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  1. Article ; Online: Assessing the utility of hybrid hydrological modeling over complex conditions of the Chitral basin, Pakistan

    Zain Syed / Prince Mahmood / Sajjad Haider / Shakil Ahmad

    Journal of Water and Climate Change, Vol 14, Iss 12, Pp 4444-

    2023  Volume 4464

    Abstract: Streamflow forecasting holds pivotal importance for planning and decision-making in the domain of water resources management. The Chitral basin in Pakistan is characterized by high altitude and glaciated terrain. Simulating streamflows in this type of ... ...

    Abstract Streamflow forecasting holds pivotal importance for planning and decision-making in the domain of water resources management. The Chitral basin in Pakistan is characterized by high altitude and glaciated terrain. Simulating streamflows in this type of region is challenging due to complex orography and uncertain climate data. This complexity persuaded us to explore three frameworks (soil and water assessment tool (SWAT), artificial neural network (ANN), and hybrid of SWAT–ANN (H2)) for simulating the Chitral river under two different climate datasets (observed climatology (OC) and reconciled gridded climatology (RGC)) to give all six model combinations. Model evaluation was done first by indices (Nash–Sutcliff efficiency, Kling–Gupta efficiency, coefficient of determination, percent bias, and root mean square error) based on which we further assigned scores to models reflecting their performance during calibration and validation epochs. The research revealed that ANN-RGC stood first with 53 points, followed by H2-RGC (50 points) and SWAT-RGC (45 points). Trailing behind in the fourth and fifth positions were SWAT-RGC and SWAT-OC (26 points each), respectively, while ANN-OC finished last (22 points). In addition, this study proposed a bias scaling approach for simulation biases resulting in reduction in recession and baseflow biases and specifically improved low-scoring models. Despite ANN's superiority over conventional models, it could be of limited utility in uncertain or data-scarce conditions. HIGHLIGHTS Reliable climate data hold pivotal importance in hydrological modeling.; Artificial neural networks scored the highest but were also found to be more sensitive to data quantity and quality.; The coupling harnessed the capabilities of the parent frameworks and performed well overall.; In uncertain data conditions, the soil and water assessment tool and hybrid models could be more suitable choices.; Implied linear scaling efficiently removed model biases.;
    Keywords ann ; climate uncertainty ; era5 land ; hybrid model ; streamflow forecasting ; swat ; Environmental technology. Sanitary engineering ; TD1-1066 ; Environmental sciences ; GE1-350
    Subject code 550
    Language English
    Publishing date 2023-12-01T00:00:00Z
    Publisher IWA Publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Bias correction and projection of temperature over the altitudes of the Upper Indus Basin under CMIP6 climate scenarios from 1985 to 2100

    Kashif Jamal / Xin Li / Yingying Chen / Muhammad Rizwan / Muhammad Adnan Khan / Zain Syed / Prince Mahmood

    Journal of Water and Climate Change, Vol 14, Iss 7, Pp 2490-

    2023  Volume 2514

    Abstract: The identification of projected changes in temperature caused by global warming at a fine-scale spatial resolution is of great importance for the high-altitude glacier and snow covered Upper Indus Basin. This study used a multimodel ensemble mean bias- ... ...

    Abstract The identification of projected changes in temperature caused by global warming at a fine-scale spatial resolution is of great importance for the high-altitude glacier and snow covered Upper Indus Basin. This study used a multimodel ensemble mean bias-correction technique which uses the ensemble empirical mode decomposition method to correct the bias of ensemble mean of seven CMIP6 GCMs outputs with reference to the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5). The bias-corrected data have a nonlinear trend of seven GCMs but interannual variance and mean climate of ERA5 dataset. The dataset spans from 1985 to 2100 for historical and future climate scenarios (SSP126, SSP245, SSP370, and SSP585) at daily time intervals with a 1 km grid resolution. The result of different scenarios indicates that the increase in maximum (Tmax) and minimum temperature (Tmin) ranging from 1.5 to 5.4 °C and 1.8 to 6.8 °C from 2015 to 2100, respectively. Similarly, elevation-dependent warming is identified in Tmin from 1.7 to 7.0 °C at elevations <2,000 to 6,000 m asl, while the contrary relationship in Tmax is projected under different scenarios from 2015 to 2100. This study provides an insight into how to improve the GCMs projections and can be helpful for further climate change impact studies. HIGHLIGHTS Bias correction of temperature maximum and minimum (Tmax and Tmin) of the multimodel ensemble mean of seven CMIP6 GCMs is carried out.; A reduction in the diurnal temperature range (DTR) is anticipated in the future due to high warming in Tmin as compared to Tmax.; Elevation-dependent warming (EDW) is only pronounced in Tmin.; The duration of snow and glacier melt can expand by 1–2 months due to rise in temperature.;
    Keywords climate change ; cmip6 ; elevation-dependent warming ; temperature ; upper indus basin ; Environmental technology. Sanitary engineering ; TD1-1066 ; Environmental sciences ; GE1-350
    Subject code 550
    Language English
    Publishing date 2023-07-01T00:00:00Z
    Publisher IWA Publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Mineral exchange within restorative materials following incomplete carious lesion removal using 3D non-destructive XMT subtraction methodology.

    Zain, Syed / Davis, Graham R / Hill, Robert / Anderson, Paul / Baysan, Aylin

    Journal of dentistry

    2020  Volume 99, Page(s) 103389

    Abstract: Objectives: The objective of this study was to quantify the changes in mineral and selected element concentrations within residual carious dentine and restorative materials following incomplete carious lesion removal (ICLR) using different cavity liners, ...

    Abstract Objectives: The objective of this study was to quantify the changes in mineral and selected element concentrations within residual carious dentine and restorative materials following incomplete carious lesion removal (ICLR) using different cavity liners, with non-destructive subtraction 3D-X-ray Microtomography (XMT, QMUL, London, UK).
    Materials and methods: A total of 126 extracted teeth with deep dental caries were assessed using International Caries Risk and Assessment (ICDAS). Eight teeth were subsequently selected after radiographic evaluation. Each lesion was removed, leaving a thin layer of leathery dentine at the deepest part of cavity. Different cavity lining materials were placed; Mineral Trioxide Aggregate (MTA), calcium hydroxide, (Ca(OH)
    Results: There were significant increases in mineral concentrations within the residual demineralised dentine in individual teeth treated with Ca(OH)
    Conclusion: Mineral changes in demineralised dentine and within restorative materials are quantifiable using non-destructive 3D-XMT subtraction methodology. This laboratory study suggested that calcium, phosphate and strontium ion-exchange occurs with GIC, MTA and Ca(OH)
    Clinical relevance: In clinical practice, incomplete carious lesion removal could be performed to avoid the dental pulp exposure. 3D non-destructive XMT subtraction methodology in a laboratory setting is advantageous to provide evidence for different restorative materials on deep carious lesions prior to clinical investigations.
    MeSH term(s) Dental Caries/diagnostic imaging ; Dental Caries/therapy ; Dental Cavity Lining ; Dental Materials ; Dentin/diagnostic imaging ; Glass Ionomer Cements ; Humans ; London ; Minerals
    Chemical Substances Dental Materials ; Glass Ionomer Cements ; Minerals
    Language English
    Publishing date 2020-05-31
    Publishing country England
    Document type Journal Article
    ZDB-ID 186068-9
    ISSN 1879-176X ; 0300-5712
    ISSN (online) 1879-176X
    ISSN 0300-5712
    DOI 10.1016/j.jdent.2020.103389
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A database for curating the associations between killer cell immunoglobulin-like receptors and diseases in worldwide populations.

    Takeshita, Louise Y C / Gonzalez-Galarza, Faviel F / dos Santos, Eduardo J M / Maia, Maria Helena T / Rahman, Mushome M / Zain, Syed M S / Middleton, Derek / Jones, Andrew R

    Database : the journal of biological databases and curation

    2013  Volume 2013, Page(s) bat021

    Abstract: The killer cell immunoglobulin-like receptors (KIR) play a fundamental role in the innate immune system, through their interactions with human leucocyte antigen (HLA) molecules, leading to the modulation of activity in natural killer (NK) cells, mainly ... ...

    Abstract The killer cell immunoglobulin-like receptors (KIR) play a fundamental role in the innate immune system, through their interactions with human leucocyte antigen (HLA) molecules, leading to the modulation of activity in natural killer (NK) cells, mainly related to killing pathogen-infected cells. KIR genes are hugely polymorphic both in the number of genes an individual carries and in the number of alleles identified. We have previously developed the Allele Frequency Net Database (AFND, http://www.allelefrequencies.net), which captures worldwide frequencies of alleles, genes and haplotypes for several immune genes, including KIR genes, in healthy populations, covering >4 million individuals. Here, we report the creation of a new database within AFND, named KIR and Diseases Database (KDDB), capturing a large quantity of data derived from publications in which KIR genes, alleles, genotypes and/or haplotypes have been associated with infectious diseases (e.g. hepatitis C, HIV, malaria), autoimmune disorders (e.g. type I diabetes, rheumatoid arthritis), cancer and pregnancy-related complications. KDDB has been created through an extensive manual curation effort, extracting data on more than a thousand KIR-disease records, comprising >50 000 individuals. KDDB thus provides a new community resource for understanding not only how KIR genes are associated with disease, but also, by working in tandem with the large data sets already present in AFND, where particular genes, genotypes or haplotypes are present in worldwide populations or different ethnic groups. We anticipate that KDDB will be an important resource for researchers working in immunogenetics. Database URL: http://www.allelefrequencies.net/diseases/.
    MeSH term(s) Data Mining ; Databases, Genetic ; Disease/genetics ; Genetic Association Studies ; Genetic Predisposition to Disease ; Genetics, Population ; Humans ; Internationality ; Internet ; Receptors, KIR/genetics ; Search Engine
    Chemical Substances Receptors, KIR
    Language English
    Publishing date 2013-04-12
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2496706-3
    ISSN 1758-0463 ; 1758-0463
    ISSN (online) 1758-0463
    ISSN 1758-0463
    DOI 10.1093/database/bat021
    Database MEDical Literature Analysis and Retrieval System OnLINE

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