528 research outputs found

    Design of a Metadata Framework for the Environmental Models with an Example Hydrologic Application in HydroShare

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    Environmental modelers rely on a variety of computational models to make predictions, test hypotheses, and address specific problems related to environmental science and natural resource management. Scientists and engineers must devote significant effort to preparing these computational models. While significant attention has been devoted to sharing and reusing environmental data, less attention has been devoted to sharing and reusing environmental models. A first step toward increasing environmental model sharing and reuse is to define a general metadata framework for models that is flexible and, therefore, applicable across the wide variety of models used by environmental modelers. This paper proposes a general approach for representing environmental model metadata that extends the Dublin Core metadata framework. The framework is implemented within the HydroShare system and applied for a hydrologic model sharing use case. This example application demonstrates how the metadata framework implemented within HydroShare can assist in model sharing, publication, reuse, and reproducibility

    Study on the Discrimination of Possible Error Sources That Might Affect the Quality of Volatile Organic Compounds Signature in Dairy Cattle Using an Electronic Nose

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    Electronic nose devices (EN) have been developed for detecting volatile organic compounds (VOCs). This study aimed to assess the ability of the MENT-EGAS prototype-based EN to respond to direct sampling and to evaluate the influence of possible error sources that might affect the quality of VOC signatures. This study was performed on a dairy farm using 11 (n = 11) multiparous Holstein-Friesian cows. The cows were divided into two groups housed in two different barns: group I included six lactating cows fed with a lactating diet (LD), and group II included 5 non-lactating late pregnant cows fed with a far-off diet (FD). Each group was offered 250 g of their respective diet; 10 min later, exhalated breath was collected for VOC determination. After this sampling, 4 cows from each group were offered 250 g of pellet concentrates. Ten minutes later, the exhalated breath was collected once more. VOCs were also measured directly from the feed's headspace, as well as from the environmental backgrounds of each. Principal component analyses (PCA) were performed and revealed clear discrimination between the two different environmental backgrounds, the two different feed headspaces, the exhalated breath of groups I and II cows, and the exhalated breath within the same group of cows before and after the feed intake. Based on these findings, we concluded that the MENT-EGAS prototype can recognize several error sources with accuracy, providing a novel EN technology that could be used in the future in precision livestock farming

    Hepatitis A virus in urban sewage from two Mediterranean countries.

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    Molecular methods for the detection and typing of hepatitis A virus (HAV) strains in sewage were applied to determine its distribution in Cairo and Barcelona. The study revealed the occurrence of different patterns of hepatitis A endemicity in each city. The circulating strains characterized, whether in Cairo or Barcelona, were genotype IB. The effects of a child vaccination programme and the increase in the immigrant population on the overall hepatitis A occurrence in Barcelona were evaluated. While vaccination contributed to a significant decrease in the number of clinical cases, the huge recent immigration flow has probably been responsible for the re-emergence of the disease in the last year of study, in the form of small outbreaks among the non-vaccinated population

    A novel homozygous TPM1 mutation in familial pediatric hypertrophic cardiomyopathy and in silico screening of potential targeting drugs.

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    Familial hypertrophic cardiomyopathy (HCM) is the most common genetic cardiac disease. While sarcomeric gene mutations explain many HCM cases, the genetic basis of about half of HCM cases remains elusive. Here we aimed to identify the gene causing HCM in a non-consanguineous Saudi Arabian family with affected family members and a history of sudden death. The impact of the identified mutation on protein structure and potential drug targets were evaluated in silico. Triplets (two HCM subjects and one patent ductus arteriosus (PDA) case) and unaffected parents were screened by targeted next-generation sequencing (NGS) for 181 candidate cardiomyopathy genes. In silico structural and functional analyses, including protein modeling, structure prediction, drug screening, drug binding, and dynamic simulations were performed to explore the potential pathogenicity of the variant and to identify candidate drugs. A homozygous missense mutation in exon 1 of TMP1 (assembly GRCh37-chr15: 63340781; G>A) was identified in the triplets [two HCM and one patent ductus arteriosus (PDA)] that substituted glycine for arginine at codon 3 (p.Gly3Arg). The parents were heterozygous for the variant. The mutation was predicted to cause a significant and deleterious change in the TPM1 protein structure that slightly affected drug binding, stability, and conformation. In addition, we identified several putative TPM1-targeting drugs through structure-based in silico screening. TPM1 mutations are a common cause of HCM and other congenital heart defects. To date, TPM1 has not been associated with isolated PDA; to our knowledge, this is the first report of the homozygous missense variation p.Gly3Arg in TPM1 associated with familial autosomal recessive pediatric HCM and PDA. The identified candidate TPM1 inhibitors warrant further prospective investigation.This research was supported by the Strategic Technologies Programs of the National Plan for Science, Technology and Innovation (MAARIFAH), Kingdom of Saudi Arabia. Project No: 12-MED3174-05, through the Science and Technology Unit (STU), Taibah University, Al Madinah Al Munawwarah, Kingdom of Saudi Arabia

    Quantitative three-dimensional reconstruction of cellular flame area for spherical hydrogen-air flames

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    The cellular flame area continues to increase with the development of cells on the spherical flame surface, which will greatly promote the flame burning rate and propagation speed. This work mainly focuses on a new three-dimensional (3D) reconstruction method of the cellular structure on the flame surface, attempting to quantitatively characterize the real flame area. Initially, the visualization investigation of hydrogen-air premixed spherical flames within a constant volume vessel was conducted using the Schlieren optical technique under room temperature and atmospheric pressure conditions. In parallel, the Cellpose 2.0 graphical user interface was used for the preliminary training of the cell segmentation model. Subsequently, this pre-trained model was applied in the image post-processing, enabling the quantitative characteristics extraction of the cellular structure, such as the cells number, area, and the flame radius, etc. Additionally, a concept of peak height h on the flame profile was proposed to characterize the fluctuation degree of flame profile. A new flame equivalent radius r was defined by the average value of valid distance from flame centroid to flame profile pixel by pixel. Based on the comparison of cell equivalent radius r and average peak height h, an innovative 3D reconstruction concept was proposed for the quantitative characterization of flame area. Finally, cellularity factor ξ was introduced to evaluate the cellularization degree on spherical flames surface. Results show that the appearance of secondary cracks marks the formal onset of flame cellularization, accompanied by an increase in the h. In the later stages of flame development, cellularization will eventually tend to a stable value of about 0.4, indicating the occurrence of “saturated state”. After 3D reconstruction, the average cell area stable at around 26 mm2 in this stage. The results of this study provide data support for the construction of combustion models in the field of premixed hydrogen-air combustion

    Bi-allelic GAD1 variants cause a neonatal onset syndromic developmental and epileptic encephalopathy.

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    Developmental and epileptic encephalopathies are a heterogeneous group of early-onset epilepsy syndromes dramatically impairing neurodevelopment. Modern genomic technologies have revealed a number of monogenic origins and opened the door to therapeutic hopes. Here we describe a new syndromic developmental and epileptic encephalopathy caused by bi-allelic loss-of-function variants in GAD1, as presented by 11 patients from six independent consanguineous families. Seizure onset occurred in the first 2 months of life in all patients. All 10 patients, from whom early disease history was available, presented with seizure onset in the first month of life, mainly consisting of epileptic spasms or myoclonic seizures. Early EEG showed suppression-burst or pattern of burst attenuation or hypsarrhythmia if only recorded in the post-neonatal period. Eight patients had joint contractures and/or pes equinovarus. Seven patients presented a cleft palate and two also had an omphalocele, reproducing the phenotype of the knockout Gad1-/- mouse model. Four patients died before 4 years of age. GAD1 encodes the glutamate decarboxylase enzyme GAD67, a critical actor of the γ-aminobutyric acid (GABA) metabolism as it catalyses the decarboxylation of glutamic acid to form GABA. Our findings evoke a novel syndrome related to GAD67 deficiency, characterized by the unique association of developmental and epileptic encephalopathies, cleft palate, joint contractures and/or omphalocele

    Estrus Detection in a Dairy Herd Using an Electronic Nose by Direct Sampling on the Perineal Region

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    Estrus detection is very important for the profitability of dairy herds. Different automatic systems for estrus detection have been developed over the last decades. Our study aimed to assess the ability of the electronic nose (EN) MENT-EGAS prototype to detect estrus, based on odor release from the perineal headspace in dairy cattle by direct sampling. The study was performed in an Italian dairy farm using 35 multiparous Holstein–Friesian cows. The cows were divided into three groups: group I included 10 lactating 5-month pregnant cows, group II included 19 lactating cycling cows, and group III included 6 cows that were artificially inseminated 18 days before the trial. Odors from the perineal headspace were collected using the MENT-EGAS prototype. In group I, odors were collected once a day for 5 consecutive days. In group II, odors were collected twice daily from day 18 until day 1 of the reproductive cycle. In group III, odors were also collected twice daily from the presumable day 18 of gestation until day 22. Principal component analyses (PCA) of the perineal headspace samples were performed. PCA in group I revealed no significant discrimination. PCA in group II revealed clear discrimination between proestrus and estrus, and between estrus and metestrus but no significant discrimination was obtained between proestrus and metestrus. PCA in group III revealed that in four cows the results were similar to group I and in two cows the results were similar to group II. On day 40 of the presumable pregnancy, the ultrasound examination revealed that only the four cows were pregnant and the other two cows were regularly cycling. On the basis of our findings, we conclude that it is possible to accurately detect estrus in dairy cattle from directly collected odor samples using the MENT-EGAS prototype. This represents the first study of estrus detection using an EN detection by direct sampling. EN technologies, such as MENT-EGAS, could be applied in the future in dairy cattle farms as a precise, non-invasive method for estrus detection

    Laminar burning velocities and Markstein numbers for pure hydrogen and methane/hydrogen/air mixtures at elevated pressures

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    Spherically expanding flame propagations have been employed to measure flame speeds for H2/CH4/air mixtures over a wide range of H2 fractions (30 %, 50 %, 70 and 100 % hydrogen by volume), at initial temperatures of 303 K and 360 K, and pressures of 0.1, 0.5 and 1.0 MPa. The equivalence ratio (ϕ) was varied from 0.5 to 2.5 for pure hydrogen and from 0.8 to 1.2 for methane/hydrogen mixtures. Experimental laminar burning velocities and Markstein numbers for methane/hydrogen/air mixtures at high pressures, which are crucial for gas turbine applications, are very rare in the literature. Moreover, simulations using three recent chemical kinetic mechanisms (Konnov-2018 detailed reaction, Aramco-2.0-2016 and San Diego Methane detailed mechanism (version 20161214)) were compared against the experimentally derived laminar burning velocities. The maximum laminar burning velocity for 30 % and 50 % H2 occurs at ϕ = 1.1. However, it shifts to ϕ = 1.2 for 70 % H2 and to ϕ = 1.7 for a pure H2 flame. The laminar burning velocities increased with hydrogen fraction and temperature, and decreased with pressure. Unexpected behaviour was recorded for pure H2 flames at low temperature and ϕ = 1.5, 1.7 wherein ul did not decrease when the pressure increased from 0.1 to 0.5 MPa. Although, the measurement uncertainty is large at these conditions, the flame structure analysis showed a minimum decline in the mass fractions of the active species (H, O, and OH) with the rise in the initial pressure. Markstein length (Lb) and Markstein number (Mab and Masr) varied non-monotonically with hydrogen volume fraction, pressure and temperature. There was generally good agreement between simulations and experimentally derived laminar burning velocities, however, for experiments of rich-pure hydrogen at high initial pressures, the level of agreement decreased but remained within the limits of experimental uncertainty
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