identify the pattern of patients' use of CAM products in dealing with diabetic foot disorders topically in a group of diabetic patients.</p> <p>Findings</p> <p>A Cross-sectional descriptive study of a representative cohort of diabetic patients living in Jeddah, Saudi Arabia was designed. A pre-designed questionnaire to identify local diabetics' practices in dealing topically with foot disorders including open wound, chronic ulcer, and skin cracks was designed. Questionnaire was administered by a group of trained nutrition female students to diabetics face to face living in their neighborhood. A total of 1634 Saudi diabetics were interviewed. Foot disorders occurred in approximately two thirds of the respondents 1006 (61.6%). Out of the 1006 patients who had foot disorders, 653 reported trying some sort of treatment as 307 patients (47.1%) used conventional topical medical treatment alone, 142 (21.7%) used CAM products alone, and 204 (31.2%) used both treatments. The most commonly used CAM product by the patients was Honey (56.6%) followed by Commiphora Molmol (Myrrh) in (37.4%) and Nigellia Sativa (Black seed) in (35.1%). The least to be used was Lawsonia inermis (Henna) in (12.1%). Ten common natural preparations used topically to treat diabetic foot disorders were also identified.</p> <p>Conclusions</p> <p>The use of CAM products in topical treatment of diabetic foot disorders is fairly common among Saudi diabetic patients. Honey headed the list as a solo topical preparation or in combination with other herbs namely black seeds and myrrh. The efficacy of the most common products needs further research.</p

Are decision trees a feasible knowledge representation to guide extraction of critical information from randomized controlled trial reports?

<p>Abstract</p> <p>Background</p> <p>This paper proposes the use of decision trees as the basis for automatically extracting information from published randomized controlled trial (RCT) reports. An exploratory analysis of RCT abstracts is undertaken to investigate the feasibility of using decision trees as a semantic structure. Quality-of-paper measures are also examined.</p> <p>Methods</p> <p>A subset of 455 abstracts (randomly selected from a set of 7620 retrieved from Medline from 1998 – 2006) are examined for the quality of RCT reporting, the identifiability of RCTs from abstracts, and the completeness and complexity of RCT abstracts with respect to key decision tree elements. Abstracts were manually assigned to 6 sub-groups distinguishing whether they were primary RCTs versus other design types. For primary RCT studies, we analyzed and annotated the reporting of intervention comparison, population assignment and outcome values. To measure completeness, the frequencies by which complete intervention, population and outcome information are reported in abstracts were measured. A qualitative examination of the reporting language was conducted.</p> <p>Results</p> <p>Decision tree elements are manually identifiable in the majority of primary RCT abstracts. 73.8% of a random subset was primary studies with a single population assigned to two or more interventions. 68% of these primary RCT abstracts were structured. 63% contained pharmaceutical interventions. 84% reported the total number of study subjects. In a subset of 21 abstracts examined, 71% reported numerical outcome values.</p> <p>Conclusion</p> <p>The manual identifiability of decision tree elements in the abstract suggests that decision trees could be a suitable construct to guide machine summarisation of RCTs. The presence of decision tree elements could also act as an indicator for RCT report quality in terms of completeness and uniformity.</p