Search Results (13)

The water regime in Pakistan’s northern region has experienced significant changes regarding hydrological extremes like floods because of climate change. Coupling hydrological models with remote sensing data can be valuable for flow simulation in data-scarce regions. This study focused on simulating the snow- and glacier-melt runoff using the snowmelt runoff model (SRM) in the Gilgit and Kachura River Basins of the upper Indus basin (UIB). The SRM was applied by coupling it with in situ and improved cloud-free MODIS snow and glacier composite satellite data (MOYDGL06) to simulate the flow under current and future climate scenarios. The SRM showed significant results: the Nash–Sutcliffe coefficient (NSE) for the calibration and validation period was between 0.93 and 0.97, and the difference in volume (between the simulated and observed flow) was in the range of −1.5 to 2.8% for both catchments. The flow tends to increase by 0.3–10.8% for both regions (with a higher increase in Gilgit) under mid- and late-21st-century climate scenarios. The Gilgit Basin’s higher hydrological sensitivity to climate change, compared to the Kachura Basin, stems from its lower mean elevation, seasonal snow dominance, and greater temperature-induced melt exposure. This study concludes that the simple temperature-based models, such as the SRM, coupled with improved satellite snow cover data, are reliable in simulating the current and future flows from the data-scarce mountainous catchments of Pakistan. The outcomes are valuable and can be used to anticipate and lessen any threat of flooding to the local community and the environment under the changing climate. This study may support flood assessment and mapping models in future flood risk reduction plans. Full article

This paper explored synthesis, characterization, and adsorption modeling for the application of nano-metal-oxide (Al₂O₃) blended biochar (NMOBC) derived from date palm waste in removing iron (Fe³⁺) from contaminated water. The pseudo-second-order model provided a goodness-of-fit that was superior to the pseudo-first-order kinetic model based on the value of R² with all of the initial concentrations. The Elovich kinetic model also presented a good fit, indicating that chemisorption is a predominant mechanism in the adsorption process. The Langmuir, Freundlich, Redlich-Petersons, Temkin, and Sips models provided an exclusive perspective of the adsorption dynamics based on the high value of R². However, the Sips model suggested the best fit of all of the employed models, with the lowest RMSE value of 0.0239 mg/g and the maximum adsorption capacity of 22.680 mg/g for NMOBC. Both adsorbents were effectively regenerated and reused in multiple cycles, thus leading to sustainable practices. Numerous analytical techniques, including SEM/EDX, FTIR, and BET, were employed in characterizing the structural, morphological, and functional properties of the synthesized NMOBC and BC. Subsequently, it revealed that the adsorption process and the role of various interactions are attributed to surface area, porosity, and ion exchange. Full article

Horticultural crops have a special impact on a nation’s economy due to their significance in raising the living standards of farmers. The traditional method for crop protection is becoming ineffective with an increase in climate change effects. Precision Agriculture (PA) presents a solution to this issue through the precise monitoring and forecasting of pests, which improves productivity and guarantees environmental sustainability. The productivity of the existing plant production system can be increased by using precision agriculture techniques. Various PA technologies that enable farmers to monitor the pest include remote sensing, the Internet of Things, geographical information systems, and artificial intelligence. The PA technique assists with pest forecasting and the management of pests and diseases in plants. The content of this article was gathered through a literature review of recent research. The approaches used in PA for pest forecasting, monitoring, and management are the main topic of this study. In the long term, this study will help farmers to manage insect pests in a way that is both affordable and environmentally beneficial. Full article

Assessment of the salt tolerance of a large genotype collection at the early growth stages may assist in the fast-tracking improvement of salt-tolerant barley genotypes in breeding programs. This study aimed to investigate the ability of traits related to seed germination ability and seedling growth performance with helping of nine sequence-related amplified polymorphism (SRAP) markers to detect the salt tolerance of 70 barley genotypes during the early growth stages. The different genotypes were exposed to three salt concentrations (0, 100, and 200 mM NaCl) and evaluated for salt tolerance by looking at germination percentage, germination index, and mean germination time during eight days as well as the lengths and weights of seedling shoot and root after 21 days from sowing. The results showed that genotypic variations in germination ability and seedling growth performance obviously appeared under 200 and 100 mM NaCl, respectively. The germination traits exhibited a strong correlation among themselves, whereas they had a poor correlation with seedling traits. A strong and positive correlation was only observed for shoot fresh weight with shoot length and root fresh weight under salinity conditions. Principal component analysis revealed that the first two components, which explained 53% of the total variability, succeeded to identify the genotypes with high salt tolerance during only one stage (germination or seedling stage) and both stages. Cluster analysis based on the stress tolerance index of germination and seedling traits grouped 70 genotypes into four key clusters, with genotypes grouped in cluster 1 and cluster 2 being salt tolerant during the germination stage and moderately tolerant during the seedling stage; the opposite was found with the genotypes grouped in cluster 4. According to Ward’s method, the salt tolerance of genotypes that ranked as most salt-tolerant (T) or salt-sensitive (S) remained almost unchanged during germination and seedling stages. In contrast, a change in salt tolerance with both stages was found for the genotypes that ranked as moderately salt-tolerant (MT) and salt-sensitive (MS) genotypes. The nine SRAP markers divided the tested genotypes into two distinct clusters, with clusters B had the most T and MT genotypes. Finally, using appropriate statistical methods presented in this study with SRAP markers will be useful for assessing the salt tolerance of a large number of barley genotypes and selecting the genotypes tolerant of and sensitive to salinity at the early growth stage. Full article

Arsenic (III) is a toxic contaminant in water bodies, especially in drinking water reservoirs, and it is a great challenge to remove it from wastewater. For the successful extraction of arsenic (III), a nanocomposite material (ZnO–CuO/g–C₃N₄) has been synthesized by using the solution method. The large surface area and plenty of hydroxyl groups on the nanocomposite surface offer an ideal platform for the adsorption of arsenic (III) from water. Specifically, the reduction process involves a transformation from arsenic (III) to arsenic (V), which is favorable for the attachment to the –OH group. The modified surface and purity of the nanocomposite were characterized by SEM, EDX, XRD, FT–IR, HRTEM, and BET models. Furthermore, the impact of various aspects (temperatures, pH of the medium, the concentration of adsorbing materials) on adsorption capacity has been studied. The prepared sample displays the maximum adsorption capacity of arsenic (III) to be 98% at pH ~ 3 of the medium. Notably, the adsorption mechanism of arsenic species on the surface of ZnO–CuO/g–C₃N₄ nanocomposite at different pH values was explained by surface complexation and structural variations. Moreover, the recycling experiment and reusability of the adsorbent indicate that a synthesized nanocomposite has much better adsorption efficiency than other adsorbents. It is concluded that the ZnO–CuO/g–C₃N₄ nanocomposite can be a potential candidate for the enhanced removal of arsenic from water reservoirs. Full article

The main objective of this study was to assess the quality and quantity of roof-harvested rainwater to overcome the water shortage problem in the study area. We also aimed to find health hazards associated with rainwater in the study area. For this purpose, rainwater samples were collected from five sites in the study area. The samples were analyzed using standard methods of the World Health Organization and the American Public Health Association in a laboratory. The analysis showed that all the physicochemical parameters were within the permissible limits of the WHO’s guidelines except pH, turbidity, and some trace metals such as iron (Fe) and lead (Pb). The mean values of pH range from 5.18 to 6.26, indicating slight acidity, while the highest mean turbidity was found at 5.77 NTU. Similarly, the highest mean concentrations of Fe and Pb were 0.95 mg/L and 0.056 mg/L, respectively, which was above the permissible limit of the WHO’s guidelines for drinking water. The annual rainwater-harvesting potential was assessed using the formula annual rainfall × roof area× runoff coefficient. The annual rainwater-harvesting potential of the study area was 56.803 L per household. At the same time, the average monthly rainwater-harvesting potential was 4733 L in the study area. This shows the potential for roof-harvested rainwater in the study area. A risk assessment of heavy metals showed that the rainwater of the study area is safe and does not pose any risk. This study concludes that rainwater is suitable for drinking and other domestic consumption if proper care is taken to clean the roof area and storage system and divert the first flush from the storage system. Full article

Human physical activity recognition from inertial sensors is shown to be a successful approach for monitoring elderly individuals and children in indoor and outdoor environments. As a result, researchers have shown significant interest in developing state-of-the-art machine learning methods capable of utilizing inertial sensor data and providing key decision support in different scenarios. This paper analyzes data-driven techniques for recognizing human daily living activities. Therefore, to improve the recognition and classification of human physical activities (for example, walking, drinking, and running), we introduced a model that integrates data preprocessing methods (such as denoising) along with major domain features (such as time, frequency, wavelet, and time–frequency features). Following that, stochastic gradient descent (SGD) is used to improve the performance of the extracted features. The selected features are catered to the random forest classifier to detect and monitor human physical activities. Additionally, the proposed HPAR system was evaluated on five benchmark datasets, namely the IM-WSHA, PAMAP-2, UCI HAR, MobiAct, and MOTIONSENSE databases. The experimental results show that the HPAR system outperformed the present state-of-the-art methods with recognition rates of 90.18%, 91.25%, 91.83%, 90.46%, and 92.16% from the IM-WSHA, PAMAP-2, UCI HAR, MobiAct, and MOTIONSENSE datasets, respectively. The proposed HPAR model has potential applications in healthcare, gaming, smart homes, security, and surveillance. Full article

The number of deaths has been increased due to COVID-19 infections and uncertain neurological complications associated with the central nervous system. Post-infections and neurological manifestations in neuronal tissues caused by COVID-19 are still unknown and there is a need to explore how brainstorming promoted congenital impairment, dementia, and Alzheimer’s disease. SARS-CoV-2 neuro-invasion studies in vivo are still rare, despite the fact that other beta-coronaviruses have shown similar properties. Neural (olfactory or vagal) and hematogenous (crossing the blood–brain barrier) pathways have been hypothesized in light of new evidence showing the existence of SARS-CoV-2 host cell entry receptors into the specific components of human nerve and vascular tissue. Spike proteins are the primary key and structural component of the COVID-19 that promotes the infection into brain cells. Neurological manifestations and serious neurodegeneration occur through the binding of spike proteins to ACE2 receptor. The emerging evidence reported that, due to the high rate in the immediate wake of viral infection, the olfactory bulb, thalamus, and brain stem are intensely infected through a trans-synaptic transfer of the virus. It also instructs the release of chemokines, cytokines, and inflammatory signals immensely to the blood–brain barrier and infects the astrocytes, which causes neuroinflammation and neuron death; and this induction of excessive inflammation and immune response developed in more neurodegeneration complications. The present review revealed the pathophysiological effects, molecular, and cellular mechanisms of possible entry routes into the brain, pathogenicity of autoantibodies and emerging immunotherapies against COVID-19. Full article

The release of phenolic-contaminated treated palm oil mill effluent (TPOME) poses a severe threat to human and environmental health. In this work, manganese-modified black TiO₂ (Mn-B-TiO₂) was produced for the photodegradation of high concentrations of total phenolic compounds from TPOME. A modified glycerol-assisted technique was used to synthesize visible-light-sensitive black TiO₂ nanoparticles (NPs), which were then calcined at 300 °C for 60 min for conversion to anatase crystalline phase. The black TiO₂ was further modified with manganese by utilizing a wet impregnation technique. Visible light absorption, charge carrier separation, and electron–hole pair recombination suppression were all improved when the band structure of TiO₂ was tuned by producing Ti³⁺ defect states. As a result of the enhanced optical and electrical characteristics of black TiO₂ NPs, phenolic compounds were removed from TPOME at a rate of 48.17%, which is 2.6 times higher than P25 (18%). When Mn was added to black TiO₂ NPs, the Ti ion in the TiO₂ lattice was replaced by Mn, causing a large redshift of the optical absorption edges and enhanced photodegradation of phenolic compounds from TPOME. The photodegradation efficiency of phenolic compounds by Mn-B-TiO₂ improved to 60.12% from 48.17% at 0.3 wt% Mn doping concentration. The removal efficiency of phenolic compounds from TPOME diminished when Mn doping exceeded the optimum threshold (0.3 wt%). According to the findings, Mn-modified black TiO₂ NPs are the most effective, as they combine the advantages of both black TiO₂ and Mn doping. Full article

Plant growth-promoting rhizobacteria play a substantial role in plant growth and development under biotic and abiotic stress conditions. However, understanding about the functional role of rhizobacterial strains for wheat growth under salt stress remains largely unknown. Here we investigated the antagonistic bacterial strain Bacillus aryabhattai PM34 inhabiting ACC deaminase and exopolysaccharide producing ability to ameliorate salinity stress in wheat seedlings under in vitro conditions. The strain PM34 was isolated from the potato rhizosphere and screened for different PGP traits comprising nitrogen fixation, potassium, zinc solubilization, indole acetic acid, siderophore, and ammonia production, along with various extracellular enzyme activities. The strain PM34 showed significant tolerance towards both abiotic stresses including salt stress (NaCl 2 M), heavy metal (nickel, 100 ppm, and cadmium, 300 ppm), heat stress (60 °C), and biotic stress through mycelial inhibition of Rhizoctonia solani (43%) and Fusarium solani (41%). The PCR detection of ituC, nifH, and acds genes coding for iturin, nitrogenase, and ACC deaminase enzyme indicated the potential of strain PM34 for plant growth promotion and stress tolerance. In the in vitro experiment, NaCl (2 M) decreased the wheat growth while the inoculation of strain PM34 enhanced the germination% (48%), root length (76%), shoot length (75%), fresh biomass (79%), and dry biomass (87%) over to un-inoculated control under 2M NaCl level. The results of experiments depicted the ability of antagonistic bacterial strain Bacillus aryabhattai PM34 to augment salt stress tolerance when inoculated to wheat plants under saline environment. Full article

Members of genus Pteris have their established role in the traditional herbal medicine system. In the pursuit to identify its biologically active constituents, the specie Pteris cretica L. (P. cretica) was selected for the bioassay-guided isolation. Two new maleates (F9 and CB18) were identified from the chloroform extract and the structures of the isolates were elucidated through their spectroscopic data. The putative targets, that potentially interact with both of these isolates, were identified through reverse docking by using in silico tools PharmMapper and ReverseScreen3D. On the basis of reverse docking results, both isolates were screened for their antioxidant, acetylcholinesterase (AChE) inhibition, α-glucosidase (GluE) inhibition and antibacterial activities. Both isolates depicted moderate potential for the selected activities. Furthermore, docking studies of both isolates were also studied to investigate the binding mode with respective targets followed by molecular dynamics simulations and binding free energies. Thereby, the current study embodies the poly-pharmacological potential of P. cretica. Full article

Traditional energy supply infrastructures are on the brink of facing a major transformation due to energy security concerns, environment pollution, renewable energy intermittency and fossil fuel scarcity. A hybrid energy system constitutes the integration of different energy carriers like electricity, heat and fuel which play a vital role in addressing the above challenges. Various technological options like combined heat and power, heat pumps, electrolysers and energy storages ease out multiple carrier integration in an energy hub to increase system flexibility and efficiency. This work models the hybrid energy system of China for the year 2030 by using EnergyPLAN. Atmosphere decarbonization is achieved by replacing conventional coal and natural gas boilers with alternative individual heating sources like hydrogen operated micro combined heat and power natural gas micro combined heat and power and heat pumps. Moreover, rockbed storage as well as single and double penstock pumped hydro storages are added in the proposed system in order to cope with the stochastic nature of intermittent renewable energy such as wind and solar photovoltaic. The technical simulation strategy is employed to analyze the optimal combination of energy producing components by determining annual costs, fuel consumption and CO₂ emissions. The results substantiate that a heat pump and double penstock pumped hydro storage addition to the individual heating and electricity network not only proves to be an economically viable option but also reduces fuel consumption and emissions. Full article

Technology plays an important role in our society, especially in the field of education. It is quite regrettable that people, particularly the deaf, still face a lot of challenges in acquiring an education. Their learning methods are different as compared to hearing people. They use Sign Language (SL) rather than natural language to communicate and learn. They are required to put a lot of effort into learning different concepts using conventional pedagogies. Therefore, there is a dire need for some assistive technology to improve their learn-ability and understandability. In the present study, 192 deaf participants aged 5–10 years were sampled from two special child institutes. The objective of the present study was to determine the effectiveness of a mobile interface through a developed mobile application for learning basic mathematical concepts using Pakistan Sign Language (PSL). The present study bridges the gap between the technology-based method and conventional teaching methods, which are used for teaching mathematical concepts using PSL. The participants were divided into two groups, that is, one group learned through conventional methods (flash cards and board) and the other group through the developed mobile application. The difference in the performance of both the groups was evaluated by conducting quizzes. The quiz results were analyzed by the Z-test and ANOVA. The findings revealed that the Experimental Group (EG) participants, who were instructed by our mobile application showed higher proficiency in the quizzes as compared to the Control Group (CG). EG participants performed better than CG by 12% in the quizzes. A gender based difference was also observed for the quiz scores. Male participants in category C (word problem learning) performed 2.7% better than females in the EG and 2.5% better in the CG. Moreover, a significant difference was also observed in the time taken by participants in both groups to complete the quizzes. CG participants took 20 min longer than EG participants to complete the quizzes. The results of the ANOVA showed that the quiz scores were directly affected by the mode of teaching used for participants in both groups. Full article