Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects.

Heavy metals (HMs) such as Lead (Pb) have played a vital role in increasing the sediments of the Australian bay's ecosystem. Several meteorological parameters (i.e., minimum, maximum and average temperature (Tmin, Tmax and TavgoC), rainfall (Rn mm) and their interactions with the other batch HMs, are hypothesized to have high impact for the decision-making strategies to minimize the impacts of Pb. Three feature selection (FS) algorithms namely the Boruta method, genetic algorithm (GA) and extreme gradient boosting (XGBoost) were investigated to select the highly important predictors for Pb concentration in the coastal bay sediments of Australia. These FS algorithms were statistically evaluated using principal component analysis (PCA) Biplot along with the correlation metrics describing the statistical characteristics that exist in the input and output parameter space of the models. To ensure a high accuracy attained by the applied predictive artificial intelligence (AI) models i.e., XGBoost, support vector machine (SVM) and random forest (RF), an auto-hyper-parameter tuning process using a Grid-search approach was also implemented. Cu, Ni, Ce, and Fe were selected by all the three applied FS algorithms whereas the Tavg and Rn inputs remained the essential parameters identified by GA and Boruta. The order of the FS outcome was XGBoost > GA > Boruta based on the applied statistical examination and the PCA Biplot results and the order of applied AI predictive models was XGBoost-SVM > GA-SVM > Boruta-SVM, where the SVM model remained at the top performance among the other statistical metrics. Based on the Taylor diagram for model evaluation, the RF model was reflected only marginally different so overall, the proposed integrative AI model provided an evidence a robust and reliable predictive technique used for coastal sediment Pb prediction.

Spatiotemporal changes in aerosols over Bangladesh using 18 years of MODIS and reanalysis data.

In this study, combined Dark Target and Deep Blue (DTB) aerosol optical depth at 550 nm (AOD550 nm) data the Moderate Resolution Imaging Spectroradiometer (MODIS) flying on the Terra and Aqua satellites during the years 2003-2020 are used as a reference to assess the performance of the Copernicus Atmosphere Monitoring Services (CAMS) and the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2) AOD over Bangladesh. The study also investigates long-term spatiotemporal variations and trends in AOD, and determines the relative contributions from different aerosol species (black carbon: BC, dust, organic carbon: OC, sea salt: SS, and sulfate) and anthropogenic emissions to the total AOD. As the evaluations suggest higher accuracy for CAMS than for MERRA-2, CAMS is used for further analysis of AOD over Bangladesh. The annual mean AOD from both CAMS and MODIS DTB is high (>0.60) over most parts of Bangladesh except for the eastern areas of Chattogram and Sylhet. Higher AOD is observed in spring and winter than in summer and autumn, which is mainly due to higher local anthropogenic emissions during the winter to spring season. Annual trends from 2003-2020 show a significant increase in AOD (by 0.006-0.014 year-1) over Bangladesh, and this increase in AOD was more evident in winter and spring than in summer and autumn. The increasing total AOD is caused by rising anthropogenic emissions and accompanied by changes in aerosol species (with increased OC, sulfate, and BC). Overall, this study improves understanding of aerosol pollution in Bangladesh and can be considered as a supportive document for Bangladesh to improve air quality by reducing anthropogenic emissions.

The concentration of potentially hazardous elements (PHEs) in drinking water and non-carcinogenic risk assessment: A case study in Bandar Abbas, Iran.

In this study, concentration of potentially hazardous elements (PHEs) including slice (Si), strontium (Sr), aluminum (Al), Fluoride (F), Iron (Fe), Zinc (Zn), Barium (Ba), Lead (Pb), Lithium (Li), Vanadium (V), selenium (Se), Chrome (Cr), Arsenic (As) and Uranium (U) in tap drinking water (n = 40) and filtration plant (n = 22) in Bandar Abbas city between March to July 2020 were analyzed. Analysis of PHEs ions was conducted by inductively coupled plasma mass spectrometry (ICP-MS). Also, concentration of F was measured by SPADNS Method. The non-carcinogenic risk in the exposed population (adult and children) were estimated. Concentration of PHEs between tap drinking water and filtration plant was compared using T statistical test. In addition, association among PHEs in tap drinking water and water filtration plant using Pearson correlation coefficient. The rank order of PHEs in tap drinking water was Si (6356.25 µg/l) > Sr (3980 µg/l) > Al (115.42 µg/l) > Fe (30.00 µg/l) > Zn (14.59 µg/l) > Ba (13.91 µg/l) > Pb (13.01 µg/l) > Li (11.60 µg/l) > V (4.43 µg/l) > Se (4.17 µg/l) > Cr (2.51 µg/l) > As (2.00 µg/l) > U (0.65 µg/l) > F (0.31 µg/l) and also in filtration plant was Si (1825.00 µg/l) > Sr (539.00 µg/l) > Fe (45.00 µg/l) > Al (26.00 µg/l) > Zn (8.08 µg/l) > Ba (2.24 µg/l) > Se (1.36 µg/l)> Pb(1.28 µg/l) > Li (1.26 µg/l) > Cr (1.17 µg/l) > F (0.66 µg/l) > V (0.61 µg/l) > As (LOD < ) ~ U (LOD <). The most of PHEs in tap drinking water was considerable different with filtration plant (p value < 0.05) therefore the chemical quality of tap drinking water should be more attention. The results of non-carcinogenic risk assessment revealed that TTHQ in the adults and children due to drinking tap water content of PHEs was 2.59E-3 and 6.05E-3 and filtration plant was 8.88E-04 and 2.07E-03, respectively. Therefore, TTHQ in adults and children was lower than 1; therefore, consumers are in the safe range due to drinking tap water and water filtration plant content of PHEs.

Designing Low-Cost Capacitive-Based Soil Moisture Sensor and Smart Monitoring Unit Operated by Solar Cells for Greenhouse Irrigation Management.

Precise and quick estimates of soil moisture content for the purpose of irrigation scheduling are fundamentally important. They can be accomplished through the continuous monitoring of moisture content in the root zone area, which can be accomplished through automatic soil moisture sensors. Commercial soil moisture sensors are still expensive to be used by famers, particularly in developing countries, such as Egypt. This research aimed to design and calibrate a locally manufactured low-cost soil moisture sensor attached to a smart monitoring unit operated by Solar Photo Voltaic Cells (SPVC). The designed sensor was evaluated on clay textured soils in both lab and controlled greenhouse environments. The calibration results demonstrated a strong correlation between sensor readings and soil volumetric water content (θV). Higher soil moisture content was associated with decreased sensor output voltage with an average determination coefficient (R2) of 0.967 and a root-mean-square error (RMSE) of 0.014. A sensor-to-sensor variability test was performed yielding a 0.045 coefficient of variation. The results obtained from the real conditions demonstrated that the monitoring system for real-time sensing of soil moisture and environmental conditions inside the greenhouse could be a robust, accurate, and cost-effective tool for irrigation management.

Thermodynamic and structural investigation of oily wastewater treatment using peach kernel and walnut shell based activated carbon.

Despite the many articles about activated carbon with different precursors in adsorption process, no in-depth research has been carried out to understand the causes of the difference in surface adsorption characteristics of activated carbon with different precursors and different activation processes. In this work, the ability of two active carbon adsorbents made of walnut shell and peach kernel by two chemical and physical methods (totally 4 different types of activated carbon) in treatment of oily wastewater including diesel, gasoline, used oil or engine lubricant has been compared. The results show that the chemical activated peach carbon active with 97% hardness has provided the highest hardness and physical activated walnut carbon active has obtained the lowest hardness value (87%). It is also found that peach activated carbon has a higher iodine number than walnut activated carbon, and this amount can be increased using chemical methods; Therefore, the highest amount of Iodine Number is related to Peach activated carbon that is made by chemical method (1230 mg/g), and the lowest amount of iodine number is seen in walnut activated carbon that is made by physical method (1020 mg/g). moreover, the pore diameter of physical activated carbon is lower than chemical activated carbon in all cases. So that the pore diameter of chemical activated peach carbon active is equal to 22.08 µm and the measured pore diameter of physical activated peach carbon active is equal to 20.42 µm. These values for walnut are obtained as 22.74 µm and 21.86 µm, respectively. Furthermore, the temperature and pH effects on the adsorption of different synthesized oily wastewater was studied and it was found that a decrease in adsorption can be seen with an increase in temperature or decreasing the pH value, which can be referred to this fact that the process of adsorption is an exothermic process. Finally, to analyze the compatibility of adsorption isotherms with experimental data and to predict the adsorption process, three different isotherms named Langmuir, Temkin, and Freundlich isotherms were applied and their parameters were correlated. The correlation results show that the Langmuir isotherm had the best correlation in all cases compared to the Freundlich and Temkin isotherms, based on the correlation coefficient, and the calculated R2 values which was greater than 0.99 in all the studied cases.

Decoding seasonal variability of air pollutants with climate factors: A geostatistical approach using multimodal regression models for informed climate change mitigation.

In response to changes in climatic patterns, a profound comprehension of air pollutants (AP) variability is vital for enhancing climate models and facilitating informed decision-making in nations susceptible to climate change. Earlier research primarily depended on limited models, potentially neglecting intricate relationships and not fully encapsulating associations. This study, in contrast, probed the spatiotemporal variability of airborne particles (CO, CH4, SO2, and NO2) under varying climatic conditions within a climate-sensitive nation, utilizing multiple regression models. Spatial and seasonal AP data were acquired via the Google Earth Engine platform, which indicated elevated AP concentrations in primarily urban areas. Remarkably, the average airborne particle levels were lower in 2020 than in 2019, though they escalated during winter. The study employed linear regression, Pearson's correlation (PC), Spearman rank correlation models, and Geographically Weighted Regression (GWR) models to probe the relationship between pollutant variability and climatic elements such as rainfall, temperature, and humidity. Across all seasons, APs showed a negative correlation with rainfall while displaying positive correlations with temperature and humidity. The GWR and PC models produced the most reliable results from all the models employed, with the GWR model superseding the rest. Moreover, heightened aerosol levels were detected within a rainfall range of 600 mm/season, a temperature range of 25-30 °C, and humidity levels of 75 %-85 %. Overall, this study emphasizes the growing levels of APs in correlation with meteorological changes. By adopting a comprehensive approach and considering multiple factors, this research provides a more sophisticated understanding of the relationship between AP variability and climatic shifts.

Delineation of urban expansion influences urban heat islands and natural environment using remote sensing and GIS-based in industrial area.

Land transformation monitoring is essential for controlling the anthropogenic activities that could cause the degradation of natural environment. This study investigated the urban heat island (UHI) effect at the Asansol and Kulti blocks of Paschim Bardhaman district, India. The increasing land surface temperature (LST) can cause the UHI effect and affect the environmental conditions in the urban area. The vulnerability of the UHI effect was measured quantitatively and qualitatively by using the urban thermal field variation index (UTFVI). The land use and land cover (LULC) dynamics are identified by utilizing the remote sensing and maximum likelihood supervised classification techniques for the years 1990, 2000, 2010, and 2020, respectively. The results indicated a decrease around 19.05 km2, 15.47 km2, and 9.86 km2 for vegetation, agricultural land, and grassland, respectively. Meanwhile, there is an increase of 35.69 km2 of the built-up area from the year 1990 to 2020. The highest LST has increased by 11.55 °C, while the lowest LST increased by 8.35 °C from 1990 to 2020. The correlation analyses showed negative relationship between LST and vegetation index, while positive correlation was observed for built-up index. Hotspot maps have identified the spatio-temporal thermal variations in Mohanpur, Lohat, Ramnagar, Madhabpur, and Hansdiha where these cities are mostly affected by the urban expansion and industrialization developments. This study will be helpful to urban planners, stakeholders, and administrators for monitoring the anthropological activities and thus ensuring a sustainable urban development.

Tropical peat subsidence rates are related to decadal LULC changes: Insights from InSAR analysis.

Peatlands in Indonesia are subject to subsidence in recent years, resulting in significant soil organic carbon loss. Their degradation is responsible for several environmental issues; however, understanding the causes of peatland subsidence is of prime concern for implementing mitigation measures. Here, we employed time-series Small BAseline Subset (SBAS) Interferometric Synthetic Aperture Radar (InSAR) using ALOS PALSAR-2 images to assess the relationship between subsidence rates and land use/land cover (LULC) change (including drainage periods) derived from decadal Landsat data (1972-2019). Overall, the study area subsided with a mean rate of -2.646 ± 1.839 cm/year in 2018-2019. The subsidence rates slowed over time, with significant subsidence decreases in peatlands after being drained for 9 years. We found that the long-time persistence of vegetated areas leads to subsidence deceleration. The relatively lower subsidence rates are in areas that changed to rubber/mixed plantations. Further, the potential of subsidence prediction was assessed using Random Forest (RF) regression based on LULC change, distance from peat edge, and elevation. With an R2 of 0.532 (RMSE = 0.594 cm/year), this machine learning method potentially enlarges the spatial coverage of InSAR method for the higher frequency SAR data (such as Sentinel-1) that mainly have limited coverage due to decorrelation in vegetated areas. According to feature importance in the RF model, the contribution of LULC change (including drainage period) to the subsidence model is comparable with distance from peat edge and elevation. Other uncertainties are from unexplained factors related to drainage and peat condition, which need to be accounted for as well. This work shows the significance of decadal LULC change analysis to supplement InSAR measurement in tropical peatland subsidence monitoring programs.

Integrated approach to evaluate unstable rocky slopes: case study of Aqabat Al-Sulbat road in Aseer Province, Saudi Arabia.

In this applied research work, the risk of rock instability in the Aqabat Al-Sulbat road section located in the north-west area of Aseer Province in Saudi Arabia was evaluated, and the primary natural trigger factors of rock slope instability on further environmental components (rock slope stability, road network, and urban areas) were estimated using satellite images (Landsat8), digital terrain models, and geoprocessing in geographical information systems software (classification, overlapping algorithms and production thematic mapping in Arctoolbox). Additionally, field geotechnical investigations testing and over-coring drilling sampling allowed the characterization of the section of road in terms of geological structure and environmental components (geology, morphology, road network, lineaments, and hydrology). As a result, rock slope instability vulnerability mapping was simulated using satellite imagery and geographical information systems (GIS) and ranking natural trigger factors using the combined fuzzy Delphi analytical hierarchic process with the technique for order performance by similarity to ideal solution (TOPSIS) as multiple-criteria decision-making (MCDM) techniques. Additionally, many rock layer discontinuity stations were implemented to evaluate rock slope instabilities, and these were visualized using the Dips program and combined with modeling using 3DEC software to predict rock slope failure based on the distinct element method (DEM) at a small scale. Thereafter, safety factors were computed depending on these previous geospatial data. Finally, vulnerability index mapping was combined with rock instability risk mapping for the Aqabat Al-Sulbat road. Within the framework of sustainable development, these results can be used to inform the urban planning of the municipality of Aseer Province.

Evaluation and Numerical Investigations of the Cyclic Behavior of Smart Composite Steel-Concrete Shear Wall: Comprehensive Study of Finite Element Model.

The composite shear wall has various merits over the traditional reinforced concrete walls. Thus, several experimental studies have been reported in the literature in order to study the seismic behavior of composite shear walls. However, few numerical investigations were found in the previous literature because of difficulties in the interaction behavior of steel and concrete. This study aimed to present a numerical analysis of smart composite shear walls, which use an infilled steel plate and concrete. The study was carried out using the ANSYS software. The mechanical mechanisms between the web plate and concrete were investigated thoroughly. The results obtained from the finite element (FE) analysis show excellent agreement with the experimental test results in terms of the hysteresis curves, failure behavior, ultimate strength, initial stiffness, and ductility. The present numerical investigations were focused on the effects of the gap, thickness of infill steel plate, thickness of the concrete wall, and distance between shear studs on the composite steel plate shear wall (CSPSW) behavior. The results indicate that increasing the gap between steel plate and concrete wall from 0 mm to 40 mm improved the stiffness by 18% as compared to the reference model, which led to delay failures of this model. Expanding the infill steel plate thickness to 12 mm enhanced the stiffness and energy absorption with a ratio of 95% and 58%, respectively. This resulted in a gradual drop in the strength capacity of this model. Meanwhile, increasing concrete wall thickness to 150 mm enhanced the ductility and energy absorption with a ratio of 52% and 32%, respectively, which led to restricting the model and reduced lateral offset. Changing the distance between shear studs from 20% to 25% enhanced the ductility and energy absorption by about 66% and 32%, respectively.

A modified approach to quantify aquifer vulnerability to pollution towards sustainable groundwater management in Irrigated Indus Basin.

The quality of groundwater in the study watershed has worsened because of industrial effluents and residential wastes from the urbanized cities; therefore, there is an important need to explore the aquifer vulnerability to pollution for sustainable groundwater management in the Irrigated Indus Basin (IIB). This study proposed a novel methodology to quantify groundwater vulnerability using two fully independent methodologies: the first by reintroducing an improved recharge factor (R) map and the second by incorporating three different weight and rating schemes into a traditional DRASTIC framework to improve the performance of the DRASTIC approach. In the current study, we composed a recharge map from Soil and Water Assessment Tool (SWAT) output (namely SWAT recharge map) with a drainage density map to retrieve an improved composite recharge map (SWAT-CRM). SWAT-CRM along with other thematic layers was combined using weightage overlay analysis to prepare the maps of groundwater vulnerability index (VI). The weight scale (w) and rating scale (r) were assigned based on a survey of available literature, and we then amended them using the analytical hierarchy process (AHP) and a probability frequency ratio (PFR) technique. Results depicted that the region under high groundwater vulnerability was found to be 5-22% using traditional recharge maps, while those are 9-23% using improved SWAT-CRM. The area under the curve (AUC) revealed that groundwater vulnerability zones predicted with SWAT-CRM outperformed the DRASTIC model applied with the traditional recharge map. Groundwater electrical conductivity (EC) was>2500 mS/cm in the high groundwater vulnerability zones, while it was <1000 mS/cm in the low groundwater vulnerability zones. The outcomes of this study can be used to improve the sustainability of the groundwater resources in IIB through proper land-use management practices.

The concentration and health risk assessment of radionuclides in the muscle of tuna fish: A worldwide systematic review and meta-analysis.

Exposure to radionuclides, especially in food, can endanger the health of consumers. In this study, a systematic review and meta-analysis were performed regarding the concentration of radionuclides in tuna fish muscle. International databases including PubMed, Scopus, and Embase were searched to find articles regarding the concentration of radionuclides in tuna fish muscle from 1 January 2000 to 20 February 2021. The lowest and highest concentration of radionuclides was related to Caesium-137 (137Cs) and Potassium-40 (4 K), respectively. The rank order of radionuclides based on their pooled concentration was 4 K (370.157 Bq/kg) > 210Po Polonium-210 (26.312 Bq/kg) > 210Pb (5.339 Bq/kg) > 226Ra (4.005 Bq/kg) > 137Cs (0.415 Bq/kg). The health risk assessment based on annual effective dose indicates that consumers are at the safe range of health risk (H < 1 mSv/y). The continuous monitoring concentration of radionuclides in seafood and health risk assessment should be recommended.

Palladium/Graphene Oxide Nanocomposite for Hydrogen Gas Sensing Applications Based on Tapered Optical Fiber.

Gaseous pollutants such as hydrogen gas (H2) are emitted in daily human activities. They have been massively studied owing to their high explosivity and widespread usage in many domains. The current research is designed to analyse optical fiber-based H2 gas sensors by incorporating palladium/graphene oxide (Pd/GO) nanocomposite coating as sensing layers. The fabricated multimode silica fiber (MMF) sensors were used as a transducing platform. The tapering process is essential to improve the sensitivity to the environment through the interaction of the evanescent field over the area of the tapered surface area. Several characterization methods including FESEM, EDX, AFM, and XRD were adopted to examine the structure properties of the materials and achieve more understandable facts about their functional performance of the optical sensor. Characterisation results demonstrated structures with a higher surface for analyte gas reaction to the optical sensor performance. Results indicated an observed increment in the Pd/GO nanocomposite-based sensor responses subjected to the H2 concentrations increased from 0.125% to 2.00%. The achieved sensitivities were 33.22/vol% with a response time of 48 s and recovery time of 7 min. The developed optical fiber sensors achieved excellent selectivity and stability toward H2 gas upon exposure to other gases such as ammonia and methane.

Farasan Island of Saudi Arabia confronts the measurable impacts of global warming in 45 years.

Coastal vulnerability assessment is the key to coastal management and sustainable development. Sea level rise (SLR) and anthropogenic activities have triggered more extreme climatic events and made the coastal region vulnerable in recent decades. Many parts of the world also noticed increased sediment deposition, tidal effects, and changes in the shoreline. Farasan Island, located in the south-eastern part of Saudi Arabia, experienced changes in sediment deposition from the Red Sea in recent years. This study used Digital Shoreline Analysis System (DSAS) to delineate the shoreline changes of Farasan Island during 1975-2020. Multi-temporal Landsat data and DSAS were used for shoreline calculation based on endpoint rate (EPR) and linear regression. Results revealed an increase in vegetation area on the island by 17.18 km2 during 1975-1989 and then a decrease by 69.85 km2 during 1990-2020. The built-up land increased by 5.69 km2 over the study period to accommodate the population growth. The annual temperature showed an increase at a rate of 0.196 °C/year. The sea-level rise caused a shift in the island's shoreline and caused a reduction of land by 80.86 km2 during 1975-2020. The highly influenced areas by the environmental changes were the north, central, northwest, southwest, and northeast parts of the island. Urban expansion and sea-level rise gradually influence the island ecosystem, which needs proper attention, management, policies, and awareness planning to protect the environment of Farasan Island. Also, the study's findings could help develop new strategies and plan climate change adaptation.

Room and High Temperature Tensile Responses of Tib2-Graphene Al 7075 Hybrid Composite Processed through Squeeze Casting.

The development of aluminium composite with the inclusion of advanced materials is a continuous research process due to the increasing industrial demand for advanced hybrid materials. To cater for this need, this research work focuses on the development of Al 7075 alloy reinforced with TiB2 and graphene and on the evaluation of its strengthening mechanism. Two different modes of improving the strength of the hybrid composite have been followed; one is by the inclusion of graphene at three levels of 0.1, 0.2 and 0.3%, and another by the processing route, squeeze casting technique by compression of the molten hybrid composite slurry before casting. The microstructure and characterisation of the composite material are examined and analysed with the help of XRD, SEM, EDAX and chemical spectroscopy. A microstructure evaluation is employed to justify the homogenous dispersal and the existence of reinforced particles. A tensile test is conducted at room temperature and high temperature environments to assess the tensile strength. The research outcome affirms that a significant improvement in tensile and hardness has been noted in comparison with base alloy. The fracture-morphology results affirm the change in fracture mode from brittle to ductile when the tensile testing environment changes from room temperature to high temperature. Finally, the dispersion strengthening mechanism is validated with an empirical approach.

A Study on the Mechanical Characteristics of Glass and Nylon Fiber Reinforced Peach Shell Lightweight Concrete.

In the current study, the utilization of glass and nylon fibers in various percentages are added to enhance the mechanical performance of peach shell lightweight concrete. Glass and nylon fibers were added at 2%, 4%, 6%, and 8% by cement weight. The results showed that, as we added the glass and nylon fibers, the density of peach shell concrete was reduced by 6.6%, and the compressive, split tensile and flexural strength were enhanced by 10.20%, 60.1%, and 63.49%. The highest strength that was obtained in compressive, split tensile, and flexural strength at 56 days was 29.4 MPa, 5.2 MPa, and 6.3 MPa, respectively, with 6% of glass fiber in peach shell concrete. Mechanical test results showed that post-failure toughness and modulus of elasticity of peach shell concrete is enhanced with the utilization of fibers. To verify our lab results, a statistical analysis, such as response surface methodology, was performed to make a statistical model, it was confirmed by both lab results and statistical analysis that the mechanical performance of peach shell concrete could be significantly improved by adding glass fibers as compared to nylon fibers. With the use of fibers, the water absorption and porosity were slightly increased. Hence, the glass and nylon fibers can be used to improve the peach shell concrete mechanical properties to make concrete eco-friendly, sustainable, and lightweight.

A step towards sustainable glass fiber reinforced concrete utilizing silica fume and waste coconut shell aggregate.

Today, it's getting harder to find natural resources for concrete production. Utilization of the waste materials not just helps in getting them used in concrete, cement, and other construction materials, but also has various secondary advantages, for example, saving in energy, decrease in landfill cost, and protecting climate from pollution. Considering this in the development of modern structural design, utilizing waste materials instead of natural aggregate is a good option to make concrete that is sustainable and eco-friendly. The present research aims to find the impact of adding glass fiber into sustainable concrete made with silica fume, as a partial replacement of cement, and coconut shell added with different ratios as a replacement of coarse aggregate, on concrete mechanical and durability aspects. Various blends were made, with coconut shell as a substitution of coarse aggregates with different ratios. Portland cement was substituted with silica fume at 5%, 10%, 15%, and 20% by cement weight in all concrete blends. The volume ratios of glass fibers utilized in this study were 0.5%, 1.0%, 1.5% and 2.0%. Adding glass fibers increases concrete density to some extent and then marginally reduces the density of coconut shell concrete. When the percentage of glass fibers increases, the compressive, flexural and split tensile strength of coconut shell concrete also increases. From the lab results and SEM images of the present research display that glass fibers might be utilized in coconut shell concrete to enhance its mechanical and durability attributes, to accomplish sustainable concrete with acceptable strength with ease.

The risk factors for intestinal Giardia spp infection: Global systematic review and meta-analysis and meta-regression.

Parasitic infections are a public health concern as they can cause aggression, growth retardation, weight loss, anemia, and other health problems. In this study, a systematic review and meta-analysis were performed to find an association between the probable social-environmental risk factors including lack of safe drinking water, no hand washing, sex, age, no access to education, no access to toilet, and Giardia spp infection. We conducted literature research among international databases including Scopus, PubMed, Web of Science and Cochrane from1 January 1995 to March 15, 2020, including 23 articles with 102 studies while the odds ratio (OR) was calculated using 2 × 2 tables or extracted. The pooled effect size with 95% confidence intervals (CIs) was estimated using a random or fixed-effects model. The results show a significant association between intestinal Giardia spp infection risk and lack of safe drinking water (OR: 1.14; 95%CI: 1.02-1.25); no access to toilet (OR: 1.22; 95%CI: 1.07-1.37); and age (2-10 vs 10-30 year) (OR: 1.42; 95%CI: 1.09-1.78). An insignificant association was observed between intestinal Giardia spp infection risk and age (<2 vs 2-10 year) (OR: 0.89; 95%CI: 0.75-1.02); no access to education (OR: 1.10; 95%CI: 0.80-1.40); Sex (male vs female) (OR: 1.04; 95%CI: 0.74-1.34); and no handwashing (OR: 1.18; 95%CI: 0.87-1.49). The results of meta-regression also indicate that intestinal Giardia spp infection has decreased over time (C= -0.024, p-value = 0.03) significantly, and also by growth of human development index (HDI) (C= - 0.42, p-value = 0.29) insignificantly. Improvement of personal hygiene, sanitation and raising public awareness can be effective in reducing Giardia spp infections.

Heat Transfer and Hydrodynamic Properties Using Different Metal-Oxide Nanostructures in Horizontal Concentric Annular Tube: An Optimization Study.

Numerical studies were performed to estimate the heat transfer and hydrodynamic properties of a forced convection turbulent flow using three-dimensional horizontal concentric annuli. This paper applied the standard k-ε turbulence model for the flow range 1 × 104 ≤ Re ≥ 24 × 103. A wide range of parameters like different nanomaterials (Al2O3, CuO, SiO2 and ZnO), different particle nanoshapes (spherical, cylindrical, blades, platelets and bricks), different heat flux ratio (HFR) (0, 0.5, 1 and 2) and different aspect ratios (AR) (1.5, 2, 2.5 and 3) were examined. Also, the effect of inner cylinder rotation was discussed. An experiment was conducted out using a field-emission scanning electron microscope (FE-SEM) to characterize metallic oxides in spherical morphologies. Nano-platelet particles showed the best enhancements in heat transfer properties, followed by nano-cylinders, nano-bricks, nano-blades, and nano-spheres. The maximum heat transfer enhancement was found in SiO2, followed by ZnO, CuO, and Al2O3, in that order. Meanwhile, the effect of the HFR parameter was insignificant. At Re = 24,000, the inner wall rotation enhanced the heat transfer about 47.94%, 43.03%, 42.06% and 39.79% for SiO2, ZnO, CuO and Al2O3, respectively. Moreover, the AR of 2.5 presented the higher heat transfer improvement followed by 3, 2, and 1.5.