Search results for: forest products pricing

Authors: Magdalena Twaruzek, Karolina Ropejko

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Mycotoxins are secondary metabolites of molds. Ochratoxin A (OTA) is the most common in the Polish climate. It is produced by fungi of the genera Aspergillus and Penicillium. It is produced as a result of improper food storage. It is present in many products that are consumed both by humans and animals: cereals, wheat gluten, coffee, dried fruit, wine, grape juice, spices, beer, and products based on them. OTA is nephrotoxic, hepatotoxic, potentially carcinogenic, and teratogenic. OTA mainly enters an organism by oral intake. The aim of the study was to detect the presence of OTA in milk, urine, and serum of lactating women. A survey was also conducted regarding the daily diet of women. The research group consisted of 32 lactating women (11 were the donors from the Milk Bank in Toruń, the other 21 were recruited for this study). Results of the analysis showed the occurrence of OTA only in 3 milk samples (9.38%). The minimum level was 0.01 ng/ml, while the maximum 0.018 ng/ml and the mean 0.0013 ng/ml. Twenty-six urine samples (81.25%) were OTA positive, with minimum level 0.013 ng/ml, maximum level 0.117 ng/ml and mean 0.0192 ng/ml. Also, all 32 serum samples (100%) were contaminated by OTA, with a minimum level of 0.099 ng/ml, a maximum level of 2.38 ng/ml, and a mean of 0.4649 ng/ml. In the case of 3 women, OTA was present in all tested body fluids. Based on the results, the following conclusions can be drawn: the breast-milk of women in the study group is slightly contaminated with ochratoxin A. Ten samples of urine contained ochratoxin A above its average content in tested samples. Moreover, serum of 8 women contains ochratoxin A at a level above the average content of this mycotoxin in tested samples. The average ochratoxin A level in serum in the presented studies was 0.4649 ng/ml, which is much lower than the average serum ochratoxin A level established in several countries in the world, i.e., 0.7 ng/ml. Acknowledgment: This study was supported by the Polish Minister of Science and Higher Education under the program 'Regional Initiative of Excellence' in 2019 - 2022 (Grant No. 008/RID/2018/19).

Keywords: breast-milk, urine, serum, contamination, ochratoxin A

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Authors: Ravi Kumar Pandit

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Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is growing a global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore the local people’s perception on climate change and the role of community forestry (CF) to combat climate change impacts. Two active community forest user groups (CFUGs) from Kaski and Syangja Districts in Nepal were selected as study sites, and various participatory tools were applied to collect primary data. Although most of the respondents were unaware about the words “Climate Change” in study sites, they were quite familiar with the irregularities in rainfall season and other weather extremities. 60% of the respondents had the idea that, due to increase in precipitation, there is a frequent occurrence of erosion, floods and landslide. Around 85% of the people agreed that community forests help in stabilizing soil, reducing the natural hazards like erosion, landslide. Biogas as an alternative source of cooking energy, and changes in crops and their varieties are the common adaptation measures that local people start practicing in both CFUGs in Nepal.

Keywords: climate change, community forestry, global warming, adaptation in Nepal

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Authors: George D. Ranis, Valasia Iakovoglou, George N. Zaimes

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Fires are one of the main types of disturbances that shape ecosystems in the Mediterranean region. However nowadays, climate alterations towards higher temperature regimes results on the increased levels of the intensity, frequency and the spread of fires inducing obstacles for the natural regeneration. Thasos Island is one of the Greek islands that have experienced those problems. Since 1984, a series of wildfires led to the reduction of forest cover from 61.6% to almost 20%. The negative impacts were devastating in many different aspects for the island. The absence of plant cover, post-wildfire precipitation and steep slopes were the major factors that induced severe soil erosion and intense flooding events. That also resulted to serious economic problems to the local communities and the ability of the burnt areas to regenerate naturally. Despite the substantial amount of published work regarding Thasos wildfires, there is no information related to post-wildfire effects on the hydrology and soil erosion. More research related to post-fire effects should help to an overall assessment of the negative impacts of wildfires on land degradation through processes such as soil erosion and flooding.

Keywords: erosion, land degradation, Mediterranean islands, regeneration, Thasos, wildfires

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Authors: Ali Mohammadi Bolban Abad, Fariborz Ahmadi

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Optimization in manufacture is a method to use limited resources to obtain the best performance and reduce waste. In this paper a new algorithm based on eurygaster life is introduced to obtain a plane in which task order and completion time of resources are defined. Evaluation results show our approach has less make span when the resources are allocated with some products in comparison to genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, NP-Hard problems, production scheduling

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Antonio J. Melendez-Martinez

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Beyond their role as natural colorants, some carotenoids are provitamins A and may be involved in health-promoting biological actions and contribute to reducing the risk of developing non-communicable diseases, including several types of cancer, cardiovascular disease, eye conditions, skin disorders or metabolic disorders. Given the versatility of carotenoids, the COST-funded European network to advance carotenoid research and applications in agro-food and health (EUROCAROTEN) is aimed at promoting health through the diet and increasing well-being by means. Stakeholders from 38 countries participate in this network, and one of its main objectives is to promote research on little-studied carotenoids. In this contribution, recent advances of our research group and collaborators in the study of two such understudied carotenoids, namely phytoene and phytofluene, the colorless carotenoids, are outlined. The study of these carotenoids is important as they have been largely neglected despite they are present in our diets, fluids, and tissues, and evidence is accumulating that they may be involved in health-promoting actions. More specifically, studies on their levels in diverse tomato and orange varieties were carried out as well as on their potential bioavailability from different dietary sources. Furthermore, the potential effect of these carotenoids on an animal model subjected to oxidative stress was evaluated. The tomatoes were grown in research greenhouses, and some of them were subjected to regulated deficit irrigation, a sustainable agronomic practice. The citrus samples were obtained from an experimental field. The levels of carotenoids were assessed using HPLC according to routine methodologies followed in our lab. Regarding the potential bioavailability (bioaccessibility) studies, different products containing colorless carotenoids, like fruits, juices, were subjected to simulated in vitro digestions, and their incorporation into mixed micelles was assessed. The effect of the carotenoids on oxidative stress was evaluated on the Caenorhabditis elegans model. For that purpose, the worms were subjected to oxidative stress by means of a hydrogen peroxide challenge. In relation to the presence of colorless carotenoids in tomatoes and orange varieties, it was observed that they are widespread in such products and that there are mutants with very high quantities of them, for instance, the Cara Cara or Pinalate mutant oranges. The studies on their bioaccessibility revealed that, in general, phytoene and phytofluene are more bioaccessible than other common dietary carotenoids, probably due to their distinctive chemical structure. About the in vivo antioxidant capacity of phytoene and phytofluene, it was observed that they both exerted antioxidant effects at certain doses. In conclusion, evidence on the importance of phytoene and phytofluene as dietary easily bioavailable and antioxidant carotenoids has been obtained in recent studies from our group, which can be important shortly to innovate in health-promotion through the development of functional foods and related products.

Keywords: carotenoids, health, functional foods, nutrition, phytoene, phytofluene

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Authors: K. Shailaja

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The advanced glycation end products (AGEs) formed between the reducing sugar and protein as a result of Oxidative stress and non-enzymatic glycosylation play an important role in pathogenesis of diabetes and aging complication. Glycation results in the production of free radicals. The oxidation process is believed to play an important role in AGEs formation. Thus agents with antioxidative property and antiglycation activity may retard the process of AGEs formation. Selected medicinal plants for the present study include Catharanthus roseus, Bougainvillea spectabilis (pink flowers), Cinnamomum tamala, Cinnamomum zeylanica, Abutilon indicum, Asparagus racemosus, and Sapindus emarginatus. The crude ethanolic extracts of the selected medicinal plants at varying concentrations ranging from 1-100 mg/ml were evaluated for in vitro antioxidant and protein glycation activities by FRAP and glucose-BSA assay respectively. Among all the plants tested, Bougainvillea spectabilis, Catharanthus roseus and Abutilon indicum showed strong antioxidant activity The antioxidant activity was expressed as mg of Gallic acid/ gm sample which was found to be 4.3 mg, 1.3mg, and 1.3mg respectively for Bougainvillea spectabilis, Catharanthus roseus and Abutilon indicum. The results of inhibition of the initial glycation product i.e., fructosamine was found to be 35% for Asparagus racemosus, Cinnamomum tamala and Abutilon indicum followed by the other plant extracts. The results indicate that these plants are potential sources of natural antioxidants which have free radical scavenging activity and might be used not only for reducing oxidative stress in diabetes but also open a new research avenues in the field of Natural Products.

Keywords: in vitro antioxidant activity, anti-glycation activity, ethanol extracts, polyphenols, Catharanthus roseus, Cinnamomum tamala

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Authors: Bo Wang

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As the first high-resolution civil optical satellite, ZY-3 satellite is able to obtain high-resolution multi-view images with three linear array sensors. The images can be used to generate Digital Elevation Models (DEM) through dense matching of stereo images. However, due to the clouds, forest, water and buildings covered on the images, there are some problems in the dense matching results such as outliers and areas failed to be matched (matching holes). This paper introduced an algorithm to verify the accuracy of DEM that generated by ZY-3 satellite with Shuttle Radar Topography Mission (SRTM). Since the accuracy of SRTM (Internal accuracy: 5 m; External accuracy: 15 m) is relatively uniform in the worldwide, it may be used to improve the accuracy of ZY-3 DEM. Based on the analysis of mass DEM and SRTM data, the processing can be divided into two aspects. The registration of ZY-3 DEM and SRTM can be firstly performed using the conjugate line features and area features matched between these two datasets. Then the ZY-3 DEM can be refined by eliminating the matching outliers and filling the matching holes. The matching outliers can be eliminated based on the statistics on Local Vector Binning (LVB). The matching holes can be filled by the elevation interpolated from SRTM. Some works are also conducted for the accuracy statistics of the ZY-3 DEM.

Keywords: ZY-3 satellite imagery, DEM, SRTM, refinement

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Authors: Grazia Disciglio, Francesco Lops, Annalisa Tarantino, Emanuele Tarantino

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The parasitic weed specie Phelipanche ramosa (L) Pomel is one of the major constraints in tomato crop in Apulia region (southern Italy). The experimental was considered to investigate the effect of six organic compounds (Olive miller wastewater, Allil isothiocyanate®, Alfa plus K®, Radicon®, Rizosum Max®, Kendal Nem®) on the naturally infested field of tomato growing season in 2016. The randomized block design with 3 replicates was adopted. Tomato seedling were transplant on 19 May 2016. During the growing cycle of the tomato at 74, 81, 93 and 103 days after transplantation (DAT), the number of parasitic shoots (branched plants) that had emerged in each plot was determined. At harvesting on 13 September 2016 the major quanti-qualitative yield parameters were determined, including marketable yield, mean weight, dry matter, soluble solids, fruit colour, pH and titratable acidity. The treatments provided the results show that none of treatments provided complete control against P. ramosa. However, among the products tested Olive miller wastewater, Alfa plus K®, Rizosum Max® and Kendal Nem® products applied to the soil show the number of emerged shoots significantly lower than Radicon® and especially than the Allil isothiocyanate® treatment and the untreated control. Regarding the effect of different treatments on the tomato productive parameters, the marketable yield resulted significantly higher in the same mentioned treatments which gave the lower P. ramosa infestation. No significative differences for the other fruit characteristics were observed.

Keywords: processing tomato crop, Phelipanche ramosa, olive-mill wastewater, organic fertilizers

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Authors: Ons Triki, Fathi Abid

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Along with the increase in the use of leasing contracts in corporate finance, multiple studies aim to model the credit risk of the lease in order to cover the losses of the lessor of the asset if the lessee goes bankrupt. In the current research paper, a convertible lease contract is elaborated in a continuous time stochastic universe aiming to ensure the financial stability of the firm and quickly recover the losses of the counterparties to the lease in case of default. This work examines the term structure of the lease rates taking into account the credit default risk and the capital structure of the firm. The interaction between the lessee's capital structure and the equilibrium lease rate has been assessed by applying the competitive lease market argument developed by Grenadier (1996) and the endogenous structural default model set forward by Leland and Toft (1996). The cumulative probability of default was calculated by referring to Leland and Toft (1996) and Yildirim and Huan (2006). Additionally, the link between lessee credit risk and lease rate was addressed so as to explore the impact of convertible lease financing on the term structure of the lease rate, the optimal leverage ratio, the cumulative default probability, and the optimal firm value by applying an endogenous conversion threshold. The numerical analysis is suggestive that the duration structure of lease rates increases with the increase in the degree of the market price of risk. The maximal value of the firm decreases with the effect of the optimal leverage ratio. The results are indicative that the cumulative probability of default increases with the maturity of the lease contract if the volatility of the asset service flows is significant. Introducing the convertible lease contract will increase the optimal value of the firm as a function of asset volatility for a high initial service flow level and a conversion ratio close to 1.

Keywords: convertible lease contract, lease rate, credit-risk, capital structure, default probability

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Authors: Nuraeni, Suryanti, Saida, Annas Boceng

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Farm forestry is a forest where farmers or landowners do cultivation and farming activities on their land. This study aims to determine the dimensions of sustainable development of farm forestry and to analyze the leverage factors to improve the sustainability status of farm forestry management in Bulukumba Regency. This research was conducted in Kajang District, Bulukumba Regency. The analysis of the sustainability of farm forestry management applied Multi-Dimensional Scaling (MDS), a modification of the Rapid Appraisal of The Status of Farming (RAPFARM). The index value of farm forestry sustainability was by 62.01% for ecological dimension, 51.54% for economic dimension, 61.00% for the social and cultural dimension, and 63.24% for legal and institutional dimension with sustainable enough category status. Meanwhile, the index value for the technology and infrastructure was by 47.16% of less sustainable category status. The result of leverage analysis of attributes for the dimensions of ecological, economic, social and cultural, legal and institutional as well as infrastructure and technology afforded twenty-two (22) leverage sensitive factors that influence the sustainability of farm forestry.

Keywords: farm forestry, South Sulawesi, management, sustainability

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Authors: Martin Grootveld, Benita Percival, Sarah Moumtaz, Kerry L. Grootveld

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Objectives/Hypotheses: The adverse health effect potential of dietary lipid oxidation products (LOPs) has evoked much clinical interest. Therefore, we employed a ¹H NMR-linked Principal Component Regression (PCR) chemometrics modelling strategy to explore relationships between data matrices comprising (1) aldehydic LOP concentrations generated in culinary oils/fats when exposed to laboratory-simulated shallow frying practices, and (2) the prior saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acid (PUFA) contents of such frying media (FM), together with their heating time-points at a standard frying temperature (180 ^oC). Methods: Corn, sunflower, extra virgin olive, rapeseed, linseed, canola, coconut and MUFA-rich algae frying oils, together with butter and lard, were heated according to laboratory-simulated shallow-frying episodes at 180 ^oC, and FM samples were collected at time-points of 0, 5, 10, 20, 30, 60, and 90 min. (n = 6 replicates per sample). Aldehydes were determined by ¹H NMR analysis (Bruker AV 400 MHz spectrometer). The first (dependent output variable) PCR data matrix comprised aldehyde concentration scores vectors (PC1* and PC2*), whilst the second (predictor) one incorporated those from the fatty acid content/heating time variables (PC1-PC4) and their first-order interactions. Results: Structurally complex trans,trans- and cis,trans-alka-2,4-dienals, 4,5-epxy-trans-2-alkenals and 4-hydroxy-/4-hydroperoxy-trans-2-alkenals (group I aldehydes predominantly arising from PUFA peroxidation) strongly and positively loaded on PC1*, whereas n-alkanals and trans-2-alkenals (group II aldehydes derived from both MUFA and PUFA hydroperoxides) strongly and positively loaded on PC2*. PCR analysis of these scores vectors (SVs) demonstrated that PCs 1 (positively-loaded linoleoylglycerols and [linoleoylglycerol]:[SFA] content ratio), 2 (positively-loaded oleoylglycerols and negatively-loaded SFAs), 3 (positively-loaded linolenoylglycerols and [PUFA]:[SFA] content ratios), and 4 (exclusively orthogonal sampling time-points) all powerfully contributed to aldehydic PC1* SVs (p 10^-3 to < 10^-9), as did all PC1-3 x PC4 interaction ones (p 10^-5 to < 10^-9). PC2* was also markedly dependent on all the above PC SVs (PC2 > PC1 and PC3), and the interactions of PC1 and PC2 with PC4 (p < 10^-9 in each case), but not the PC3 x PC4 contribution. Conclusions: NMR-linked PCR analysis is a valuable strategy for (1) modelling the generation of aldehydic LOPs in heated cooking oils and other FM, and (2) tracking their unsaturated fatty acid (UFA) triacylglycerol sources therein.

Keywords: frying oils, lipid oxidation products, frying episodes, chemometrics, principal component regression, NMR Analysis, cytotoxic/genotoxic aldehydes

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Ching Shya Lee, Mohamed Kheireddine Aroua, Wan Mohd Ashri Wan Daud, Patrick Cognet, Yolande Peres, Mohammed Ajeel

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In recent years, with the decreasing supply of fossil fuel, renewable energy has received a significant demand. Biodiesel which is well known as vegetable oil based fatty acid methyl ester is an alternative fuel for diesel. It can be produced from transesterification of vegetable oils, such as palm oil, sunflower oil, rapeseed oil, etc., with methanol. During the transesterification process, crude glycerol is formed as a by-product, resulting in 10% wt of the total biodiesel production. To date, due to the fast growing of biodiesel production in worldwide, the crude glycerol supply has also increased rapidly and resulted in a significant price drop for glycerol. Therefore, extensive research has been developed to use glycerol as feedstock to produce various added-value chemicals, such as tartronic acid, mesoxalic acid, glycolic acid, glyceric acid, propanediol, acrolein etc. The industrial processes that usually involved are selective oxidation, biofermentation, esterification, and hydrolysis. However, the conversion of glycerol into added-value compounds by electrochemical approach is rarely discussed. Currently, the approach is mainly focused on the electro-oxidation study of glycerol under potentiostatic mode for cogenerating energy with other chemicals. The electro-organic synthesis study from glycerol under galvanostatic mode is seldom reviewed. In this study, the glycerol was converted into various added-value compounds by electrochemical method under galvanostatic mode. This work aimed to study the possible compounds produced from glycerol by electrochemical technique in a one-pot electrolysis cell. The electro-organic synthesis study from glycerol was carried out in a single compartment reactor for 8 hours, over the platinum cathode and anode electrodes under acidic condition. Various parameters such as electric current (1.0 A to 3.0 A) and reaction temperature (27 °C to 80 °C) were evaluated. The products obtained were characterized by using gas chromatography-mass spectroscopy equipped with an aqueous-stable polyethylene glycol stationary phase column. Under the optimized reaction condition, the glycerol conversion achieved as high as 95%. The glycerol was successfully converted into various added-value chemicals such as ethylene glycol, glycolic acid, glyceric acid, acetaldehyde, formic acid, and glyceraldehyde; given the yield of 1%, 45%, 27%, 4%, 0.7% and 5%, respectively. Based on the products obtained from this study, the reaction mechanism of this process is proposed. In conclusion, this study has successfully converted glycerol into a wide variety of added-value compounds. These chemicals are found to have high market value; they can be used in the pharmaceutical, food and cosmetic industries. This study effectively opens a new approach for the electrochemical conversion of glycerol. For further enhancement on the product selectivity, electrode material is an important parameter to be considered.

Keywords: biodiesel, glycerol, electrochemical conversion, galvanostatic mode

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Authors: Isa Muhammad Zumo

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The African Great Green Wall (GGW) is a significant initiative in northern Nigeria because it promotes land restoration and conservation utilizing both commercial and species of forest trees while also helping to mitigate desertification and hazards from the sand dunes and shifting Sahara deserts. Conflicts and weather, however, pose a significant danger to the achievement of these goals. The scientific method for monitoring the vegetation dynamics since inception has not received the required attention, despite the African Development Bank (ADB)'s help in funding the project and its integration into the state's development plans for GGW initiatives. This study will monitor the changes in the vegetation cover of the great green wall within Yobe State Nigeria from 2014 to 2023. The vegetation dynamics will be monitored using Landsat 8 Operational Land Imager (OLI) for 6 years at 2 years intervals. The result will show the fluctuations in the vegetation cover density within the period of study. This will guide the design and implementation of policies of the GGW in achieving its objectives. The result can also contribute to the realization of Sustainable Development Goal (SDG) Target 13.2: Integrate climate change measures into national policies, strategies, and planning.

Keywords: monitoring, green wall, Landsat 8, Nigeria

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Authors: Maria Jose Granero Paris, Ana Isabel Jimenez Zarco, Agustin Pablo Alvarez Herranz

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In the industrial sector the collaboration along the supply chain is key especially in order to develop product, production methods or process innovations. The access to resources and knowledge not being available inside the company, the achievement of cost competitive solutions, the reduction of the time required to innovate are some of the benefits linked with the collaboration with suppliers. The big industrial manufacturers have a long tradition to collaborate with their suppliers to develop new products in the developed countries. Since they have increased their global supply chains and global sourcing activities, the objective of the research is to analyse if the same best practices, way of working, experiences, information technology tools, governance methodologies are applied when collaborating with suppliers in the developed world or in developing countries. Most of the current research focuses to analyse the Supply Chain Collaboration in the developed countries and in recent years the number of publications related to the Supply Chain Collaboration in developing countries has increased, but there is still a lack of research comparing both and analysing the similarities, differences and key success factors among the Supply Chain Collaboration practices in developed and developing countries. With this gap in mind, the research under preparation will focus on the following goals: -Identify the most important elements required for a successful supply chain collaboration in the developed and developing countries. -Set up the optimal governance framework to manage the supply chain collaboration in the developed and developing countries. -Define some recommendations about required improvements in the current supply chain collaboration business relationship practices in place. Following the case methodology we will analyze the way manufacturers and suppliers collaborate in the development of new products, production methods or process innovations and in the set up of new global supply chains in two industries with different level of technology intensity and collaboration history being the automotive and aerospace industries.

Keywords: global supply chain networks, Supply Chain Collaboration, supply chain governance, supply chain performance

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Authors: Zhang Hui, Wu Caiqiu, Yuan Xuyin, Qiu Jie, Zhang Hanpei

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The heavy metal contaminations were determined with a detailed soil survey in roadside soils along Shenyang-Dalian Highway of Liaoning Province (China) and Pb, Cu, Cd, Ni and Zn were analyzed using the atomic absorption spectrophotometric method. The average concentration of Pb, Cu, Cd, Ni and Zn in roadside soils was determined to be 43.8, 26.5, 0.119, 32.1, 71.3 mg/kg respectively, and all of the heavy metal contents were higher than the background values. Different heavy metal distribution regularity was found in different land use type of roadside soil, there was an obvious peak of heavy concentration at 25m from road edge in the farmland, while in the forest and orchard soil, all heavy metals gradually decreased with the increase of distance from road edge and conformed to the exponential model. Furthermore, the heavy metal contents of heavy metals except Cd were markedly increased compared with those in 1999 and 2007, and the heavy metals concentrations of Shenyang- Dalian Highway were considered medium or low in comparison with those in other cities around the world. The assessment of heavy metal contamination of roadside soils illustrated a common low pollution for all heavy metal and recommended that more attention should be paid to Pb contamination in roadside soils in Shenyang-Dalian Highway.

Keywords: heavy metal contamination, roadside, highway, Nemerow Pollution Index

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Authors: K. B. Ramappa, A. V. Manjunatha

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Consumerism in India is witnessing unprecedented growth driven by favourable demographics, rising young and working population, rising income levels, urbanization and growing brand orientation. In addition, the increasing level of awareness on health, hygiene and quality has made the consumers to think on the fairly traded goods and brands. This has made retailing extremely important to everyone because without retailers’ consumers would not have access to day-to-day products. The increased competition among different retailers has contributed significantly towards rising consumer awareness on quality products and brand loyalty. Many existing empirical studies have mainly focused on net saving of consumers at organised retail via-a-vis unorganised retail shops. In this article, authors have analysed the Bangalore consumers' attitudes towards buying of fruits and vegetables and their choice of retail outlets. The primary data was collected from 100 consumers belonging to the Bangalore City during October 2014. Sample consumers buying at supermarkets, convenience stores and hypermarkets were purposively selected. The collected data was analyzed using descriptive statistics and multinomial logit model. It was found that among all variables, quality and prices were major accountable factors for buying fruits and vegetables at organized retail shops. The empirical result of multinomial logit model reveals that annual net income was positively associated with the Big Bazar and Food World consumers and negatively associated with the Reliance Fresh, More and Niligiris consumers, as compared with the HOPCOMS consumers. Per month expenditure on fruits and vegetables was positively and age of the consumer was negatively related to the consumers’ choice of buying at modern retail markets. Consumers were willing to buy at modern retail outlets irrespective of the distance.

Keywords: organized retailers, consumers' attitude, consumers' preference, fruits, vegetables, multinomial logit, Bangalore

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Authors: Josiane Yaguibou, Ngoy Kishimba, Issiaka V. Coulibaly, Sabrina Pestilli, Falinirina Razanalison, Hantanirina V. Andremanisa

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Background In Madagascar modern contraceptive prevalence rate increased from 18% in 2003 to 43% in 2021. Anecdotal evidence suggests that increased use and frequent stock out in public health facilities of male condoms and medroxyprogesterone acetate (MPA) can be related to diverted use of these products. This study analyzed the use of contraceptives and mode of utilization (correct or diverted) at the community level in the period 2019-2023 in Madagascar. Methodology: The study included a literature review, a quantitative survey combined with a qualitative study. It was carried out in 10 regions out of the 23 of the country. Eight regions (Bongolava, Vakinakaratra, Italy, Hautre Matsiatra, Betsiboka, Diana, Sofia and Anosy) were selected based on a study that showed existence of medroxyprogesterone acetate in pigs (MPA). The remaining 2 regions were selected due to high mCPR (Atsimo Andrefana) and to ensure coverage of all geographical zones in the country (Alaotra Mangoro). Sample random method was used, and the sample size was identified at 300 individuals per region. Zonal distribution is based on the urbanization rate for the region. 6 focus group discussions were organized in 3 regions, equally distributed between rural and urban areas. Key findings: Overall, 67% of those surveyed or their partner are currently using contraception. Injectables (MPA) are the most popular choice (33%), followed by implants and male condoms, 12% and 9%, respectively. The majority of respondents use condoms to prevent unwanted pregnancy but also to prevent STDs. Still, 43% of respondents use condoms for other purposes, reaching 52% of respondents in urban areas and 71,2% in the age group 15-18. Diverted use includes hair growth (18.9%), as a toy (18.8%), cleaning the screen of electronic devices (10 %), cleaning shoes (3.1%) and for skincare (1.6%). Injectables are the preferred method of contraception both in rural areas (35%) and urban areas (21.2%). However, diverted use of injectables was confirmed by 4% of the respondents, ranging from 3 % in rural areas to 12% in urban. The diverted use of injectables in pig rearing was to avoid pregnancy and facilitate pig’s growth. Program Implications: The study confirmed the diverted use of some contraceptives. The misuse of male condoms is among the causes of stockouts of products in public health facilities, limiting their availability for pregnancy and STDs prevention. The misuse of injectables in pigs rearing needs to be further studied to learn the full extent of the misuse and eventual implications for meat consumption. The study highlights the importance of including messages on the correct use of products during sensibilization activities. In particular, messages need to address the anecdotal and false effects of male condoms, especially amongst young people. For misuse of injectables is critical to sensibilize farmers and veterinaries on possible negative effects for humans.

Keywords: diverted use, injectables, male condoms, sensibilization

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Authors: Prashant Verma

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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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Authors: Pradeep Kulshrestha, Maulana Ayoub Ali

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The concept of financial inclusion has been tabled in the whole world where practitioners, academicians, policy makers and economists are working hard to look for the best possible opportunities in order to enable the whole society to be in the banking cycle. The Islamic banking system is considered to be one of the said opportunities. Countries like the United Kingdom, United States of America, Malaysia, Saudi Arabia, the whole of the United Arab Emirates and many African countries have accommodated the aspect of Islamic banking in the conventional banking system as one of the financial inclusion strategies. This paper tries to analyse the current state of affairs of the Islamic Banking system in Tanzania in order to understand the improvement of the provision of Islamic banking products and services in the said country. The paper discusses the historical background of the banking system in Tanzania, the level of penetration of banking products and services and the coming of the Islamic banking system in the country. Furthermore, the paper discusses banking regulatory bodies, legal instruments governing banking operations as well as number of legal challenges facing Islamic banking operations in the country. Following a critical literature review, the paper discovered that there is no legal instrument which talks about the introduction and provision of Islamic banking system in Tanzania. Furthermore, the Islamic banking system was considered as a banking product which is absolutely incorrect because Islamic banking is considered to be as a banking system of its own. In addition to that, it has been discovered that lack of a proper regulatory system and legal instruments to harmonize the conventional and Islamic banking systems has resulted in the closure of one Islamic window in the country, which in the end affects the credibility of the newly introduced banking system. In its conclusive remarks, the paper suggests that Tanzania should work on all legal challenges affecting the smooth operations of the Islamic banking system. This can be in a way of adopting various Islamic banking legal models which are used in countries like Malaysia and others, or a borrowing legal harmonization process which has been adopted by the UK, Uganda, Nigeria and Kenya.

Keywords: Islamic banking, Islamic windows, regulations, banks

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

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In recent times awareness about the environment and green purchase has been on the increase across nations due to global warming. Previous researchers have attempted to determine what actually influences the purchase intention of consumers in this environmentally conscious epoch. The consumers too have become conscious of what to buy and who to buy from in their purchasing decisions as this action will reflect their concern about the environment and their personal well-being. This trend is a widespread phenomenon in most developed countries of the world. On the contrary evidence revealed that only 5% of the populations of Nigeria involve in green purchase activities thus making the country lag behind its counterparts in green practices. This is not a surprise as Nigeria is facing problems of inadequate green knowledge, non-enforcement of environmental regulations, sensitivity to the price of green products when compared with the conventional ones and distrust towards green products which has been deduced from prior studies of other regions. The main objectives of this study is to examine the direct antecedents of green purchase intention (green availability, government regulations, perceived green knowledge, perceived value and green price sensitivity) in Nigeria and secondly to establish the mediating role of perceived behavioral control on the relationship between these antecedents and green purchase intention. The study adopts quantitative method whereby 700 questionnaires were administered to lecturers in three Nigerian universities. 502 datasets were collected which represents 72 percent response rate. After screening the data only 440 were usable and analyzed using structural equation modeling (SEM) and bootstrapping. From the findings, three antecedents have significant direct relationships with green purchase intention (perceived green knowledge, perceived behavioral control, and green availability) while two antecedents have positive and significant direct relationship with perceived behavioral control (perceived value and green price sensitivity). On the other hand, PBC does not mediate any of the paths from the predictors to criterion variable. This result is discussed in the Nigerian context.

Keywords: Green Availability, Green Price Sensitivity, Green Purchase Intention, Perceived Green Knowledge, Perceived Value

Procedia PDF Downloads 426

Authors: Loveline Ambo Angwah

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The processing of cassava from tubers or roots into food using crude and rudimentary method (hand peeling, grating, frying and to sun drying) is a very cumbersome and difficult process. The crude methods are time consuming and labour intensive. While on the other hand, modern processing method, that is using machines to perform the various processes as washing, peeling, grinding, oven drying, fermentation and frying is easier, less time consuming, and less labour intensive. Rudimentarily, cassava roots are processed into numerous products and utilized in various ways according to local customs and preferences. For the people of Ngwo village, cassava is transformed locally into flour or powder form called ‘cumcum’. It is also sucked into water to give a kind of food call ‘water fufu’ and fried to give ‘garri’. The leaves are consumed as vegetables. Added to these, its relative high yields; ability to stay underground after maturity for long periods give cassava considerable advantage as a commodity that is being used by poor rural folks in the community, to fight poverty. It plays a major role in efforts to alleviate the food crisis because of its efficient production of food energy, year-round availability, tolerance to extreme stress conditions, and suitability to present farming and food systems in Africa. Improvement of cassava processing and utilization techniques would greatly increase labor efficiency, incomes, and living standards of cassava farmers and the rural poor, as well as enhance the-shelf life of products, facilitate their transportation, increase marketing opportunities, and help improve human and livestock nutrition. This paper presents a general overview of crude ways in cassava processing and utilization methods now used by subsistence and small-scale farmers in Ngwo village of the North West region in Cameroon, and examine the opportunities of improving processing technologies. Cassava needs processing because the roots cannot be stored for long because they rot within 3-4 days of harvest. They are bulky with about 70% moisture content, and therefore transportation of the tubers to markets is difficult and expensive. The roots and leaves contain varying amounts of cyanide which is toxic to humans and animals, while the raw cassava roots and uncooked leaves are not palatable. Therefore, cassava must be processed into various forms in order to increase the shelf life of the products, facilitate transportation and marketing, reduce cyanide content and improve palatability.

Keywords: cassava roots, crude ways, food system, poverty

Procedia PDF Downloads 166

Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

Procedia PDF Downloads 82

Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

Procedia PDF Downloads 313

Authors: Haritha Saranga

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Service quality has become an important driver of competition in manufacturing industries of late, as many products are being sold in conjunction with service offerings. With increase in computational power and data capture capabilities, it has become possible to analyze and estimate various aspects of service quality at the granular level and determine their impact on business performance. In the current study context, dealer level, model-wise warranty data from one of the top two-wheeler manufacturers in India is used to estimate service quality of individual dealers and its impact on warranty related costs and sales performance. We collected primary data on warranty costs, number of complaints, monthly sales, type of quality upgrades, etc. from the two-wheeler automaker. In addition, we gathered secondary data on various regions in India, such as petrol and diesel prices, geographic and climatic conditions of various regions where the dealers are located, to control for customer usage patterns. We analyze this primary and secondary data with the help of a variety of analytics tools such as Auto-Regressive Integrated Moving Average (ARIMA), Seasonal ARIMA and ARIMAX. Study results, after controlling for a variety of factors, such as size, age, region of the dealership, and customer usage pattern, show that service quality does influence sales of the products in a significant manner. A more nuanced analysis reveals the dynamics between product quality and service quality, and how their interaction affects sales performance in the Indian two-wheeler industry context. We also provide various managerial insights using descriptive analytics and build a model that can provide sales projections using a variety of forecasting techniques.

Keywords: service quality, product quality, automobile industry, business analytics, auto-regressive integrated moving average

Procedia PDF Downloads 120

Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 196

Authors: Mathias Twizeyimana, Urmila Adhikari, Julius P. Sserumaga, David Ingham

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The management of aflatoxins (naturally occurring toxins produced by certain fungi, most importantly Aspergillus flavus and A. parasiticus) relies mostly on the use of best cultural practices and, in some cases, the use of the biological control consisting of atoxigenic strains inhibiting the toxigenic strains through competition resulting in considerable toxin reduction. At AgBiome, we have built a core collection of over 100,000 fully sequenced microbes from diverse environments and employ both the microbes and their sequences in the discovery of new biological products for disease and pest control. The most common approach to finding beneficial microbes consists of isolating microorganisms from samples collected from diverse environments, selecting antagonistic strains through empirical screening, studying modes of action, and stabilization through the formulation of selected microbial isolates. A total of 608 diverse bacterial strains were screened using a high-throughput assay (48-well assay) to identify strains that inhibit toxigenic A. flavus growth on maize kernels. Active strains in 48-well assay had their pathogen inhibiting activity confirmed using the Flask Assay and were concurrently tested for their ability to reduce the aflatoxin content in maize grains. Strains with best growth inhibition and reduction of aflatoxin were tested in the greenhouse and field trials. From the field trials, three bacterial strains, AFS000009 (Pseudomonas chlororaphis), AFS032321 (Bacillus subtilis), AFS024683 (Bacillus velezensis), had aflatoxin concentrations (ppb) values that were significantly lower than those of inoculated control. The identification of biological products with high efficacy in inhibiting pathogen growth and eventually reducing the aflatoxin content will provide a valuable alternative to control strategies used in aflatoxin contamination management.

Keywords: aflatoxin, microorganism bacteria, biocontrol, beneficial microbes

Procedia PDF Downloads 182

Authors: Mustafa M. Donma, Orkide Donma

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Metabolisms of macrominerals, those of calcium, phosphorus and magnesium, are closely associated with the metabolism of vitamin D. Particularly magnesium, the second most abundant intracellular cation, is related to biochemical and metabolic processes in the body, such as those of carbohydrates, proteins and lipids. The status of each mineral was investigated in obesity to some extent. Their products and ratios may possibly give much more detailed information about the matter. The aim of this study is to investigate possible relations between each macromineral and some obesity-related parameters. This study was performed on 235 children, whose ages were between 06-18 years. Aside from anthropometric measurements, hematological analyses were performed. TANITA body composition monitor using bioelectrical impedance analysis technology was used to establish some obesity-related parameters including basal metabolic rate (BMR), total fat, mineral and muscle masses. World Health Organization body mass index (BMI) percentiles for age and sex were used to constitute the groups. The values above 99^th percentile were defined as morbid obesity. Those between 95^th and 99^th percentiles were included into the obese group. The overweight group comprised of children whose percentiles were between 95 and 85. Children between the 85^th and 15^th percentiles were defined as normal. Metabolic syndrome (MetS) components (waist circumference, fasting blood glucose, triacylglycerol, high density lipoprotein cholesterol, systolic pressure, diastolic pressure) were determined. High performance liquid chromatography was used to determine Vitamin D status by measuring 25-hydroxy cholecalciferol (25-hydroxy vitamin D₃, 25(OH)D). Vitamin D values above 30.0 ng/ml were accepted as sufficient. SPSS statistical package program was used for the evaluation of data. The statistical significance degree was accepted as p < 0.05. The important points were the correlations found between vitamin D and magnesium as well as phosphorus (p < 0.05) that existed in the group with normal BMI values. These correlations were lost in the other groups. The ratio of phosphorus to magnesium was even much more highly correlated with vitamin D (p < 0.001). The negative correlation between magnesium and total fat mass (p < 0.01) was confined to the MetS group showing the inverse relationship between magnesium levels and obesity degree. In this group, calcium*magnesium product exhibited the highest correlation with total fat mass (p < 0.001) among all groups. Only in the MetS group was a negative correlation found between BMR and calcium*magnesium product (p < 0.05). In conclusion, magnesium is located at the center of attraction concerning its relationships with vitamin D, fat mass and MetS. The ratios and products derived from macrominerals including magnesium have pointed out stronger associations other than each element alone. Final considerations have shown that unique correlations of magnesium as well as calcium*magnesium product with total fat mass have drawn attention particularly in the MetS group, possibly due to the derangements in some basic elements of carbohydrate as well as lipid metabolism.

Keywords: macrominerals, metabolic syndrome, pediatric obesity, vitamin D

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Authors: Aldrin R. Logdat

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The insights and wisdom of the Alangan Mangyans offer valuable guidance for developing alternative ecological and development frameworks. Their reverence for the sacredness of the land, rooted in their traditional cosmology, guides their harmonious relationship with nature. Through their practice of swidden farming, ecosystem preservation takes precedence as they carefully manage agricultural activities and allow for forest regeneration. This approach aligns with natural processes, reflecting their profound understanding of the natural world. Similar to early advocates like Aldo Leopold, the emphasis is on shifting our perception of land from a commodity to a community. The indigenous wisdom of the Alangan Mangyans provides practical and sustainable approaches to preserving the interdependence of the biotic community and ecosystems. By integrating their cultural heritage, we can transcend the prevailing anthropocentric mindset and foster a meaningful and sustainable connection with nature. The revitalization of cultural energy and the embrace of alternative frameworks require learning from indigenous peoples like the Alangan Mangyans, where reverence for the land and the recognition of the interconnectedness between humanity and nature are prioritized. This paves the way for a future where harmony with nature and the well-being of the Earth community prevail.

Keywords: Alangan Mangyans, ecological frameworks, sacredness of the land, cultural energy

Procedia PDF Downloads 104