Water quality parameters in relation to chronic kidney disease in Sri Lanka

In Sri Lanka, high concentrations of certain water quality parameters in drinking water are assumed to be causing Chronic Kidney Disease (CKD). Nmih Central Province (NCP) in Sri Lanka repotis the highest number of CKD patients and mmiality rates. The repmied research herein concentrates on re-examining diverse causative factors identified by previous researchers on CKD and analysis of water quality in samples from shallow wells supplying drinking water to CKD patients and non-patients in NCP. The samples were tested for a number of parameters such as anions, cations, and heavy metals. These include Cd, Na, Ca, F and Cl which previous researchers have suggested as causative factors for CKD. The preliminmy analyses of data indicated majority of water quality parameters collected from the study area did not exceed the WHO drinking water quality standards. The critical water quality parameters that could cause the CKD were investigated using Factor Analysis techniques. From the water samples collected from the CKD Patients the parameters of Na, Cl, Mg, F and Ca could be grouped into one Factor and identified as hydro-geologically originating. Another Factor which could be due to nutrients from fetiilizer was identified consisting of N and P whereas Cd was grouped into a single Factor. In contrast, the water quality parameters in water samples collected from CKD Non-Patients were different and could not be clearly grouped into any special category

Evaluation of brick kiln performances using computational fluid dynamics (CFD)

Modern history of civilization is concurrent to the use of brick and its manufacturing. Nowadays tunnel kiln is the most widely used technology for brick production. This paper tries to provide an idea of the brick making process in tunnel kiln. The computational fluid dynamics (CFD) software, ANSYS CFX is being used to evaluate kiln performances using gas as its fuel. Simplified geometry was drawn and meshed using appropriate tools of ANSYS CFX. Several pertinent assumptions were made to reduce the complication of the simulation. Turbulence, combustion, radiation and NO models were adopted for simulation of a realistic tunnel kiln environment. Simulated temperature profile almost replicates industrial kiln situation as found in existing literature. CFD analysis helps to simulate the temperature profile of the brick kilns, the mass flow fractions of CO2 and NO emissions at outlet, and also the air velocity profile inside the kiln. The simulated temperature generated in a tunnel kiln is found to be between 1300 K and 300 K. CO2 and NOx volume generated inside the kiln is estimated as 1.01 m3/s and 0.108 m3/s respectively

Sudden cardiac death among general population and sport related population in forensic experience.

PURPOSE: The goal of the study was to assess the causes and analyze the cases of sudden cardiac death (SCD) victims referred to the department of forensic medicine in Lausanne, with a particular focus on sports-related fatalities including also leisure sporting activities. To date, no such published assessment has been done nor for Switzerland nor for the central Europe. METHODS: This is a retrospective study based on autopsy records of SCD victims, from 10 to 50 years of age, performed at the University Centre of Legal Medicine in Lausanne from 1995 to 2010. The study population was divided into two groups: sport-related (SR) and not sport-related (NSR) SCDs. RESULTS: During the study period, 188 cases of SCD were recorded: 166 (88%) were NSR and 22 (12%) SR. The mean age of the 188 victims was 37.3 ± 10.1 years, with the majority of the cases being male (79%). A cause of death was established in 84%, and the pathology responsible for death varied according to the age of the victims. In the NSR group, the mean age was 38.2 ± 9.2 years and there was 82% of male. Coronary artery disease (CAD) was the main diagnosis in the victims aged 30-50 years. The majority of morphologically normal hearts were observed in the 15-29 year age range. There was no case in the 10-14 year age range. In the SR group, 91% of victims died during leisure sporting activities. In this group the mean age was 30.5 ± 13.5 years, with the majority being male (82%). The main cause of death was CAD, with 6 cases (27%) and a mean age of 40.8 ± 5.5 years. The youngest victim with CAD was 33 years old. A morphologically normal heart was observed in 5 cases (23%), with a mean age of 24.4 ± 14.9 years. The most frequently implicated sporting activities were hiking (26%) and swimming (17%). CONCLUSION: In this study, CAD was the most common cause of death in both groups. Although this pathology most often affects adults over 35 years of age, there were also some victims under 35 years of age in both groups. SCDs during sport are mostly related to leisure sporting activities, for which preventive measures are not yet usually established. This study highlights also the need to inform both athletes and non athletes of the cardiovascular risks during sport activities and the role of a forensic autopsy and registries involving forensic pathologists for SR SCD

Low-Flow (7-Day, 10-Year) Classical Statistical and Improved Machine Learning Estimation Methodologies

Water resource managers require accurate estimates of the 7-day, 10-year low flow (7Q10) of streams for many reasons, including protecting aquatic species, designing wastewater treatment plants, and calculating municipal water availability. StreamStats, a publicly available web application developed by the United States Geologic Survey that is commonly used by resource managers for estimating the 7Q10 in states where it is available, utilizes state-by-state, locally calibrated regression equations for estimation. This paper expands StreamStats’ methodology and improves 7Q10 estimation by developing a more regionally applicable and generalized methodology for 7Q10 estimation. In addition to classical methodologies, namely multiple linear regression (MLR) and multiple linear regression in log space (LTLR), three promising machine learning algorithms, random forest (RF) decision trees, neural networks (NN), and generalized additive models (GAM), are tested to determine if more advanced statistical methods offer improved estimation. For illustrative purposes, this methodology is applied to and verified for the full range of unimpaired, gaged basins in both the northeast and mid-Atlantic hydrologic regions of the United States (with basin sizes ranging from 2–1419 mi2) using leave-one-out cross-validation (LOOCV). Pearson’s correlation coefficient (R2), root mean square error (RMSE), Kling–Gupta Efficiency (KGE), and Nash–Sutcliffe Efficiency (NSE) are used to evaluate the performance of each method. Results suggest that each method provides varying results based on basin size, with RF displaying the smallest average RMSE (5.85) across all ranges of basin sizes

Metal-organic vapor-phase epitaxial growth of InGaN and InAlN for multi-junction tandem solar cells

MOVPE growth of InGaN and InAlN has been studied to prepare a wanted band gap from 0.65 to 2.5 eV for multi-junction tandem solar cells. The main subjects in the growth of InGaN are the suppression of phase separation and metallic In incorporation and the control of composition in grown films. Both phase separation and metallic In segregation can be avoided by choosing the appropriate substrate position on the susceptor. By optimizing growth temperature and TMI/(TMI+TEG) molar ratio, InGaN films with full composition range are successfully grown. The Mg-doping behavior of MOVPE InGaN (In composition 0.1~0.4) is also studied using Cp2Mg as a Mg source. The growth behavior of InAlN is studied with the dominant parameters such as growth pressure, TMI/(TMI+TMA) molar ratio and substrate position on the susceptor. The major difficulty in the InAlN growth is found to be the adduct formation by the parasitic reaction of TMA and NH3. By employing the atmospheric-pressure growth, adduct-free InAlN films are grown with a reasonable growth rate (~ 1m/h). This enables us to grow InAlN films with an In content from 0.3 to 1, corresponding to band gaps from 3.6 to 0.65 eV. In order to demonstrate an ability to prepare these different alloys sequentially, InAlN/InGaN hetero-structures are prepared and the photo-response is observed for the first time for an n-InAlN/p-InGaN hetero-junction

Evaluation of predictive models for post-fire debris flow occurrence in the western United States

Abstract. Rainfall-induced debris flows in recently burned mountainous areas cause significant economic losses and human casualties. Currently, prediction of post-fire debris flows is widely based on the use of power-law thresholds and logistic regression models. While these procedures have served with certain success in existing operational warning systems, in this study we investigate the potential to improve the efficiency of current predictive models with machine-learning approaches. Specifically, the performance of a predictive model based on the random forest algorithm is compared with current techniques for the prediction of post-fire debris flow occurrence in the western United States. The analysis is based on a database of post-fire debris flows recently published by the United States Geological Survey. Results show that predictive models based on random forest exhibit systematic and considerably improved performance with respect to the other models examined. In addition, the random-forest-based models demonstrated improvement in performance with increasing training sample size, indicating a clear advantage regarding their ability to successfully assimilate new information. Complexity, in terms of variables required for developing the predictive models, is deemed important but the choice of model used is shown to have a greater impact on the overall performance

Structural coloration of chitosan-cationized cotton fabric using photonic crystals

Conventional textile coloration is a wet process involving high levels of water and chemicals consumption and wastewater generation. However, colour in textiles can also be generated by other mechanisms such as: absorption, emission, diffraction, interference and photochromism.[1] Chromotropic effect refers to reversible colour transformation due to external chemical or physical influence.[2] Photonic crystals are an important class of chromotropic materials. Colloidal crystals with a periodicity on the scale of half the wavelength of visible light exhibit structural colours similar to natural opals due to a diffraction effects that result in the appearance of a photonic band gap that forbids propagation of certain wavelengths.[3] Structural colouration is emerging as an innovative technology to produce colourful textiles materials.[4] Various colours impossible to reproduce by chemical coloration can be created by modifying the periodicity of the nanostructures or the environmental conditions using a single material.[5, 6] Photonic crystals can be applied on textile fabrics by colloid self-assembly and the structural colours can be controlled by adjusting the microspheres size and the viewing angles.[7] However, their application for textile structural coloration has been barely reported.[8] In this work, P(St-MMA-AA) composite nanospheres were deposited onto chitosan-cationized woven cotton fabrics. The structural colours of the deposited photonic crystals on the fabrics and its washing fastness were investigated.info:eu-repo/semantics/publishedVersio

Evidence of Balanced Diversity at the Chicken Interleukin 4 Receptor Alpha Chain Locus

Background: The comparative analysis of genome sequences emerging for several avian species with thefully sequenced chicken genome enables the genome-wide investigation of selective processes infunctionally important chicken genes. In particular, because of pathogenic challenges it is expected thatgenes involved in the chicken immune system are subject to particularly strong adaptive pressure.Signatures of selection detected by inter-species comparison may then be investigated at the populationlevel in global chicken populations to highlight potentially relevant functional polymorphisms.Results: Comparative evolutionary analysis of chicken (Gallus gallus) and zebra finch (Taeniopygia guttata)genes identified interleukin 4 receptor alpha-chain (IL-4Rα), a key cytokine receptor as a candidate with asignificant excess of substitutions at nonsynonymous sites, suggestive of adaptive evolution. Resequencingand detailed population genetic analysis of this gene in diverse village chickens from Asia and Africa,commercial broilers, and in outgroup species red jungle fowl (JF), grey JF, Ceylon JF, green JF, grey francolinand bamboo partridge, suggested elevated and balanced diversity across all populations at this gene, actingto preserve different high-frequency alleles at two nonsynonymous sites.Conclusion: Haplotype networks indicate that red JF is the primary contributor of diversity at chickenIL-4Rα: the signature of variation observed here may be due to the effects of domestication, admixtureand introgression, which produce high diversity. However, this gene is a key cytokine-binding receptor inthe immune system, so balancing selection related to the host response to pathogens cannot be excluded

Gene expression profiling and silencing reveal that monolignol biosynthesis plays a critical role in penetration defence in wheat against powdery mildew invasion

Cell wall apposition (CWA) formation is one of the first lines of defence used by plants to halt invading fungi such as powdery mildew. Lignin is a complex polymer of hydroxylated and methoxylated phenylpropane units (monolignols) and lignification renders the cell wall more resistant to pathogen attack. The role of monolignol biosynthesis in CWA-mediated defence against powdery mildew penetration into cereals is demonstrated here using RNA interference (RNAi)-mediated gene silencing and enzyme-specific inhibitors. Thirteen cDNAs representing eight genes involved in monolignol biosynthesis were cloned from an expression sequence tag (EST) library derived from the epidermis of diploid wheat (Triticum monococcum) infected with Blumeria graminis f. sp. tritici (Bgt). Differential expression patterns were found for these genes in susceptible and resistant plants after infection. Transcripts of phenylalanine ammonia lyase (PAL), caffeic acid O-methyltransferase (CAOMT), ferulic acid hydroxylase (FAH), caffeoyl-CoA O-methyltransferase (CCoAMT), and cinnamyl alcohol dehydrogenase (CAD) were accumulated, particularly in the epidermis. RNAi-mediated transient gene silencing in the epidermis led to a higher penetration efficiency of Bgt than in the controls. Gene silencing also compromised penetration resistance to varying degrees with different genes against an inappropriate pathogen, B. graminis f. sp. hordei (Bgh). Co-silencing led to greater penetration of Bgt or Bgh than when the genes were silenced separately. Fluorescence emission spectra analyses revealed that gene silencing hampered host autofluorescence response at fungal contact sites. These results illustrate that monolignol biosynthesis is critically important for host defence against both appropriate and inappropriate pathogen invasion in wheat

Identification and molecular characterisation of Lausanne Institutional Biobank participants with familial hypercholesterolaemia - a proof-of-concept study.

We aimed to identify familial hypercholesterolaemia mutation carriers among participants to the Lausanne Institutional Biobank (BIL). Our experimental workflow was designed as a proof-of-concept demonstration of the resources and services provided by our integrated institutional clinical research support platform. Familial hypercholesterolaemia was used as a model of a relatively common yet often underdiagnosed and inadequately treated Mendelian disease. Clinical and laboratory information was extracted from electronic hospital records. Patients were selected using elevated plasma cholesterol levels (total cholesterol ≥7.5 mM or low-density lipoprotein cholesterol ≥5 mM), premature coronary artery disease status and age (18-60 yr) as main inclusion criteria. LDLR, APOB and PCSK9 were analysed by high-throughput DNA sequencing. The most relevant mutations were confirmed by Sanger sequencing. Of 23 737 patients contacted by the BIL, 17 760 individuals consented to participate and 13 094 wished to be recontacted if there were findings requiring clinical action. Plasma cholesterol records were available for 5111 participants, of whom 94 were selected for genetic screening. Twenty-five of the tested patients presented with premature coronary artery disease while 69 had no such diagnosis. Seven heterozygous carriers of eight rare coding missense variants were identified. Three mutations were pathogenic (APOB p.R3527Q) or likely pathogenic (LDLR p.C27W, LDLR p.P526S) for hypercholesterolaemia, while the others were either benign or of unknown significance. One patient was a double heterozygote for variants APOB p.R3527Q and LDLR p.P526S. This work illustrates how clinical and translational research can benefit from a dedicated platform integrating both a hospital-based biobank and a data support team