Search results for: forest soil

Authors: Zaenal Mutaqin

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The level of erosion that occurs in the upsteam watersheed will lead to limited infiltrattion, land degradation and river trivialisation and estuaries in the body. One of the watesheed that has been degraded caused by using land is the DA Ci Liwung Upstream. The high degradation that occurs in the DA Ci Liwung upstream is indicated by the hugher rate of erosion on the region, especially in the area of agriculture. In this case, agriculture cultivation intent to the agricultural land that has been applied conservation techniques. This study is applied to determine the quantity of erosion by reviewing Hidrologic Response Unit (HRU) in agricuktural cultivation land which is contained in DA Ci Liwung upstream by using the Soil and Water Assessmen Tool (SWAT). Conservation techniques applied are terracing, agroforestry and gulud terrace. It was concluded that agroforestry conservation techniques show the best value of erosion (lowest) compared with other conservation techniques with the contribution of erosion of 25.22 tonnes/ha/year. The results of the calibration between the discharge flow models with the observation that R²=0.9014 and NS=0.79 indicates that this model is acceptable and feasible applied to the Ci Liwung Hulu watershed.

Keywords: conservation, erosion, SWAT analysis, watersheed

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Authors: Meera A. Albloushi, Adel B. Gougam

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The development in the field of piezoelectrics has led to a renewed interest in ZnO nanowires (NWs) as a promising material in the nanogenerator devices category. It can be used as a power source for self-powered electronic systems with higher density, higher efficiency, longer lifetime, as well as lower cost of fabrication. Highly aligned ZnO nanowires seem to exhibit a higher performance compared with nonaligned ones. The purpose of this study was to develop ZnO nanowires and to investigate their electrical and chemical properties for various applications. They were grown on silicon (100) and glass substrates. We have used a low temperature and non-hazardous method: aqueous chemical growth (ACG). ZnO (non-doped) and AZO (Aluminum doped) seed layers were deposited using RF magnetron sputteringunder Argon pressure of 3 mTorr and deposition power of 180 W, the times of growth were selected to obtain thicknesses in the range of 30 to 125 nm. Some of the films were subsequently annealed. The substrates were immersed tilted in an equimolar solution composed of zinc nitrate and hexamine (HMTA) of 0.02 M and 0.05 M in the temperature range of 80 to 90 ᵒC for 1.5 to 2 hours. The X-ray diffractometer shows strong peaks at 2Ө = 34.2ᵒ of ZnO films which indicates that the films have a preferred c-axis wurtzite hexagonal (002) orientation. The surface morphology of the films is investigated by atomic force microscope (AFM) which proved the uniformity of the film since the roughness is within 5 nm range. The scanning electron microscopes(SEM) (Quanta FEG 250, Quanta 3D FEG, Nova NanoSEM 650) are used to characterize both ZnO film and NWs. SEM images show forest of ZnO NWs grown vertically and have a range of length up to 2000 nm and diameter of 20-300 nm. The SEM images prove that the role of the seed layer is to enhance the vertical alignment of ZnO NWs at the pH solution of 5-6. Also electrical and optical properties of the NWs are carried out using Electrical Force Microscopy (EFM). After growing the ZnO NWs, developing the nano-generator is the second step of this study in order to determine the energy conversion efficiency and the power output.

Keywords: ZnO nanowires(NWs), aqueous chemical growth (ACG), piezoelectric NWs, harvesting enery

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Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Wicleffe Musingarimi

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Currently, the rising energy demand as a result of an increase in the world’s population and the sustainable use of abundant natural resources are key issues facing many developed and developing countries including South Africa. Most of the energy to meet this growing demand comes from fossil fuel. Use of fossil fuels has led to environmental problems such air pollution, climate change, and acid rain. In addition, fossil fuels are facing continual depletion, which has led to the rise in oil prices, leading to the global economies melt down. Hence development of alternative clean and renewable energy source is a global priority. Renewable biomass from forest products, agricultural crops, and residues, as well as animal and municipal waste are promising alternatives. South Africa is one of the leading wine producers in the world; leading to a lot of winery waste (ww) being produced which can be used in anaerobic digestion (AD) to produce biogas. Biogas was produced from batch anaerobic digestion of zebra manure (zm) and batch anaerobic co-digestion of winery waste (ww) and zebra manure through water displacement. The batch digester with slurry of winery waste and zebra manure in the weight ratio of 1:2 was operated in a 1L container at 37°C for 30days. Co-digestion of winery waste and zebra manure produced higher amount of biogas as compared to zebra manure alone and winery waste alone. No biogas was produced by batch anaerobic digestion of winery waste alone. Chemical analysis of C/N ratio and total solids (TS) of zebra manure was 21.89 and 25.2 respectively. These values of C/N ratio and TS were quite high compared to values of other studied manures. Zebra manure also revealed unusually high concentration of Fe reaching 3600pm compared to other studies of manure. PCR with communal DNA of the digestate gave a positive hit for the presence of archaea species using standard archea primers; suggesting the presence of methanogens. Methanogens are key microbes in the production of biogas. Therefore, this study demonstrated the potential of zebra manure as an inoculum in the production of biogas.

Keywords: anaerobic digestion, biogas, co-digestion, methanogens

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Rapid urban development leads to the construction of urban tunnels for transport. Passage of tunnels under the surface structures and utilities prompted the changes in the site conditions and hence alteration of the dynamic response of surface structures. Therefore, in this study, the effect of the interaction of tunnel-superstructure on the site response is investigated numerically. For this purpose, Fast Lagrangian Analysis of Continua (FLAC 2D) is used, and stratification and properties of soil layers are selected based on the line No 7 of Tehran subway. The superstructure is modeled both as an equivalent surcharge and the actual structure, and the results are compared. A comparison of the results shows that consideration of structure geometry is necessary for dynamic analysis and it leads to the changes in displacements and accelerations. Consequently, the geometry of the superstructure should be modeled completely instead of the application of an equivalent load. The effect of tunnel diameter and depth on the settlement of superstructures is also studied. Results show that when the tunnel depth and diameter grow, the settlements increase considerably.

Keywords: tunnel, FLAC2D, settlement, dynamic analysis

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Authors: Rahim Shahrokhi, Junboum Park

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Per- and Polyfluoroalkyl Substances (PFASs) are environmentally persistent halogenated hydrocarbons that have been widely used in many industrial and commercial applications. Recently, contaminating the soil and groundwater due to the ubiquity of PFAS in environments has raised great concern. Adsorption technology is one of the most promising methods for PFAS removal. Chitosan is a biopolymer substance with abundant amine and hydroxyl functional groups, which render it a good adsorbent. This study has tried to enhance the adsorption capacity of chitosan by grafting more amine functional groups on its surface for the removal of two long (PFOA and PFOS) and two short-chain (PFBA, PFBS) PFAS substances from the aqueous phase. A series of batch adsorption tests have been performed to evaluate the adsorption capacity of the used sorbent. Also, the sorbent was analyzed by SEM, FT-IR, zeta potential, and XRD tests. The results demonstrated that both chitosan beads have good potential for adsorbing short and long-chain PFAS from the aqueous phase.

Keywords: PFAS, chitosan beads, adsorption, grafted chitosan

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Authors: Mohammed Sghir Taleb

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Introduction The date palm (Phoenix dactylifera L.) represents an essential element of the oasis ecosystem for Saharan and pre-Saharan regions of Morocco. It plays an important role, not only due to its economic importance, but also its ecological adaptation to, firstly, to ensure necessary protection for crops against underlying warm and dry sales, and secondly to contribute to the fight against desertification. This is one of the oldest cultivated plant species best adapted to difficult climatic conditions of the Saharan and pre-Saharan regions, because of its ecological requirements and economically most suitable for investing in oasis agriculture. Methodology The methodology is mainly based on a literature review of principal theses and projects for the conservation of flora and vegetation. Results The date palm has multiple uses. Indeed, it produces fruits rich in nutrients, provides a multitude of secondary products and generates needed revenue for the survival of oasis populations. In Morocco, the development and modernization of the date palm sector face, both upstream and downstream of the industry, several major constraints. In addition to climate constraints (prolonged drought), in its environment (lack of water resources), to the incessant invasion of disease Bayoud, Moroccan palm ecosystem suffers from a low level of technical and traditional practices prevail and traditional, from the choice of variety and site preparation up to harvesting and recycling of products. Conclusion The date palm plays an important role in the socioeconomic development of local and national level. However, this ecosystem however, is subject to numerous degradation factors caused by anthropogenic action and climate change. to reverse the trends, several programs have been developed by Morocco for the restoration of degraded areas and the development of the Phoenix dactylifera ecosystem to meet the needs of local populations and the development of the national economy.

Keywords: efforts, flora, ecosystem, forest, conservation, Morocco

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Authors: Mahmoud Huleihel, George Abu-Aqil, Manal Suleiman, Klaris Riesenberg, Itshak Lapidot, Ahmad Salman

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Urinary tract infections (UTIs) are considered to be the most common bacterial infections worldwide, which are caused mainly by Escherichia (E.) coli (about 80%). Klebsiella pneumoniae (about 10%) and Pseudomonas aeruginosa (about 6%). Although antibiotics are considered as the most effective treatment for bacterial infectious diseases, unfortunately, most of the bacteria already have developed resistance to the majority of the commonly available antibiotics. Therefore, it is crucial to identify the infecting bacteria and to determine its susceptibility to antibiotics for prescribing effective treatment. Classical methods are time consuming, require ~48 hours for determining bacterial susceptibility. Thus, it is highly urgent to develop a new method that can significantly reduce the time required for determining both infecting bacterium at the species level and diagnose its susceptibility to antibiotics. Fourier-Transform Infrared (FTIR) spectroscopy is well known as a sensitive and rapid method, which can detect minor molecular changes in bacterial genome associated with the development of resistance to antibiotics. The main goal of this study is to examine the potential of FTIR spectroscopy, in tandem with machine learning algorithms, to identify the infected bacteria at the species level and to determine E. coli susceptibility to different antibiotics directly from patients' urine in about 30minutes. For this goal, 1600 different E. coli isolates were isolated for different patients' urine sample, measured by FTIR, and analyzed using different machine learning algorithm like Random Forest, XGBoost, and CNN. We achieved 98% success in isolate level identification and 89% accuracy in susceptibility determination.

Keywords: urinary tract infections (UTIs), E. coli, Klebsiella pneumonia, Pseudomonas aeruginosa, bacterial, susceptibility to antibiotics, infrared microscopy, machine learning

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Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau, Dong Hun Kwak, Nicolae-Alexandru Colceriu

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Background: Stress management (SM) is a topic of great academic interest and equally a task to accomplish. In addition, it is recognized the beneficial role of unconventional therapies (UCT) in stress modulation. Aims: The aim was to evaluate medical (MS) versus non-medical students’ (NMS) opinions about academic stress management (ASM) using UCT. Methods: MS (n=103, third year males and females) and NMS (n=112, males and females, from humanities faculties, different years of study), out of their academic program, voluntarily answered to a questionnaire concerning: a) Classification of the four most important academic stress factors; b) The extent to which their daily life influences academic stress; c) The most important SM methods they know; d) Which of these methods they are applying; e) the UCT they know or about which they have heard; f) Which of these they know to have stress modulation effects; g) Which of these UCT, participants are using or would like to use for modulating stress; and if participants use UTC for their own choose or following a specialist consultation in those therapies (SCT); h) If they heard about the following UCT and what opinion they have (using visual analogue scale) about their use (following CST) for the ASM: Phytotherapy (PT), apitherapy (AT), homeopathy (H), ayurvedic medicine (AM), traditional Chinese medicine (TCM), music therapy (MT), color therapy (CT), forest therapy (FT). Results: Among the four most important academic stress factors, for MS more than for NMS, are: busy schedule, large amount of information taught; high level of performance required, reduced time for relaxing. The most important methods for SM that MS and NMS know, hierarchically are: listen to music, meeting friends, playing sport, hiking, sleep, regularly breaks, seeing positive side, faith; of which, NMS more than MS, are partially applying to themselves. UCT about which MS and less NMS have heard, are phytotherapy, apitherapy, acupuncture, reiki. Of these UTC, participants know to have stress modulation effects: some plants, bee’s products and music; they use or would like to use for ASM (the majority without SCT) certain teas, honey and music. Most of MS and only some NMS heard about PT, AT, TCM, MT and much less about H, AM, CT, TT. NMS more than MS, would use these UCT, following CST. Conclusions: 1) Academic stress is similarly reflected in MS and NMS opinions. 2) MS and NMS apply similar but very few UCT for stress modulation. 3) Information that MS and NMS have about UCT and their ASM application is reduced. 4) It is remarkable that MS and especially NMS, are open to UCT use for ASM, following an SCT.

Keywords: academic stress, stress management, stress modulation, medical students, non-medical students, unconventional therapies

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Authors: Dana Madalina Pohrib, Elena Irina Ciobanu

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In compaction works, the most often used codes and standards are those for road embankments and refer to a maximum filling height of 3.00m. When filling a height greater than 3.00m, such codes are no longer valid and thus their application may lead to technical difficulties in the process of compaction and to the achievement of a sufficient degree of compaction. For this reason, in the case of controlled fillings with heights greater than 3.00m it is necessary to formulate and apply a number of special techniques, which can be determined by performing a full scale test. This paper presents the results of the studies and full scale tests conducted for the stabilization of a ravine with vertical banks and a depth of about 12.00m. The fillings will support a heavy traffic road connecting the two parts of a village in Vaslui County, Romania. After analyzing two comparative intervention solutions, the variant of a controlled filling bordered by a monolith concrete retaining wall was chosen. The results obtained by the authors highlighted the need to insert a geogrid reinforcement at every 2.00m for creating a 12.00m thick compacted fill.

Keywords: compaction, dynamic probing, stability, soil stratification

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Authors: AbdelRahman A. Faragalla, Mohamed H. Alqhtani, Mohamed M. M.Ahmed

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Saudi Arabia has currently been beset by a barrage of bizarre assemblages of subterranean termite fauna, inflicting heavy catastrophic havocs on human valued properties in various homes, storage facilities, warehouses, agricultural and horticultural crops including okra, sweet pepper, tomatoes, sorghum, date palm trees, citruses and many forest domains and green lush desert oases. The most pressing urgent priority is to use modern technologies to alleviate the painstaking obstacle of taxonomic identification of these injurious noxious pests that might lead to effective pest control in both infested agricultural commodities and field crops. Our study has indicated the use of DNA fingerprinting technologies, in order to generate basic information of the genetic similarity between 3 predominant families containing the most destructive termite species. The methodologies included extraction and DNA isolation from members of the major families and the use of randomly selected primers and PCR amplifications with the nucleotide sequences. GC content and annealing temperatures for all primers, PCR amplifications and agarose gel electrophoresis were also conducted in addition to the scoring and analysis of Random Amplification Polymorphic DNA-PCR (RAPDs). A phylogenetic analysis for different species using statistical computer program on the basis of RAPD-DNA results, represented as a dendrogram based on the average of band sharing ratio between different species. Our study aims to shed more light on this intriguing subject, which may lead to an expedited display of the kinship and relatedness of species in an ambitious undertaking to arrive at correct taxonomic classification of termite species, discover sibling species, so that a logistic rational pest management strategy could be delineated.

Keywords: DNA fingerprinting, Western Saudi Arabia, DNA primers, RAPD

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Authors: Olusegun Raphael Adeyemi, Samuel Oluwaseun Osunleti, Abiddin Adekunle Bashiruddin

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Field trials were conducted in 2020 and 2021 at the Teaching and Research Farm of the Federal University of Agriculture Abeokuta, Ogun State, Nigeria to evaluate the effect of biochar application under different weeding regimes on growth and yield of okra. Treatments were laid out in split- plot in a randomized complete block design with three replications. Main plot treatments were three levels of biochar namely 0t/ha, 10t/ha and 20t/ha while sub-plots treatments consisted of four weeding regimes (weeding at 3, 6 and 9 WAS, weeding at 3 and 6 WAS, weeding at 3 WAS and weedy check as control). Data collected on growth and yield of okra, and weed parameters were subjected to analysis of variance and treatment means were separated using least significant difference at p < 0.05. Results showed that biochar applied at 20 t/ha increased okra yield by 47.5% compared to the control. Weeding at 3, 6 and 9 WAS gave the highest okra yield. Uncontrolled weed infestation throughout crop growth resulted in 87.3% yield reduction in okra. It is concluded that weed suppression , growth and yield of okra can be enhanced by the application of biochar at 20t/ha and weeding at 3, 6 and 9 WAS hence recommended.

Keywords: biochar, okra, weeding, weed competition

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Authors: Nuo Xu, Kok Hun Goh, Jeyatharan Kumarasamy

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Pile load testing is significant during foundation construction due to its traditional role of design validation and routine quality control of the piling works. In order to verify whether piles can take loadings at specified settlements, piles will have to undergo working load test where the test load should normally up to 150% of the working load of a pile. Selection or sampling of piles for the working load test is done subject to the number specified in Singapore National Annex to Eurocode 7 SS EN 1997-1:2010. This paper presents an innovative way to rationalize the number of pile load test by adopting statistical analysis approach and looking at the coefficient of variance of pile elastic modulus using a case study at Singapore Tuas depot. Results are very promising and have shown that it is possible to reduce the number of working load test without influencing the reliability and confidence on the pile quality. Moving forward, it is suggested that more load test data from other geological formations to be examined to compare with the findings from this paper.

Keywords: elastic modulus of pile under soil interaction, jurong formation, kentledge test, pile load test

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Authors: A. Kourou, A. Ioakeimidou, E. Bafa, C. Fassoulas, M. Panoutsopoulou

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The role of volunteers in disaster management is of decisive importance and the need of their involvement is well recognized, both for prevention measures and for disaster management. During major catastrophes, whereas professional personnel are outsourced, the role of volunteers is crucial. In Greece experience has shown that various groups operating in the civil protection mechanism like local administration staff or volunteers, in many cases do not have the necessary knowledge and information on best practices to act against natural disasters. One of the major problems is the lack of volunteers’ education and training. In the above given framework, this paper presents the results of a survey aimed to identify the level of education and preparedness of civil protection volunteers in Greece. Furthermore, the implementation of earthquake protection measures at individual, family and working level, are explored. More specifically, the survey questionnaire investigates issues regarding pre-earthquake protection actions, appropriate attitudes and behaviors during an earthquake and existence of contingency plans in the workplace. The questionnaires were administered to citizens from different regions of the country and who attend the civil protection training program: “Protect Myself and Others”. A closed-form questionnaire was developed for the survey, which contained questions regarding the following: a) knowledge of self-protective actions; b) existence of emergency planning at home; c) existence of emergency planning at workplace (hazard mitigation actions, evacuation plan, and performance of drills); and, d) respondents` perception about their level of earthquake preparedness. The results revealed a serious lack of knowledge and preparedness among respondents. Taking into consideration the aforementioned gap and in order to raise awareness and improve preparedness and effective response of volunteers acting in civil protection, the EVANDE project was submitted and approved by the European Commission (EC). The aim of that project is to educate and train civil protection volunteers on the most serious natural disasters, such as forest fires, floods, and earthquakes, and thus, increase their performance.

Keywords: civil protection, earthquake, preparedness, volunteers

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Authors: Olusegun Raphael Adeyemi, Samuel Oluwaseun Osunleti, Abiddin Adekunle Bashiruddin

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Field trials were conducted in 2020 and 2021 at the Teaching and Research Farm of the Federal University of Agriculture Abeokuta, Ogun State, Nigeria, to evaluate the effect of biochar application under different weeding regimes on the growth and yield of okra. Treatments were laid out in a split- plot in a randomized complete block design with three replications. Main plot treatments were three levels of biochar, namely 0t/ha, 10t/ha and 20t/ha while sub-plot treatments consisted of four weeding regimes (weeding at 3, 6 and 9 WAS, weeding at 3 and 6 WAS, weeding at 3 WAS and weedy check as control). Data collected on growth and yield of okra and weed parameters were subjected to analysis of variance, and treatment means were separated using the least significant difference at p < 0.05. Results showed that biochar applied at 20 t/ha increased okra yield by 47.5% compared to the control. Weeding at 3, 6 and 9 WAS gave the highest okra yield. Uncontrolled weed infestation throughout crop growth resulted in an 87.3% yield reduction in okra. It is concluded that weed suppression, growth and yield of okra can be enhanced by the application of biochar at 20t/ha and weeding at 3, 6 and 9 WAS hence recommended.

Keywords: biochar, okra, weeding, weed competition, yield

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Authors: Adilah Shariff, Radin Hakim, Nurhayati Abdullah

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Utilisation of biomass feedstock for biochar has received increasing attention because of their potential for carbon sequestration and soil amendment. The aim of this study is to investigate the characteristics of rubber wood as a biomass feedstock for biochar via slow pyrolysis process. This was achieved by using proximate, ultimate, and thermogravimetric analysis (TGA) as well as heating value, pH and lignocellulosic determination. Rubber wood contains 4.13 mf wt.% moisture, 86.30 mf wt.% volatile matter, 0.60 mf wt.% ash content, and 13.10 mf wt.% fixed carbon. The ultimate analysis shows that rubber wood consists of 44.33 mf wt.% carbon, 6.26 mf wt.% hydrogen, 19.31 mf wt.% nitrogen, 0.31 mf wt.% sulphur, and 29.79 mf wt.% oxygen. The higher heating value of rubber wood is 22.5 MJ/kg, and its lower heating value is 21.2 MJ/kg. At 27 °C, the pH value of rubber wood is 6.83 which is acidic. The lignocellulosic analysis revealed that rubber wood composition consists of 2.63 mf wt.% lignin, 20.13 mf wt.% cellulose, and 65.04 mf wt.% hemicellulose. The volatile matter to fixed carbon ratio is 6.58. This led to a biochar yield of 25.14 wt.% at 500 °C. Rubber wood is an environmental friendly feedstock due to its low sulphur content. Rubber wood therefore is a suitable and a potential feedstock for biochar production via slow pyrolysis.

Keywords: biochar, biomass, rubber wood, slow pyrolysis

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Authors: Pinna Beatrice., Laini Alex, Negro Giovanni, Burgazzi Gemma, Viaroli Pierluigi, Vezza Paolo

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Habitat models rarely consider macroinvertebrates as ecological targets in rivers. Available approaches mainly focus on single macroinvertebrate species, not addressing the ecological needs and functionality of the entire community. This research aimed to provide an approach to model the habitat of the macroinvertebrate community. The approach is based on the recently developed Flow-T index, together with a Random Forest (RF) regression, which is employed to apply the Flow-T index at the meso-habitat scale. Using different datasets gathered from both field data collection and 2D hydrodynamic simulations, the model has been calibrated in the Trebbia river (2019 campaign), and then validated in the Trebbia, Taro, and Enza rivers (2020 campaign). The three rivers are characterized by a braiding morphology, gravel riverbeds, and summer low flows. The RF model selected 12 mesohabitat descriptors as important for the macroinvertebrate community. These descriptors belong to different frequency classes of water depth, flow velocity, substrate grain size, and connectivity to the main river channel. The cross-validation R² coefficient (R²𝒸ᵥ) of the training dataset is 0.71 for the Trebbia River (2019), whereas the R² coefficient for the validation datasets (Trebbia, Taro, and Enza Rivers 2020) is 0.63. The agreement between the simulated results and the experimental data shows sufficient accuracy and reliability. The outcomes of the study reveal that the model can identify the ecological response of the macroinvertebrate community to possible flow regime alterations and to possible river morphological modifications. Lastly, the proposed approach allows extending the MesoHABSIM methodology, widely used for the fish habitat assessment, to a different ecological target community. Further applications of the approach can be related to flow design in both perennial and non-perennial rivers, including river reaches in which fish fauna is absent.

Keywords: ecological flows, macroinvertebrate community, mesohabitat, river habitat modeling

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Authors: Iram Gul, Maria Manzoor, Muhammad Arshad

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The enhanced phytoextraction techniques have been proposed for the remediation of heavy metals contaminated soil. Chelating agents enhance the availability of Cd, which is the main factor in the phytoremediation. This study was conducted to assessed the potential of two Pelargonium species (Pelargonium zonale, Pelargonium hortorum) in EDTA enhanced phytoextraction of Cd using pot experiment. Different doses of EDTA (0, 1, 2, 3, 4, 5 mmol kg-1) was used, and results showed that there was significant increase (approximately 2.1 folds) in the mobility of Cd at EDTA 5 mg kg-1 as compared to control. Both plants have TF and BCF more than 1 and have potential for the phytoextraction of Cd. However, the Pelargonium hortorum showed higher biomass and Cd uptake as compared to Pleragonium zonale. The maximum Cd accumulation in shoot and root of Pelargonium zonale was 484.4 and 264.41 mg kg-1 respectively at 2 mmol kg-1. However, the Pelargonium hortorum accumulate 996.9 and 350 mg kg-1 of Cd in shoot and root respectively at 4 mmol kg-1. Pelargonium hortorum uptake approximately 10.7 folds higher Cd concentration as compared to the Pelargonium zonale. Results revealed that P. hortorum performed better than P. zonal even at higher Cd and EDTA doses however toxicity and leaching potential of increased Cd and EDTA concentrations needs to be explored before field application.

Keywords: Cadmium, EDTA, Pelargonium, phytoextraction

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Authors: Tomasz Balabanski, Anna Biedunkiewicz

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Research on basic bacteriological and physicochemical parameters conducted by state institutions (Provincial Sanitary and Epidemiological Station and District Sanitary and Epidemiological Station) are limited to bathing waters under constant sanitary and epidemiological supervision. Unfortunately, no routine or monitoring tests are carried out for the presence of microfungi. This also applies to beach sand used for recreational purposes. The purpose of the planned own research was to determine the diversity of the mycobiota present on supervised and unsupervised sandy beaches, on the shores of lakes, of municipal baths used for recreation. The research material consisted of microfungi isolated from April to October 2019 from sandy beaches of supervised and unsupervised lakes located within the administrative boundaries of the city of Olsztyn (North-Eastern Poland, Europe). Four lakes, out of the fifteen available (Tyrsko, Kortowskie, Skanda, and Ukiel), whose bathing waters are subjected to routine bacteriological tests, were selected for testing. To compare the diversity of the mycobiota composition on the surface and below the sand mixing layer, samples were taken from two depths (10 cm and 50 cm), using a soil auger. Micro-fungi from sand samples were obtained by surface inoculation on an RBC medium from the 1st dilution (1:10). After incubation at 25°C for 96-144 h, the average number of CFU/dm³ was counted. Morphologically differing yeast colonies were passaged into Sabouraud agar slants with gentamicin and incubated again. For detailed laboratory analyses, culture methods (macro- and micro-cultures) and identification methods recommended in diagnostic mycological laboratories were used. The conducted research allowed obtaining 140 yeast isolates. The total average population ranged from 1.37 × 10⁻² CFU/dm³ before the bathing season (April 2019), 1.64 × 10⁻³ CFU/dm³ in the season (May-September 2019), and 1.60 × 10⁻² CFU/dm³ after the end of the season (October 2019). More microfungi were obtained from the surface layer of sand (100 isolates) than from the deeper layer (40 isolates). Reported microfungi may circulate seasonally between individual elements of the lake ecosystem. From the sand/soil from the catchment area beaches, they can get into bathing waters, stopping periodically on the coastal phyllosphere. The sand of the beaches and the phyllosphere are a kind of filter for the water reservoir. The presence of microfungi with various pathogenicity potential in these places is of major epidemiological importance. Therefore, full monitoring of not only recreational waters but also sandy beaches should be treated as an element of constant control by appropriate supervisory institutions, allowing recreational areas for public use so that the use of these places does not involve the risk of infection. Acknowledgment: 'Development Program of the University of Warmia and Mazury in Olsztyn', POWR.03.05.00-00-Z310/17, co-financed by the European Union under the European Social Fund from the Operational Program Knowledge Education Development. Tomasz Bałabański is a recipient of a scholarship from the Programme Interdisciplinary Doctoral Studies in Biology and Biotechnology (POWR.03.05.00-00-Z310/17), which is funded by the 'European Social Fund'.

Keywords: beach, microfungi, sand, yeasts

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Authors: Yiwei Huang, Chunyu Zhao, Jingjing Ding

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Electrical Resistivity Tomography has been widely used in the medicine and the geology, such as the imaging of the lung impedance and the analysis of the soil impedance, etc. Linear Back Projection is the core algorithm of Electrical Resistivity Tomography, but the traditional Linear Back Projection can not make full use of the information of the electric field. In this paper, an imaging method of Parallel Electrode Linear Back Projection for Electrical Resistivity Tomography is proposed, which generates the electric field distribution that is not linearly related to the traditional Linear Back Projection, captures the new information and improves the imaging accuracy without increasing the number of electrodes by changing the connection mode of the electrodes. The simulation results show that the accuracy of the image obtained by the inverse operation obtained by the Parallel Electrode Linear Back Projection can be improved by about 20%.

Keywords: electrical resistivity tomography, finite element simulation, image optimization, parallel electrode linear back projection

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Authors: James Ladzekpo

Abstract:

Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

Procedia PDF Downloads 28

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 87

Authors: Leonie Bradfield, Stephen Fityus, John Simmons

Abstract:

The shearing behavior of current and planned coal mine spoil dumps up to 400m in height is studied using large-sample-high-stress direct shear tests performed on a range of spoils common to the coalfields of Eastern Australia. The motivation for the study is to address industry concerns that some constructed spoil dump heights ( > 350m) are exceeding the scale ( ≤ 120m) for which reliable design information exists, and because modern geotechnical laboratories are not equipped to test representative spoil specimens at field-scale stresses. For more than two decades, shear strength estimation for spoil dumps has been based on either infrequent, very small-scale tests where oversize particles are scalped to comply with device specimen size capacity such that the influence of prototype-sized particles on shear strength is not captured; or on published guidelines that provide linear shear strength envelopes derived from small-scale test data and verified in practice by slope performance of dumps up to 120m in height. To date, these published guidelines appear to have been reliable. However, in the field of rockfill dam design there is a broad acceptance of a curvilinear shear strength envelope, and if this is applicable to coal mine spoils, then these industry-accepted guidelines may overestimate the strength and stability of dumps at higher stress levels. The pressing need to rationally define the shearing behavior of more representative spoil specimens at field-scale stresses led to the successful design, construction and operation of a large direct shear machine (LDSM) and its subsequent application to provide reliable design information for current and planned very-high dumps. The LDSM can test at a much larger scale, in terms of combined specimen size (720mm x 720mm x 600mm) and stress (σn up to 4.6MPa), than has ever previously been achieved using a direct shear machine for geotechnical testing of rockfill. The results of an extensive LDSM testing program on a wide range of coal-mine spoils are compared to a published framework that widely accepted by the Australian coal mining industry as the standard for shear strength characterization of mine spoil. A critical outcome is that the LDSM data highlights several non-compliant spoils, and stress-dependent shearing behavior, for which the correct application of the published framework will not provide reliable shear strength parameters for design. Shear strength envelopes developed from the LDSM data are also compared with dam engineering knowledge, where failure envelopes of rockfills are curved in a concave-down manner. The LDSM data indicates that shear strength envelopes for coal-mine spoils abundant with rock fragments are not in fact curved and that the shape of the failure envelope is ultimately determined by the strength of rock fragments. Curvilinear failure envelopes were found to be appropriate for soil-like spoils containing minor or no rock fragments, or hard-soil aggregates.

Keywords: coal mine, direct shear test, high dump, large scale, mine spoil, shear strength, spoil dump

Procedia PDF Downloads 144

Authors: Meysam Abedinpour

Abstract:

Water limitation is the main challenge for crop production in a semi-arid environment. Deficit irrigation is a strategy that allows a crop to sustain some degree of water deficit in order to reduce costs and potentially increase income. For this goal, a field experimental carried out at Asrieh fields of Gorgan city in the north of Iran, during summer season 2011. The treatments imposed were different irrigation water regimes (i.e. W1:70, W2:80, W3:90, and W4:100) percent of field capacity (FC). The results showed that there was Significant difference between the yield and (WUE) under different levels of irrigation, excepting of soil moisture content at field capacity (W4) and 90% of field capacity (W3) on yield and water use efficiency (WUE). The seasonal irrigation water applied were (i.e. 375, 338, 300, and 263 mm ha-1) under different irrigation water treatments (100, 90, 80, 80 and 70%) of FC, respectively. Grain yield productions under treatments were 4180, 3955, 3640, and 3355 (kg ha-1) respectively. Furthermore, the results showed that water use efficiency (WUE) at different treatments were 7.67, 7.79, 7.74, and 7.75 Kg mm ha-1 for (100, 90, 80, and 70) per cent of field capacity, therefore the 90 % of FC treatment (W3) is recommended for Soybean irrigation for water saving. Furthermore, the result showed that the treatment of 90 % of filed capacity (W3) seemed to be better adapted to product a high crop yield with acceptable yield coupling with water use efficiency in Golestan province.

Keywords: deficit irrigation, water use efficiency, yield, soybean

Procedia PDF Downloads 443

Authors: Arun Dhakal, Geoff Cockfield

Abstract:

This paper examines the emission potential of different farming practices that the farmers have adopted in Dhanusha District of Nepal and scope of these practices in climate change mitigation. Which practice is more climate-smarter is the question that this aims to address through a life cycle assessment (LCA) of greenhouse gas (GHG) emissions. The LCA was performed to assess if there is difference in emission potential of broadly two farming systems (agroforestry–based and traditional agriculture) but specifically four farming systems. The required data for this was collected through household survey of randomly selected households of 200. The sources of emissions across the farming systems were paddy cultivation, livestock, chemical fertilizer, fossil fuels and biomass (fuel-wood and crop residue) burning. However, the amount of emission from these sources varied with farming system adopted. Emissions from biomass burning appeared to be the highest while the source ‘fossil fuel’ caused the lowest emission in all systems. The emissions decreased gradually from agriculture towards the highly integrated agroforestry-based farming system (HIS), indicating that integrating trees into farming system not only sequester more carbon but also help in reducing emissions from the system. The annual emissions for HIS, Medium integrated agroforestry-based farming system (MIS), LIS (less integrated agroforestry-based farming system and subsistence agricultural system (SAS) were 6.67 t ha-1, 8.62 t ha-1, 10.75 t ha-1 and 17.85 t ha-1 respectively. In one agroforestry cycle, the HIS, MIS and LIS released 64%, 52% and 40% less GHG emission than that of SAS. Within agroforestry-based farming systems, the HIS produced 25% and 50% less emissions than those of MIS and LIS respectively. Our finding suggests that a tree-based farming system is more climate-smarter than a traditional farming. If other two benefits (carbon sequestered within the farm and in the natural forest because of agroforestry) are to be considered, a considerable amount of emissions is reduced from a climate-smart farming. Some policy intervention is required to motivate farmers towards adopting such climate-friendly farming practices in developing countries.

Keywords: life cycle assessment, greenhouse gas, climate change, farming systems, Nepal

Procedia PDF Downloads 588

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 95

Authors: Satyavati Shukla, Lakhan V. Rathod, Mohan V. Khire

Abstract:

Rapid urbanization changes the land use/land cover pattern of a developing region. Due to these land surface changes, stream flow of the rivers also changes. It is important to investigate the factors affecting hydrological characteristics of the river basin for better river basin management planning. This study is aimed to understand the effect of Land Use/Land Cover (LU/LC) changes on stream flow of Upper Bhima River basin which is highly stressed in terms of water resources. In this study, Upper Bhima River basin is divided into two adjacent sub-watersheds: Mula-Mutha (urbanized) sub-watershed and Bhima (non-urbanized) sub-watershed. First of all, LU/LC changes were estimated over 1980, 2002, and 2009 for both Mula-Mutha and Bhima sub-watersheds. Further, stream flow simulations were done using Soil and Water Assessment Tool (SWAT) for the streams draining both watersheds. Results revealed that stream flow was relatively higher for urbanized sub-watershed. Through Sensitivity Analysis it was observed that out of all the parameters used, base flow was the most sensitive parameter towards LU/LC changes.

Keywords: land use/land cover, remote sensing, stream flow, urbanization

Procedia PDF Downloads 296

Authors: Meiyan Xing, Cenran Li, Liang Xiang

Abstract:

Impacts of excess sludge vermicompost on the germination and early growth of plant were tested. The better effect of cow dung vermicompost (CV) on seed germination and seedling growth proved that cow dung was indeed the preferred additive in sludge vermicomposting as reported by plentiful researchers worldwide. The effects and the best amount of application of CV were further discussed. Results demonstrated that seed germination and seedling growth (seedlings number, plant height, stem diameter) were the best and heavy metal (Zn, Pb, Cr and As) contents of plant were the lowest when soil amended with CV by 15%. Additionally, CV fostered higher contents of chlorophyll a and chlorophyll b compared to the control when concentration ranged from 5 to 15%, thereafter a slight increase in chlorophyll content was observed form 15% to 25%. Thus, CV at the optimum proportion of 15% could serve as a feasible and satisfactory way of sludge agricultural utilization of sewage sludge. In summary, sewage sludge can be gainfully utilized in producing organic fertilizer via vermicomposting, thereby not only providing a means of sewage sludge treatment and disposal, but also stimulating the growth of plant and the ability to resist disease.

Keywords: cow dung vermicompost, seed germination, seedling growth, sludge utilization

Procedia PDF Downloads 239

Authors: Sayyed Yaghoub Zolfegharifar, Khairul Anuar Kassim, Hossein Khoramrooz, Khodayar Farhadiasl, Sadegh Jahan

Abstract:

Iran is one of the world's seismically active countries so that it experiences many small to medium earthquakes annually and a large earthquake every ten years. Due to seism tectonic conditions and special geographical and climatic position, Iran has the potential to create numerous severe earthquakes. Therefore, seismicity studies and seismic zonation of seismic zones of the country are necessary. In this article, the effect of local site conditions on the characteristics of seismic design in Rahmormoz will be examined. After analyzing the seismic hazard for Rahmormoz through deterministic and statistical methods and preparing the necessary geotechnical models based on available data, the ground response will be analyzed for different parts of the city based on four inputs and acceleration level estimated for bedrock through the equivalent linear method and by means of Deep Soil program. Finally, through the analysis of the obtained results, the seismic profiles of the ground surface for different parts of the city will be presented.

Keywords: seismic microzonation, ground response, resonance spectrum, period, site conditions

Procedia PDF Downloads 321

Authors: Mohammad Atiqur Rahman

Abstract:

The study aimed at inventorying the threatened biodiversity of Bangladesh and assessing the rate of loss of biodiversity caused due to environmental degradation for conservation management. The impact assessment of environmental depletion and rate of biodiversity loss determination have been made by a long term field investigation, examination of preserved herbarium specimens and survey of relevant floristic literature following the IUCN’s threatened criteria of assessing Red List Plants under the Flora Bangladesh Project. Biodiversity of Bangladesh, as evaluated, has been affected to a large extent during the last four and half decades due to spontaneous environmental degradation caused by frequent occurrence of cyclonic storms and tidal bores since 1970 and flooding, draught, unilateral diversion of trans-boundary waters by operating Farakka Barrage since 1975, indiscriminate destruction and over exploitation of natural resources, unplanned development and industrialization, overpopulation etc. Depletion of world’s largest mangrove biodiversity in Sundarbans, coastal and island biodiversity in southern part, agro-biodiversity and agro-fisheries all over the country, Haor and wetland biodiversity of plain lands, terrestrial and forest biodiversity in central and eastern hilly part of Bangladesh, as assessed, have greatly been occurred at a higher rate due to environmental degradation which in turn affect directly or indirectly the economy, food security and environmental health of the country. Complete inventory of 30 plant families resulted in the recognition of 45.18% species of Bangladesh as threatened environmentally and 13.23% species as possibly extinct from the flora since these have neither been reported or could be traced in the field for more than 100 years. The rate of extinction is determined to be 2.65% per 20 years. Hence the study indicates that the loss of biodiversity and environmental degradation in Bangladesh occurring at an alarming rate. The study focuses on the issues of environment, the extent of loss of different plant biodiversities in Bangladesh, prioritizing and implementing national conservation strategies for sustainable management of the environment.

Keywords: Bangladesh, biodiversity, conservation, environmental management

Procedia PDF Downloads 230