Kuwait Journal of Science最新文献

Sulaibikhat Bay, a shallow embayment dominated by tides and extensive mud flats along the northern coast of Kuwait Bay, serves as a crucial nursery ground for various commercially important species of finfish and shellfish in the Northwestern Arabian Gulf (NWAG). As the location of Kuwait's inaugural marine protected area (MPA), Sulaibikhat Bay plays a vital role in fostering numerous fish and marine invertebrate species of commercial importance in the Arabian/Persian Gulf. Accurate identification of larval specimens from this habitat is essential for understanding their spawning dynamics and recruitment process. However, limitations in taxonomic identification hinder scientific understanding of fish larval recruitment. To address this, our baseline study employed an integrated taxonomic approach, combining conventional morphology with molecular techniques. Fish larvae collected from the MPA and surrounding waters in Spring (2022) were identified up to the genus and species levels using partial gene sequencing of 16 S rRNA and mitochondrial cytochrome oxidase (COI) genes. Morphological analysis indicated the prevalence of Sparidae, Sillaginidae, and Dorosomatidae families. Molecular analysis confirmed the presence of these families and identified two species, Crenidens crenidens (Sparidae) and Nematalosa nasus (Dorosomatidae), along with two genera, Diplodus sp. (Sparidae) and Sillago sp. (Sillaginidae), which exhibited maximum similarity to available COI sequences of Diplodus sargus, and Sillago maculata, respectively. This represents the first baseline molecular study on fish larvae from NWAG, laying the groundwork for future in-depth analyses with more larval specimens and spatiotemporal samplings from the entire exclusive economic zone (EEZ) of Kuwait in the Arabian/Persian Gulf.

Increasing levels of polystyrene microplastics (PS-MPs) in the environment poses huge global health threat. Prolonged exposure to PS-MPs results in both male and female infertility, with a deleterious effect on reproductive health. In rats, the disruptive effects of chemotoxicants have been countered by lycopene (LYC). This study examined the protective benefits of lycopene (LYC) against spermatological damage and hormonal alterations brought on by polystyrene microplastics (PS-MPs) in male rats. Twenty Wistar rats were split into four groups of five rats, each consisting of: the control group, the PSMPs treatment group, the PS-MPs + LYC co-treatment group, and the LYC supplementation group. Severe testicular histological damage was seen to have resulted from exposure to PS-MPs. The PS-MPs treatment dramatically reduced the antioxidant enzyme activities while raising the levels of ROS and MDA, thus reducing sperm progressive motility. Also, spermatological damage and hormonal alterations brought on by polystyrene microplastics (PS-MPs) were also prevented by the effects of lycopene (LYC). In conclusion, LYC supplementation has the ability to reduce the harmful effects of PS-MPs on the male reproductive system. Accordingly, LYC prevented PS-MPs-induced spermatological damage and reproductive hormonal changes in rats via its anti-oxidant, androgenic, anti-apoptotic, anti-inflammatory properties.

The Indonesian throughflow (ITF) in the eastern part of Indonesia passes through the Maluku, Taliabu, Sula, and Buru Islands to the Banda Sea. The average depth of the Buru and Sula Islands is between 1000 m and 5000 m, with a narrow gap (sill) located to the north and south at a depth of 165 m on the sea map. This topography makes for interesting research on the western waters of Buru Island. Therefore, this study aimed to obtain salinity, temperature, and density values as water column stratification associated with the internal wave (IW), thermocline area, and current patterns at specific depths in the waters of Buru Island, Banda Sea. Data were collected from initial observations of Sentinel 1 satellite imagery of Buru Island to obtain an image of the waves in the water area. Furthermore, a single beam echosounder (SBES), conductivity temperature depth (CTD), and Copernicus Marine were analysed at the same position and time. The research found a non-linear IW Mode 2 at depths of 440–540 m with an estimated amplitude length is 40 km and an amplitude height of 100 m. Based on SBES echogram imaging, CTD data analysis, and modelling, there was an increase in IW density, a 35.25 PSU increase in salinity value at depths of 50∼200 m, a temperature decrease of 27.5 °C to 10 °C at depths of 50∼300 m, and a density stratification of 23.5 kg/m³ to 27 kg/m³ at depths of 50∼300 m.

The tsunami disaster in Palu, Indonesia, on September 28, 2018, caused many casualties and damage along Palu Bay, Indonesia. Prior to the tsunami, an earthquake was recorded 25 km northeast of Donggala. The analysis suggests that the tsunami was triggered by a landslide beneath the waters of Palu Bay. The investigation then focused on the earthquake's impact on the tsunami. This study conducts simulations to discern the dominant causes of tsunamis, comparing the effects of landslides with earthquakes. Three distinct tsunami sources were identified: earthquake-only (T-E), earthquake and submarine landslide (T-EL), and submarine landslide-only (T-L). Interpretation of tsunami source parameters for underwater landslides is carried out accurately. A nesting grid numerical method was employed to increase resolution and accuracy in the simulations. This study accurately interprets tsunami source parameters using data from the Bathymetry National Data-Geospatial Information Agency (185 m resolution) and the field survey data from Baruna Jaya IV-BPPT Research Vessel Indonesia (25 m resolution), thereby contributing to the creation of a tsunami inundation model map. This map serves to inform preparedness efforts and guide recommendations for infrastructure development in the Palu Bay area. The tsunami inundation model map is verified with field data and estimated using tide gauge monitoring data. The characteristics of the tsunami waves on September 28, 2018, reflect a T-EL-type tsunami source, while the T-L type source produces tsunami waves with longer periods compared to earthquake-generated tsunamis (T-EL). The T-E type, located on land, had minimal influence in causing the tsunami, despite the destructive potential of the shallow-depth M7.5 earthquake.

Multispectral remote sensing data provided valuable information for hydrothermal minerals exploration. In this article, Landsat-8 Operational Land Imager (OLI) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data were processed and analyzed using band ratio and principal component techniques to demarcate areas of hydrothermal mineral resources by highlighting the most influenced zone of hydrothermal alteration (high-grade) in Egypt. The area is a part of the Arabian-Nubian Shield, covering 1068 km^2, and comprises wide varieties of Pre- and Pan-African rock assemblages. Preparing and integrating thematic layers consisting of the grade of hydrothermal intensity in a GIS technique supported generating a hydrothermal mineral predictive map (HMPM) using a multi-criteria decision-making technique. The plausible zone of very high mineral resources covers about 6.57 %. Analysis of ASTER data revealed that this zone is reliable with phyllic and argillic minerals and iron-oxides. The results of OLI data helped in demarcating potential areas of hydrothermal alteration areas (Al–OH) mixed with iron oxides. Field observations and investigations enabled the validation of the HMPM. The spatial distribution of hydrothermal zones throughout the study was reliable to that observed in the mine areas. Field and ore microscopic examination verified the existence of Au-sulfide minerals connected with hydrothermal alteration zones (HAZs) in different areas e.g., Abu-Marawat, Gidami, Semna, Abu-Gaharish, and Hamama mines. Overall, integrating multi-spectral data through overlay analysis techniques can provide valuable information about hydrothermal mineral resources in an accurate and cost-effective approach.

To develop a specific watershed scenario, the quantity and quality of groundwater resources must be assessed and monitored locally. In the present study, an attempt has been made to identify possible groundwater potential zones, determine the quality of groundwater resources in this region, and evaluate their suitability for drinking and irrigation purposes. This goal has been achieved with the combined use of the weighted index overlay analysis (WIOA), groundwater quality index (GWQI), Remote Sensing (RS), and Geographic Information System (GIS) techniques. The proposed study area, Shanmuganadhi, is marked with superior rainfall, oscillating temperature, and runoff with litho-units encompassing charnockite (CHK) and hornblende biotite gneiss (HBG). Over-abstraction of groundwater and intensive agricultural practices have resulted in declining and degrading water quantity and quality in this area. The resulting integrated thematic map has been classified into five groundwater potential zones, namely poor, low, moderate, high, and very high, covering 3.2, 45.49, 15.3, 27.9, and 8.1% area, respectively. Sixty groundwater samples were collected during the pre-monsoon (PRM) and analyzed for major Physico-chemical parameters. From the water quality index assessment, over 28.0% of the samples fall within the “excellent,” 8.0% “good” and 4.0% “poor” in CHK, followed by 5.71% “excellent,” 48.57% “good,” 37.14% “poor,” 5.71% “very poor” and 2.87% “unsuitable” for drinking purposes in HBG terrain of this region. Irrigation indices also demonstrated that most of the groundwater samples in the CHK and HBG exposed zones exhibited good classes for irrigation purposes, as evidenced by the SAR and %Na⁺. The outcome, which shows the research area's groundwater potential zones, is beneficial for improved groundwater resource planning and management. It is concluded that for larger-scale groundwater-quality investigation and assessment, the groundwater quality index-making approach (GWQI) is more practical and dependable. Water planners and decision-makers may find it helpful in effectively controlling and monitoring groundwater quality at the basin or watershed scale. Reducing urban land use and natural runoff from farms can help prevent water contamination in some regions. To ensure the safe use of groundwater, long-term monitoring of these groundwater was suggested.

The aim of this research is to synthesize multifunctional mixed matrix cellulose acetate (CA) membranes that can provide better CO₂/N₂ selectivity and will simultaneously fight against bacteria, to immaculate the indoor environment. For that purpose, two different fillers labelled as binary ZnO@Zeolite (1:10, ZZ) and ternary ZnO–CuO@Zeolite (0.8:0.2:10, ZZC) composites have been synthesized via co-precipitation method to entrench into CA matrix with 8 wt% each. The solution mixing technique assisted by thermal evaporation process (TEAP) has been adopted to formulate the desired membranes. Surface morphology, crystalline structure, thermal decomposition, and mechanical properties of novel composites ZZ and ZZC, along with their respective corresponding membranes CA/ZZ-8 and CA/ZZC-8, have been analyzed using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and universal testing machine (UTM). The inclusion of tri-zeolitic composite (ZZC) favors the formation of denser CA membranes, with a smaller crystallite size (10.8 nm), higher thermal stability (%), and a notable increase in mechanical strength (MPa) in contrast to virgin CA as well as bi-zeolitic composite (ZZ) loaded membranes. The selectivity for CO₂/N₂ separation of tri-zeolitic composite loaded membranes (CA/ZZC-8) is almost six folds higher compared to the pristine CA membrane, whereas it is five folds for bi-zeolitic composite impregnated membrane (CA/ZZ-8). To eradicate bacterial fouling, bi/tri-zeolitic composite loaded membranes are tested against E. coli bacteria by broth culture method and the results validate their antibiotic nature. Synthesized novel CA membranes with hybrid composites provide convenient access towards the development of multipurpose membranes.

Land Surface Temperature (LST) is a crucial parameter in Earth observation and environmental studies due to its significance in various fields. The purpose of this study is to investigate the effects of including spatial information into the Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) models for forecasting LST. The significance and impact of each input parameter on the models' predictive capabilities are assessed using the SHAP (SHapley Additive exPlanations) approach and the model intercomparisons were done using the error evaluation metrices. The predictions were further validated using the Pearson correlation, independent samples t-test and potential geographic anomalies in the predictions are examined by spatial comparison of predicted errors using classification maps and error envelopes. The projected errors are within the acceptable range and range from −2.267 °C to 1.292 °C for the spatially enhanced RF model and from −1.675 °C to 1.439 °C for the spatially enhanced XGBoost model. These error ranges closely align with the training data's quality flag of ±2 °C, demonstrating the models' capability to predict LST accurately and within a reasonable error range. The findings show the significance of adding spatial information for precise LST prediction and draw attention to possible uses for such models in environmental monitoring and management. The work advances our understanding of spatial modelling strategies and offers practical guidelines for enhancing LST forecasts.

In the last few years, the COVID-19 pandemic has increased the usage of antigen rapid test (ART) kits and improper disposal of these kits has led to the mixing of toxic chemical compounds present in the ART reagent solution container into drinking water sources. When consumed with drinking water, these compounds can be harmful and toxic to both humans and aquatic life. Therefore, this research presents a study on the photocatalytic degradation of the Antigen Rapid Test-Reagent solution (ART-RS) using a single-phase titanium oxycarbide - TiO_0.25 C_0.75 (TiOC) photocatalyst synthesized through a solid-state reaction. The synthesized samples were studied using various characterization tools to analyze their structural, morphological, and optical characteristics. In the photocatalytic experiment, it was found that the synthesized titanium oxycarbide photocatalyst exhibited superior ART-RS degradation efficiency of 77% compared to commercial titanium dioxide (22%). The improved photocatalytic degradation efficiency of ART-RS is attributed to a combination of several factors. These factors include a narrower band gap, more efficient charge transfer kinetics, enhanced absorption of visible light, and an upward shift of the valence band (VB) edge in titanium oxycarbide. These collective effects contribute to the enhanced ART-RS photocatalytic degradation activity.

Ranked set sampling is widely acknowledged for its superior efficiency compared with simple random sampling. Only a small amount of work has been conducted using ranked set sampling when measurement errors are present. This study introduces innovative estimators utilizing ranked set sampling to assess the population mean when faced with both correlated and uncorrelated measurement errors. The expressions for the bias and mean squared error of the proposed estimators are derived up to the first-order approximation, revealing their superior performance compared to the other examined estimators. The efficacy of the suggested estimators in handling measurement errors was demonstrated through numerical illustration and simulation study investigations. The recommended estimators are further compared to the existing ones using the percentage relative efficiency and mean squared error, and the impact of measurement errors on the results is highlighted through the percentage computation of measurement errors. The innovative estimators suggested were formulated by judiciously incorporating ratio, exponential, and log estimators. Numerical examples involving expenditure and income, as well as simulated data generated from a normal population using R software, affirm the superior performance of the proposed estimators over existing ones such as the usual mean estimator and those proposed by Vishwakarma and Singh (2022), as evidenced by the higher percent relative efficiency and lower mean squared error. The evaluation of the percentage contribution of measurement error values confirms the impact of measurement errors on the properties of the estimators.