Moderate Zones Research Articles

Early warning of heavy metals contamination in agricultural soils: Spatio-temporal distribution and future trends in the Hexi Corridor

Conducting risk and early warning assessments of heavy metals (HMs) pollution in agricultural soils holds significant importance for pollution prevention and sustainable agricultural development. Early warning studies on heavy metal contamination of agricultural soils in oases in arid zones are rare in previous studies, therefore, this study carried out spatial and temporal simulation and early warning studies on the environmental capacity of agricultural soils in the Hexi Corridor based on field monitoring data and remote sensing technology and other methods. The results revealed that agricultural soils have been affected by human activities, leaving HMs at a moderate pollution level. The mean environmental capacity indices for Cr, Ni, Cu, Zn, As and Pb showed that they all belonged to the medium-capacity state, and 7.01 % of the sampling points being overloaded and in the low capacity for As. Cr, Ni, Zn and As were found in the moderate and high capacity zones located in the study area's western part, and the spatial distribution was basically the same. HMs in the middle parts area were dominated by low to medium capacity status, which may be related to agricultural activities such as application of fertilizers and pesticides and sewage irrigation. Based on the soil dynamic capacity model, it was found that in the next 20 years, HMs showed a decrease of 70–80 %, and the soil environment dynamic capacity was smaller than both the static and existing capacity, and it showed a decreasing trend with the change of time, which indicated that the soil's capacity for pollutants in the study area would be reduced if no pollution control measures were taken. Risk warning results showed that the overall spatial distribution pattern of the probability of pollution in the study area during the next 10 and 20 years was lower in the west and the northern part of Wuwei City, and higher in the middle part. This study suggests constructing a management system of “pollution evaluation - source treatment - risk early warning” for heavy metal contaminated sites, formulating corresponding policies and early warning measures, strengthening the research and development of monitoring, remediation, and treatment technologies, and realizing the prevention and control of agricultural soil pollution and sustainable development in the study area.

Dynamic simulation of landscape ecological security and analysis of coupling coordination degree: A case study of Bole.

The ecological security of oasis cities in arid and semi-arid regions is highly susceptible to changes in regional landscape patterns and the degree of coordination between human activities and the environment. At the same time, the ecological security of urban landscapes also profoundly affects the success of regional economic and environmental coordination and development. This study is based on land use data from 1990, 2000, 2010, and 2020, as well as land use data from the natural development scenario (NLD), economic development scenario (ECD), ecological development scenario (ELD) and ecological-economic development scenario (EED) simulated by the patch-generating land use simulation (PLUS) model in 2030. From the perspective of production-living-ecological land (PLEL), it analyzes the changes in the past and future landscape ecological security and coupling coordination characteristics of Bole. The results show that from 1990 to 2020, Bole was mainly dominated by grassland ecological land (GEL) and other ecological land (OEL), accounting for a total proportion of 69.51%, with a large increase in production and living land area; the average value of landscape ecological risk is decreasing, and the landscape ecological security of Bole is developing towards benignity; the area of highly coupled coordination zone is decreasing continuously, while that of basic coordination zone and moderate coordination zone is increasing continuously. Under the 2030 EED scenario, the overall changes in various types of land use are not significant, and the average value of landscape ecological risk is the smallest, but it is higher than that in 2020 as a whole; under EED scenario, the area of highly coordinated zone and moderate coordinated zone is the largest among four scenarios, and the best coupling coordination level among the four scenarios. Landscape ecological security and its coupling coordination will be affected by land use patterns. Optimizing regional land use patterns is of great significance for improving urban landscape ecological security and sustainable high-quality development.

Comparative Antibacterial Activity of Bharangyadi Yoga Variants w.s.r. to Salmonella Typhi

Salmonella typhi, the causative organism of typhoid fever, remains a major global public health concern. Despite the availability of conventional antibiotics, the emergence of antibiotic-resistant strains of Salmonella typhi poses a serious challenge in combating this infectious pathogen. As a result, the exploration of alternative therapeutic options, such as traditional herbal remedies, has gained prominence. Bharangyadi Yoga is a combination of specific herbal ingredients, used in traditional medicine system to address various types of fever and related ailments as mentioned in Sahasrayogam, has to be prepared and administered in the form of Kashaya. In vitro antibacterial activity of Bharangyadi Kashaya and Bharangyadi Arka was carried out by well diffusion method with different concentrations against Salmonella typhi and the area of inhibition of microbial growth is measured. Moderate zone of inhibition was observed in Arka, while no zone of inhibition was seen in any of the concentration of Kashaya. The antibacterial effectiveness of Bharangyadi Arka can be attributed to its volatile and other aqueous extract content, enhanced solubility and release of volatile active constituents. In this study, Arka is established to have better antibacterial activity compare to Kashaya as a new dosage form. However, Negative antibacterial result of Kashaya does not indicate lack of therapeutic effectiveness.

Accuracy and reliability of perception of bar velocity loss for autoregulation in resistance exercise

Background The perception of bar velocity loss (PVL) can be used as an alternative method for autoregulating intraset repetitions during velocity-based training. This study analyzed the accuracy and reliability of the PVL as a method to autoregulate the intraset repetitions using a moderate velocity loss (VL) threshold (15–30%). Methods A total of 22 resistance-trained men were familiarized with the PVL in a single session. Test–retest was performed in two sessions 1 week apart, in which participants completed three sets of bench press and back squat at 40, 60, and 80% 1 repetition maximum (1RM). Participants stopped the sets when they reached a moderate VL zone using their PVL. Accuracy was assessed by analyzing whether the mean VL (actual) and the lower and upper limits of the confidence interval (CI) (95%) of each set were within the established VL range and quantifying the relative frequency of correctly interrupted sets. Test–retest reliability was examined by the intraclass correlation coefficient and coefficient of variation. Results PVL showed acceptable accuracy in both exercises at 60 and 80% 1RM (50–65% success rate) and retest for all loads (53–76% success rate). Similar PVL percentages were observed between most of the sets for the test and retest ( p > 0.05). Accuracy improved during the retest, especially for bench press (40% 1RM) and back squat (40 and 80% 1RM). PVL was not reliable in the test–retest comparison. Conclusion PVL can be a strategy with acceptable accuracy to autoregulate the intraset repetitions in a moderate zone (VL15–30%), but its reliability does not appear satisfactory after one familiarization session.

Spatial evaluation of groundwater vulnerability using the DRASTIC-L model with the analytic hierarchy process (AHP) and GIS approaches in Edo State, Nigeria

The drinking of contaminated water is potentially hazardous to the well-being of humanity. Effective groundwater management depends on detecting groundwater contamination before it hits a critical point. The DRASTIC framework, modified globally to include land use (L), is utilized to evaluate groundwater vulnerability in various regions. In this study, an assessment of groundwater's susceptibility to contamination and a water quality index map to determine its fitness for Edo State have been done using the DRASTIC, DRASTIC-AHP, and DRASTIC-L-AHP models. The distinction of potential-risk water zones in Edo State, Nigeria, was made possible by the GIS that was used to create and combine several attribute maps. Results established that in the study area, very low (1,741.683 km2; 45%), low (1,741.683 km2; 10%), moderate (3,483.366 km2; 20%), and high (4,354.2075 km2; 25%) risk zones of groundwater contamination were identified on the overall DRASTIC-L-AHP map. The study found a significant pollution risk in one-fourth of the area, primarily in the Edo north and south regions of the study area. The significance of each factor for groundwater susceptibility and contamination risk was evaluated through a sensitivity analysis (SA). The SA indicated that the impact of the vadose zone is the most efficient variable in the DRASTIC-L-AHP model, with an effective weight value of 33.45% that is much larger than the theoretical value of 21.51%. The DRASTIC-L-AHP model, validated through hydrochemical analysis, is the least inaccurate and suitable for the current study area, serving as a useful pre-decisional tool for managing and preserving groundwater.

Curie Point Depth from Spectral Analysis of Magnetic Data in Potiskum and Environs, Yobe State, Nigeria

The area under investigation, is part of Chad basin of northeastern Nigeria, located between latitudes 11o00´ to 12o00´N and Longitudes 11o30´ to 12o30´E, with the objective to discover more about the thermal structure of the crust in the area, a research was carried out over Potiskum and surrounding regions in Yobe State, Nigeria to estimate the curie point depth, geothermal gradient, and heat flow using spectrum analysis and empirical formula of aeromagnetic data. To acquire the regional and residual data, polynomial fitting was applied to the high-resolution digital aeromagnetic data. In order to calculate the depth to the centroid and the depth to the top boundary, the upward continued residual data was processed to produce the upward continued data, that was subjected to spectral analysis. The depth to the centroid is between 10.50 and 11.50 kilometers, the depth to the top boundary is between 5.90 and 7.16 kilometers, the depth to the Curie point is between 14.84 and 16.83 kilometers, the geothermal gradient is between 34.462 and 39.083 oCkm-1, and the heat flow is between 86.135 and 97.707 mWm-2. The Curie point depth inferred from the study indicates that the crust is thinning due to thermal upwhirling of magma and is moderately decreasing toward areas of volcanic activity that occurred in the area during the Tertiary Period. The Geothermal gradient shows that the area is a moderate temperature zone, which could likely result in partial thermal maturation of sediments and hence probable oil generation as time goes on with an increase in temperature. In the research area, the geothermal gradient is proportional to the heat flow, whereas the connection between curie depth and heat flow is inversely linear. These findings are in line with the geotectonic regime that is now in effect in the research area. However, this analysis shows that the heat flow that was obtained from the study is sufficient to be utilized as a geothermal energy source.

Flood susceptibility assessment using machine learning approach in the Mohana-Khutiya River of Nepal

Nepal, known for its challenging topography and fragile geology is confronted with the constant threat of floods leading to substantial socio-economic losses annually. However, the country's efforts in planning and managing flood risks remain insufficient, especially in the vulnerable Mohana-Khutiya River. Therefore, this study focused on the Mohana-Khutiya River and utilizes the Maximum Entropy (MaxEnt) model to comprehensively map flood susceptibility and fill crucial gaps in flood risk assessments. This study employed a combination of 10 geospatial environmental layers and field-based past flood inventory to implement the MaxEnt machine learning model for flood susceptibility modeling. The available past flood data were divided into two sets, with 75% allocated for model construction and the remaining 25% for model validation. This study demonstrated that the proximity of the river had a significant impact (33.1%) on the occurrence of the flood. Surprisingly, the amount of annual precipitation throughout the year exhibited no detectable contribution to the flood event in the study site. About 4.9% area came under the high flood susceptible zone followed by 12.75 % in the moderate zone and 82.34% in the low-risk zone. The model exhibited excellent performance with an Area Under Curve (AUC) value of 0.935 and a low standard deviation of 0.018, indicating accurate predictions and consistent precision. These results highlight the model's reliability and its significance for developing disaster management policy by local government in the study site. Future research should refine the MaxEnt model by including more variables, validating against observed flood events, and exploring integration with other flood modeling approaches.

Monte-Carlo Simulation for Moderate Seismic Zones Using Artificial Accelerograms

The present technical note deals with a new method to generate seismic accelerograms based on statistical characteristics and the classification of seismic waves. A short heterogeneous site- based analyse of these accelerograms is given with a seismic wave propagation code in 1D. After, a numerical simulation is done in order to obtain PGA using Newmark’s implicit scheme, and finally, Monte-Carlo simulation is used to determinate failure’s probability of structures localised in moderate seismic zones in hexagonal France

Comparative Protein Profiling of Blood and Milk of Early Pregnant Buffaloes Using SDS-PAGE

Conventional methods for detecting pregnancy in buffalo are inefficient before 30-days after artificial insemination. A proteomic approach for high-resolution analysis of blood plasma and milk proteins by SDS polyacrylamide gel electrophoresis (PAGE) is of great importance. Blood and milk samples were collected on days 0 (before insemination) and 20 and 25 after insemination from retrospective pregnant (n = 6) and non-pregnant (n = 6) animals. An equal volume of samples was loaded in (12%-4%) SDS gel to resolve major plasma and milk proteins. Plasma proteins showed three distinct zones – high, medium, and low molecular weight (MW). In the high MW zone (135 - 250 kDa), ~208 kDa and ~190 kDa proteins were visible. In the moderate MW zone (60 -75 kDa), 5-6 proteins like albumin (~70 kDa), 75 kDa, and 63 kDa consisting of pregnancy-associated glycoproteins, ~73 kDa being dominant. In the low MW zone (25 – 35 kDa), a clear band of 27 kDa was visible. Proteins in milk supernatants showed four distinct zones of proteins – very high, high, medium, and low molecular weight (MW) zones. In the very high MW zone (135 - 250 kDa), ~208 kDa and ~190 kDa proteins were visible. In the high MW zone (60 -75 kDa), proteins like lactoferrin (~78.2 kDa), 73 kDa, albumen (~66 kDa), and a heavy chain of immunoglobulin (IgG) (~54 kDa) were detected. In the medium MW zone (25 – 35 kDa), clear bands of milk caseins, namely thick alpha S2 casein (29 kDa), and other caseins. In the low MW zone (11 – 20 kDa), two thick bands of 18 kDa and 12 kDa were visible. The mean gray values (sum of the gray values of all the pixels in the peak divided by the number of pixels) of the 73 kDa protein peak were analyzed in two-way ANOVA using GraphPad (ver 8.0). Repeated measures of ANOVA were selected where pregnancy status (pregnant and non-pregnant) defined column factor and time (0-, 20- and 25-day) defined row factor. The expression of 73 kDa protein in blood plasma was higher (P = 0.04) in pregnant women than in non-pregnant buffaloes at 20- and 25-days after insemination. However, in milk, there was no difference in the expression of the 73 kDa protein between pregnant and non-pregnant buffaloes across time. Variation in animals within the groups was significantly high. The differential expression of ~73 kDa protein in plasma and precise identification of the protein can be a diagnostic marker for early pregnancy detection in buffaloes.

Antibacterial Activity of Extract Green Seaweed Ulva intestinalis in North Waters of Aceh

The appearance of bacterial resistance and pathogenic infections makes efforts to find new drugs as natural bacterial agents continue. One of them is through the utilization of marine organisms such as seaweed. Some studies show the content of seaweed bioactive compounds has potential in the pharmacological field. This study aims to determine the type of secondary metabolite compounds and antibacterial activity of ethanol extract of Ulva intestinalis. Seaweed extraction using the maceration method for 3 x 24 hours and antibacterial activities were tested by disc diffusion method. The results showed that there were 5 types of secondary metabolite compounds in the extract, namely alkaloids, flavonoids, glycosides, saponins, and steroids. The antibacterial activity test of seaweed extract against Propionibacterium acnes and Aeromonas hydrophila bacteria in the concentration range of 50% to 100% showed a moderate inhibition zone diameter

ANALYSIS OF SPATIAL RELATIONSHIP BETWEEN GROUNDWATER POTENTIAL ZONES AND BOREHOLE YIELDS IN OKENE LOCAL GOVERNMENT AREA, KOGI STATE, NIGERIA

The quantity of water that can be extracted from a borehole is directly related to the groundwater potential of an area among other things. Boreholes drilled in areas of low groundwater potential have every tendency to fail. There have been reported cases of borehole failures in Okene Local Government Area of Kogi state. This study therefore aimed at analyzing the potentiality of groundwater and the spatial relationship between borehole yield and groundwater potential zones in the area. Various data which include Sentinel 2 satellite image, Digital Elevation Model, geological map, rainfall data and borehole yield data were analyzed to produce various zones of groundwater potential, and validated using existing borehole yields and the relationship was tested using Pearson correlation. The result of this study reveals that the low potential zone covers 33.2%; moderate potential zone occupies 44.9% which cuts across the whole of Okene LGA and the high potential zone covers 21.9% mainly found around the western part of the area. The Pearson moment correlation analysis result revealed a strong positive correlation (R) value of 0.919. The correlation value shows that there is a strong positive relationship between the existing borehole yields in the study area and the groundwater potentiality map produced from the analysis. The study concluded that there is a strong positive relationship between the existing borehole yields and the groundwater potential zones in Okene Local Government Area.

GIS based Groundwater Vulnerability Assessment of Lahore a Metropolitan using Modified DRASTIC Model

The metropolitans of the developing countries are experiencing the hazard of low quality drinking water. Lahore, the heart of Pakistan, has over 12 million population and is going to face the shortage of clean drinking water. The study was designed to create a groundwater vulnerability map of Lahore using modified DRASTIC model. The water table, land use/cover, hydraulic conductivity, vadose zone, soil and aquifer media layers of Lahore aquifer were analyzed using ‘geostatistical analyst’ and ‘spatial analyst’ extensions of ArcGIS software to compute the groundwater vulnerability. The Vulnerability index of modified DRASTIC model ranged from 64 – 144. The spatial variability of modified DRASTIC index were divided into 4 categories, namely, Low, Moderate, High and Very High groundwater vulnerable zones. The modified DRASTIC model revealed that 51.38% areas have low vulnerability, 36.77% areas have moderate vulnerability, 9.48% areas have high vulnerability and 2.37% areas have very high vulnerability to groundwater pollution. The ‘high’ and ‘very high’ vulnerability classes were found in the western parts of Lahore. The results of modified DRASTIC model were validated using the groundwater contamination data of arsenic in the study area. The groundwater arsenic concentrations map also showed higher values in the northwestern parts while in the eastern parts of the study area, the arsenic concentrations had a decreasing trend. In Ravi Town, the arsenic concentrations were positively correlated with modified DRASTIC vulnerability index and inversely correlated with water table depth (p < 0.01). It is recommended that the arsenic removal plants should be installed at all the tubewells with higher arsenic levels (arsenic concentration > 50 ppb) to provide safe drinking water to the citizens of Lahore. It is recommended that the modified DRASTIC model based on geospatial techniques can be applied on other metropolitans of the world for taking preventive measures against massive water pollution.

Landslide susceptibility assessment along the National Highway-244 from Batote to Doda, J & K, India: A study based on the Frequency Ratio Method

The National Highway-244 is highly susceptible to landslide occurrences, frequently resulting in road blockades and causing significant hardships for the local population. These landslides pose a threat to human lives, property and the environment, leading to substantial losses. In this study, an attempt has been made to carry out landslide susceptibility assessment through frequency ratio method along the National Highway-244 utilizing GIS and statistical computations. It considers eight parameters, which include topographical (slope, slope aspect, slope curvature, hill shade, and relief), anthropogenic (distance to road and distance to river) and geological parameters that mostly influence the occurrence of landslides in the area under investigation. The present study focuses only along National Highway-244 and data has been gathered from field visits and secondary sources. The results of the study inferred that the area under investigation falls into different susceptibility zones, namely very high, high, moderate, low, and very low, covering approximately 15%, 31%, 27%, 19%, and 8%, respectively of the total area. This study reveals that a considerable proportion, around 73%, of the study area falls within very high to moderate susceptibility zones. The conclusions drawn from this study hold significant implications for stakeholders and also provide valuable insights for future planning and infrastructure development, enabling them to make informed decisions. By considering the susceptibility zones identified in this study, stakeholders can implement appropriate measures to mitigate the impact of landslides, ensuring the safety and stability of the region.

Development of landslide susceptibility maps of Tripura, India using GIS and analytical hierarchy process (AHP).

Landslides are one of the most extensive and destructive geological hazards on the globe. Tripura, a northeastern hilly state of India experiences landslides almost every year during monsoon season causing casualties and huge economic losses. Hence, it is required to assess the landslide susceptibility of the area that would support short- and long-term planning and mitigation. The analytic hierarchy process (AHP) integrated with geospatial technology has been adopted for landslide susceptibility mapping in the state. Eight influencing factors such as slope, lithology, drainage density, rainfall, land use land cover, distance from rivers and roads, and soil type were selected to map the landslide susceptibility. Landslide susceptibility index (LSI) was found to vary from 6.205 during monsoon to 1.427 during post-monsoon season. The LSI values were classified into very high, high, moderate, low, and very low susceptibility. Landslide susceptibility maps for three different seasons, namely, pre-monsoon, monsoon, and post-monsoon, were prepared. The study showed that most of the areas of the state come under very low to moderate landslide susceptibility zones. Around 73.2% area of the state is found to be under low landslide-susceptible zones during the pre-monsoon season, around 62% area is prone to landslides with moderate susceptibility during the monsoon season, and 68.5% area comes under landslides with low susceptibility zones during the post-monsoon season. The resultsof this study may be referred to the engineers and planners for the assessment, control, and mitigation of landslides and the development of basic infrastructure in the state.

Flood hazard zonation using GIS-based multi-parametric Analytical Hierarchy Process

Flood is considered to be a serious environmental hazard, especially in the tropical countries owing to its devastating consequence on human life. Tripura, a small hilly state of northeast India has faced large scale flood events over the last few decades. The present study is an attempt to identify flood hazard zones along the lower course of the Dhalai River flowing through the Dhalai district of Tripura State. An integrated approach of remote sensing and GIS coupled together with Analytical Hierarchy Process (AHP) was applied to identify the flood hazard zones of the study area and nine parameters were selected for this purpose. Thematic maps of the parameters were reclassified after assigning ranks to different classes. A pair-wise comparison matrix among all the parameters was prepared using AHP to determine the relative weight of each parameter. Finally, flood hazard zoning (FHZ) map of the study area was prepared by multiplying the reclassified values with the weighted values using raster calculator of Arc GIS 10.1. The outcome of the study revealed that 109.69 km2 (27.65%) of the study area fall under low flood risk category. At the same time, around 114.46 km2 (28.85%) and 90.43 km2 (22.80%) areas fall under moderate and high flood risk zone respectively. The study also disclosed that the high risk zone has maximum concentration of agricultural land (68.63%) and settled area (9.77%) in comparison to the other two zones which has increased vulnerability of flood hazard. The results validated the efficiency of AHP technique in generating fast and cost effective information regarding flood hazard assessment, especially in no data regions. Hence, the derived information could be very much helpful for the planners to prepare proper strategies to reduce the vulnerability of this hazard.

Remote sensing, GIS, and analytic hierarchy process-based delineation and sustainable management of potential groundwater zones: a case study of Jhargram district, West Bengal, India.

The present investigation delineates groundwater potential zones (GPZ) in the Jhargram district through an integrated approach employing analytical hierarchical process (AHP), remote sensing, and geographical information systems (GIS). Twelve parameters were utilized for GPZ analysis based on the Groundwater Potential Index, subsequent to multicollinearity testing. Classification of GPZ yielded five distinct categories: very poor, poor, moderate, good, and very good. Validation through receiver operating characteristics (ROC) and cross-validation with borewell yield data affirmed prediction accuracies of 78.4% and 84%, respectively. Spatial distribution analysis revealed that 30.39%, 30.86%, and 13.19% of the surveyed area fell within the poor, moderate, and good potentiality zones, respectively, whereas 15.86% and 9.69% were categorized as very poor and very good GPZs. Sensitivity analysis highlighted the significance of geology, elevation, geomorphology, slope, and lineament density as influencing parameters; elimination of any single parameter engendered significant alterations in the GPZ classification. The investigation culminated in the formulation of a block-wise sustainable groundwater management blueprint designed to inform policy initiatives.

Redefining landslide susceptibility under extreme rainfall events using deep learning

The apparent changes in the Indian summer monsoon rainfall pattern and the nature of extreme rainfall events (EREs) in the southern Western Ghats (WG) caused widespread landslides across the region. Landslide susceptibility maps generated using the past landslide inventory are one of the efficient tools that can help mitigate the deleterious effects of landslides. Landslide susceptibility maps produced using the landslide inventory of normal and extreme rainfall years by deep neural network (DNN) modelling vary in terms of their degree of susceptibility, and the differences are prominent in the moderate and high susceptibility zones. The DNN model trained by landslide inventory of normal rainfall years is capable of predicting landslides during EREs (with Area Under the Curve (AUC) value >0.90). The inclusion of the landslides that occurred during recent EREs (since 2018) into the existing landslide inventory provides a more accurate and refined prediction of landslide susceptibility, which facilitates risk-informed landscape planning and development of the region. In addition, the result reveals that 13 % of the Kerala state is extremely susceptible for landslide occurrence, among this Idukki, Palakkad, Malappuram, Pathanamthitta, and Wayanad districts are highly vulnerable to the occurrence of landslides. Besides, the study also shows an increase of 3.46 % area in extreme susceptibility zone after the 2018 ERE. The updated landslide susceptibility map of the region may be used as a vital tool for planning landslide mitigation activities in the wake of recurrent EREs and associated landslide occurrences.

Forest Fire Dynamics in Nepal’s Mid-hills: Insights from Spatial Analysis and Risk Mapping of Doti District

Forest fires have significantly contributed to forest degradation and pollution all over Nepal. Despite their high severity, limited studies have been conducted on the spatial-temporal analysis and risk mapping of these fires especially in the Mid-hill region. This study aims to fill this gap by analyzing Visible Infrared Imaging Radiometer Suite (VIIRS) data from 2012 to 2022, along with satellite imagery, using remote sensing and geographic information systems (GIS) technology. Nine variables, including land class, distance to roads, proximity to settlements, temperature, wind speed, precipitation, slope, aspect, and elevation, were utilized to identify forest fire patterns and create a fire risk map. A multi-parametric hierarchical weighted index model was employed, with multicollinearity checked (VIF<2) to ensure model accuracy and validated by Area Under Curve (AUC=0.787). The study revealed an increasing trend of forest fires, particularly during March to May, in broad-leaved forests near human interference. Out of the total forested area of 1447.58 km2, 42.9%, 46.03%, and 11.07% were classified under high, moderate, and low-risk zones, respectively. The study emphasizes the recurring forest fire problem in often-neglected Mid-hill districts and underscores the need to prioritize them in future strategies.

Modeling and Mapping of Groundwater Potential Zones of the Shewasoor Sub-Basin Using Analytical Hierarchy Process, RS and GIS Techniques in Kirkuk, Northeastern Iraq

Groundwater is considered one of the most vital natural resources for sustaining life. The demand for water in the Shewasoor sub-basin is constantly increasing due to formidable population growth and the development of human activities. Besides, groundwater is scarce due to climatic changes in arid and semi-arid. This study aims to determine spatial distribution of groundwater potential in the Shewasoor sub-basin. This study relied on seven layers (geology, slope, elevation, lineament, drainage density, soil, and land use/land covers) using geographic information systems, remote sensing, and applying the analytical hierarchy process method after determining the weights for each parameter by a multi-criteria decision analysis; to model the groundwater potential map in the Shewasoor sub-basin. The result appeared as a map of groundwater potential categorized into five zones. The majority of the sub-basin (61.8 km2) falls under a very high-high groundwater potential zone, which distributes over an area of elevations, drainage density, and slopes low of the Bai-Hassan Formation; from the center towards the north of the sub-basin. The moderate groundwater potential zone (47.6 km2) mainly encompasses an area of elevations and slopes moderate to the Bai-Hassan formation. About 49.6 km2 is a very low to low groundwater potential zone, mainly found over the area of the elevations and slopes high within the Mukdadiyah Formation east of the sub-basin; in addition to, low groundwater potential within the Bai-Hassan Formation in the south, west, and some part center of the sub-basin due of the elevations and slopes high.

Evaluation of antimicrobial activity of a herbal mixture

Due to adverse effects of using allopathic medicines, the use and search for pharmaceuticals made from plants has increased recently. A mixture of herbal extracts known as “Chukku Kashaya” is widely used as home remedy in Kerala for respiratory disorders. Additionally, it relieves cold and fever symptoms. The present investigation focused on evaluating the antimicrobial activity of methanolic extracts obtained by soxhlet extraction of leaves of Ocimum tenuiflorum and Plectranthus amboinicus and fruits of Piper nigrum and rhizome of Zingiber officinalae and their combination in equal ratios and their activity was determined using agar well diffusion method against Staphylococcus aureus (gram positive), Klebsiella pneumoniae (gram negative), and Pseudomonas aeruginosae (gram negative). Streptomycin was used as positive control. Zingiber officinalae showed maximum zone of inhibition against all the bacteria and herbal mixture showed moderate zone of inhibition. The mixture was more active than Ocimum tenuiflorum , Piper nigrum and Plectranthus amboinicus. Staphylococcus aureus was shown to be the most sensitive to all the extracts and herbal mixtures, whereas Klebsiella pneumoniae showed the least activity. Though Z.officinalae has higher antimicrobial activity, there is limited literature support to prove its activity against fever, cold and other symptoms of respiratory tract infections. Z.officinalae is mainly used for GI related disorders. This herbal blend is more efficient because it includes of O.tenuiflorum : having antipyretic, analgesic and voice improving activity ; P.amboinicus: providing relief from cough, asthma, bronchitis and other symptoms of respiratory tract infections; P. nigrum which can improve appetite and digestion .