Ranking Of Sites Research Articles

The impact of psychopathology, social adversity and stress-relevant DNA methylation on prospective risk for post-traumatic stress: A machine learning approach

BackgroundA range of factors have been identified that contribute to greater incidence, severity, and prolonged course of post-traumatic stress disorder (PTSD), including: comorbid and/or prior psychopathology; social adversity such as low socioeconomic position, perceived discrimination, and isolation; and biological factors such as genomic variation at glucocorticoid receptor regulatory network (GRRN) genes. This complex etiology and clinical course make identification of people at higher risk of PTSD challenging. Here we leverage machine learning (ML) approaches to identify a core set of factors that may together predispose persons to PTSD. MethodsWe used multiple ML approaches to assess the relationship among DNA methylation (DNAm) at GRRN genes, prior psychopathology, social adversity, and prospective risk for PTS severity (PTSS). ResultsML models predicted prospective risk of PTSS with high accuracy. The Gradient Boost approach was the top-performing model with mean absolute error of 0.135, mean square error of 0.047, root mean square error of 0.217, and R2 of 95.29%. Prior PTSS ranked highest in predicting the prospective risk of PTSS, accounting for >88% of the prediction. The top ranked GRRN CpG site was cg05616442, in AKT1, and the top ranked social adversity feature was loneliness. ConclusionMultiple factors including prior PTSS, social adversity, and DNAm play a role in predicting prospective risk of PTSS. ML models identified factors accounting for increased PTSS risk with high accuracy, which may help to target risk factors that reduce the likelihood or course of PTSD, potentially pointing to approaches that can lead to early intervention. LimitationOne of the limitations of this study is small sample size.

Complex raw materials and the supply system: Mineralogical and geochemical study of the jade artefacts of the Longshan Culture (2400–2000 bce) from Sujiacun site in coastal Shandong, China

X‐ray fluorescence (XRF), X‐ray diffraction (XRD) and Raman spectroscopy were employed to analyse the chemical compositions and phase structures of nine pieces of jade artefacts unearthed from Sujiacun, a Longshan Culture (2400–2000 bce) site in coastal Shandong, eastern China. The results of the analyses indicated these samples were primarily made from multiple raw mineral materials, including antigorite, actinolite, clinochlore, turquoise and muscovite. No nephrite was recovered from the Sujiacun site. This is strikingly different from other top‐ranking settlements of Longshan Culture, such as Dantu, Liangchengzhen and Xizhufeng, in which nephrite was the main material of jade artefacts. This may reflect the distinctions in the supply system of jade raw materials among different rankings of Longshan period sites. In addition, laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) was used to analyse the composition of the rare earth elements of serpentine jade. These preliminary results were compared with published data on the composition of serpentine jade and it was found that the Sujiacun serpentine jade artefacts were likely sourced from the Taishan jade deposit.

Identification of Potential Eco-tourism Site Suitability Using AHP and GIS in Dinsho District of Bale Zone, Southeastern Ethiopia

Ecotourism is one of the fastest growing sectors in the tourism industry at present. Ecotourism has attracted increasing attention in recent years, not only as an alternative to mass tourism, means of economic development and environmental conservation. The present study is identifying the potential ecotourism sites in Dinsho district of Bale Zone, Southeastern Ethiopia using Geographic information system (GIS) and Analytic Hierarchy Process (AHP). This study was assessed the potential suitable areas for ecotourism based on Landscape (land use land cover), Topography (elevation, slope, aspect) and Climate Characteristics (rainfall). These factors were selected based to the literature reviews and the data availability. First, a resource inventory and a list of ecotourism criteria and factors were developed using the AHP method on ArcGIS 10.5. At the next stage GIS techniques were used to measure the ranking of different sites according to the set factors and identify those with the high, moderate, less and not suitable. Later, the ecotourism potential suitability map for ecotourism was created, based on the linear combination of the criteria and factors with their respective weights. The degree of suitability of each factor was classified as highly suitable, moderately suitable, less suitable and not suitable for ecotourism. The result of the study revealed that highly suitable for ecotourism potential area accounts for 24.43% (15873.6 ha), moderately suitable accounts 15.48% (10062.7ha), less potential areas 52.79% (34298.4 ha) and 7.30% (4739.7ha) not suitable in the study area. Therefore, this study shows that the district has high potential of ecotourism which can contribute to the livelihood of the community through sustainable natural resource management. GIS and AHP are essential and effective for ecotourism site suitability selection. Keywords: Ecotourism, Suitability, Analytic Hierarchy Process, GIS, Factors DOI: 10.7176/JTHS/52-02 Publication date: December 31 st 2020

The Impact of Informational Content of Intangible Assets on the Firm Performance: Evidence from MENA Countries Stock Exchanges

This paper attempts to investigate the impact of informational content of intangible assets on the firm performance. Informational content of intangible assets has been measured by “Current Site Rank” (RAN), “No. of Engagements on the Site” (ENG), “No. of Site Visitors” (VIS), “Change in No. of Site Visitors” (CIV), “Bounce Rate” (BOU) and “Change in Bounce Rate” (CIB), while firm performance has been measured by Price to Tangibles Ratio (PTR) and “Return on Assets” (ROA). This has been applied on companies listed in stock exchanges of 4 MENA countries (Egypt, KSA, Tunisia and UAE), on daily basis during the 4th quarter 2019 and 1st quarter 2020. Results indicate that Price to Tangibles Ratio” seem to be affected by each of “No. of Site Visitors”, “Change in No. of Site Visitors”, and “Change in Bounce Rate”. Besides, “Return on Assets” (ROA) may have been affected by each of “Current Site Rank”, “No. of Engagements on the Site” and “Bounce Rate”.

Optimum Municipal Solid Waste Disposal Site Selection Using Gis Based Multi-Criteria Decision Analysis: A Case of Nekemte Town, Oromia Regional State, Ethiopia

Solid waste is a major global concern particularly in developing countries. Municipal landfill site selection is becoming the main challenge as a result of various factors. To make the site to be selected environmentally sound, socially acceptable and economically feasible, GIS based multi-criteria decision analysis ( MCDA ) method that has the capability to combine spatially referenced data with experts’ value judgment was used in this study. The analytic hierarchy process ( AHP ) was the major technique of MCDA used to derive the weights of the nine criteria considered – distance from road network, geology, distance from fault lines, soil permeability, slope, distance from rivers/streams, distance from lakes, distance from the built-up areas and land use/land cover types. After creating Multiple-ring Buffers for road network, fault lines, rivers/streams, lakes and built-up areas by reviewing various literatures, all the criteria were standardized by reclassifying them into suitability classes. The weights of the reclassified criteria were derived using AHP Pair-wise Comparison Matrix in Microsoft Excel and then combined together using the Weighted Overlay tool in ArcGIS to produce the composite suitability map of the study area. Accordingly, 0.43% and 0.02% of the study area are unsuitable and highly suitable, respectively. The remaining 41.64%, 51.12%, and 6.8% of the study area are poorly suitable, moderately suitable and suitable, respectively. The raster composite suitability map of study area was then converted into vector map to select candidate disposal sites. Accordingly, six candidate municipal solid waste disposal sites were selected, evaluated with respect to their area (size), distance from center and distance from the nearby built-up area. They were weighted with respect to these three evaluating criteria using AHP Pair-wise Comparison Matrix and finally mapped and ranked. The first, second and third ranked candidate disposal sites have an area of 46 ha, 29 ha and 35ha, respectively. The first and second candidate sites are located in Burka Jato sub-town, while the third one is located in Sorga sub-town. In order to reduce the adverse impact of surface water pollution in the downstream, runoff should not flow into and out of the MSW disposal sites. To minimize groundwater pollution, detailed investigation on sub-surface condition of the site should be made during design. Greenhouse gases collection should also be designed to reduce air pollution. Keywords: multi-criteria decision analysis; analytic hierarchy process; Pair-wise Comparison Matrix; Weight Overlay DOI: 10.7176/JEES/10-11-01 Publication date: November 30 th 2020

The readability and reliability of Greek web-based information on rhinoplasty

BACKGROUND: A constantly increasing number of patients seek for Internet sources on diseases or surgical operations before consulting with a medical specialist. Popular among surgical procedures is rhinoplasty. Depending on the quality of information, patient decision making, expectations and satisfaction may be affected in a positive or negative manner. The aim of this study is to objectively assess the readability and reliability of Internet health information in the Greek language on rhinoplasty. MATERIALS and METHODS: We performed a search in the Google engine using a combination of Greek language terms relating to rhinoplasty. After collation and rejection of duplicate, irrelevant or invalid links, the first twenty highest ranking Greek Web sites were analyzed using the on-line Greek Language Centre Literacy Level calculator, the on-line Greek text readability calculator, and the DISCERN publication quality assessment instrument. RESULTS: From the twenty Web sites, 40% required very good and 35% required excellent Greek Language Literacy Level for com- prehension. Content reading was considered quite difficult in 15%, difficult in 60% and very difficult in 25% of the Web sites. The quality of the Web sites appraised by the DISCERN instrument was low to medium. No correlation was found between Google site rank and DISCERN total score. CONCLUSIONS: In general, the reliability of Internet health information in the Greek language on rhinoplasty is mediocre at best and the readability of the respective texts is lower than recommended. Patients should be cautious and always consult one or more medical specialists before reaching a final decision. Evaluation and accreditation of Internet health information sites would greatly assist on sound patient decision-making and satisfaction.

Definition of Phishing Sites Based on the Team Model of Fuzzy Neural Networks

This paper solves the problem of defining phishing sites based on building a team model of fuzzy neural networks (FNNs). The main methods of phishing are analyzed. Attention is drawn to the fact that phishing has become widespread on the Internet through the use of phishing sites. The expediency of identifying phishing sites based on the analysis of their URLs is noted. The main approaches to identifying phishing sites are described. The need toimplement an approach based on machine learning by constructing fuzzy neural networks for the creation of fuzzy knowledge bases and their use to identify phishing sites is actualized. Automating the identification of phishing sites based on the neuro-fuzzy approach required solving the problems of collecting and preparing initial data for analysis,building a team model of fuzzy neural networks, and forming a fuzzy knowledge base, as well as conducting research, and assessing the accuracy of identifying phishing sites based on the constructed model. The initial data was formed from various sources. The total amount of initial data was 50,000. Of these, 10 input features for analysis were selected by an expert. After carrying out the correlation analysis, 4 most informative input features were selected for analysis: site lifetime, site rank, URL length, and the registered status of the site. An output feature of the site was its type: phishing or legitimate. After assessing the quality and cleaning the selected data, the resulting sample was formed of 34718 rows, of which 70% were used for learning (24303 rows), and 30% (10415 rows) for testing. A team model offuzzy neural networks was built and a knowledge base was formed on the basis of the data obtained, including 4608 fuzzy rules. Studies have shown that the number of errors of the 1st type in identifying phishing sites is 2.01%, and 2.89% for errors of the 2nd type. The general classification error based on knowledge base rules is 4.9%. The accuracy of identifying phishing sites was 95.1%, which exceeds the accuracy of other classification methods: multilayer neural network, decision tree, linear and logistic regression. The knowledge base formed on the basis of the team model of fuzzy neural networks can be effectively used to identify phishing sites on the Internet.

Geochemical Composition of the Lomé Lagoon Sediments, Togo: Seasonal and Spatial Variations of Major, Trace and Rare Earth Element Concentrations

The concentrations of major, trace (TE), and rare earth (REE) elements and their seasonal and spatial distribution were studied on the fine fraction (<63 µm) of the sediments of the Lomé lagoons (West Lake, East Lake, and Lake Bè). The sediments were collected on a total of nine sampling sites (three per Lake) during two campaigns (dry season and rainy season). The quality of the sediments was assessed on the basis of the enrichment factor (EF) and the labile or non-residual fraction (NRF) in relation to the values recommended for the quality of the sediments (Sediment Quality Guidelines, SQG). The distribution of rare earth elements shows enrichments in light rare earths superior to those of heavy rare earth elements during any season. Positive Ce anomalies are less noticeable and less variable between seasons than Eu anomalies. La/Yb ratios are positively correlated with the percentage of Al and Fe oxides and with the percentage of fine fractions. The main bearing phases of rare earth elements are, therefore, Al and Fe oxides and the finest fractions of the sediments. The concentrations of trace elements vary little, according to the seasons, but show strong variations from one element to another. The degrees of enrichment obtained are moderate for Bi, Cr, Ga, Mo, Pb, Sn, and Zn (1.5 < EF < 5) to significant for As, Cd, and Sb (5 < EF < 20) for all sites of Lake Bè. For the sites of West Lake, the degrees of enrichment obtained are moderate for As, Cd, Cu, Mo, and Pb (1.5 < EF < 5) to a significance for As, Bi, Cd, Pb, Sb, Sn, and Zn (5 < EF < 20). Only the East Lake sites show high degrees of enrichment for elements such as Sb and Sn (20 < EF < 40). Trace elements (TE) such as As, Cd, Cu, and Ni have total concentrations within the range of variation of the SQG concentrations (particularly Probable Effect Level (PEL) and Effect Range Median (ERM)), whereas Cr, Pb, and Zn total concentrations are higher. The ranking of priority sites with respect to the sediment contamination is determined according to ERM and PEL quotients in relation to the probability of toxicity for benthic organisms. For almost all the sites, the priority is lowest to medium-low with regard to As, Cd, and Cu and medium-high (Cr and Ni) to highest (Pb and Zn), particularly for the East and West Lakes. Moreover, the NRF can represent significant percentages of the total TE concentrations: 5% to 15% for As, Bi, Ni, V, Mo, and Sc, 15% to 25% for Co, Cu, and Sr, 25% to 40% for Pb and Zn and, lastly, 47% to 55% for Cd.

Nestedness and underlying processes of bird assemblages in Nanjing urban parks.

Nestedness is an important pattern frequently reported for species assemblages on islands or fragmented systems. However, to date, there are few studies that comprehensively investigated faunal nestedness and underlying processes in urbanized landscapes. In this study, we examined the nestedness of bird assemblages and its underlying causal mechanisms in 37 urban parks in Nanjing, China. We used the line-transect method to survey birds from April 2019 to January 2020. We used the Weighted Nestedness metric based on Overlap and Decreasing Fill (WNODF) to estimate the nestedness of bird assemblages. We applied spearman partial correlation test to examine the relationships between nestedness ranks of sites and park characteristics (area, isolation, anthropogenic noise, number of habitat types, and building index), as well as between nestedness ranks of species and their ecological traits (body size, geographic range size, clutch size, minimum area requirement, dispersal ratio, and habitat specificity). We found that bird assemblages in urban parks were significantly nested. Park area, habitat diversity, building index, habitat specificity, and minimum area requirement of birds were significantly correlated with nestedness. Therefore, the nestedness of bird assemblages was caused by selective extinction, habitat nestedness, and urbanization. However, the nestedness of bird assemblages did not result from passive sampling, selective colonization, or human disturbance. Overall, to maximize the number of species preserved in our system, conservation priority should be given to parks with large area, rich habitat diversity, and less building index. From a species perspective, we should focus on species with large area requirement and high habitat specificity for their effective conservation.

Retrospective Study of Factors Affecting Efficacy of Therapy with Dye Pulsed Light for Erythematotelangiectatic Rosacea.

IntroductionDye pulsed light (DPL) was proven to be effective at treating erythematous and telangiectatic skin disorders. However, there are limited data on the efficacy of DPL treatment for erythematotelangiectatic rosacea (ETR), and researchers do not fully understand the factors that may affect the efficacy. Here, we performed a study to investigate the efficacy of DPL treatment for ETR and determine the factors affecting that efficacy.MethodsSixty-five patients with ETR underwent three treatment sessions with DPL at 4-week intervals and were followed up at 4 weeks after the last treatment session. Skin type, sex, age, lesion site, severity of erythema and telangiectasia, VISIA percentile ranking, clinical photographs and red area images were recorded at baseline. The post-treatment erythematous and telangiectatic scores and VISIA percentile rankings were recorded, and the effects of different personal and clinical factors on the efficacy were statistically analysed.ResultsThe erythema and telangiectasia scores and VISIA percentile rankings showed significant improvement after the DPL procedures (p < 0.01). With regard to erythema, treatment efficacy was not affected by any of the investigated variables, including pre-treatment erythema scores, skin type, pre-treatment VISIA percentile ranking, sex, age and lesion site (p > 0.05). With regard to telangiectasia, the treatment efficacy was greater for mild telangiectasia than for severe telangiectasia (odds ratio = 4.14, p < 0.05). There was no significant difference in treatment efficacy between the moderate and severe categories (odds ratio = 4.00, p > 0.05).ConclusionDPL is not the optimal procedure for treating severe telangiectasia in patients with ETR, whereas the efficacy of the treatment for erythema was not affected by the severity of the condition.

Evaluating tourism potentials for site development tourism along River Ethiope, Abraka, Nigeria

Purpose: The empirical research study evaluated environmental potentials of site locations for Tourism development along River Ethiope, Abraka Delta State, Nigeria, Four(4)sites’ 40 environmental features were considered important in the tourism sites evaluation. The primary data sources used include oral interview and administration of questionnaires. Research methodology: These are physical, biological and human components of tourism destinations, evaluated for each of the 4sites, and compared. Each of the 40 factors was measured using appropriate instruments like measuring tape and floater (for velocity). Students t test was undertaken to compare the evaluations of the two groups of professional and non-professional assessors. With a calculated value of 0.143, and table value of 0.283, with df2:3 at 0.05 level, the difference in site ranking between the first and second evaluation was not considered significant. High confidence or reliability can therefore be placed on the tourism site evaluation results obtained at the 0.05 significance level. The use of nominal or interval scales was to estimate variables, which were not subject to direct measurements in interval scale. Three groups of sites emerged from the preliminary survey of those selected: Natural or undeveloped sites, relate. Results: Result obtained showed that undeveloped and natural sites emerged most highly rated in environmental potentials for tourism site development compared to underdeveloped or highly developed sites. Limitation: The area lies within tropical equatorial rain forest vegetation which is an impenetrable ticket of under growth with trees and climbers. Moreover, dangerous reptiles especially (snakes and crocodile) as well as insect (Mosquitos and tsetse fly) are present and harmful to man in the environment. Contribution: The study concludes and suggests natural sites be accord priority in tourism site development along River Ethiope and invariably other related natural area worldwide for maximum patronage implications based on advocated research methodology. Keywords: Tourism, Site, Evaluation, Development, River Ethiope, Abraka

Cannot see the diversity for all the species: Evaluating inclusion criteria for local species lists when using abundant citizen science data.

Abundant citizen science data on species occurrences are becoming increasingly available and enable identifying composition of communities occurring at multiple sites with high temporal resolution. However, for species displaying temporary patterns of local occurrences that are transient to some sites, biodiversity measures are clearly dependent on the criteria used to include species into local species lists. Using abundant opportunistic citizen science data from frequently visited wetlands, we investigated the sensitivity of α‐ and β‐diversity estimates to the use raw versus detection‐corrected data and to the use of inclusion criteria for species presence reflecting alternative site use. We tested seven inclusion criteria (with varying number of days required to be present) on time series of daily occurrence status during a breeding season of 90 days for 77 wetland bird species. We show that even when opportunistic presence‐only observation data are abundant, raw data may not produce reliable local species richness estimates and rank sites very differently in terms of species richness. Furthermore, occupancy model based α‐ and β‐diversity estimates were sensitive to the inclusion criteria used. Total species lists (all species observed at least once during a season) may therefore mask diversity differences among sites in local communities of species, by including vagrant species on potentially breeding communities and change the relative rank order of sites in terms of species richness. Very high sampling effort does not necessarily free opportunistic data from its inherent bias and can produce a pattern in which many species are observed at least once almost everywhere, thus leading to a possible paradox: The large amount of biological information may hinder its usefulness. Therefore, when prioritizing among sites to manage or preserve species diversity estimates need to be carefully related to relevant inclusion criteria depending on the diversity estimate in focus.

A new ranking scale for assessing leaching potential pollution from abandoned mining wastes based on the Mexican official leaching test

Potentially toxic elements (PTEs) present in abandoned mining wastes (AMW) are of great concern because of potential risks to human health and ecosystems. Indices of contamination (IC) applied to mining wastes are calculated using the total concentration of PTEs and comparing them with regional geochemical backgrounds. However, determining the total content of heavy metals is insufficient to assess the hazard of mining wastes. Therefore, in addition to total concentration, the potential risk is also evaluated through water mobility of elements. Accordingly, leaching procedures are useful tools for the geochemical characterization of soluble constituents that are mobilized. In this study, the solubility of PTEs from different types of mining wastes is comparatively assessed using three standard leaching methods (European; U.S. Geological Survey and; Mexican). The Hazard Average Quotient (HAQ) was calculated to assess the potential Toxicity Factor (TF). TF is an indicator of the relative potential toxicity of wastes and is the basis for the classification of AMW. A comparative assessment provides evidence that there are no statistically significant differences in PTEs solubility by the three leaching methods and it was also found that the pH of the eluates was dictated by the type of waste. Results suggest that the IC gives an indicator of the potential contamination of soils and sediments by erosive processes, or a long-term measure, whereas TF assesses the possibility of contaminating water in the short term. The most significant finding is the new ranking scale of TF, as a function of HAQ, applied to the Mexican standard leaching test. This factor, together with other considerations relating to risk-generating processes, might then be applied in places having large amounts of recorded AMW, such as the Iberian Peninsula and Latin America, where effective management is required to rank sites, based on preliminary environmental and human risk assessment.

A new spatial count data model with Bayesian additive regression trees for accident hot spot identification

The identification of accident hot spots is a central task of road safety management. Bayesian count data models have emerged as the workhorse method for producing probabilistic rankings of hazardous sites in road networks. Typically, these methods assume simple linear link function specifications, which, however, limit the predictive power of a model. Furthermore, extensive specification searches are precluded by complex model structures arising from the need to account for unobserved heterogeneity and spatial correlations. Modern machine learning (ML) methods offer ways to automate the specification of the link function. However, these methods do not capture estimation uncertainty, and it is also difficult to incorporate spatial correlations. In light of these gaps in the literature, this paper proposes a new spatial negative binomial model which uses Bayesian additive regression trees to endogenously select the specification of the link function. Posterior inference in the proposed model is made feasible with the help of the Pólya-Gamma data augmentation technique. We test the performance of this new model on a crash count data set from a metropolitan highway network. The empirical results show that the proposed model performs at least as well as a baseline spatial count data model with random parameters in terms of goodness of fit and site ranking ability.

Applying a joint model of crash count and crash severity to identify road segments with high risk of fatal and serious injury crashes

Both crash count and severity are thought to quantify crash risk at defined transport network locations (e.g. intersections, a particulate section of highway, etc.). Crash count is a measure of the likelihood of occurring a potential harmful event, whereas crash severity is a measure of the societal impact and harm to the society. As the majority of safety improvement programs are focused on preventing fatal and serious injury crashes, identification of high-risk sites—or blackspots—should ideally account for both severity and frequency of crashes. Past research efforts to incorporate crash severity into the identification of high-risk sites include multivariate crash count models, equivalent property damage only models and two-stage mixed models. These models, however, often require suitable distributional assumptions for computational efficiency, neglect the ordinal nature of crash severity, and are inadequate for capturing unobserved heterogeneity arising from possible correlations between crash counts of different severity levels. These limitations can ultimately lead to inefficient allocation of resources and misidentification of sites with high risk of fatal and serious injury crashes. Moreover, the implication of these models in blackspot identification is an important, unanswered question.While a joint econometric model of crash count and crash severity has the flexibility to account for the limitations mentioned previously, its ability to identify high-risk sites also needs to be examined. This study aims to fill this research gap by employing the joint model for blackspot identification. Using data from state-controlled roads in Queensland, Australia, a new risk score is developed based on predicted crash counts by severity, weighted by the cost ratio of severity levels. This weighted risk score is then used for identifying road segments with high risk of fatal and injury crashes. Results show that the joint model of crash count and crash severity has substantially improved prediction accuracy compared to the traditional count models. The correlation between crash counts of different severity levels captures the unobserved heterogeneity caused by the extra-variation in total crash counts and moderates the parameters in the joint model. In comparison with the traditional approaches, the proposed weighted risk score approach with the joint model of crash count and crash severity leads to the identification of a higher number of fatal and serious injury crashes in the top ranked sites flagged for safety improvements.

Large-scale evaluation of deposition, bioavailability and ecological risks of the potentially toxic metals in the sediment cores of the hotspot coral reef ecosystems (Persian Gulf, Iran)

Coral reefs of the Persian Gulf are vulnerable to the potentially toxic metals (PTMs) accumulated in the ambient sediments. Nonetheless, few studies have investigated the PTMs pollution and risk in the hotspot coral ecosystems of the Persian Gulf at a large-scale. Hereupon, this study focused on the PTMs contamination, their potential ecological risks, historical depositions, geochemical controls and the plausible pollution sources in the core sediments (0-40 cm) collected from the ten coral ecosystems of the Persian Gulf, Iran. Both total and fraction analysis indicated considerable metal pollution levels. Contamination was steadily decreasing towards the bottom of the sediment core, revealing the impact of a recent anthropogenic input. High metal association with the exchangeable and other mobile fractions was observed, indicating their high bioavailability. Of all the elements analyzed, toxic metals Cd, Hg and As exhibited the highest potential ecological risk (RI). Site rank index (SRI), modified degree of contamination (mCd), and contamination severity index (CSI) based approaches identified stations ST5, ST9 and ST10 as the most contaminated sites of the study area. The same stations were also found to possess considerable ecological risk. Principal component analysis (PCA) revealed that the stations located in the zone of the highest anthropogenic impact contain pollution sources for all the metals analyzed, whereas areas with low anthropogenic activity are mainly affected by the river runoff and urban emissions.

In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization.

Computational chemistry has now been widely accepted as a useful tool for shortening lead times in early drug discovery. When selecting new potential drug targets, it is important to assess the likelihood of finding suitable starting points for lead generation before pursuing costly high-throughput screening campaigns. By exploiting available high-resolution crystal structures, an in silico druggability assessment can facilitate the decision of whether, and in cases where several protein family members exist, which of these to pursue experimentally. Many of the algorithms and software suites commonly applied for in silico druggability assessment are complex, technically challenging and not always user-friendly. Here we applied the intuitive open access servers of DoGSite, FTMap and CryptoSite to comprehensively predict ligand binding pockets, druggability scores and conformationally active regions of the NUDIX protein family. In parallel we analyzed potential ligand binding sites, their druggability and pocket parameter using Schrödinger's SiteMap. Then an in silico docking cascade of a subset of the ZINC FragNow library using the Glide docking program was performed to assess identified pockets for large-scale small-molecule binding. Subsequently, this initial dual ranking of druggable sites within the NUDIX protein family was benchmarked against experimental hit rates obtained both in-house and by others from traditional biochemical and fragment screening campaigns. The observed correlation suggests that the presented user-friendly workflow of a dual parallel in silico druggability assessment is applicable as a standalone method for decision on target prioritization and exclusion in future screening campaigns.

The Research of Walmart Global Expansion

Purpose: To entering into the international market successfully, the company ought to do all-round and in-depth research. This paper aims to study the process of Walmart’s global expansion and find the solutions to solve the relevant risks. Design/Methodology/Approach: In-depth interviews with 5 persons were conducted to collect their rankings of social media sites and the reasons for visiting each of the sites.

Gender-based vulnerability: combining Pareto ranking and spatial statistics to model gender-based vulnerability in Rohingya refugee settlements in Bangladesh

BackgroundThe Rohingya refugee crisis in Bangladesh continues to outstrip humanitarian resources and undermine the health and security of over 900,000 people. Spatial, sector-specific information is required to better understand the needs of vulnerable populations, such as women and girls, and to target interventions with improved efficiency and effectiveness. This study aimed to create a gender-based vulnerability index and explore the geospatial and thematic variations in gender-based vulnerability of Rohingya refugees residing in Bangladesh by utilizing pre-existing, open source data.MethodsData sources included remotely-sensed REACH data on humanitarian infrastructure, United Nations Population Fund resource availability data, and the Needs and Population Monitoring Survey conducted by the International Organization for Migration in October 2017. Data gaps were addressed through probabilistic interpolation. A vulnerability index was designed through a process of literature review, variable selection and thematic grouping, normalization, and scorecard creation, and Pareto ranking was employed to rank sites based on vulnerability scoring. Spatial autocorrelation of vulnerability was analyzed with the Global and Anselin Local Moran’s I applied to both combined vulnerability index rank and disaggregated thematic ranking.ResultsOf the settlements, 24.1% were ranked as ‘most vulnerable,’ with 30 highly vulnerable clusters identified predominantly in the northwest region of metropolitan Cox’s Bazar. Five settlements in Dhokkin, Somitapara, and Pahartoli were categorized as less vulnerable outliers amongst highly vulnerable neighboring sites. Security- and health-related variables appear to be the most significant drivers of gender-specific vulnerability in Cox’s Bazar. Clusters of low security and education vulnerability measures are shown near Kutupalong.ConclusionThe humanitarian sector produces tremendous amounts of data that can be analyzed with spatial statistics to improve research targeting and programmatic intervention. The critical utilization of these data and the validation of vulnerability indexes are required to improve the international response to the global refugee crisis. This study presents a novel methodology that can be utilized to not only spatially characterize gender-based vulnerability in refugee populations, but can also be calibrated to identify and serve other vulnerable populations during crises.

Arteriovenous Fistula for dialysis – Let's Google it. Readability and quality of online information

BackgroundThis study evaluated the readability and quality of information regarding arteriovenous (AV) fistula for dialysis on the Internet in the English language. Study designUsing Google© search, the keywords “AV Fistula for dialysis” were searched. The top 75 ranking sites were analyzed. One website was excluded due to repetition. Each landing page was assessed independently by two authors (RB, LR) for readability using the Flesch Reading Ease Score (FRES) and Gunning Fog Index (GFI). Web site quality was assessed using the DISCERN instrument. The individual position of the top 15 websites in the search engine ranking order list was noted. The country of origin, organization type and issuance of Health on the Net (HoN) Certification was recorded. Statistical analyses were performed using unpaired t-tests and ANOVA variance. ResultsThe mean GFI score was 9.2 and the mean FRES score was 50.6, indicating poor readability. The mean DISCERN score was 48.4, indicating weak quality of websites. Website quality was influenced by the academic/healthcare organization type (p = 0.012). Organization type was not found to impact GFI and FRES scores. Presence of a HoN Certification was not found to impact the quality of information. The majority of sites originated from the United States (61%). ConclusionOur study demonstrates that internet information pertaining to AV fistula for dialysis is of poor quality necessitating improvements to readability and overall website quality to improve the patient experience. Further research into how to improve healthcare web information is needed.