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The disposal of waste at wild dumpsites poses significant environmental challenges. This study evaluates heavy metal (HM) contamination in soil around wild dumpsites in Bijeljina-Zvornik, Republic of Srpska, Bosnia and Herzegovina. Forty-five soil samples were analyzed for Ni, Cr, Mn, Zn, Cu, Pb, Cd, Fe, and Al. The highest concentrations observed were for Fe (average 9211.96 mg/kg, maximum 33,275.16 mg/kg) and Zn (average 109.76 mg/kg, maximum 1054.24 mg/kg). The highest daily total exposure dose (ADD) for both adults and children was for Fe, with ADDing for children at 7.07E-01 mg/kg/day and for adults at 3.03E-01 mg/kg/day. Hazard quotient (HQ) contributions to non-carcinogenic exposure risk (HI) were 99.93%, 0.02%, and 0.05% for children and 99.23%, 0.07%, and 0.70% for adults. The results suggest acceptable carcinogenic risk, with the highest carcinogenic risk (CR) observed for Cr, at 9.26E-05 for children and 4.67E-05 for adults. The positive matrix factorization (PMF) model identified five contamination sources: geogenic, solid waste leaching, industrial waste, surface runoff, and agricultural practices. This analysis provides insights into the ecosystem risks posed by these metals. [ABSTRACT FROM AUTHOR]

Maternal health risks can cause a range of complications for women during pregnancy. High blood pressure, abnormal glucose levels, depression, anxiety, and other maternal health conditions can all lead to pregnancy complications. Proper identification and monitoring of risk factors can assist to reduce pregnancy complications. The primary goal of this research is to use real-world datasets to identify and predict Maternal Health Risk (MHR) factors. As a result, we developed and implemented the Quad-Ensemble Machine Learning framework to predict Maternal Health Risk Classification (QEML-MHRC). The methodology used a vacxsriety of Machine Learning (ML) models, which then integrated with four ensemble ML techniques to improve prediction. The dataset collected from various maternity hospitals and clinics subjected to nineteen training and testing tests. According to the exploratory data analysis, the most significant risk factors for pregnant women include high blood pressure, low blood pressure, and high blood sugar levels. The study proposed a novel approach to dealing with high-risk factors linked to maternal health. Dealing with class-specific performance elaborated further to properly understand the distinction between high, low, and medium risks. All tests yielded outstanding results when predicting the amount of risk during pregnancy. In terms of class performance, the dataset associated with the "HR" class outperformed the others, predicting 90% correctly. GBT with ensemble stacking outperformed and demonstrated remarkable performance for all evaluation measure (0.86) across all classes in the dataset. The key success of the models used in this work is the ability to measure model performance using a class-wise distribution. The proposed approach can help medical experts assess maternal health risks, saving lives and preventing complications throughout pregnancy. The prediction approach presented in this study can detect high-risk pregnancies early on, allowing for timely intervention and treatment. This study's development and findings have the potential to raise public awareness of maternal health issues. [ABSTRACT FROM AUTHOR]

Metal pollution in water, soil, and vegetation is an emerging environmental issue. Therefore, this study investigated the abundance of heavy metals (HMs) within roots and shoots of native plant species i.e., Bromus pectinatus, Cynodon dactylon, Poa annua, Euphorbia heliscopa, Anagallis arvensis, and Stellaria media grown in the adjoining area of municipal wastewater channels of a Pakistani city of Abbottabad. HMs concentrations (mg L−1) in municipal wastewater were: chromium (Cr) (0.55) > nickel (Ni) (0.09) > lead (Pb) (0.07) > cadmium (Cd) (0.03). Accumulation of HMs in both roots and shoots of plant species varied as B. pectinatus > C. dactylon > P. annua > E. heliscopa > A. arvensis > S. media. Irrespective of the plant species, roots exhibited higher concentrations of HMs than shoots. Higher amount of Cr (131.70 mg kg−1) was detected in the roots of B. pectinatus and the lowest amount (81 mg kg−1) in A. arvensis, Highest Cd concentration was found in the shoot of B. pectinatus and the lowest in the E. heliscopa. The highest concentration of Ni was found in the roots of S. media (37.40 mg kg−1) and the shoot of C. dactylon (15.70 mg kg−1) whereas the lowest Ni concentration was achieved in the roots of A. arvensis (12.10 mg kg−1) and the shoot of E. heliscopa (5.90 mg kg−1). The concentration of HMs in individual plant species was less than 1000 mg kg−1. Considering the higher values (> 1) of biological concentration factor (BCF), biological accumulation co-efficient (BAC), and translocation factor (TF), B. pectinatus and S. media species showed greater potential for HMs accumulation than other species. Therefore, these plants might be helpful for the remediation of HM-contaminated soil. [ABSTRACT FROM AUTHOR]

Groundwater contamination with arsenic (As) is a significant concern in Pakistan's Punjab Province. This study analyzed 69 groundwater samples from Faisalabad, Gujranwala, Lahore, and Multan to understand hydrogeochemistry, health impacts, contamination sources, and drinking suitability. Results revealed varying as concentrations across districts, with distinctive cation and anion orders. Faisalabad exhibited Na+ > Mg2+ > Ca2+ > K+ > Fe2+ for cations and SO42– > Cl– > HCO3– > NO3– > F– for anions. Gujranwala showed Na+ > Ca2+ > Mg2+ > K+ for cations and HCO3– > SO42– > Cl– > NO3– > F– for anions. In Lahore, demonstrated: Na+ > Ca2+ > Mg2+ > Fe > K+ for cations and HCO3– > SO42– > Cl– > NO3– > F– for anions. Multan indicated K+ > Ca2+ > Mg2+ > Na+ > Fe for cations and HCO3– > SO42– > Cl– > F– > NO3–) for anions. Hydrochemical facies were identified as CaHCO3 and CaMgCl types. Principal Component Analysis (PCA), highlighted the influence of natural processes and human activities on groundwater pollution. Water Quality Index (WQI) result reveal that most samples met water quality standards. The carcinogenic risk values for children exceeded permissible limits in all districts, emphasizing a significant cancer risk. The study highlights the need for rigorous monitoring to mitigate (As) contamination and protect public health from associated hazards. [ABSTRACT FROM AUTHOR]

The objective of the current research was to examine the water quality of the River Ravi and the River Sutlej, with a specific focus on potentially toxic elements (PTEs). Additionally, we sought to monitor the sources of pollution in these rivers by gathering samples from the primary drains that carry industrial and municipal waste into these water bodies. Furthermore, we aimed to evaluate the impact of PTEs in surface water on groundwater quality by collecting groundwater samples from nearby populated areas. A total of 30 samples were collected from these three sources: rivers (6 samples), drains (9 samples), and groundwater (15 samples). The analysis revealed that the levels of PTEs in the samples from these three resources having a mean value: arsenic (As) 23.5 µg/L, zinc (Zn) 2.35 mg/L, manganese (Mn) 0.51 mg/L, lead (Pb) 6.63 µg/L, and chromium (Cr) 10.9 µg/L, exceeded the recommended values set by the World Health Organization (WHO). Furthermore, PTEs including (As 84%), (Zn 65%), (Mn 69%), (Pb 53%), (Cr 53%), and (Ni 27%), samples were beyond the recommended values of WHO. The results of the Principal Component Analysis indicated that surface water and groundwater exhibited total variability of 83.87% and 85.97%, respectively. This indicates that the aquifers in the study area have been contaminated due to both natural geogenic factors and anthropogenic sources. These sources include the discharge of industrial effluents, wastewater from municipal sources, mining activities, agricultural practices, weathering of rocks, and interactions between rocks and water. Spatial distribution maps clearly illustrated the widespread mobilization of PTEs throughout the study area. Furthermore, a health risk assessment was conducted to evaluate the potential adverse health effects of PTEs through the ingestion of drinking groundwater by both children and adults. Health risk assessment result show the mean carcinogenic values for As, Cr, Pb and Ni in children are calculated to be (1.88E-04), (2.61E-04), (2.16E-02), and (5.74E-05), respectively. Similarly, the mean carcinogenic values for the above mentioned PTEs in adults were recorded to be (2.39E-05), (3.32E-05), (1.19E-03), and (7.29E-06) respectively. The total hazard index values for As, Zn, Cr, Pb, Mn, Cu, and Ni in children were observed to be (9.07E + 00), (9.95E-07), (4.59E-04), (5.75E-04), (4.72E-05), (2.78E-03), and (5.27E-05) respectively. The analysis revealed that As has an adverse effect on the population of the study area as compared to other PTEs investigated in this study. [ABSTRACT FROM AUTHOR]

In recent years, the growing concern over the presence of toxic aquatic pollutants has prompted intensive research into effective and environmentally friendly remediation methods. Photocatalysis using semiconductor quantum dots (QDs) has developed as a promising technology for pollutant degradation. Among various QD materials, indium phosphide (InP) and its hybrid with zinc sulfide (ZnS) have gained considerable attention due to their unique optical and photocatalytic properties. Herein, InP and InP/ZnS QDs were employed for the removal of dyes (crystal violet, and congo red), polyaromatic hydrocarbons (pyrene, naphthalene, and phenanthrene), and pesticides (deltamethrin) in the presence of visible light. The degradation efficiencies of crystal violet (CV) and congo red (CR) were 74.54% and 88.12% with InP, and 84.53% and 91.78% with InP/ZnS, respectively, within 50 min of reaction. The InP/ZnS showed efficient performance for the removal of polyaromatic hydrocarbons (PAHs). For example, the removal percentage for naphthalene, phenanthrene, and pyrene was 99.8%, 99.6%, and 88.97% after the photocatalytic reaction. However, the removal percentage of InP/ZnS for pesticide deltamethrin was 90.2% after 90 min light irradiation. Additionally, advanced characterization techniques including UV–visible spectrophotometer (UV–Vis), photoluminescence (PL), X-ray diffractometer (XRD), energy-dispersive spectrometer (EDS) elemental mapping, transmission electron microscopy (TEM), and thermogravimetric analysis (TGA) were used to analyze the crystal structure, morphology, and purity of the fabricated materials in detail. The particle size results obtained from TEM are in the range of 2.28–4.60 nm. Both materials (InP and InP/ZnS) exhibited a spherical morphology, displaying distinct lattice fringes. XRD results of InP depicted lattice planes (111), (220), and (311) in good agreement with cubic geometry. Furthermore, the addition of dopants was discovered to enhance the thermal stability of the fabricated material. In addition, QDs exhibited efficacy in the breakdown of PAHs. The analysis of their fragmentation suggests that the primary mechanism for PAHs degradation is the phthalic acid pathway. [ABSTRACT FROM AUTHOR]

Short-chain olefins are the important feedstock for the chemical industries. The selection of a proper catalyst for oxidative dehydrogenation (ODH) reaction is critical. Here, the study summarized different catalysts by physicochemical techniques such as BET surface area, Raman spectroscopy, and temperature programmed reduction (TPR). The BET analysis of different catalysts gives an optimum value of active and metal loading catalysts for optimum alkenes selectivity. From different Raman spectroscopy analyses, the study pointed out the factor responsible for varying mono vanadate and poly vanadate formation. From TPR analysis of different catalysts, this study pointed out the factors that varied on increasing or decreasing temperature and the effect on the selectivity of alkenes. The effect of different operating conditions was studied. Without catalyst regeneration after each ODH run, the catalyst under the study shows stable behavior and increases the selectivity of the desired product. The CREC riser simulator was used for ODH of propane and ethane, while two zones of fluidized bed reactor (TZFBR) and ICFBR reactors were used for ODH of butane. From the study of MoO3/MgO catalyst, it was observed that TZFBR have high selectivity of butadiene than CFBR and fixed bed reactor. It was concluded that the catalyst VOx–Nb/La-ɣAl2O3 has high conversion (20.1%) of ethane and good selectivity of (85.7%) of ethylene, while in ODH of propane and butane the catalyst 7.5 VOx/ɣAl2O3·ZrO2 (1:1) and MoO3/MgO have high selectivity of propane and 1,3-butadiene respectively. This review will help researchers in decision making for the selection of proper catalyst for ODH of alkane to alkenes. [ABSTRACT FROM AUTHOR]

Arsenic contamination in the groundwater occurs in various parts of the world due to anthropogenic and natural sources, adversely affecting human health and ecosystems. The current study intends to examine the groundwater hydrogeochemistry containing elevated arsenic (As), predict As levels in groundwater, and determine the aptness of groundwater for drinking in the Vehari district, Pakistan. Four hundred groundwater samples from the study region were collected for physiochemical analysis. As levels in groundwater samples ranged from 0.1 to 52 μg/L, with an average of 11.64 μg/L, (43.5%), groundwater samples exceeded the WHO 2022 recommended limit of 10 μg/L for drinking purposes. Ion-exchange processes and the adsorption of ions significantly impacted the concentration of As. The HCO3− and Na+ are the dominant ions in the study area, and the water types of samples were CaHCO3, mixed CaMgCl, and CaCl, demonstrating that rock–water contact significantly impacts hydrochemical behavior. The geochemical modeling indicated negative saturation indices with calcium carbonate and other salt minerals, encompassing aragonite, calcite, dolomite, and halite. The dissolution mechanism suggested that these minerals might have implications for the mobilization of As in groundwater. A combination of human-induced and natural sources of contamination was unveiled through principal component analysis (PCA). Artificial neural networks (ANN), random forest (RF), and logistic regression (LR) were used to predict As in the groundwater. The data have been divided into two parts for statistical analysis: 20% for testing and 80% for training. The most significant input variables for As prediction was determined using Chi-squared analysis. The receiver operating characteristic area under the curve and confusion matrix were used to evaluate the models; the RF, ANN, and LR accuracies were 0.89, 0.85, and 0.76. The permutation feature and mean decrease in impurity determine ten parameters that influence groundwater arsenic in the study region, including F−, Fe2+, K+, Mg2+, Ca2+, Cl−, SO42−, NO3−, HCO3−, and Na+. The present study shows RF is the best model for predicting groundwater As contamination in the research area. The water quality index showed that 161 samples represent poor water, and 121 samples are unsuitable for drinking. Establishing effective strategies and regulatory measures is imperative in Vehari to ensure the sustainability of groundwater resources. [ABSTRACT FROM AUTHOR]

Arsenic (As), contamination in drinking groundwater resources is commonly environmental problem in many developing countries including Pakistan, with significant human health risk reports. In order to examine the groundwater quality concerning As contamination, its geochemical behavior along with physicochemical parameters, 42 samples were collected from community tube wells from District Bahawalpur, Punjab, Pakistan. The results showed the concentration of elevated As, its source of mobilization, and associated public health risk. The As concentration detected in groundwater samples varied from 0.12 to 104 µg/L with an average value of 34.7 µg/L. Among 42 groundwater samples, 27 samples were beyond the permitted limit of 10 µg/L recommended by World Health Organization (WHO), for drinking purposes. Statistical analysis result show that the groundwater cations values are in decreasing order such as: Na+ > Mg2+ > Ca2+ > K+, while anions were HCO3– > SO42– > Cl– > NO3–. Hydrochemical facies result depict that the groundwater samples of the study area, 14 samples belong to CaHCO3 type, 5 samples belong to NaCl type, 20 samples belong to Mixed CaMgCl type, and 3 samples belong to CaCl2 type. It can be accredited due to weathering and recharge mechanism, evaporation processes, and reverse ion exchange. Gibbs diagram shows that rock water interaction controls the hydrochemistry of groundwater resources of the study area. Saturation Index (SI) result indicated the saturation of calcite, dolomite, gypsum, geothite, and hematite mineral due their positive SI values. The principal component analysis (PCA) results possess a total variability of 80.69% signifying the anthropogenic and geogenic source of contamination. The results of the exposure-health-risk-assessment method for measuring As reveal significant potential non-carcinogenic risk (HQ), exceeding the threshold level of (> 1) for children in the study area. Water quality assessment results shows that 24 samples were not suitable for drinking purposes. [ABSTRACT FROM AUTHOR]

Misuse of antibiotics leads to the worldwide spread of antibiotic resistance, which motivates scientists to create new antibiotics. The recurring UTI due to antibiotics-resistant microorganism's challenges scientists globally. The biogenic nanoparticles have the potential to meet the escalating requirements of novel antimicrobial agents. The green synthesis of nanoparticles (NPs) gained more attention due to their reliable applications against resistant microbes. The current study evaluates the biogenic ZnO NPs of Mentha piperata extract against resistant pathogens of urinary tract infections by agar well diffusion assay. The biogenic ZnO NPs revealed comparatively maximum inhibition in comparison to synthetic antibiotics against two bacterial strains (Proteus mirabilis, Pseudomonas aeruginosa) and a fungal strain (Candida albicans).The synthesized biogenic ZnO NPs alone revealed maximum activities than the combination of plant extract (PE) and ZnO NPs, and PE alone. The physiochemical features of ZnO NPs characterized through UV–Vis spectroscopy, FTIR, XRD, SEM, and EDX. The UV–Vis spectroscopy revealed 281.85 nm wavelengths; the XRD pattern revealed the crystalline structure of ZnO NPs. The FTIR analysis revealed the presence of carboxylic and nitro groups, which could be attributed to plant extract. SEM analysis revealed spherical hollow symmetry due to electrostatic forces. The analysis via EDX confirmed the presence of Zn and oxygen in the sample. The physiochemical features of synthesized ZnO NPs provide pivotal information such as quality and effectiveness. The current study revealed excellent dose-dependent antimicrobial activity against the pathogenic isolates from UTI-resistant patients. The higher concentration of ZnONPs interacts with the cell membrane which triggers oxidative burst. They may bind with the enzymes and proteins and brings epigenetic alteration which leads to membrane disruption or cell death. [ABSTRACT FROM AUTHOR]

Delphinium uncinatum Wall. (Ranunculaceae) is a native medicinal plant found on the sub-continent that is utilized to cure various human diseases. Using a total of three different tissue parts i.e., the stem, root, and mixed plant (leaves, stem, and root), methanolic extracts were prepared and evaluated to determine the best candidate for potential bioactivity. Phytochemical constituents in prepared extracts were quantified through high-performance liquid chromatography analysis that demonstrated the presence of four flavonoid compounds, rutoside, nicotiflorin, narcissoside, and violanthin in varying proportions. Strong antibacterial and antioxidant potency but mild α-amylase and cytotoxic potential was elucidated. Highest anti-inflammatory potential was found against PLA2 (36.6 ± 2.08) and 15-LOX (30.33 ± 1.52) followed by COX-1 (25.1 ± 2.02) and COX-2 (19.33 ± 1.52). Anti-aging potential showed strong inhibitory actions toward pentosidine advanced glycation end products (AGEs) and visperlysine AGEs; however, least inhibitory activities were observed against hyaluronidase and elastase. These findings made us aware of further detailed research to determine a novel drug. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy (DR) is a diabetes complication that can cause vision loss among patients due to damage to blood vessels in the retina. Early retinal screening can avoid the severe consequences of DR and enable timely treatment. Nowadays, researchers are trying to develop automated deep learning-based DR segmentation tools using retinal fundus images to help Ophthalmologists with DR screening and early diagnosis. However, recent studies are unable to design accurate models due to the unavailability of larger training data with consistent and fine-grained annotations. To address this problem, we propose a semi-supervised multitask learning approach that exploits widely available unlabelled data (i.e., Kaggle-EyePACS) to improve DR segmentation performance. The proposed model consists of novel multi-decoder architecture and involves both unsupervised and supervised learning phases. The model is trained for the unsupervised auxiliary task to effectively learn from additional unlabelled data and improve the performance of the primary task of DR segmentation. The proposed technique is rigorously evaluated on two publicly available datasets (i.e., FGADR and IDRiD) and results show that the proposed technique not only outperforms existing state-of-the-art techniques but also exhibits improved generalisation and robustness for cross-data evaluation. [ABSTRACT FROM AUTHOR]

Main conclusion: The study provided an insight toward better understanding of stay-green mechanisms for drought tolerance improvement and identified that synthetic-derived wheats proved as a promising germplasm for improved tolerance against water stress. Stay-green (SG) trait is considered to be related with the ability of wheat plants to maintain photosynthesis and CO2 assimilation. The present study explored the interaction of water stress with SG expression through physio-biochemical, agronomic and phenotypic responses among diverse wheat germplasm comprising of 200 synthetic hexaploids, 12 synthetic derivatives, 97 landraces and 16 conventional bread wheat varieties, for 2 years. The study established that variation of SG trait existed in the studied wheat germplasm and there was positive association between SG trait and tolerance to water stress. The relationship of SG trait with chlorophyll content (r = 0.97), ETR (r = 0.28), GNS (r = 0.44), BMP (r = 0.34) and GYP (r = 0.44) was particularly promising under water stress environment. Regarding chlorophyll fluorescence, the positive correlation of фPSII (r = 0.21), qP (r = 0.27) and ETR (r = 0.44) with grain yield per plant was noted. The improved ΦPSII and Fv/Fm of PSII photochemistry resulted in the high photosynthesis activity in SG wheat genotypes. Regarding relative water content and photochemical quenching coefficient, synthetic-derived wheats were better by maintaining 20.9, 9.8 and 16.1% more RWC and exhibiting 30.2, 13.5 and 17.9% more qP when compared with landraces, varieties and synthetic hexaploids, respectively, under water stress environment. Synthetic derived wheats also exhibited relatively more SG character with good yield and were more tolerant to water stress in terms of grain yield, grain weight per plant, better photosynthetic performance through chlorophyll fluorescence measurement, high leaf chlorophyll and proline content, and hence, may be used as novel sources for breeding drought tolerant materials. The study will further facilitate research on wheat leaf senescence and will add to better understanding of SG mechanisms for drought tolerance improvement. [ABSTRACT FROM AUTHOR]

Consumption of high fluoride (F−) and nitrate (NO3−) containing water may pose serious health hazards. One hundred sixty-one groundwater samples were collected from drinking wells in Khushab district, Punjab Province, Pakistan, to determine the causes of elevated F− and NO3− concentrations, and to estimate the human health risks posed by groundwater contamination. The results showed pH of the groundwater samples ranged from slightly neutral to alkaline, and Na+ and HCO3− ions dominated the groundwater. Piper diagram and bivariate plots indicated that the key factors regulating groundwater hydrochemistry were weathering of silicates, dissolution of evaporates, evaporation, cation exchange, and anthropogenic activities. The F− content of groundwater ranged from 0.06 to 7.9 mg/L, and 25.46% of groundwater samples contained high-level fluoride concentration (F− > 1.5 mg/L), which exceeds the (WHO Guidelines for drinking-water quality: incorporating the first and second addenda, WHO, Geneva, 2022) guidelines of drinking-water quality. Inverse geochemical modeling indicates that weathering and dissolution of fluoride-rich minerals were the primary causes of F− in groundwater. High F− can be attributed to low concentration of calcium-containing minerals along the flow path. The concentrations of NO3− in groundwater varied from 0.1 to 70 mg/L; some samples are slightly exceeding the (WHO Guidelines for drinking-water quality: incorporating the first and second addenda, WHO, Geneva, 2022) guidelines for drinking-water quality. Elevated NO3− content was attributed to the anthropogenic activities revealed by PCA analysis. The high levels of nitrates found in the study region are a result of various human-caused factors, including leaks from septic systems, the use of nitrogen-rich fertilizers, and waste from households, farming operations, and livestock. The hazard quotient (HQ) and total hazard index (THI) of F− and NO3− showed high non-carcinogenic risk (> 1) via groundwater consumption, demonstrating a high potential risk to the local population. This study is significant because it is the most comprehensive examination of water quality, groundwater hydrogeochemistry, and health risk assessment in the Khushab district to date, and it will serve as a baseline for future studies. Some sustainable measures are urgent to reduce the F− and NO3− content in the groundwater. [ABSTRACT FROM AUTHOR]

This paper proposes an algorithm for the dynamic assignment of Restricted Access Window (RAW) for IEEE 802.11 ah. The Internet of Things (IoT) has groups of sensors and stations interacting over a common network. Wireless Local Area Network (WLAN) standard IEEE 802.11ah is best for IoT because it has high data rate and wide coverage while consuming low power. IEEE 802.11ah uses cautiously selected fixed RAW through an Access Point (AP), so that the chances of packet collision is minimized and energy efficiency is improved. By keeping it static, however, the effectiveness of RAW to utilize channels is reduced. We are suggesting an algorithm in which AP roughly calculates network packet transmission and the number of transmitting stations, and assigns resources to IoT networks by modifying RAW dynamically. The proposed algorithm shows improvement in average delay, throughput, PDR and jitter. The proposed algorithm achieves one of the best performances with an average delay of 0.43 sec, throughput of about 23 kbps, maximum packet delivery ratio (PDR) of about 98%, and jitter of about 80 sec. [ABSTRACT FROM AUTHOR]

Plant species diversity patterns and vegetation structure are influenced by climatic and other environmental factors. We hypothesized that a combination of edaphic and topographic factors affect not only plant community patterns, vegetation structure and heterogeneity but also the indicator species in the dry temperate zone of the Liakot forests, Hindu Raj series of Hindu Kush Mountains, Pakistan. Quadrat along the elevation gradient were used for vegetation sampling. Soil samples were collected from each quadrat and analyzed by using standard protocols. All the collected data were analyzed using Cluster Analysis, Indicator Species Analyses and Data attribute plots via Canonical Correspondance Analyses. Cluster Analysis using Sorensen distance measurements grouped the plant species into three communities based on microclimatic indicators. These communities were: (1) Celtis caucasica-Lonicera hispida-Pennisetum orientale, (2) Juglans regia-Rubus idaeus-Tragopogon gracilis, and (3) Abies pindrow-Parrotiopsis jacquemontiana-Agrostis gigantea. Elevation, aspect, organic matter, electrical conductivity and potassium were the strong ecological factors responsible for different communities' formation and their associated indicators in the region. Techniques and criteria used in the current study for communities formation and their respective indicator identification could be used further for management and conservation of the Liakot forest of the Hindu Raj series of Hindu Kush Mountains and other adjacent ecosystems of the northern Pakistan. Findings of the study can also be utilized in the reforestation drives. [ABSTRACT FROM AUTHOR]

Dachang mining area in China is known as "paradise for mineralogists" due to its most reserves of Sn, Sb, Pb, and Zn non-ferrous metal resources; thus, its evaluation for heavy metal assessment and consequent health risk is unavoidable. Sixty road dust samples were collected from study area to explore pollution level, ecological, and health risks from heavy metals and were analyzed by an inductively coupled plasma optical emission spectrometer and atomic fluorescence spectrometer. The results showed that average concentration of all the heavy metals in road dust in both mining and residential areas were remarkable higher than its corresponding background values, the former being more severe, except for Cr and Co. The morphological investigation showed that most of the particles were much less than 100 μm illustrating fine part of the road dust samples. Based on integrated pollution indices, Cd, Sb, As, Zn, and Pb were extremely contaminated and exceeded hundred times of the maximum risk value. The health risk assessment revealed substantially higher carcinogenic and non-carcinogenic risks to children and adult. Highest non-carcinogenic risk resulted from arsenic in mining and residential area with HQing of 644.56 and 267.94 respectively (standard HQ ≥ 1) while carcinogenic risk to children (1.94E + 00) which greatly exceeded from the threshold value of (1.0E-4). Sb, Cd, and Pb also posed carcinogenic and non-carcinogenic risk in road dust which is caused by excessive mining activities and heavy vehicle movement in the study area. [ABSTRACT FROM AUTHOR]

Automatic COVID-19 detection using chest X-ray (CXR) can play a vital part in large-scale screening and epidemic control. However, the radiographic features of CXR have different composite appearances, for instance, diffuse reticular-nodular opacities and widespread ground-glass opacities. This makes the automatic recognition of COVID-19 using CXR imaging a challenging task. To overcome this issue, we propose a densely attention mechanism-based network (DAM-Net) for COVID-19 detection in CXR. DAM-Net adaptively extracts spatial features of COVID-19 from the infected regions with various appearances and scales. Our proposed DAM-Net is composed of dense layers, channel attention layers, adaptive downsampling layer, and label smoothing regularization loss function. Dense layers extract the spatial features and the channel attention approach adaptively builds up the weights of major feature channels and suppresses the redundant feature representations. We use the cross-entropy loss function based on label smoothing to limit the effect of interclass similarity upon feature representations. The network is trained and tested on the largest publicly available dataset, i.e., COVIDx, consisting of 17,342 CXRs. Experimental results demonstrate that the proposed approach obtains state-of-the-art results for COVID-19 classification with an accuracy of 97.22%, a sensitivity of 96.87%, a specificity of 99.12%, and a precision of 95.54%. [ABSTRACT FROM AUTHOR]

Mining activities have serious environmental impacts, thus releasing heavy metals (HMs) such as cadmium (Cd), lead (Pb), chromium (Cr), zinc (Zn) and nickel (Ni) into the surrounding environment. The current paper investigated the impacts of mining activities of Pb-Zn sulfide on soil and medicinal plants. Hence, soil samples (n = 36) and medicinal plants (n = 36) samples were collected, acid extracted and were analyzed through Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for HMs quantification. Our results showed that mineralized zones showed high HMs enrichment levels as compared to non-mineralized zones. Various Indices for HMs assessment revealed that the contaminated soil of the study area had low to extreme level. The mean concentrations of HMs in mining degraded soil and medicinal plants were significantly higher (p ≤ 0.01) and were found in order of Zn > Pb > Cr > Ni > Cd and Cr > Zn > Pb > Ni > Cd respectively. Similarly, some widely consumable medicinal plants showed good metal accumulation for Cd, Cr and Pb i.e., 3.57 mg kg1, 350 mg kg–1 and 335 mg kg–1 in C. sativa, while 5.9 mg kg–1, 276.9 mg kg–1 and 188.7 mg kg–1 in R. hestatus respectively. Hence, the present study recommended that medicinal plants grown in mining areas should be analyzed for HMs concentration before consumption. [ABSTRACT FROM AUTHOR]

Potable groundwater (GW) contamination through arsenic (As) is a commonly reported environmental issue in Pakistan. In order to examine the groundwater quality for As contamination, its geochemical behavior, and other physicochemical parameters, 69 samples from various groundwater sources were collected from the mining area of Pind Dadan Khan, Punjab, Pakistan. The results showed the concentration of elevated As, its source of mobilization, and linked public health risk. Arsenic detected in the groundwater samples varied from 0.5 to 100 µg/L, with an average value of 21.38 µg/L. Forty-two samples were beyond the acceptable limit of 10 µg/L of the WHO for drinking purposes. The statistical summary showed that the groundwater cation concentration was in decreasing order such as Na+ > Ca2+ > Mg2+ > K+, while anions were as follows: HCO3− > SO42− > Cl− > NO3−. Hydrochemical facies results depicted that groundwater samples belong to CaHCO3 type. Rock-water interactions control the hydrochemistry of groundwater. Saturation indices' results indicated the saturation of the groundwater sources for CO3 minerals due to their positive SI values. Such minerals include aragonite, calcite, dolomite, and fluorite. The principal component analysis (PCA) findings possess a total variability of 77.36% suggesting the anthropogenic and geogenic contributing sources of contaminant. The results of the Exposure-health-risk-assessment model for measuring As reveal significant potential carcinogenic risk exceeding the threshold level (value > 10−4) and HQ level (value > 1.0). [ABSTRACT FROM AUTHOR]

Vegetation structures and dynamics are the result of interactions between abiotic and biotic factors in an ecosystem. The present study was designed to investigate vegetation structure and species diversity along various environmental variables in the Yakhtangay Hills of the Hindu-Himalayan Mountain Pakistan, by using multivariate statistical analysis. Quadrat quantitative method was used for the sampling of vegetation. PC-ORD version 5 software was used to classify the vegetation into different plants communities using cluster analysis. The results of regression analysis among various edaphic variables shows that soil organic matter, total dissolved solids, electrical conductivity, CaCO3 and moisture contents shows a significant positive correlation with species abundance, while the soil pH has inverse relationship with plant species abundance. Similarly, species richness increases with increase in soil organic matter, CaCO3 and moisture contents, while decrease with increase in soil pH, total dissolved solids and electrical conductivity (p < 0.05). The vegetation was classified into four major plant communities and their respective indicators were identified using indicator species analysis. Indicator species analysis reflects the indicators of the study area are mostly the indicators to the Himalayan or moist temperate ecosystem. These indicators could be considered for micro-habitat conservation and respective ecosystem management plans not only in the study area but also in other region with similar sort of environmental conditions. [ABSTRACT FROM AUTHOR]

The Sheikhan Limestone of Eocene age has been studied in detail covering its microfacies analysis, depositional setting, being a reservoir potential, and diagenetic sequence. For this purpose, two best exposed geological sections at Sheikhan Nala and Panoba section, Kohat Basin (Pakistan) have been selected. The techniques used for this research work are petrographic analysis, X-ray diffraction (XRD), cathodoluminescence (CL), pore plug porosity, and Scanning Electron Microscope (SEM) analysis. Typically, the Sheikhan Limestone is compacted, fossiliferous, and yellowish-grey in color, medium-thin bedded limestone with interbedded shale partings. The thickness of the studied limestone is 32 m to 44 m in the Sheikhan Nala and Panoba sections, respectively. A petrographic study reveals that calcite occurs in the form of micrite with a minor quantity of spare. Carbonate-filled fractures are common, as micro-veins. Detailed study reveals the diagenetic processes, and these include the imprints of micritization, neomorphism, cementation, compaction, dissolution, and fracturing. The dissolution and fractures enhance the reservoir characteristic, whereas clay minerals, micritization, compaction, and cementation reduces the reservoir potential of Sheikhan Limestone. The outcrop and petrographic studies have been used as a powerful tool to identify different microfacies. Based on all petrographic studies and microfacies analysis, it is suggested that the Eocene Sheikhan Limestone has been deposited under a shallow neritic inner shelf environment. Dissolution and fractures enhance the reservoir characteristics, whereas micritization, cementation, and compaction reduce the reservoir quality. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) pandemic adversely affected human beings. The novel coronavirus has claimed millions of lives all over the globe. Most countries around the world, including Pakistan, restricted people’s social activities and ordered strict lockdowns throughout the country, to control the fatality of the novel coronavirus. The persuaded lockdown impact on the local environment was estimated. In the present study, we assessed air quality changes in four cities of Pakistan, namely Islamabad, Karachi, Lahore, and Peshawar, based on particulate matter (PM2.5), using “Temtop Airing 1000,” which is capable of detecting and quantifying PM2.5. The Air Quality Index (AQI) was evaluated in three specific time spans: the COVID-19 pandemic pre- and post-lockdown period (January 1, 2020 to March 20, 2020, and May 16, 2020 to June 30, 2020 respectively), and the COVID-19 pandemic period (March 21 2020 to May 15, 2020). We compared land-monitored AQI levels for the above three periods of time. For validation, air quality was navigated by the Moderate Resolution Imaging Spectrometer (MODIS) satellite during the first semester (January 1 to June 30) of 2019 and 2020. It is seen that the concentration of PM2.5 was considerably reduced in 2020 (more than 50%), ranging from ~ 0.05 to 0.3 kg⋅m3, compared to the same period in 2019. The results revealed that the AQI was considerably reduced during the lockdown period. This finding is a very promising as the inhabitants of the planet Earth can be guaranteed the possibility of a green environment in the future. [ABSTRACT FROM AUTHOR]

In current era, the next generation networks like 5th generation (5G) and 6th generation (6G) networks requires high security, low latency with a high reliable standards and capacity. In these networks, reconfigurable wireless network slicing is considered as one of the key element for 5G and 6G networks. A reconfigurable slicing allows the operators to run various instances of the network using a single infrastructure for better quality of services (QoS). The QoS can be achieved by reconfiguring and optimizing these networks using Artificial intelligence and machine learning algorithms. To develop a smart decision-making mechanism for network management and restricting network slice failures, machine learning-enabled reconfigurable wireless network solutions are required. In this paper, we propose a hybrid deep learning model that consists of convolution neural network (CNN) and long short term memory (LSTM). The CNN performs resource allocation, network reconfiguration, and slice selection while the LSTM is used for statistical information (load balancing, error rate etc.) regarding network slices. The applicability of the proposed model is validated by using multiple unknown devices, slice failure, and overloading conditions. An overall accuracy of 95.17% is achieved by the proposed model that reflects its applicability. [ABSTRACT FROM AUTHOR]

This research was conducted to determine the adverse health effects of transport-related air pollution on the people specifically linked to this sector as well as people exposed to vehicular emissions. Body mass index, lead (Pb) exposure, and osteoarthritis risk were measured, while detailed health records were taken through a questionnaire-based survey. Blood lead level (BLL) was higher than the acceptable level; mean BLLs were 27.79 μg/dl and 21.33 μg/dl for significantly exposed and less exposed individuals. Some respondents showed exceptionally high BLL 60 μg/dl. Type II collagen (C2C) cleavage neoepitope, a collagen degrader and Pb biomarker, was also observed in high-exposure (0.056 μg/dl) and low-exposure (0.0126 μg/dl) respondents. This study revealed serious health effects in the transport workers of Abbottabad caused by vehicular emissions. Good percentages of exposed (40–45%) participants were found to have severe cough and hypertension, while a small proportion (15–20%) had acute skin diseases, eye disease, asthma, hearing loss, chronic obstructive pulmonary disease, headache, and lung cancer. It was disappointing that people were unaware of the automobile emissions' adverse effects. This study revealed significant health effects of transport occupation. [ABSTRACT FROM AUTHOR]

Silicon (Si) is a beneficial nutrient and is known for imparting resistance to many of the abiotic and biotic stresses in crop plants. A pot experiment was conducted in wire house to elucidate the effect of exogenous Si on growth, physiological, and biochemical activities in wheat at different phenological stages (seedling, vegetative, and maturity) under cadmium (Cd) stress. Surface sterilized seeds of Ujala-2016 wheat cultivar were sown in plastic pots. Foliar applied Si (3mM) inform of in the form of Si-NPs used in the present experiment under control (−Cd) and Cd stress (25mg/kg soil) conditions. Plants were harvested after 14 days of foliar spray at different phenological stages. The experimental treatments were arranged in completely randomized design with three replicates per treatment. Cadmium stress caused significant reduction in biomass production, photosynthetic pigments, total soluble protein (TSP), free amino acids (FAA), total soluble sugar (TSS), and phenolic contents, whereas increase of antioxidant enzymes activities such as ascorbate peroxidase (APX), catalase (CAT), peroxidase (POD) and superoxide dismutase (SOD), reducing sugar (RS), and proline contents as well as malondialdehyde (MDA), hydrogen peroxide (H2O2) content, and electrolyte leakage (EL) was recorded. Foliar application of Si-NPs significantly improved the growth, photosynthetic pigments, levels of flavonoids, TSP, phenolics, FAA, proline, TSS, activities of APX, CAT, POD, and SOD enzymes. The oxidative damage measured in the form of endogenous levels of H2O2 and MDA was reduced in plants treated with exogenous application of Si. Further, Si application increased mineral ions in controlled and Cd-stressed plants and significantly reduced the Cd uptake. In short, this study revealed that foliar spray of Si alleviates the adverse effect of Cd on wheat by enhancing growth, metabolite accumulation, strengthening antioxidant defense system, reducing oxidative injury, improving plant nutrient status, and decreasing the Cd uptake. [ABSTRACT FROM AUTHOR]

Fossil fuels account for more than 80% of the world's energy consumption. Constituents of the atmosphere have changed perceptibly due to the increased use of fossil fuels. Therefore, many researchers have tried to relate their effect on society. In Pakistan, fossil fuel consumption and its CO2-based emission factor have been significantly correlated to economic growth. However, it needs further attention to study the adverse effects of fossil fuels. This study is an attempt to assess the cost of fossil fuels to society. Damages caused by fossil fuels are evaluated for the years of 2005–2009, using local pollution factors based on CO2 emission. Results show that the market price of fossil fuels increases after adding up the cost of damage caused by the final use of the fuel. People pay a huge amount of PKR 133 billion per year for taxes, health services, insurance premiums, and low living standards. Accordingly, it is suggested that we must shift from fossil fuels to other alternative clean types of energy. [ABSTRACT FROM AUTHOR]

Kalam Kohistan is a dry, temperate hilly region in the Hindu Raj Series of the Greater Hindu Kush Mountains with diverse forests. As plant distribution and composition is expression of a range of various environmental variables, ecological and floristic attributes of vegetation in the Laikot Forests were therefore evaluated via consecutive explorative trips. These forests have not been evaluated ecologically before due to harsh climatic conditions and issues of accessibility and the study in hand is one of the first in its nature. Quantitative ecological techniques were used to sample forest vegetation and identify species in quadrats of 2 m × 2 m for herbs, 5 m × 5 m for shrubs and 10 m × 10 m for trees. All the data of 195 plant species and environmental factors were analyzed via Two-way Cluster Analysis and Canonical Correspondence Analysis using PCORD and CANOCO software. Among 195 plant species from 63 families were 27 species of Asteraceae, the most-speciose family, followed by Poaceae (20 spp.). The dominant life form was therophyte (86 spp.; 44% share), followed by phanerophyte (41 spp.; 21% share). For the leaf size spectrum, most prevalent was nanophyll (73 spp.; 44%) followed by microphyll (66 spp., 34%) and mesophyll (44 spp.; 23%). Calcium carbonate, pH, potassium, sand, silt, organic matter, slope aspect and grazing significantly influenced species composition, distribution and habitat. The floristic variation in the region was diverse due to elevational and aspect gradients and thus devided into three zones. This vegetation zonation can be utilized for forest management, species and habitat conservation. Both in situ and ex situ conservation of threatened plant species may improve their conservation status in future if address properly. [ABSTRACT FROM AUTHOR]

Wireless Body Area Networks (WBANs) is a revolutionary achievement in the field of health services. The field is envisioned to play an important role in medical, psychological, and even in non-medical applications. Different routing protocols are being designed in WBAN to enhance its performance, focusing on delay, energy efficiency, throughput, and network lifetime. Line-of-sight (LoS) and Non-Line-of-Sight (NLoS) communications and clustering are the least focused areas in the literature. This paper presents a routing protocol called Dual Sink approach using Clustering in Body Area Network (DSCB) which is more reliable in terms of network stability, and energy efficient in comparison to its counterparts. This protocol enhances network life-time by introducing the concept of clustering while using two sink nodes. The proposed scheme is compared with existing protocols named as SIMPLE and DARE. The cost function is established for selection of forwarder node, based on nodal distance from the sink, residual energy, and transmission power. Simulation results depict that the proposed protocol achieves significant performance improvement in network throughput by attaining 55% and 22% more efficient results compared to SIMPLE and DARE respectively. Furthermore, the results show improved performance of DSCB protocol, in terms of network stability and end-to-end delay performance metrics. [ABSTRACT FROM AUTHOR]

An effective numerical method is proposed for the three-dimensional nonlinear analysis of mooring cables using catenary theory. In this method, the mooring line is divided into finite number of catenary elements. In addition to self-weight, each catenary element is subjected to drag force due to steady ocean currents. The proposed procedure is validated by comparing the results with those of the shooting optimization and the finite element methods. Finally, a parametric study is conducted to study the effect of extensibility on the static response of mooring cables. The effects of fluid drag forces and cable extensibility on mooring cable tension, equilibrium configurations, and stressed lengths are illustrated for two- and three-dimensional mooring cable problems. From the numerical results, the method is found to be numerically stable, and it provides a more rational static response for mooring cables. [ABSTRACT FROM AUTHOR]

Geometrical channel modeling has been one of the hot topics in wireless communication systems since the last two decades. It has been used for variety of scattering model characterizations like spatial and temporal statistical behavior of the channel, level crossing rate of the fading channel along with the analysis of average fade duration etc. In this paper, we propose a three dimensional (3D) semi-ellipsoid geometric scattering model for cellular mobile communication systems, where, elevated base station is considered in scattering free region while the mobile station is assumed to be surrounded by uniformly distributed scatterers in the proposed geometrical shape. Exploiting the proposed geometry, expressions for the joint and marginal probability density functions for angle-of-arrival and time-of-arrival in azimuth and elevation planes are derived. This model is suitable for macro-cellular environment. [ABSTRACT FROM AUTHOR]

Urbanization tendency is growing rapidly in the developing countries. It may cause microclimatic change in these areas. Therefore, it is necessary to investigate the impact of past and present urbanization on the microclimate of cities. Microclimatic change and its relation to the rapidly increasing population in a northern city (Abbottabad) of Pakistan were investigated. This is one of the wettest cities in Pakistan, which receives the maximum of its rainfall in the monsoon rainfall season. The climatic data (temperature and precipitation) for the last 50 years were used for the study. A contrast was found between mean maximum and mean minimum temperature trends. The average increase in mean maximum temperature was ±0.67 °C. The contribution of urban warming to the total mean annual temperature was 2.87 % in five decades. The average decrease in temperature was ±2 °C. The maximum temperature indicated a increasing trend while the minimum temperature had a decreasing trend with a declining rainfall. [ABSTRACT FROM AUTHOR]

Ternary content addressable memories (TCAMs) perform high-speed search operation in a deterministic time. However, when compared with static random access memories (SRAMs), TCAMs suffer from certain limitations such as low-storage density, relatively slow access time, low scalability, complex circuitry, and higher cost. One fundamental question is that can we utilize SRAM to combine it with additional logic to achieve the TCAM functionality? This paper proposes an efficient memory architecture, called E-TCAM, which emulates the TCAM functionality with SRAM. E-TCAM logically divides the classical TCAM table along columns and rows into hybrid TCAM subtables and then maps them to their corresponding memory blocks. During search operation, the memory blocks are accessed by their corresponding subwords of the input word and a match address is produced. An example design of $$512\times 36$$ of E-TCAM has been successfully implemented on Xilinx Virtex- $$5$$ , Virtex- $$6$$ , and Virtex- $$7$$ field-programmable gate arrays (FPGAs). FPGA implementation results show that E-TCAM obtains $$33.33$$ % reduction in block-RAMs, $$71.07$$ % in slice registers, $$77.16$$ % in lookup tables, $$53.54$$ % in energy/bit/search, and offers $$63.03$$ % improvement in speed, compared with the best available SRAM-based TCAM designs. [ABSTRACT FROM AUTHOR]

Untreated wastewater discharges may have significant short term and long term effects on the quality of a river system. Present study was undertaken to assess the present status of the water quality of the River Kabul near Peshawar in Pakistan. Seven sites were sampled upstream and downstream in the River Kabul in 2009. Samples were also taken from waste water channel (Budni Drain) that carries waste-water of Peshawar Industrial Estate as well as the domestic sewers to assess the pollution contribution of these sources to the River Kabul. Physico-chemical and microbiological parameters of the samples were analyzed during the study, as well as possible sources of contamination were investigated. The study showed that the pollution level in river is rising from upstream (at city entrance) to downstream (at city exit) due to discharge of domestic waste water effluents, agricultural activities, and solid waste dumping directly into the river. [ABSTRACT FROM AUTHOR]

Industries that are ever increasing are major contributors to environmental pollution due to inappropriate waste handling. Textile wastewater contains mutagenic and carcinogenic chemicals which are harmful to natural phenomenon of receiving water channels. Therefore, textile wastes should be treated before discharging in the environment. Treatment of red bronze dye was investigated in the upflow anaerobic bioreactor. Varying dye concentrations (40~325 mg/L) were treated by adjusting primary pH at neutral. The performance of reactor was judged by conventional process parameters like pH, turbidity, dissolved oxygen (DO), electroconductivity (EC), total dissolve solids (TDS), removal efficiency, and chemical oxygen demand (COD). The maximum removal efficiency occurred at 150 mg/L dye concentration with addition of 50 ml of biomass. The pH of the water remained basic, COD removal ranged between 60 and 91%, and the maximum removal was done at 91%. EC and TDS were also low indicating good dye removal efficiency of the reactor. [ABSTRACT FROM AUTHOR]

Industrial sector is the backbone of the development of a country; however, its untreated effluents are damaging various ecological phenomena. Every day huge amounts of municipal, industrial and agricultural wastes are being released into the environment, causing serious ecological problems. Pakistan is currently experiencing profound demographic, economic changes and energy crisis that pose serious limitations on spending capital on water treatment. However, no serious effort has been put forth by any agency in Pakistan to characterize the exact nature and concentrations of contaminants found in wastewaters originating from various industrial zones. The current study aimed to characterize the industrial effluent quality of Hattar Industrial Estate, Hattar, Pakistan. The effluent samples were collected from five different drains, each having the combined effluent of many industries. All the samples were characterized for pH, temperature, TS, TDS, TSS, EC, DO, BOD, COD, turbidity, nitrates (NO3–N), phosphates (PO4), ammonia (NH4–N) and different heavy metals according to the standard methods. Majority of the water quality parameters exceeded the National Environmental Quality Standards in the country. These pollutants may have serious impacts on the soil profile, groundwater quality and freshwater ecosystems and thus need attention of policy makers to install a centralized wastewater treatment plant. [ABSTRACT FROM AUTHOR]

Previously, wastewaters containing organic matter such as sulfur and other nitrogenous compounds were treated by employing separate biotechnologies. The current investigation investigated simultaneous carbon, nitrogen, and sulfur removal in single bioreactor under oxygen and oxygen deficient experimental conditions. Two separate bioreactors (aerobic and anaerobic) were operated under similar mesophilic conditions. It was revealed that the products of COD, nitrate, and sulfate mainly depended on the medium pH which was the main determining factor. The substrates ratios like C:N, C:S, and N:S could result in the diverse end products. Under aerobic conditions, COD completely degraded into CO2 and H2O, nitrate was anticipated to be converted as ammonium through dissimilatory nitrate reduction to ammonium which could become part of cellular metabolism. The bulk of sulfate was converted to elemental sulfur. While the results of anaerobic digestion showed that COD mainly contributed to methanogenesis, the COD conversion was lower as compared with the aerobic conversion. Nitrate was anticipated to be converted to nitrogen gas via denitrification. However, mass balance suggested lower amount of elemental sulfur formed as compared with aerobic treatment. Such information may help to understand complex nature of bacterial interactions employed in aerobic and anaerobic wastewater treatments. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) are emerged technology where vehicles and roadside units (RSUs) communicate with each other. VANETs can be categorized as a subbranch of mobile ad hoc networks (MANETs). VANETs help to improve traffic efficiency and safety and provide infotainment facility as well. The dissemination of messages must be relayed through nodes in VANETs. However, it is possible that a node may propagate false information in a network due to its malicious behaviour or selfishness. False information in VANETs can change drivers’ behaviour and create disastrous consequences in the network. Therefore, sometimes false safety messages may endanger human life. To avoid any lass, it is more important to detect and avoid false messages. This paper has explained some important algorithms that can detect false messages in VANETs. The categorization of false message detection schemes based on local and cooperative behaviour has been presented in this article. The limitations and consequences of existing schemes as well as future work has been discussed. [ABSTRACT FROM AUTHOR]