Search results for: catchment forest restoration

Authors: Abeer A. Aljohani

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COVID-19 virus spread has been one of the extreme pandemics across the globe. It is also referred to as coronavirus, which is a contagious disease that continuously mutates into numerous variants. Currently, the B.1.1.529 variant labeled as omicron is detected in South Africa. The huge spread of COVID-19 disease has affected several lives and has surged exceptional pressure on the healthcare systems worldwide. Also, everyday life and the global economy have been at stake. This research aims to predict COVID-19 disease in its initial stage to reduce the death count. Machine learning (ML) is nowadays used in almost every area. Numerous COVID-19 cases have produced a huge burden on the hospitals as well as health workers. To reduce this burden, this paper predicts COVID-19 disease is based on the symptoms and medical history of the patient. This research presents a unique architecture for COVID-19 detection using ML techniques integrated with feature dimensionality reduction. This paper uses a standard UCI dataset for predicting COVID-19 disease. This dataset comprises symptoms of 5434 patients. This paper also compares several supervised ML techniques to the presented architecture. The architecture has also utilized 10-fold cross validation process for generalization and the principal component analysis (PCA) technique for feature reduction. Standard parameters are used to evaluate the proposed architecture including F1-Score, precision, accuracy, recall, receiver operating characteristic (ROC), and area under curve (AUC). The results depict that decision tree, random forest, and neural networks outperform all other state-of-the-art ML techniques. This achieved result can help effectively in identifying COVID-19 infection cases.

Keywords: supervised machine learning, COVID-19 prediction, healthcare analytics, random forest, neural network

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Authors: M. Mohan, J. P. Roise, G. P. Catts

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Despite living in an era where conservation zones are de-facto the central element in any sustainable wildlife management strategy, we still find ourselves grappling with several pareto-optimal situations regarding resource allocation and area distribution for the same. In this paper, a multi-objective decision making (MODM) model is presented to answer the question of whether or not we can establish mutual relationships between these contradicting objectives. For our study, we considered a Red-cockaded woodpecker (Picoides borealis) habitat conservation scenario in the coastal plain of North Carolina, USA. Red-cockaded woodpecker (RCW) is a non-migratory territorial bird that excavates cavities in living pine trees for roosting and nesting. The RCW groups nest in an aggregation of cavity trees called ‘cluster’ and for our model we use the number of clusters to be established as a measure of evaluating the size of conservation zone required. The case study is formulated as a linear programming problem and the objective function optimises the Red-cockaded woodpecker clusters, carbon retention rate, biofuel, public safety and Net Present Value (NPV) of the forest. We studied the variation of individual objectives with respect to the amount of area available and plotted a two dimensional dynamic graph after establishing interrelations between the objectives. We further explore the concept of interdependency by integrating the MODM model with GIS, and derive a raster file representing carbon distribution from the existing forest dataset. Model results demonstrate the applicability of interdependency from both linear and spatial perspectives, and suggest that this approach holds immense potential for enhancing environmental investment decision making in future.

Keywords: conservation, interdependency, multi-objective decision making, red-cockaded woodpecker

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Authors: Priya Madhuri P., Kamini J., Jayanthi S. C.

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Rooftop rainwater harvesting is a crucial practice to address water scarcity, pollution, and flooding. This study aims to estimate the rooftop rainwater harvesting potential (RRWHP) for Suryapet, India, using building footprint data and average rainfall data. The study uses rainfall grids from the India Meteorological Department and Very High Resolution Satellite data to capture building footprints and calculate the RRWHP for a five-year period (2015-2020). Buildings with an area of more than 20 square meters are considered. A conservative figure of 60% efficiency for the catchment area is considered. The study chose 31,770 buildings with an effective rooftop area of around 1.56 sq. km. The city experiences annual rainfall values ranging from 791 mm to 987 mm, with August being the wettest month. The projected annual rooftop rainwater harvesting potential is 1.3 billion litres.

Keywords: buildings, rooftop rainwater harvesting, sustainable water management, urban

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Authors: Richard G. Boakye, Dara A Stanley, Mathavan Vickneswaran, Blanaid White

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The cultivation of cocoa (Theobroma cocoa), an important cash crop that contributes immensely towards the economic growth of several Western African countries, depends almost entirely on pesticide application owing to the plant’s vulnerability to pest and disease attacks. However, the extent to which pesticides inputted for cocoa cultivation impact bees and bee products has rarely received attention in research. Through this study, the effects of pesticides applied for cocoa cultivation on honey in Ghana were examined by evaluating honey samples from cocoa and forest ecosystems in Ghana. An analysis of five honey samples from each land use type confirmed pesticide contaminants from these land use types at measured concentrations for acetamiprid (0.051mg/kg); imidacloprid (0.004-0.02 mg/kg), thiamethoxam (0.013-0.017 mg/kg); indoxacarb (0.004-0.045 mg/kg) and sulfoxaflor (0.004-0.026 mg/kg). None of the observed pesticide concentrations exceeded EU maximum residue levels, indicating no compromise of the honey quality for human consumption. However, from the results, it could be inferred that toxic effects on bees may not be ruled out because observed concentrations largely exceeded the threshold of 0.001 mg/kg at which sublethal effects on bees have previously been reported. One of the most remarkable results to emerge from this study is the detection of imidacloprid in all honey samples analyzed, with sulfoxaflor and thiamethoxam also being detected in 93% and 73% of the honey samples, respectively. This suggests the probable prevalence of pesticide use in the landscape. However, the conclusions reached in this study should be interpreted within the scope of pesticide applications within Bia West District and not necessarily extended to other cocoa-producing districts in Ghana. Future studies should therefore include multiple cocoa-growing districts and other non-cocoa farming landscapes. Such an approach can give a broader outlook on pesticide residues in honey produced in Ghana.

Keywords: honey, cocoa, pesticides, bees, land use, landscape, residues, Ghana

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Authors: Nada Al-Qallaf, Aisha Al-Barood, Djamel Lekmine, Srinivasan Vedhapuri

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Kuwait Oil Company (KOC) under the supervision of Kuwait National Focal Point (KNFP) is planning to remediate 26 million (M) m3 of oil-contaminated soil in oil fields of Kuwait as a direct and indirect fallout of the Gulf War during 1990-1991. This project is funded by the United Nations Compensation Commission (UNCC) under the Kuwait Environmental Remediation Program (KERP). Oil-contamination of the soil occurred due to the destruction of the oil wells and spilled crude oil across the land surface and created ‘oil lakes’ in low lying land. Aerial fall-out from oil spray and combustion products from oil fires combined with the sand and gravel on the ground surface to form a layer of hardened ‘Tarcrete’. The unique fresh groundwater lenses present in the Raudhatain and Sabriya subsurface areas had been impacted by the discharge and/or spills of dissolved petroleum constituents. These fresh groundwater aquifers were used for drinking water purposes until 1990, prior to invasion. This has significantly damages altered the landscape, ecology and habitat of the flora and fauna and in Kuwait Desert. Under KERP, KOC is fully responsible for the planning and execution of the remediation and restoration projects in KOC oil fields. After the initial recommendation of UNCC to construct engineered landfills for containment and disposal of heavily contaminated soils, two landfills were constructed, one in North Kuwait and another in South East Kuwait of capacity 1.7 million m3 and 0.5 million m3 respectively. KOC further developed the Total Remediation Strategy in conjunction with KNFP and has obtained UNCC approval. The TRS comprises of elements such as Risk Based Approach (RBA), Bioremediation of low Contaminated Soil levels, Remediation Treatment Technologies, Sludge Disposal via Beneficial Recycling or Re-use and Engineered landfills for Containment of untreatable materials. Risk Based Assessment as a key component to avoid any unnecessary remedial works, where it can be demonstrated that human health and the environment are sufficiently protected in the absence of active remediation. This study demonstrates on the risks of tarcrete materials spread over areas 20 Km2 on the fresh Ground water lenses/catchment located beneath the Sabriyah and Raudhatain oil fields in North Kuwait. KOC’s primary objective is to provide justification of using RBA, to support a case with the Kuwait regulators to leave the tarcrete material in place, rather than seek to undertake large-scale removal and remediation. The large-scale coverage of the tarcrete in the oil fields and perception that the residual contamination associated with this source is present in an environmentally sensitive area essentially in ground water resource. As part of this assessment, conceptual site model (CSM) and complete risk-based and fate and transport modelling was carried out which includes derivation of site-specific assessment criteria (SSAC) and quantification of risk to identified waters resource receptors posed by tarcrete impacted areas. The outcome of this assessment was determined that the residual tarcrete deposits across the site area shall not create risks to fresh groundwater resources and the remedial action to remove and remediate the surficial tarcrete deposits is not warranted.

Keywords: conceptual site model, fresh groundwater, oil-contaminated soil, tarcrete, risk based assessment

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Authors: P. J. Kagosi, M. Mndolwa, E. Japhate

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The study was conducted to communities adjacent MNR, Lushoto district, Tanzania. The MNR is one of the nine nature reserves in the Eastern Arc Mountains of Tanzania with an area of 8,700ha with high biological diversity. However, biodiversity in MNR have been threatened by increasing human activities for livelihood in 1970s. The AF systems in the study area was practised since 1980s however, no study was conducted on AF impacts. This paper presents the influence of AF on livelihood of communities adjacent MNR and biodiversity conservation. Qualitative and quantitative data were collected using socio-economic survey and botanical surveys. Data were analysed using Statistical Packages for Social Sciences and content analysis. The study found that in 1970s free livestock grazing caused considerable surface runoff, soil erosion and reduction of crop production. Since 1980s, the study area received various interventions based on the land conservations and improved livelihood through practising AF systems. It was further found that the AF farming improved crop productivity, reduced soil erosion, increased firewood (80.2%) and other forest products availability and AF encouraged community members practicing indoor livestock keeping.The dominant agroforestry tree found in the study area is grevillea reported by 74.1% of respondents planting an average of 40 trees. The study found that the AF reduced pressure to MNR as forest products and fodders were obtained from community's farms in turn, currently water flow from MNR has been increased. Thus AF products support livelihood needs and conserve biodiversity. The study recommends continuity education on new AF technology packages.

Keywords: impact of agroforestry, biodiversity management, communities’ livelihoods, Magamba nature reserve

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Authors: Tsegaw Abebe, Temesgen Abebe

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Land degradation is one of a serious environmental challenge in Ethiopia and is one of the major underlying causes for declining agricultural productivity. The Ethiopia government realized the significance of environmental restoration specifically on deforested and degraded land after the 1973 and 1984/85 major famines that struck the country. Among the various conservation strategies, the establishment of area exclosures have been regarded as an effective response to halt and reverse the problems of land degradation. There are limited studies in Ethiopia dealing how the conversion of free grazing lands and degraded lands by closures increase biomass accumulation. However, these studies are not sufficient to conclude about the strength of area closures to restore degraded vegetations at the diverse agro-ecological condition. The overall objective of this study was, therefore, to assess and evaluate the usefulness of area closure technique in enhancing rehabilitation of degraded ecosystem and thereby increase the natural capital in the study site (southern Ethiopia). Woody plant species were collected from area exclosure for eight year and adjacent degraded land with similar landscape positions using systematic sampling plot design technique. Woody species diversity was determined by Shannon diversity. Comparative assessment result of woody plant species analysis showed that the density of woody species in the exclosure and degraded site were 778 and 222 individuals per hectare, respectively. A total of 16 woody species, representing 12 families were recorded in the study site. Out of the 12 families, all were recorded in the exclosure while 5 were recorded in the degraded site. Out of the 16 species, 15 were recorded in the exclosure while six were in the degraded site. A total of 10 species were recorded in the exclosure, which were absent in the degraded site. Similarly, one species was recorded in the degraded site which was not present in the exclosure. The results showed that protecting of degraded site from human and animal disturbances promotes woody plant species regenerations and productivity Apart from increasing woody plant species, the local communities have benefited from the exclosure in the form of both products (grass harvesting) and services (ecological). Due to this reason the local communities have positive attitudes and contribute a lot for the success of enclosures in the study site. The present study clearly showed that area closure interventions should be oriented towards managing and improving the productivity of the degraded land, in such a way that both the need for conservation of biodiversity and environmental sustainability, and the demands of the local people for biomass resources can be achieved.

Keywords: degraded land, exclosure, land restoration, woody vegetation

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Authors: Maffo Maffo Nicole Liliane, Mounmeni Kpoumie Hubert, Mbaire Matindje Karl Marx, Zapfack Louis

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Sacred forests play a valuable role in conserving local biodiversity and provide numerous ecosystem services in Cameroon. The study was carried out in the sacred forests of Bandrefam and Batoufam (western Cameroon). The aim was to estimate the diversity of woody species, carbon stocks and degradation factors in these sacred forests. The floristic inventory was carried out in plots measuring 25m × 25m for trees with diameters greater than 10 cm and 5m × 5m for trees with diameters less than 10 cm. Carbon stocks were estimated using the non-destructive method and the allometric equations. Data on degradation factors were collected using semi-structured surveys in the Bandrefam and Batoufam neighborhoods. The floristic inventory identified 65 species divided into 57 genera and 30 families in the Bandrefam Sacred Forest and 45 species divided into 42 genera and 27 families in the Batoufam Sacres Forest. The families common to both sacred forests are as follows: Phyllanthaceae, Fabaceae, Moraceae, Lamiaceae, Malvaceae, Rubiaceae, Meliaceae, Anacardiaceae, and Sapindaceae. Three genera are present in both sites. These are: Albizia, Macaranga, Trichillia. In addition, there are 27 species in common between the two sites. The total carbon stock is 469.26 tC/ha at Batoufam and 291.41 tC/ha at Bandrefam. The economic value varies between 15 823 877.05 fcfa at Batoufam and 9 825 530.528 fcfa at Bandrefam. The study shows that despite the sacred nature of these forests, they are subject to degradation factors such as bushfires (35.42 %), the creation of plantations (23.96 %), illegal timber exploitation (21.88 %), young people's lack of interest in the notion of conservation (9.38 %), climate change (7.29 %) and growing urbanization (2.08 %). These factors threaten biodiversity and reduce carbon storage in these forests.

Keywords: sacred forests, degradation factors, carbon stocks, semi-structured surveys

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Authors: Younmin Shin, Jin Kyu Kim, Mirim Jin, Jeong June Choi

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Demilitarized Zone (DMZ) is a peace region located between South and North Korea border to avoid accidental armed conflict. Because human accessing to the area was forced to be prohibited for more than 60 years, DMZ is one of the cleanest land keeping wild lives as nature itself in South Korea. In this study, we evaluated the biological efficacies of plants (SS, PC, and AR) inhabiting in DMZ for the development of functional cosmetics. First, we tested the cytotoxicity of plant extracts in keratinocyte and melanocyte, which are the major cell components of skin. By 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay with the cell lines, we determined the safety concentrations of the extracts for the efficacy tests. Next, we assessed the anti-wrinkle cosmetic function of SS by demonstrating that SS treatment decreased the expression of Matrix metalloproteinase-1 (MMP-1) in UV-irradiated keratinocytes via real-time PCR. The suppressive effect of SS was greatly potentiated by combination with other DMZ-inhabiting plants, PC and AR. The expression of tyrosinase, which is one the main enzyme that producing melanin in melanocyte, was also down-regulated by the DMZ-inhabiting SS extract. Wound healing activity was also investigated by in vitro test with HaCat cell line, a human fibroblast cell line. All the natural materials extracted form DMZ habiting plants accelerated the recovery of the cells. These results suggested that DMZ is a treasure island of functional plants and DMZ-inhabiting natural products are warranted to develop functional cosmetic materials. This study was carried out with the support of R&D Program for Forest Science Technology (Project No. 2017027A00-1819-BA01) provided by Korea Forest Service (Korea Forestry Promotion Institute).

Keywords: anti-wrinkle, Demilitarized Zone, functional cosmetics, whitening

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Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Properly selecting the most suitable and effective geostatistics method in the parameterization step of groundwater modeling is critical to attain a satisfactory model. In this paper, two geostatistics methods, i.e., Grid-Based Pilot Point (GB-PP) and Head-Zonation Based Pilot Point (HZB-PP) methods, were applied in an eogenetic karst catchment and compared using as model performances and computation time the criteria. Overall, the results show that appropriate selection of method is substantial in the parameterization of physically-based groundwater models, as it influences both the accuracy and simulation times. It was found that GB-PP method performed comparably superior to HZB-PP method. However, reflecting its model performances, HZB-PP method is promising for further application in groundwater modeling.

Keywords: groundwater model, geostatistics, pilot point, parameterization step

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Dessie Tegegne Tibebu, Kirsi Mononen, Ari Pappinen

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In areas with forest management, agricultural, and industrial activity, sediments and biomass are accumulated in lakes through drainage system, which might be a cause for biodiversity loss and health problems. One possible solution can be utilization of lake bottom biomass and sediments for biogas production. The main objective of this study was to investigate the potentials of lake bottom materials for production of biogas by anaerobic digestion and to study the effect of pretreatment methods for feed materials on biogas yield. In order to study the potentials of biogas production lake bottom materials were collected from two sites, Likokanta and Kutunjärvi lake. Lake bottom materials were mixed with straw-horse manure to produce biogas in a laboratory scale reactor. The results indicated that highest yields of biogas values were observed when feeds were composed of 50% lake bottom materials with 50% straw horse manure mixture-while with above 50% lake bottom materials in the feed biogas production decreased. CH4 content from Likokanta lake materials with straw-horse manure and Kutunjärvi lake materials with straw-horse manure were similar values when feed consisted of 50% lake bottom materials with 50% straw horse manure mixtures. However, feeds with lake bottom materials above 50%, the CH4 concentration started to decrease, impairing gas process. Pretreatment applied on Kutunjärvi lake materials showed a slight negative effect on the biogas production and lowest CH4 concentration throughout the experiment. The average CH4 production (ml g-1 VS) from pretreated Kutunjärvi lake materials with straw horse manure (208.9 ml g-1 VS) and untreated Kutunjärvi lake materials with straw horse manure (182.2 ml g-1 VS) were markedly higher than from Likokanta lake materials with straw horse manure (157.8 ml g-1 VS). According to the experimental results, utilization of 100% lake bottom materials for biogas production is likely to be impaired negatively. In the future, further analyses to improve the biogas yields, assessment of costs and benefits is needed before utilizing lake bottom materials for the production of biogas.

Keywords: anaerobic digestion, biogas, lake bottom materials, sediments, pretreatment

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Authors: Farhan Aljuaidi

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The rapid expansion of Alkarj city, Saudi Arabia, towards the outlet of Wadi AlAin is critical for the planners and decision makers. Nowadays, two major projects such as Salman bin Abdulaziz University compound and new industrial area are developed in this flood prone area where no channels are clear and identified. The main contribution of this study is to divert the flow away from these vital projects by reconstructing new channels. To do so, Lidar data were used to generate contour lines for the actual elevation of the highways and local roads. These data were analyzed and compared to the contour lines derived from the topographical maps 1:50.000. The magnitude of the expected flow was estimated using Snyder's Model based on the morphometric data acquired by DEM of the catchment area. The results indicate that maximum discharge peak reaches 2694,3 m3/sec, the mean is 303,7 m3/sec and the minimum is 74,3 m3/sec. The runoff was estimated at 252,2. 610 m3/s, the mean is 41,5. 610 m3/s and the minimum is 12,4. 610 m3/s.

Keywords: Desert flood, Saudi Arabia, Snyder's Model, flow estimation

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Authors: Yogita Tulsian, A. Yadav

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Background: India reports 3,600 cholera cases annually. In August 2013, a cholera outbreak was reported in Jalgaon district, Maharashtra state. We sought to describe the epidemiological characteristics,identify risk factors, and recommend control measures. Methods: We collected existing stool and water testing laboratory results, and conducted a1: 1 matched case-control study. A cholera case was defined as a resident of Vishnapur or Malapur villagewith onset of acute watery diarrhea on/ after 1-July-2013. Controls were matched by age, gender and village and had not experienced any diarrhea for 3 months. We collected socio-demographic characteristics, clinical presentation, and food/travel/water exposure history and conducted conditional logistic regression. Results: Of 50 people who met the cholera case definition, 40 (80%) were from Vishnapur village and 30 (60%) were female. The median age was 8.5 years (range; 0.3-75). Twenty (45%) cases were hospitalized, twelve (60%) with severe dehydration. Three of five stool samples revealed Vibrio cholerae 01 El Tor, Ogawa and samples from 7 of 14 Vishnapur water sources contained fecal coliforms. Cases from Vishnapur were significantly more likely to drink from identified contaminated water sources (matched odds ratio (MOR) 3.5; 95% confidence interval (CI): 1-13), or from a river/canal (MOR=18.4;95%CI: 2-504). Cases from Malapur were more likely to drink from a river/canal (MOR=6.2; 95%CI: 0.6-196). Cases from both villages were significantly more likely to visit the forest (MOR 6.3; 95%CI: 2-30) or another village (MOR 3.5; 95%CI; 0.9-17). Conclusions: This outbreak was caused by Vibrio cholerae, likely through contamination of water in Vishnapur village and/or through drinking river/canal water. We recommended safe drinking water for forest visitors and all residents of these villages and use of regular water testing.

Keywords: cholera, case control study, contaminated water, river

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Talal Alharigi, Kawther Alshlash, Mariska Weijerman

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The government of Saudi Arabia has developed an ambitious “Vision 2030”, which includes a Green Initiative (i.e., the planting of 10 billion trees) and the establishment of seven Royal Reserves as protected areas that comprise 13% of the total land area. The main objective of the reserves is to restore ecosystem balance and reconnect people with nature. Two royal reserves are managed by The Imam Abdulaziz bin Mohammed Royal Reserve Development Authority, including Imam Abdulaziz bin Mohammed Royal Reserve and King Khalid Royal Reserve. The authority has developed a management plan to enhance the habitat through seed dispersal and the planting of 10 million trees, and to restock wildlife that was once abundant in these arid ecosystems (e.g., oryx, Nubian ibex, gazelles, red-necked ostrich). Expectations are that with the restoration of the native vegetation, soil condition and natural hydrologic processes will improve and lead to further enhancement of vegetation and, over time, an increase in biodiversity of flora and fauna. To evaluate the management strategies in reaching these expectations, a comprehensive monitoring and evaluation program was developed. The main objectives of this program are to (1) monitor the status and trends of indicator species, (2) improve desert ecosystem understanding, (3) assess the effects of human activities, and (4) provide science-based management recommendations. Using a random stratified survey design, a diverse suite of survey methods will be implemented, including belt and quadrant transects, camera traps, GPS tracking devices, and drones. Data will be gathered on biotic parameters (plant and animal diversity, density, and distribution) and abiotic parameters (humidity, temperature, precipitation, wind, air, soil quality, vibrations, and noise levels) to meet the goals of the monitoring program. This case study intends to provide a detailed overview of the management plan and monitoring program of two royal reserves and outlines the types of data gathered which can be made available for future research projects.

Keywords: camera traps, desert ecosystem, enhancement, GPS tracking, management evaluation, monitoring, planting, restocking, restoration

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Authors: Abdullah Alsaeed

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Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

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Authors: Mariana Volpini, Volker Bartenbach, Marcos Pinotti, Robert Riener

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Restoration of gait ability is an important task in the rehabilitation of people with neurological disorders presenting a great impact in the quality of life of an individual. Based on the motor learning concept, robotic assisted treadmill training has been introduced and found to be a feasible and promising therapeutic option in neurological rehabilitation but unfortunately it is not available for most patients in developing countries due to the high cost. This paper presents the concept of a low cost rehabilitation robot to help consolidate the robotic-assisted gait training as a reality in clinical practice in most countries. This work indicates that it is possible to build a simpler rehabilitation device respecting the physiological trajectory of the ankle.

Keywords: bioengineering, gait therapy, low cost rehabilitation robot, rehabilitation robotics

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Authors: Ombir Singh

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In spite of the religious and cultural pre-dominance of the river Ganga in the Indian ethos, fragmentation and degradation of the river continued down the ages. Recognizing the national concern on environmental degradation of the river and its basin, Ministry of Water Resources, River Development & Ganga Rejuvenation (MoWR,RD&GR), Government of India has initiated a number of pilot schemes for the rejuvenation of river Ganga under the ‘Namami Gange’ Programme. Considering the diversity, complexity, and intricacies of forest ecosystems and pivotal multiple functions performed by them and their inter-connectedness with highly dynamic river ecosystems, forestry interventions all along the river Ganga from its origin at Gaumukh, Uttarakhand to its mouth at Ganga Sagar, West Bengal has been planned by the ministry. For that Forest Research Institute (FRI) in collaboration with National Mission for Clean Ganga (NMCG) has prepared a Detailed Project Report (DPR) on Forestry Interventions for Ganga. The Institute has adopted an extensive consultative process at the national and state levels involving various stakeholders relevant in the context of river Ganga and employed a science-based methodology including use of remote sensing and GIS technologies for geo-spatial analysis, modeling and prioritization of sites for proposed forestation and conservation interventions. Four sets of field data formats were designed to obtain the field based information for forestry interventions, mainly plantations and conservation measures along the river course. In response, five stakeholder State Forest Departments had submitted more than 8,000 data sheets to the Institute. In order to analyze a voluminous field data received from five participating states, the Institute also developed a software to collate, analyze and generation of reports on proposed sites in Ganga basin. FRI has developed potential plantation and treatment models for the proposed forestry and other conservation measures in major three types of landscape components visualized in the Ganga riverscape. These are: (i) Natural, (ii) Agriculture, and (iii) Urban Landscapes. Suggested plantation models broadly varied for the Uttarakhand Himalayas and the Ganga Plains in five participating states. Besides extensive plantations in three type of landscapes within the riverscape, various conservation measures such as soil and water conservation, riparian wildlife management, wetland management, bioremediation and bio-filtration and supporting activities such as policy and law intervention, concurrent research, monitoring and evaluation, and mass awareness campaigns have been envisioned in the DPR. The DPR also incorporates the details of the implementation mechanism, budget provisioned for different components of the project besides allocation of budget state-wise to five implementing agencies, national partner organizations and the Nodal Ministry.

Keywords: conservation, Ganga, river, water, forestry interventions

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Authors: Seung Ho Park, Young Su Moon, Nam Ik Cho

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We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods.

Keywords: compression artifact reduction, deblocking, image denoising, image restoration

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Min Ho Kwon, Woo Young Jung, Hyun Su Seo

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A Polymer Cement Mortar (PCM) has been widely used as the material of repair and restoration work for concrete structure; however a PCM usually induces an environmental pollutant. Therefore, there is a need to develop PCM which is less impact to environments. Usually, UM resin is known to be harmless to the environment. Accordingly, in this paper, the properties of the PCM using UM resin were studied. The general cement mortar and UM resin was mixed in the specified ratio. A certain percentage of PVA fibers, steel fibers and mixed fibers (PVA fiber and steel fiber) were added to enhance the flexural strength. The flexural tests were performed in order to investigate the flexural strength of each PCM. Experimental results showed that the strength of proposed PCM using UM resin is improved when they are compared with general cement mortar.

Keywords: polymer cement mortar, UM resin, compressive strength, PVA fiber, steel fiber

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Authors: Luis M. Ribeiro, Jorge Raposo, Ricardo Oliveira, David Caballero, Domingos X. Viegas

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Under the scope of European project WUIWATCH a set of experimental tests on house vulnerability was performed in order to assess the resistance of selected house components during the passage of a forest fire. Among the individual elements most affected by the passage of a wildfire the windows are the ones with greater exposure. In this sense, a set of exploratory experimental tests was designed to assess some particular aspects related to the vulnerability of windows and blinds. At the same time, the importance of leaving them closed (as well as the doors inside a house) during a wild fire was explored in order to give some scientific background to guidelines for homeowners. Three sets of tests were performed: 1. Windows and blinds resistance to heat. Three types of protective blinds were tested (aluminium, PVC and wood) on 2 types of windows (single and double pane). The objective was to assess the structures resistance. 2. The influence of air flow on the transport of burning embers inside a house. A room was built to scale, and placed inside a wind tunnel, with one window and one door on opposite sides. The objective was to assess the importance of leaving an inside door opened on the probability of burning embers entering the room. 3. The influence of the dimension of openings on a window or door related to the probability of ignition inside a house. The objective was to assess the influence of different window openings in relation to the amount of burning particles that can enter a house. The main results were: 1. The purely radiative heat source provides 1.5 KW/m2 of heat impact in the structure, while the real fire generates 10 Kw/m2. When protected by the blind, the single pane window reaches 30ºC on both sides, and the double pane window has a differential of 10º from the side facing the heat (30ºC) and the opposite side (40ºC). Unprotected window constantly increases temperature until the end of the test. Window blinds reach considerably higher temperatures. PVC loses its consistency above 150ºC and melts. 2. Leaving the inside door closed results in a positive pressure differential of +1Pa from the outside to the inside, inhibiting the air flow. Opening the door in half or full reverts the pressure differential to -6 and -8 times respectively, favouring the air flow from the outside to the inside. The number of particles entering the house follows the same tendency. 3. As the bottom opening in a window increases from 0,5 cm to 4 cm the number of particles that enter the house per second also increases greatly. From 5 cm until 80cm there is no substantial increase in the number of entering particles. This set of exploratory tests proved to be an added value in supporting guidelines for home owners, regarding self-protection in WUI areas.

Keywords: forest fire, wildland urban interface, house vulnerability, house protective elements

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Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: Surachart Koyadun

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Currently, Plasmodium knowlesi malaria has spread to almost all countries in Southeast Asia. This research aimed to 1) describe the epidemiology of Plasmodium knowlesi malaria, 2) examine the clinical symptoms of P. knowlesi malaria patients 3) analyze the ecology, animal reservoir and entomology of P. knowlesi malaria. 4) summarize the diagnosis, blood parasites, and treatment of P. knowlesi malaria. The study design was a case report combined with retrospective descriptive survey research. A total of 34 study subjects were patients with a confirmed diagnosis of P. knowlesi malaria who received treatment at hospitals and vector-borne disease control units in Songkhla Province during 2021 – 2022. The results of the epidemiological study unveiled the majority of the samples were male, had a history of staying overnight in the forest before becoming sick, the source of the infection was in the forest, and the season during which they were sick was mostly summer. The average length of time from the onset of illness until receiving a blood test was 3.8 days. The average length of hospital stay was 4 days. Patients were treated with Chloroquine Phosphate, Primaquine, Artesunate, Quinine, and Dihydroartemisinin-piperaquine (40 mg DHA-320 mg PPQ). One death was seen in 34 P. knowlesi malaria patients. All remaining patients recovered and responded to treatment. All symptoms improved after drug administration. No treatment failures were found. Analyses of ecological, zoonotic and entomological data revealed an association between infected patients and forested, monkey-hosted and mosquito-transmitted areas. The recommendation from this study was that the Polymerase Chain Reaction (PCR) method should be used in conjunction with the Thick/Thin Film test and blood parasite test (Parasitaemia) for the specificity of the infection, accuracy of diagnosis, leading to treatment of disease in a timely manner and be effective in disease control.

Keywords: human malaria, Plasmodium knowlesi, zoonotic disease, diagnosis and treatment, epidemiology, ecology

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Authors: Negin Binesh, Mohammad Hossein Niksokhan, Amin Sarang

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Best Management Practices (BMPs) are considered as one of the most important structural adaptive measures to climate change and urban development challenges in recent decades. However, not every location is appropriate for applying BMPs in the watersheds. In this paper, location prioritization of two kinds of BMPs was done: Pourous pavement and Detention pond. West Flood-Diversion (WFD) catchment in northern parts of Tehran, Iran, was considered as the case study. The methodology includes integrating the results of Storm Water Management Model (SWMM) into Fuzzy Analytic Hierarchy Process (FAHP) method using Geographic Information System (GIS). The results indicate that mostly suburban areas of the watershed in northern parts are appropriate for applying detention basin, and downstream high-density urban areas are more suitable for using permeable pavement.

Keywords: adaptive measures, BMPs, location prioritization, urban flooding

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Authors: Yechan Kim, Bonhyuk Ku, Minkyung Jung, Hyoungku Kang

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This study presents the remanufacturing of a 25kV gas insulated switchgear (GIS) that operated indoors for 27 years before being decommissioned due to aging. The research involved a detailed process of dismantling, visual inspection, component-wise examination, and various testing methodologies to assess the equipment's condition. The focus was on evaluating the GIS's integrity and feasibility for remanufacturing. The results highlight the potential of remanufacturing in extending the life of electrical power equipment, offering insights into the best practices, challenges, and technical considerations of such an undertaking. This contributes to a sustainable approach in the power industry, emphasizing the reuse and restoration of aging equipment.

Keywords: remanufacturing, dismantling, gas insulated switchgear, sustainability, life extension

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Authors: Lydia Murugi Mugendi

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The promotion of tree growing as a lucrative enterprise is the focus of this paper as management practices have shifted focus from protection of natural forest resources to community/government partnerships with the aim of resource conservation, management and increase of on-farm tree growing. Using KEFRI as (the source) of information pertaining Melia volkensii (the medium or message) being transferred, this paper investigates the current perception towards forestry and the behavioural attitudes of recipients of forest intervention activities. The two objectives explored in this paper are to find out the level of adoption of Mukau in Kitui, Kibwezi and Samburu/Taru and secondly, to find out the characteristics of the adoption process between Kitui, Kibwezi and Samburu/Taru. The methodologies used during data collection were participatory rural appraisal tools in conjunction with the social survey questionnaires. Simple random sampling and snowball sampling were used to identify respondents within the three target sites and analysis was done using SPSS. Results of the study of indicating that adoption rates of the Mukau in Samburu/Taru, where forestry-related activities were introduced within the past one decade had significantly increase despite initial resistance. The other areas, which had benefited from numerous decades of intense forestry extension projects and activities, indicated a decline in re-adoption rates of Mukau as an enterprise. This study has brought out the reality of adoption trends and state of Mukau population within the three counties while providing a glimpse towards the communities’ perception in regards to adoption of forestry and other environmental innovations. The outcome of the study is to provide a guideline for extension/ dissemination officers in KEFRI and related stakeholders to promote seamless cohesive interaction between the recipient communities of the proposed interventions.

Keywords: adoption, innovation, enterprise, extension, DOI Theory

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Authors: Stephen Dankwa, Zheng Wenfeng, Xiaolu Li

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Climate change is recently gaining the attention of many countries across the world. Climate change, which is also known as global warming, referring to the increasing in average surface temperature has been a concern to the Environmental Protection Agency of Ghana. Recently, Ghana has become vulnerable to the effect of the climate change as a result of the dependence of the majority of the population on agriculture. The clearing down of trees to grow crops and burning of charcoal in the country has been a contributing factor to the rise in temperature nowadays in the country as a result of releasing of carbon dioxide and greenhouse gases into the air. Recently, petroleum stations across the cities have been on fire due to this climate changes and which have position Ghana in a way not able to withstand this climate event. As a result, the significant of this research paper is to project how the rise in the average surface temperature will be like at the end of the mid-21st century when agriculture and deforestation are allowed to continue for some time in the country. This study uses the Coupled Modeled Intercomparison Project phase 5 (CMIP5) experiment RCP 8.5 model output data to monitor the future climate changes from 2041-2050, at the end of the mid-21st century over the ten (10) major cities (Accra, Bolgatanga, Cape Coast, Koforidua, Kumasi, Sekondi-Takoradi, Sunyani, Ho, Tamale, Wa) in Ghana. In the models, Support Vector Machine and Random forest, where the cities as a function of heat wave metrics (minimum temperature, maximum temperature, mean temperature, heat wave duration and number of heat waves) assisted to provide more than 50% accuracy to predict and monitor the pattern of the surface air temperature. The findings identified were that the near-surface air temperature will rise between 1°C-2°C (degrees Celsius) over the coastal cities (Accra, Cape Coast, Sekondi-Takoradi). The temperature over Kumasi, Ho and Sunyani by the end of 2050 will rise by 1°C. In Koforidua, it will rise between 1°C-2°C. The temperature will rise in Bolgatanga, Tamale and Wa by 0.5°C by 2050. This indicates how the coastal and the southern part of the country are becoming hotter compared with the north, even though the northern part is the hottest. During heat waves from 2041-2050, Bolgatanga, Tamale, and Wa will experience the highest mean daily air temperature between 34°C-36°C. Kumasi, Koforidua, and Sunyani will experience about 34°C. The coastal cities (Accra, Cape Coast, Sekondi-Takoradi) will experience below 32°C. Even though, the coastal cities will experience the lowest mean temperature, they will have the highest number of heat waves about 62. Majority of the heat waves will last between 2 to 10 days with the maximum 30 days. The surface temperature will continue to rise by the end of the mid-21st century (2041-2050) over the major cities in Ghana and so needs to be addressed to the Environmental Protection Agency in Ghana in order to mitigate this problem.

Keywords: climate changes, CMIP5, Ghana, heat waves, random forest, SVM

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Authors: Saloni Khandelwal

Abstract:

The Aravalli hills are one of the oldest and most distinctive mountain chains of peninsular India spanning in around 692 Km. More than 60% of it falls in the state of Rajasthan and influences ecological equilibrium in about 30% of the state. Because of natural and human-induced activities, physical gaps in the Aravallis are increasing, new gaps are coming up, and its physical structure is changing. There are no strict regulations to protect and monitor the Aravallis and no comprehensive research and study has been done for the enhancement of ecosystem functions of these ranges. Through this study, various factors leading to Aravalli’s degradation are identified and its impacts on selected areas are analyzed. A literature study is done to identify factors responsible for the degradation. To understand the severity of the problem at the lowest level, two tehsils from different districts in Rajasthan, which are the most affected due to illegal mining and increasing physical gaps are selected for the study. Case-1 of three-gram panchayats in Kishangarh Tehsil of Ajmer district focuses on the expanding physical gaps in the Aravalli range, and case-2 of three-gram panchayats in Tijara Tehsil of Alwar district focuses on increasing illegal mining in the Aravalli range. For measuring the degradation, physical, biological and social indicators are identified through literature review and for both the cases analysis is done on the basis of these indicators. Primary survey and focus group discussions are done with villagers, mining owners, illegal miners, and various government officials to understand dependency of people on the Aravalli and its importance to them along with the impact of degradation on their livelihood and environment. From the analysis, it has been found that green cover is continuously decreasing in both cases, dense forest areas do not exist now, the groundwater table is depleting at a very fast rate, soil is losing its moisture resulting in low yield and shift in agriculture. Wild animals which were easily seen earlier are now extinct. Cattles of villagers are dependent on the forest area in the Aravalli range for food, but with a decrease in fodder, their cattle numbers are decreasing. There is a decrease in agricultural land and an increase in scrub and salt-affected land. Analysis of various national and state programmes, acts which were passed to conserve biodiversity has been done showing that none of them is helping much to protect the Aravalli. For conserving the Aravalli and its forest areas, regional level and local level initiatives are required and are proposed in this study. This study is an attempt to formulate conservation and management strategies for the Aravalli range. These strategies will help in improving biodiversity which can lead to the revival of its ecosystem functions. It will also help in curbing the pollution at the regional and local level. All this will lead to the sustainable development of the region.

Keywords: Aravalli, ecosystem, LULC, Rajasthan

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