The Inhibitory Effect of Lactobacillus acidophilus and Lactobacillus plantarum against Candida albicans Associated with Denture Stomatitis

In this study Candida speices was diagnosed in 26 swab samples from patients with denture stomatitis , investigates the antagonism activity of Lactobacillus was investigated against the yeast of Candida albicans in vitro.Results revealed that The inhibition effect of Lactic Acid Bacteria against C.albicans was examined in solid medium, L.plantarum gave higher inhibition average 11mm followed by L.acidophillus with average 9 mm and, L.fermentum , L.casei with averages 7 mm. Whereas the filtrates, the highest inhibition zone were 20 and 16 mm by L. plantarum and L.acidophillus, respectively

Voldgiftsavtalens subjektive grenser: Når og på hvilken måte kan en voldgiftsklausul påberopes av eller overfor tredjemann?

MasteroppgaveJUS399MAJUR-2MAJU

Isoflavones and alzheimer’s disease: the effects of soy in diet

Pathologically, Alzheimer’s disease is a result of aggregation of amyloid peptides and protein tau in the brain forming neurofibrillary tangles which are highly toxic to neuronal circuits in the brain. Recent evidences report that apart from aging, estrogen deficiency is one of the risk factors predisposing to the development of Alzheimer’s disease. Isoflavones, also known as phytoestrogens, are metabolized by the body forming compounds that are known to interfere with neurotoxic pathways and through their anti-fibrillization effects they play a role in reducing apoptosis of neurons and glial cells and promote axonal regeneration. Experimental studies on transgenic models with Alzheimer’s disease as well as various observational and clinical trials suggest that dietary interventions with Isoflavones may have a significant role in improving portions of memory, cognition and decreasing the risk of Alzheimer’s disease

A Systematic Evidence Map Protocol of Time Activity Data in Exposure Science

Time Activity Data (TAD) describe the frequency, duration, and timing of human activities. Given that activity dictates the rate of contact a person has with an environmental hazard, activity data can be used to derive rigorous estimates of exposure. TAD have been used to support exposure estimation in a variety of contexts, though there has been no systematic characterization of the use of this approach in exposure science and environmental epidemiology. Here, we propose a protocol in pursuit of characterizing the body of peer-reviewed literature using TAD in the estimation of exposure to chemical, biological, and physical hazards in the form of an evidence map. This protocol details the proposed search strategy and plan for data extraction including study population demographics, methods of TAD collection, and study participant activities. Reflexive journaling, codebook development, and descriptive statistics will be conducted to analyze the data collected as part of this evidence map

GNSS-free outdoor localization techniques for resource-constrained IoT architectures : a literature review

Large-scale deployments of the Internet of Things (IoT) are adopted for performance improvement and cost reduction in several application domains. The four main IoT application domains covered throughout this article are smart cities, smart transportation, smart healthcare, and smart manufacturing. To increase IoT applicability, data generated by the IoT devices need to be time-stamped and spatially contextualized. LPWANs have become an attractive solution for outdoor localization and received significant attention from the research community due to low-power, low-cost, and long-range communication. In addition, its signals can be used for communication and localization simultaneously. There are different proposed localization methods to obtain the IoT relative location. Each category of these proposed methods has pros and cons that make them useful for specific IoT systems. Nevertheless, there are some limitations in proposed localization methods that need to be eliminated to meet the IoT ecosystem needs completely. This has motivated this work and provided the following contributions: (1) definition of the main requirements and limitations of outdoor localization techniques for the IoT ecosystem, (2) description of the most relevant GNSS-free outdoor localization methods with a focus on LPWAN technologies, (3) survey the most relevant methods used within the IoT ecosystem for improving GNSS-free localization accuracy, and (4) discussion covering the open challenges and future directions within the field. Some of the important open issues that have different requirements in different IoT systems include energy consumption, security and privacy, accuracy, and scalability. This paper provides an overview of research works that have been published between 2018 to July 2021 and made available through the Google Scholar database.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/

An Entrepreneurial Tourism Project through Agro-Tourism Farm in Iran

This study aims to provide a mechanism that helps to achieve sustainable development through the implementation of Agro-tourism plans. Clustering theory employed to provide a technical guideline for execution of the project as a sustainable approach for improvement of welfare of marginal communities. A medium scale entrepreneurial project proposed "“ "Agro-tourism complex". Results of this research produced useful implications for both public and private sector. Study revealed that such projects have potential for job creation, inverse migration, sustainability, and land conservation. The study is based on conceptual research method (Shuang et al, 2013). The study revealed that the welfare of marginalized indigenous communities, where the clusters of potentially available tourism products exist, could be improved dramatically if government policies and rural communities involve in shared vision

Semi-Automatic Reconstruction of Patient-Specific Stented Coronaries based on Data Assimilation and Computer Aided Design

Purpose The interplay between geometry and hemodynamics is a significant factor in the development of cardiovascular diseases. This is particularly true for stented coronary arteries. To elucidate this factor, an accurate patient-specific analysis requires the reconstruction of the geometry following the stent deployment for a computational fluid dynamics (CFD) investigation. The image-based reconstruction is troublesome for the different possible positions of the stent struts in the lumen and the coronary wall. However, the accurate inclusion of the stent footprint in the hemodynamic analysis is critical for detecting abnormal stress conditions and flow disturbances, particularly for thick struts like in bioresorbable scaffolds. Here, we present a novel reconstruction methodology that relies on Data Assimilation and Computer Aided Design. Methods The combination of the geometrical model of the undeployed stent and image-based data assimilated by a variational approach allows the highly automated reconstruction of the skeleton of the stent. A novel approach based on computational mechanics defines the map between the intravascular frame of reference (called L-view) and the 3D geometry retrieved from angiographies. Finally, the volumetric expansion of the stent skeleton needs to be self-intersection free for the successive CFD studies; this is obtained by using implicit representations based on the definition of Nef-polyhedra. Results We assessed our approach on a vessel phantom, with less than 10% difference (properly measured) vs. a customized manual (and longer) procedure previously published, yet with a significant higher level of automation and a shorter turnaround time. Computational hemodynamics results were even closer. We tested the approach on two patient-specific cases as well. Conclusions The method presented here has a high level of automation and excellent accuracy performances, so it can be used for larger studies involving patient-specific geometries

Low-Cost Traffic Sensing System Based on LoRaWAN for Urban Areas

The advent of Low Power Wide Area Networks (LPWAN) has enabled the feasibility of wireless sensor networks for environmental traffic sensing across urban areas. In this study, we explore the usage of LoRaWAN end nodes as traffic sensing sensors to offer a practical traffic management solution. The monitored Received Signal Strength Indicator (RSSI) factor is reported and used in the gateways to assess the traffic of the environment. Our technique utilizes LoRaWAN as a long-range communication technology to provide a largescale system. In this work, we present a method of using LoRaWAN devices to estimate traffic flows. LoRaWAN end devices then transmit their packets to different gateways. Their RSSI will be affected by the number of cars present on the roadway. We used SVM and clustering methods to classify the approximate number of cars present. This paper details our experiences with the design and real implementation of this system across an area that stretches for miles in urban scenarios. We continuously measured and reported RSSI at different gateways for weeks. Results have shown that if a LoRaWAN end node is placed in an optimal position, up to 96% of correct environment traffic level detection can be obtained. Additionally, we share the lComment: 7 pages, accepted to Emerging Topics in Wireless (EmergingWireless) in CoNEXT 202

Low-cost traffic sensing system based on LoRaWAN for urban areas

The advent of Low Power Wide Area Networks (LPWAN) has enabled the feasibility of wireless sensor networks for environmental traffic sensing across urban areas. In this study, we explore the usage of LoRaWAN end nodes as traffic sensing sensors to offer a practical traffic management solution. The monitored Received Signal Strength Indicator (RSSI) factor is reported and used in the gateways to assess the traffic of the environment. Our technique utilizes LoRaWAN as a long-range communication technology to provide a large-scale system. In this work, we present a method of using LoRaWAN devices to estimate traffic flows. LoRaWAN end devices then transmit their packets to different gateways. Their RSSI will be affected by the number of cars present on the roadway. We used SVM and clustering methods to classify the approximate number of cars present. This paper details our experiences with the design and real implementation of this system across an area that stretches for miles in urban scenarios. We continuously measured and reported RSSI at different gateways for weeks. Results have shown that if a LoRaWAN end node is placed in an optimal position, up to 96% of correct environment traffic level detection can be obtained. Additionally, we share the lessons learned from such a deployment for traffic sensing.5311-8814-F0ED | Sara Maria da Cruz Maia de Oliveira PaivaN/