Search results for: forest wastes

Authors: John Gichimu Mbaka, Jan Helmrich Martin von Baumbach, Celia Somlai, Denis Köpfer, Andreas Maeck, Andreas Lorke, Ralf Schäfer

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Leaf litter decomposition is an important process providing energy to biotic communities. Additionally, methane gas (CH4) has been identified as an important alternative source of carbon and energy in some freshwater food webs.Flow regulation and dams can strongly alter freshwater ecosystems, but little is known about the effect of small impoundments on leaf litter decomposition and methane derived carbon in streams. In this study, we tested the effect of small water storage impoundments on leaf litter decomposition rates and methane derived carbon. Leaf litter decomposition rates were assessed by comparing treatment sites located close to nine impoundments (Rheinland Pfalz state, Germany) and reference sites located far away from the impoundments.CH4 concentrations were measured in eleven impoundments and correlated with the δ13C values of two subfamilies of chironomid larvae (i.e. Chironomini and Tanypodinae). Leaf litter break down rates were significantly lower in study sites located immediately above the impoundments, especially associated with a reduction in the abundance of shredders. Chironomini larvae had the lower mean δ13C values (‒29.2 to ‒25.5 ‰), than Tanypodinae larvae (‒26.9 to ‒25.3 ‰).No significant relationships were established between CH4 concentrations and δ13C values of chironomids (p> 0.05).Mean δ13C values of chironomid larvae (mean: ‒26.8‰, range: ‒ 29.2‰ to ‒ 25.3‰) were similar to those of sedimentary organic matter (SOM) (mean: ‒28.4‰, range: ‒ 29.3‰ to ‒ 27.1‰) and tree leaf litter (mean: ‒29.8 ‰, range: ‒ 30.5‰ to ‒ 29.1‰). In conclusion, this study demonstrates that small impoundments may have a negative effect on leaf litter decomposition in forest streams and that CH4 has limited influence on the benthic food web in stream impoundments.

Keywords: river functioning, chironomids, Alder tree, stable isotopes, methane oxidation, shredder

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Authors: R. F. Vieira, D. Lopes, I. Baptista, S. A. Figueiredo, V. F. Domingues, R. Jorge, C. Delerue-matos, O. M. Freitas

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Odours are generated in municipal solid wastes management plants as a result of decomposition of organic matter, especially when anaerobic degradation occurs. Information was collected about the substances and respective concentration in the surrounding atmosphere of some management plants. The main components which are associated with these unpleasant odours were identified: ammonia, hydrogen sulfide and mercaptans. The first is the most common and the one that presents the highest concentrations, reaching values of 700 mg/m3. Biofiltration, which involves simultaneously biodegradation, absorption and adsorption processes, is a sustainable technology for the treatment of these odour emissions when a natural packing material is used. The packing material should ideally be cheap, durable, and allow the maximum microbiological activity and adsorption/absorption. The presence of nutrients and water is required for biodegradation processes. Adsorption and absorption are enhanced by high specific surface area, high porosity and low density. The main purpose of this work is the exploitation of natural waste materials, locally available, as packing media: heather (Erica lusitanica), chestnut bur (from Castanea sativa), peach pits (from Prunus persica) and eucalyptus bark (from Eucalyptus globulus). Preliminary batch tests of ammonia removal were performed in order to select the most interesting materials for biofiltration, which were then characterized. The following physical and chemical parameters were evaluated: density, moisture, pH, buffer and water retention capacity. The determination of equilibrium isotherms and the adjustment to Langmuir and Freundlich models was also performed. Both models can fit the experimental results. Based both in the material performance as adsorbent and in its physical and chemical characteristics, eucalyptus bark was considered the best material. It presents a maximum adsorption capacity of 0.78±0.45 mol/kg for ammonia. The results from its characterization are: 121 kg/m3 density, 9.8% moisture, pH equal to 5.7, buffer capacity of 0.370 mmol H+/kg of dry matter and water retention capacity of 1.4 g H2O/g of dry matter. The application of natural materials locally available, with little processing, in biofiltration is an economic and sustainable alternative that should be explored.

Keywords: ammonia removal, biofiltration, natural materials, odour control

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Authors: Ambika Prasad Gupta, Harshit Sosan Lakra

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Food security is an important issue that has been widely discussed in literature. However, there is a lack of research on the specific food security challenges faced by tribal communities. Tribal food security refers to the ability of indigenous or tribal communities to consistently access and afford an adequate and nutritious supply of food. These communities often have unique cultural, social, and economic contexts that can impact their food security. The study aims to assess the food security status of all thirty-two major tribes, including Particularly Vulnerable Tribal Groups (PVTG) people living in various blocks of Jharkhand State. The methodology of this study focuses on measuring the food security index of indigenous people by developing and redefining a new Tribal Food Security Index (TFSI) as per the indigenous community-level indicators identified by the Global Food Security Index and other indicators relevant to food security. Affordability, availability, quality and safety, and natural resources were the dimensions used to calculate the overall Tribal Food Security Index. A survey was conducted for primary data collection of tribes and PVTGs at the household level in various districts of Jharkhand with a considerable tribal population. The result shows that due to the transition from rural to urban areas, there is a considerable change in TFSI and a decrease in forest dependency of tribal communities. Socioeconomic factors like occupation and household size had a significant correlation with TFSI. Tribal households living in forests have a higher food security index than tribal households residing in urban transition areas. The study also shows that alternative methodology adopted to measure specific community-level food security creates high significant impact than using commonly used indices.

Keywords: indigenous people, tribal food security, particularly vulnerable tribal groups, Jharkhand

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Authors: Murat Iskender Aktaş, Sadi Ergin, Rasime Acar Aktaş

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In the light of fast-paced changes and developments in the health sector, the Ministry of Health started a new structuring with decree law numbered 663 within the scope of the Project of Transformation in Health. Accordingly, hospitals should ensure patient satisfaction through more efficient, more effective use of resources and sustainable finance by placing patients in the centre and should operate to increase efficiency to its maximum level while doing these. Within this study, in order to find out how efficient the hospitals were in terms of medical waste management between the years 2011-2014, the data from six hospitals of Amasya Public Hospitals Union were evaluated separately through Data Envelopment Analysis (DEA) method. First of all, input variables were determined. Input variables were the number of patients admitted to polyclinics, the number of inpatients in clinics, the number of patients who were operated and the number of patients who applied to the laboratory. Output variable was the cost of medical wastes in Turkish liras. Each hospital’s total medical waste level before and after public hospitals union; the amounts of average medical waste per patient admitted to polyclinics, per inpatient in clinics, per patient admitted to laboratory and per operated patient were compared within each group. In addition, average medical waste levels and costs were compared for Turkey in general and Europe in general. Paired samples t-test was used to find out whether the changes (increase-decrease) after public hospitals union were statistically significant. The health facilities that were unsuccessful in terms of medical waste management before and after public hospital union and the factors that caused this failure were determined. Based on the results, for each health facility that was ineffective in terms of medical waste management, the level of improvement required for each input was determined. The results of the study showed that there was an improvement in medical waste management applications after the health facilities became a member of public hospitals union; their medical waste levels were lower than the average of Turkey and Europe while the averages of cost of disposal were the highest.

Keywords: medical waste management, cost of medical waste, public hospitals, data envelopment analysis

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Authors: Francielo Vendruscolo

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During industrial processing of raw materials of animal and vegetable origin, large amounts of solid, liquid and gaseous wastes are generated. Solid residues are usually materials rich in carbohydrates, protein, fiber and minerals. Brewer’s spent grain (BSG) is the main waste generated in the brewing industry, representing 85% of the waste generated in this industry. It is estimated that world’s BSG generation is approximately 38.6 x 106 t per year and represents 20-30% (w/w) of the initial mass of added malt, resulting in low commercial value by-product, however, does not have economic value, but it must be removed from the brewery, as its spontaneous fermentation can attract insects and rodents. For every 100 grams in dry basis, BSG has approximately 68 g total fiber, being divided into 3.5 g of soluble fiber and 64.3 g of insoluble fiber (cellulose, hemicellulose and lignin). In addition to dietary fibers, depending on the efficiency of the grinding process and mashing, BSG may also have starch, reducing sugars, lipids, phenolics and antioxidants, emphasizing that its composition will depend on the barley variety and cultivation conditions, malting and technology involved in the production of beer. BSG demands space for storage, but studies have proposed alternatives such as the use of drying, extrusion, pressing with superheated steam, and grinding to facilitate storage. Other important characteristics that enhance its applicability in bioremediation, effluent treatment and biotechnology, is the surface area (SBET) of 1.748 m2 g-1, total pore volume of 0.0053 cm3 g-1 and mean pore diameter of 121.784 Å, characterized as a macroporous and possess fewer adsorption properties but have great ability to trap suspended solids for separation from liquid solutions. It has low economic value; however, it has enormous potential for technological applications that can improve or add value to this agro-industrial waste. Due to its composition, this material has been used in several industrial applications such as in the production of food ingredients, fiber enrichment by its addition in foods such as breads and cookies in bioremediation processes, substrate for microorganism and production of biomolecules, bioenergy generation, and civil construction, among others. Therefore, the use of this waste or by-product becomes essential and aimed at reducing the amount of organic waste in different industrial processes, especially in breweries.

Keywords: brewer’s spent malt, agro-industrial residue, lignocellulosic material, waste generation

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Authors: S. K. Dewangan, K. R. Sahu, S. Soni

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Unemployment is today’s basic socio-economic problem eroding national income and living standards, aggravating national development and poverty alleviation. The farmers are encouraged to take up non-agriculture practices which are integrated with Sericulture. Sericulture is one of the primary occupations for livelihood of poor people in tribal area. Most of tribal are involved in Sericulture. Tasar, Eri are the main forest-based cultivation. Among these sericultures is the major crop adopted by the Tribal’s and practiced in respective areas. Out of the 6, 38,588 villages in India, sericultures are practiced in about 69000 villages providing employment to about 7.85 million people. Sericulture is providing livelihood for 9, 47,631 families. India continues to be the second largest producer of silk in the World. Among the four varieties of silk produced, as in 2012-13, Mulberry accounts for 18,715 MT, Eri 3116 MT, Tasar 1729 MT and Muga 119MT of the total raw silk production in the country. Sericulture with its unique features plays an important role in upgrading the socio-economic conditions of the rural folk and with employment opportunities to the educated rural youth and women. In view of the importance of sericulture enterprise for the biodiversity conservation as well as its cultural bondage, the paper tries to enlighten and discuss the significance of sericulture and strategies to be taken for the employment generation in Indian sericulture industry. The present paper explores the possible employment opportunities derived from problem analysis and strategies to be adopted aiming at revolutionary biodiversity conservation in the study area. The paper highlights the sericulture is a way for biodiversity conservation, employment generation in Raigarh district, their utilization and needs as they act as a tool for socio-economic change for tribal. The study concludes with some suggestions to improve the feasibility of sericulture in long term.

Keywords: bio-diversity, employment, sericulture, tribal, income, socio-economic

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Authors: Moses Kolade Ogun, Ina Korner

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To improve on the sustainable resource management in the wastepaper recycling industry, studies into the valorization of wastes generated by the industry are necessary. The industry produces different residues, among which is the deinking sludge (DS). The DS is generated from the deinking process and constitutes a major fraction of the residues generated by the European pulp and paper industry. The traditional treatment of DS by incineration is capital intensive due to energy requirement for dewatering and the need for complementary fuel source due to DS low calorific value. This could be replaced by a biotechnological approach. This study, therefore, investigated the biogas potential of different DS streams (different dewatering degrees) and the influence of the high calcium carbonate content of DS on its biogas potential. Dewatered DS (solid fraction) sample from filter press and the filtrate (liquid fraction) were collected from a partner wastepaper recycling company in Germany. The solid fraction and the liquid fraction were mixed in proportion to realize DS with different water content (55–91% fresh mass). Spiked samples of DS using deionized water, cellulose and calcium carbonate were prepared to simulate DS with varying calcium carbonate content (0– 40% dry matter). Seeding sludge was collected from an existing biogas plant treating sewage sludge in Germany. Biogas potential was studied using a 1-liter batch test system under the mesophilic condition and ran for 21 days. Specific biogas potential in the range 133- 230 NL/kg-organic dry matter was observed for DS samples investigated. It was found out that an increase in the liquid fraction leads to an increase in the specific biogas potential and a reduction in the absolute biogas potential (NL-biogas/ fresh mass). By comparing the absolute biogas potential curve and the specific biogas potential curve, an optimal dewatering degree corresponding to a water content of about 70% fresh mass was identified. This degree of dewatering is a compromise when factors such as biogas yield, reactor size, energy required for dewatering and operation cost are considered. No inhibitory influence was observed in the biogas potential of DS due to the reported high calcium carbonate content of DS. This study confirms that DS is a potential bioresource for biogas production. Further optimization such as nitrogen supplementation due to DS high C/N ratio can increase biogas yield.

Keywords: biogas, calcium carbonate, deinking sludge, dewatering, water content

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Authors: Emmanuel Billy

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This work is in the CABRISS project (H2020 projects) which aims at developing innovative cost-effective methods for the extraction of materials from the different sources of PV waste: Si based panels, thin film panels or Si water diluted slurries. Aluminum, silicon, indium, and silver will especially be extracted from these wastes in order to constitute materials feedstock which can be used later in a closed-loop process. The extraction of metals from silicon solar cells is often an energy-intensive process. It requires either smelting or leaching at elevated temperature, or the use of large quantities of strong acids or bases that require energy to produce. The energy input equates to a significant cost and an associated CO2 footprint, both of which it would be desirable to reduce. Thus there is a need to develop more energy-efficient and environmentally-compatible processes. Thus, ‘ionometallurgy’ could offer a new set of environmentally-benign process for metallurgy. This work demonstrates that ionic liquids provide one such method since they can be used to dissolve and recover silver. The overall process associates leaching, recovery and the possibility to re-use the solution in closed-loop process. This study aims to evaluate and compare different ionic liquids to leach and recover silver. An electrochemical analysis is first implemented to define the best system for the Ag dissolution. Effects of temperature, concentration and oxidizing agent are evaluated by this approach. Further, a comparative study between conventional approach (nitric acid, thiourea) and the ionic liquids (Cu and Al) focused on the leaching efficiency is conducted. A specific attention has been paid to the selection of the Ionic Liquids. Electrolytes composed of chelating anions are used to facilitate the lixiviation (Cl, Br, I,), avoid problems dealing with solubility issues of metallic species and of classical additional ligands. This approach reduces the cost of the process and facilitates the re-use of the leaching medium. To define the most suitable ionic liquids, electrochemical experiments have been carried out to evaluate the oxidation potential of silver include in the crystalline solar cells. Then, chemical dissolution of metals for crystalline solar cells have been performed for the most promising ionic liquids. After the chemical dissolution, electrodeposition has been performed to recover silver under a metallic form.

Keywords: electrodeposition, ionometallurgy, leaching, recycling, silver

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Authors: Aswandi Anas Husin, Cut Rizlani Kholibrina

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Harvesting camphor resin has been carried out since the beginning of civilization on the west coast of Sumatra. Oil or crystals that containing borneol are harvested from the camphor tree (Dryobalanops aromatica). Non-timber forest products are utilized for the manufacture of fragrances, antiseptics, anti-inflammatory, analgesic as well as effective for the treatment of blocked arteries. Based on exploration on the west coast of Sumatra, these endemic tree species were found remaining growing in groups on small spots in the lowlands to the hills. Some populations are found at an altitude of 700 meters above sea level in Kadabuhan, Jongkong and Sultan Daulat in Subulussalam district, Singkohor and Lake Paris in Aceh Singkil district, and Sirandorung and Manduamas in the north of Barus, Central Tapanuli district. These multi-purpose tree species was also identified as being able to adapt to the Singkil Peat Swamp. The decline in tree population has a direct impact on reducing their productivity. Conventionally, the crystals are harvested by cutting and splitting the stem into wooden blocks. In this way about 1.5-2.5 kg of crystals are obtained with various qualities. Camphor retrieval can also be done by making a notch on a standing tree trunk and collecting liquid resin (ombil) that is removed from the injured resin channel. Twigs and leaves also contain borneol. The aromatic content in this section opens opportunities for the supply of borneol through the distillation process. Vegetative propagation technology is needed to overcome the limitations of available seeds. This breeding strategy for vulnerable species starts with gathering genetic material from various provenances which are then used to support the provision of basic populations, breeding populations, multiplication populations and production populations for extensive development of camphor tree plantations

Keywords: camphor, conservation, natural borneol, productivity, vulnerable species

Procedia PDF Downloads 119

Authors: Y. Sakai, C. Wang

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The decrease in agricultural production due to soil deterioration has been an urgent task. Soil acidification is a potentially serious land degradation issue and it will have a major impact on agricultural productivity and sustainable farming systems. In China, acid soil is mainly distributed in the southern part, the decrease in agricultural production and heavy metal contamination are serious problems. In addition, not only environmental and health problems due to the exhaust gas such as mainly sulfur dioxide (SO₂) but also the generation of a huge amount of construction and demolition wastes with the accelerating urbanization has emerged as a social problem in China. Therefore, the need for the recycling and reuse of both desulfurization waste and waste concrete is very urgent and necessary. So we have investigated the effectiveness as acid soil amendments of both coal bio-briquette ash and waste concrete. In this paper, acid soil (AS1) in Nanjing (pH=6.0, EC=1.6dSm-1) and acid soil (AS2) in Guangzhou (pH=4.1, EC=0.2dSm-1) were investigated in soil amelioration test. Soil amendments were three coal bio-briquette ashes (BBA1, BBA2 and BBA3), the waste cement fine powders (CFP) ( < 200µm (particle diameter)), waste concrete particles (WCP) ( < 4.75mm ( < 0.6mm, 0.6-1.0mm, 1.0-2.0mm, 2.0-4.75mm)), and six mixtures with two coal bio-briquette ashes (BBA2 and BBA3), CFP, WCP( < 0.6mm) and WCP(2.0-4.75mm). In acid soil amelioration test, the three BBAs, CFP and various WCPs based on exchangeable calcium concentration were added to two acid soils. The application rates were from 0 wt% to 3.5 wt% in AS1 test and from 0 wt% to 6.0 wt% in AS2 test, respectively. Soil chemical properties (pH, EC, exchangeable and soluble ions (Na, Ca, Mg, K)) before and after mixing with soil amendments were measured. In addition, Al toxicity and the balance of salts (CaO, K₂O, MgO) in soil after amelioration was evaluated. The order of pH and exchangeable Ca concentration that is effective for acid soil amelioration was WCP(0.6mm) > CFP > WCP(2.0-4.25mm) > BB1 > BB2 > BB3. In all AS 1 and AS 2 amelioration tests using three BBAs, the pH and EC increased slightly with the increase of application rate and reached to the appropriate value range of both pH and EC in BBA1 only. Because BBA1 was higher value in pH and exchangeable Ca. After that, soil pH and EC with the increase in the application rate of BBA2, BBA3 and by using CFP, WC( < 0.6mm), WC(2.0-4.75mm) as soil amendment reached to each appropriate value range, respectively. In addition, the mixture amendments with BBA2, BBA3 CFP, WC( < 0.6mm), and WC(2.0-4.75mm) could ameliorate at a smaller amount of application rate in case of BBA only. And the exchangeable Al concentration decreased drastically with the increase in pH due to soil amelioration and was under the standard value. Lastly, the heavy metal (Cd, As, Se, Ni, Cr, Pb, Mo, B, Cu, Zn) contents in new soil amendments were under control standard values for agricultural use in China. Thus we could propose a new acid soil amelioration method using coal bio-briquette ash and waste concrete in China.

Keywords: acid soil, coal bio-briquette ash, soil amelioration, waste concrete

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Authors: Daisy Biswas, Samar Kanti Bose, M. Mozaffar Hossain

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The development of value added composite products from bamboo with the application of gluing technology can play a vital role in economic development and also in forest resource conservation of any country. In this study, the gluability of Bambusa balcooa and Bambusa vulgaris, two locally grown bamboo species of Bangladesh was assessed. As the culm wall thickness of bamboos decreases from bottom to top, a culm portion of up to 5.4 m and 3.6 m were used from the base of B. balcooa and B. vulgaris, respectively, to get rectangular strips of uniform thickness. The color of the B. vulgaris strips was yellowish brown and that of B. balcooa was reddish brown. The strips were treated in borax-boric, bleaching and carbonization for extending the service life of the laminates. The preservative treatments changed the color of the strips. Borax–boric acid treated strips were reddish brown. When bleached with hydrogen peroxide, the color of the strips turned into whitish yellow. Carbonization produced dark brownish strips having coffee flavor. Chemical constituents for untreated and treated strips were determined. B. vulgaris was more acidic than B. balcooa. Then the treated strips were used to develop three-layered bamboo laminated panel. Urea formaldehyde (UF) and polyvinyl acetate (PVA) were used as binder. The shear strength and abrasive resistance of the panel were evaluated. It was found that the shear strength of the UF-panel was higher than the PVA-panel for all treatments. Between the species, gluability of B. vulgaris was better and in some cases better than hardwood species. The abrasive resistance of B. balcooa is slightly higher than B. vulgaris; however, the latter was preferred as it showed well gluability. The panels could be used as structural panel, floor tiles, flat pack furniture component, and wall panel etc. However, further research on durability and creep behavior of the product in service condition is warranted.

Keywords: Bambusa balcooa, Bambusa vulgaris, polyvinyl acetate, urea formaldehyde

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Authors: Siah Koka, Rony Swennen

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Arumeru district is located in Arusha region in Upper Pangani basin in Tanzania. Economically it is dominated with agricultural activities. Banana, coffee, maize, beans, tomatoes, and cassava are the most important food and cash crops. This paper characterized the banana-based farming system of Arumeru district, evaluates its sustainability as well as research needs. The household questionnaire was performed on-site and on farm observation. Transect walk also involved to identify different agro- ecological zones. Results show that farm holdings (home gardens) are smaller than a hectare (0.7 ha) and continue to fragment as population continues to grow. Banana cultivation is the backbone of the farming systems present both in the upland and plains. In the upper belt banana found their place in the forest, which form the home garden structure typical to East African highland banana production systems. However, in the plains, cultivation is done in monoculture and depends heavily on irrigation. We found slightly less cultivars present and hypothetically more pest and disease pressure. This was mainly seen for Fusarium oxysporum species, which eradicates susceptible cultivars such as Mchare cultivars rapidly given the method of irrigation. The smaller permanent upland home garden plots provide thus a more suitable environment where banana perform better. It should be noted that findings indicated good performance to occur in the less suitable plains too. Good management is believed to be the most influencing factor, although our survey failed in identifying them. Population pressure is currently pushing the sustainable system in the uplands to its boundaries. Nutrient mining, deforestation and changing rain patterns threat production not only on Mt. Meru but on a global scale.

Keywords: Arumeru district, banana-based farming system, Tanzania, Arumeru district

Procedia PDF Downloads 172

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 97

Authors: Wiwin Tyas Istikowati, Futoshi Ishiguri, Haruna Aisho, Budi Sutiya, Imam Wahyudi, Kazuya Iizuka, Shinso Yokota

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The objective of this study was to investigate the anatomical characteristics of three native fast-growing species, terap (Artocarpus elasticus Reinw. ex Blume), medang (Neolitsea latifolia (Blume) S. Moore), and balik angin (Alphitonia excelsa (Fenzel) Reissek ex Benth) growing in the secondary forest in South Kalimantan, Indonesia for evaluating the possibility of tree breeding for wood quality. Cell lengths were investigated for 5 trees in each species at several different height positions (1.0, 3.0, 5.0, 7.0, 9.0, and 11.0 m above the ground). The mean values of fiber and vessel element lengths in terap, medang, and balik angin were 1.52 and 0.44, 1.16 and 0.53, and 1.02 and 0.49 mm, respectively. Fiber length in terap and balik angin gradually increased from pith to bark, whereas it increased up to 2 cm and then became nearly constant to the bark in medang. Vessel element length was almost constant from pith to bark in terap and balik angin, while slightly increased from pith to bark in medang. Fiber length in terap has a fluctuation pattern from ground level to top of the tree. It decreased up to 3 m above the ground, increased up to 5 m, and then decreased to the top of the tree. On the other hand, vessel element length slightly increased up to 5 m above the ground, and then decreased to the top of the tree. Both fiber and vessel element lengths in medang were almost constant from ground level to top of the tree, whereas decreased from ground level to top of the tree in balik angin. Significant difference at 1% level among trees was found in both fiber and vessel element length in both radial and longitudinal directions for terap and medang. Based on obtained results, it is concluded that the wood quality in fiber and vessel element lengths of terap and medang can be improved by tree breeding programs.

Keywords: anatomical properties, fiber length, vessel elements length, fast-growing species

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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: 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: 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: 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: 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

Procedia PDF Downloads 234

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: Luís R. Silva, Fábio Jesus, Catarina Bento, Ana C. Gonçalves

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Over the last few years, the traditional medicine has gained ground at nutritional and pharmacological level. The natural products and their derivatives have great importance in several drugs used in modern therapeutics. Plant-based systems continue to play an essential role in primary healthcare. Additionally, the utilization of their plant parts, such as leaves, stems and flowers as nutraceutical and pharmaceutical products, can add a high value in the natural products market, not just by the nutritional value due to the significant levels of phytochemicals, but also by to the high benefit for the producers and manufacturers business. Stems of Prunus avium L. are a byproduct resulting from the processing of cherry, and have been consumed over the years as infusions and decoctions due to its bioactive properties, being used as sedative, diuretic and draining, to relief of renal stones, edema and hypertension. In this work, we prepared a hydroethanolic and infusion extracts from stems of P. avium collected in Fundão Region (Portugal), and evaluate the phenolic profile by LC/DAD, antioxidant capacity, α-glucosidase inhibitory activity and protection of human erythrocytes against oxidative damage. The LC-DAD analysis allowed to the identification of 19 phenolic compounds, catechin and 3-O-caffolquinic acid were the main ones. In a general way, hydroethanolic extract proved to be more active than infusion. This extract had the best antioxidant activity against DPPH• (IC50=22.37 ± 0.28 µg/mL) and superoxide radical (IC50=13.93 ± 0.30 µg/mL). Furthermore, it was the most active concerning inhibition of hemoglobin oxidation (IC50=13.73 ± 0.67 µg/mL), hemolysis (IC50=1.49 ± 0.18 µg/mL) and lipid peroxidation (IC50=26.20 ± 0.38 µg/mL) on human erythrocytes. On the other hand, infusion revealed to be more efficient towards α-glucosidase inhibitory activity (IC50=3.18 ± 0.23 µg/mL) and against nitric oxide radical (IC50=99.99 ± 1.89 µg/mL). The Sweet cherry sector is very important in Fundão Region (Portugal), and taking profit from the great wastes produced during processing of the cherry to produce added-value products, such as food supplements cannot be ignored. Our results demonstrate that P. avium stems possesses remarkable antioxidant and free radical scavenging properties. It is therefore, suggest, that P. avium stems can be used as a natural antioxidant with high potential to prevent or slow the progress of human diseases mediated by oxidative stress.

Keywords: stems, Prunus avium, phenolic compounds, biological potential

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Authors: Lotsmart Fonjong

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The livelihood of rural communities in the West African state of Cameroon, which is largely dictated by natural forces (rainfall, temperatures, and soil), is today threatened by climate change and armed conflict. This paper investigates the extent to which rural communities are aware of climate change, how their perceptions of changes across different agro-ecological zones have impacted farming practices, output, and lifestyles, on the one hand, and the extent to which local armed conflicts are confounding their efforts and adaptation abilities. The paper is based on a survey conducted among small farmers in selected localities within the forest and savanna ecological zones of the conflict-ridden Northwest and Southwest Cameroon. Attention is paid to farmers’ gender, scale, and type of farming. Farmers’ perception of/and response to climate change are analysed alongside local rainfall and temperature data and mobilization for climate justice. Findings highlight the fact that farmers’ perception generally corroborates local climatic data. Climatic instability has negatively affected farmers’ output, food prices, standards of living, and food security. However, the vulnerability of the population varies across ecological zones, gender, and crop types. While these factors also account for differences in local response and adaptation to climate change, ongoing armed conflicts in these regions have further complicated opportunities for climate-driven agricultural innovations, inputs, and exchange of information among farmers. This situation underlines how poor communities, as victims, are forced into many complex problems outsider their making. It is therefore important to mainstream farmers’ perceptions and differences into policy strategies that consider both climate change and Anglophone conflict as national security concerns foe sustainable development in Cameroon.

Keywords: adaptation policies, climate change, conflict, small farmers, cameroon

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Authors: James Ladzekpo

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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

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Authors: Sokkhey Phauk, Takeo Okazaki

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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

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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

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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

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Authors: Shanti Swaroop Gupta, Bibekananda Mohapatra, S. K. Chaturvedi, Anand Bohra

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For sustainable development in India, there is an urgent need to follow the principles of industrial symbiosis in the industrial processes, under which the scraps, wastes, or by‐products of one industry can become the raw materials for another. This will not only help in reducing the dependence on natural resources but also help in gaining economic advantage to the industry. Gypsum is one such area in India, where the linear economy model of by-product gypsum utilization has resulted in unutilized legacy phosphogypsum stock of 64.65 million tonnes (mt) at phosphoric acid plants in 2020-21. In the future, this unutilized gypsum stock will increase further due to the expected generation of Flue Gas Desulphurization (FGD) gypsum in huge quantities from thermal power plants. Therefore, it is essential to transit from the linear to circular economy in Gypsum in India, which will result in huge environmental as well as ecological benefits. Gypsum is required in many sectors like Construction (Cement industry, gypsum boards, glass fiber reinforced gypsum panels, gypsum plaster, fly ash lime bricks, floor screeds, road construction), agriculture, in the manufacture of Plaster of Paris, pottery, ceramic industry, water treatment processes, manufacture of ammonium sulphate, paints, textiles, etc. The challenges faced in areas of quality, policy, logistics, lack of infrastructure, promotion, etc., for complete utilization of by-product gypsum have been discussed. The untapped potential of by-product gypsum utilization in various sectors like the use of gypsum in agriculture for sodic soil reclamation, utilization of legacy stock in cement industry on mission mode, improvement in quality of by-product gypsum by standardization and usage in building materials industry has been identified. Based on the measures required to tackle the various challenges and utilization of the untapped potential of gypsum, a comprehensive action plan for the transition from linear to the circular economy in gypsum in India has been formulated. The strategies and policy measures required to implement the action plan to achieve a circular economy in Gypsum have been recommended for various government departments. It is estimated that the focused implementation of the proposed action plan would result in a significant decrease in unutilized gypsum legacy stock in the next five years and it would cease to exist by 2027-28 if the proposed action plan is effectively implemented.

Keywords: circular economy, FGD gypsum, India, phosphogypsum

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Authors: Louise H. Gracioso, Marcela P.G. Baltazar, Ingrid R. Avanzi, Bruno Karolski, Luciana J. Gimenes, Claudio O. Nascimento, Elen A. Perpetuo

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Introduction: Higher copper concentrations promote a selection pressure on organisms such as plants, fungi and bacteria, which allows surviving only the resistant organisms to the contaminated site. This selective pressure keeps only the organisms most resistant to a specific condition and subsequently increases their bioremediation potential. Despite the bacteria importance for biosphere maintenance, it is estimated that only a small fraction living microbial species has been described and characterized. Due to the molecular biology development, tools based on analysis 16S ribosomal RNA or another specific gene are making a new scenario for the characterization studies and identification of microorganisms in the environment. News identification of microorganisms methods have also emerged like Biotyper (MALDI / TOF), this method mass spectrometry is subject to the recognition of spectroscopic patterns of conserved and features proteins for different microbial species. In view of this, this study aimed to isolate bacteria resistant to copper present in a Copper Processing Area (Sossego Mine, Canaan, PA) and identifies them in two different methods: Recent (spectrometry mass) and conventional. This work aimed to use them for a future bioremediation of this Mining. Material and Methods: Samples were collected at fifteen different sites of five periods of times. Microorganisms were isolated from mining wastes by culture enrichment technique; this procedure was repeated 4 times. The isolates were inoculated into MJS medium containing different concentrations of chloride copper (1mM, 2.5mM, 5mM, 7.5mM and 10 mM) and incubated in plates for 72 h at 28 ºC. These isolates were subjected to mass spectrometry identification methods (Biotyper – MALDI/TOF) and 16S gene sequencing. Results: A total of 105 strains were isolated in this area, bacterial identification by mass spectrometry method (MALDI/TOF) achieved 74% agreement with the conventional identification method (16S), 31% have been unsuccessful in MALDI-TOF and 2% did not obtain identification sequence the 16S. These results show that Biotyper can be a very useful tool in the identification of bacteria isolated from environmental samples, since it has a better value for money (cheap and simple sample preparation and MALDI plates are reusable). Furthermore, this technique is more rentable because it saves time and has a high performance (the mass spectra are compared to the database and it takes less than 2 minutes per sample).

Keywords: copper mining area, bioremediation, microorganisms, identification, MALDI/TOF, RNA 16S

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