Search results for: catchment forest restoration

Authors: David Robert Irvine

Abstract:

In the dental restoration sector, there has been a shift to using zirconia. With the ever increasing need to decrease lead times to deliver restorations faster the zirconia is machined in its pre-sintered state instead of grinding the very hard sintered state. As with all machining, there is tool wear and while investigating the tooling used to machine pre-sintered zirconia it became apparent that the wear rate is based more on material build up and abrasion than it is on plastic deformation like conventional metal machining. It also came to light that the tool material can currently not be selected based on wear resistance, as there is no data. Different works have analysed the effect of the individual wear mechanism separately using similar if not the same material. In this work, the testing method used to analyse the wear was a modified from ISO 8688:1989 to use the pre-sintered zirconia and the cutting conditions used in dental to machine it. This understanding was developed through a series of tests based in machining operations, to give the best representation of the multiple wear factors that can occur in machining of pre-sintered zirconia such as 3 body abrasion, material build up, surface welding, plastic deformation, tool vibration and thermal cracking. From the testing, it found that carbide grades with low trans-granular rupture toughness would fail due to abrasion while those with high trans-granular rupture toughness failed due to edge chipping from build up or thermal properties. The results gained can assist the development of these tools and the restorative dental process. This work was completed with the aim of assisting in the selection of tool material for future tools along with a deeper understanding of the properties that assist in abrasive wear resistance and material build up.

Keywords: abrasive wear, cemented carbide, pre-sintered zirconia, tool wear

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Authors: Ezman Fitriansyah, Lestari Diah Restu, Wawan

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Adaro coal mine in South Kalimantan-Indonesia maintains catchment area of approximately 15,000 Ha for its mine operation. As an open pit surface coal mine with high erosion rate, the mine water in Adaro coal mine contains high TSS that needs to be treated before being released to rivers. For the treatment process, Adaro operates 21 Settling Ponds equipped with combination of physical and chemical system to separate solids and water to ensure the discharged water complied with regional environmental quality standards. However, the sludge created from the sedimentation process reduces the settling ponds capacity gradually. Therefore regular maintenance activities are required to recover and maintain the ponds' capacity. Trucking system and direct dredging had been the most common method to handle sludge in Adaro. But the main problem in applying these two methods is excessive area required for drying pond construction. To solve this problem, Adaro implements an alternative method called Geotube®. The principle of Geotube® method is the sludge contained in the Settling Ponds is pumped into Geotube® containers which have been designed to release water and retain mud flocks. During the pumping process, an amount of flocculants chemicals are injected into the sludge to form bigger mud flocks. Due to the difference in particle size, the mud flocks are settled in the container whilst the water continues to flow out through the container’s pores. Compared to the trucking system and direct dredging method, this method provides three advantages: space required to operate, increasing of overburden waste dump volume, and increasing of water treatment process speed and quality. Based on the evaluation result, Geotube® method only needs 1:8 of space required by the other methods. From the geotechnical assessment result conducted by Adaro, the potential loss of waste dump volume capacity prior to implementation of the Geotube® method was 26.7%. The water treatment process of TSS in well maintained ponds is 16% more optimum.

Keywords: geotube, mine water, settling pond, sludge handling, wastewater treatment

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Authors: Laxmi Prasad Bhattarai

Abstract:

Climate change is regarded as one of the most fundamental threats to sustainable livelihood and global development. There is a growing global concern in linking community-managed forests as potential climate change mitigation projects. This study was conducted to explore 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: community forestry, climate change, global warming, adaptation, Nepal

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Authors: Shahid-ul-Islam, Faqeer Mohammad

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The present study was conducted to investigate the effect of annatto, teak and flame of the forest natural dyes on color, fastness, and antimicrobial property of protein based textile substrate. The color strength (K/S) of wool samples at various concentrations of dyes were analysed using a Reflective Spectrophotometer. The antimicrobial activity of natural dyes before and after application on wool was tested against common human pathogens Escherichia coli, Staphylococcus aureus, and Candida albicans, by using micro-broth dilution method, disc diffusion assay and growth curve studies. The structural morphology of natural protein fibre (wool) was investigated by Scanning Electron Microscopy (SEM). Annatto and teak natural dyes proved very effective in inhibiting the microbial growth in solution phase and after application on wool and resulted in a broad beautiful spectrum of colors with exceptional fastness properties. The results encourage the search and exploitation of new plant species as source of dyes to replace toxic synthetic antimicrobial agents currently used in textile industry.

Keywords: annatto, antimicrobial agents, natural dyes, green textiles

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Authors: Ahmed M. Kabel, Maaly A. Abd Elmaaboud

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Scleroderma is one of the connective tissue disorders characterized by skin and systemic fibrosis. Its pathogenesis involves multiple interrelated processes of autoimmunity, vasculopathy, inflammation, and oxidative stress. This study was a trial to explore the possible ameliorative effects of sodium valproate on an experimental model of skin fibrosis induced by bleomycin. Forty male BALB/c mice were divided into four equal groups as follows: control group; bleomycin group; bleomycin + sodium valproate group, and sodium valproate group. Mice were assessed for their body weight every four days throughout the whole study. Skin tissues were used to evaluate the oxidative stress parameters, transforming growth factor beta 1 (TGF-β1), tumor necrosis factor alpha (TNF-α), interleukin 15, and mammalian target of rapamycin (mTOR). Skin fibrosis was evaluated by measuring dermal thickness and staining the skin tissues with Masson trichrome stain. Also, the skin tissues were immunostained with alpha smooth muscle actin (α-SMA). Administration of sodium valproate to bleomycin-treated mice resulted in the restoration of the body weight with a significant decrease in the dermal thickness, amelioration of oxidative stress, suppression of TGF-β1 and mTOR expression, and significant reduction of the percentage of α-SMA immunostaining and the proinflammatory cytokine levels compared to mice treated with bleomycin alone. In conclusion, sodium valproate has an antifibrotic effect on skin fibrosis which may represent a beneficial therapeutic modality for the management of scleroderma.

Keywords: scleroderma, bleomycin, sodium valproate, skin fibrosis

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Authors: Wei-Chia Huang, Jane Wang

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Damage to nerves is considered one of the most irreversible injuries. The regeneration of nerves has always been an important topic in regenerative medicine. In general, damage to human tissue will naturally repair overtime. However, when the nerves are damaged, healed flesh wound cannot guarantee full restoration to its original function, as truncated nerves are often irreversible. Therefore, the development of treatment methods to successfully guide and accelerate the regeneration of nerves has been highly sought after. In order to induce nerve tissue growth, nerve conduits are commonly used to help reconnect broken nerve bundles to provide protection to the location of the fracture while guiding the growth of the nerve bundles. To prevent the protected tissue from becoming necrotic and to ensure the growth rate, the conduits used are often modified with microstructures or blended with neuron growth factors that may facilitate nerve regeneration. Electrical stimulation is another attempted treatment for medical rehabilitation. With appropriate range of voltages and stimulation frequencies, it has been demonstrated to promote cell proliferation and migration. Biodegradability are critical for medical devices like nerve conduits, while conductive polymers pose great potential toward the differentiation and growth of nerve cells. In this work, biodegradability and conductivity were combined into a novel biodegradable, photocurable, conductive polymer composite materials by embedding conductive nanoparticles in poly(glycerol sebacate) acrylate (PGSA) and 3D-printed into nerve conduits. Rat pheochromocytoma cells and rat neuronal Schwann cells were chosen for the in vitro tests of the conduits and had demonstrate selective growth upon culture in the conductive conduits with built-in microchannels and electrical stimulation.

Keywords: biodegradable polymer, 3d printing, neural regeneration, electrical stimulation

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Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar

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Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.

Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices

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Authors: Fedor Semenov

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One of the most widespread facial bones’ malformations – the congenital palatoschisis – significant impact on drainage and ventilation of the middle ear through the incorrect work of soft palate muscles, which results in recurrent middle ear inflammation and subsequently leads to the hearing dysfunction. The purpose of this research is to evaluate the auditory tube function and hearing condition before the operative treatment (uranoplasty) and after 3 and 12 months. 42 patients aged from 6 months to 17 years who had soft and hard palate cleft and B and C type tympanogram were included in that study. The examination includes otoscopy, pure tone audiometry (for patients older than 8 years – 11 patients), tympanometry. According to the otoscopy results all the patients were divided into two groups: those who had a retracted eardrum and those who had a normal one. The results of pure tone audiometry showed that there were six patients with an air-bone gap of more than 10 dB and the five with normal audiograms. According to the results of this research, uranoplasty demonstrated strongly positive effects on the auditory tube function: normalization of eardrum view upon otoscopy was observed in 64% of children with a retracted eardrum three month after surgery and 85 % twelve months. The quantity of patients with A-type of tympanogram improved in 25 children out of 41 in 3 month and in 35 out of 41 in twelve months after operation. While before the operative treatment, six patients older than 8 years had had an air-bone gap of more than 10 dB; only two of them still had it in 12 months, and the others’ audiograms were normal. To sum it up, the uranoplasty showed a significant contribution in the restoration of auditory tube functioning. Some patients had signs of auditory dysfunction even after the operative treatment. That group of children needs further treatment by an otorhinolaryngologist.

Keywords: auditory tube dysfunction, palatoschisis, uranoplasy, otitis

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Authors: Yuning Guan

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Under the background of rapid urbanization, mountainous counties need to break through mountain barriers for urban expansion due to undulating topography, resulting in ecological problems such as landscape fragmentation and reduced biodiversity. Green infrastructure networks are constructed to alleviate the contradiction between urban expansion and ecological protection, promoting the healthy and sustainable development of urban ecosystems. This study applies the MSPA model, the MCR model and Linkage Mapper Tools to identify eco-sources and eco-corridors in the Shapingba District of Chongqing and combined with landscape connectivity assessment and circuit theory to delineate the importance levels to extract ecological pinch point areas on the corridors. The results show that: (1) 20 ecological sources are identified, with a total area of 126.47 km², accounting for 31.88% of the study area, and showing a pattern of ‘one core, three corridors, multi-point distribution’. (2) 37 ecological corridors are formed in the area, with a total length of 62.52km, with a ‘more in the west, less in the east’ pattern. (3) 42 ecological pinch points are extracted, accounting for 25.85% of the length of the corridors, which are mainly distributed in the eastern new area. Accordingly, this study proposes optimization strategies for sub-area protection of ecological sources, grade-level construction of ecological corridors, and precise restoration of ecological pinch points.

Keywords: green infrastructure network, morphological spatial pattern, minimal cumulative resistance, mountainous counties, circuit theory, shapingba district

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Yosiya Chanta, Jantrararuk Tovaranont

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Species distribution model (SDMs) is one of the powerful tools used to create a suitability map used to predict and address ecology and conservation approaches. MaxEnt is a tool used among SDMs that is highly popular because it only uses presence data. Zanthoxylum rhetsa has more than 200 species distributed in the tropics. Most commonly found in cooler forest environments, there are 8-9 species found in Thailand. In northern Thailand, 3 varieties are commonly grown: Zanthoxylum myriacanthum, Zanthoxylum rhetsa and Zanthoxylum armatum. In the northern regions, these varieties are mainly used as a spice and as a cooking ingredient. MaxEnt has been used in this study to predict potential habitats for these Zanthoxylums in current and future times (2041and 2060). Suitable habitats are predicted using data from the EC-Earth3-Veg general circulation model with 19 climatic variables. The results indicate that the suitability of future habitats of Zanthoxylum rhetsa may expand into the lower northern part of Thailand. The habitat suitability map obtained from the MaxEnt tool shows that the Precipitation of Wettest Quarter (Bio16) is the most important climatic variable influencing the current and future spread of Zanthoxylum rhetsa.

Keywords: MaxEnt, Zanthoxylum rhets, species distribution modelling, climate change

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Authors: JiYoung Park, SueGoo Rhee, HyunAe Woo

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In liver regeneration, quiescent hepatocytes need to be primed to fully respond to growth factors such as hepatocyte growth factor. To understand the priming process, it is necessary to analyze patterns of gene expression that occur during liver regeneration after partial hepatectomy (PHx). Recently, tyrosine phosphorylation of signal transducer and activator of transcription 3 (pYSTAT3) has been shown to play an important role in initiating liver regeneration. In order to evaluate the role of pYSTAT3 on liver regeneration after PHx, we used an intrabody which can selectively inhibit pYSTAT3. In our previous studies, an intrabody had been shown that it bound specifically to the pYSTAT3. Adenovirus-mediated expression of the intrabody in HepG2 cells, as well as mouse liver, blocked both accumulation of pYSTAT3 in the nucleus and downstream target of pYSTAT3. In this study, PHx was performed on intrabody-expressing mice and the expression levels of liver regeneration-related genes were analyzed. We also measured liver/body weight ratios and the related cellular signaling pathways were analyzed. Acute phase response genes were reduced in an intrabody-expressing mice during liver regeneration than in control virus-injected mice. However, the time course of liver mass restoration in intrabody-expressing mice was similar to that observed in control virus-injected mice. We also observed that the expression levels of anti-apoptotic genes, such as Bcl2 and Bcl-xL were decreased in intrabody-expressing mice whereas the expression of cell cycle-related genes such as cyclin D1, and c-myc was increased. Liver regeneration after PHx was partially impaired by the selective inhibition of pYSTAT3 with a phosphorylation site-specific intrabody and these results indicated that pYSTAT3 might have limited role in liver mass recovery.

Keywords: STAT3, pYSTAT3, liver regeneration, intrabody

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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

Procedia PDF Downloads 254

Authors: Aya Gamal Khattab

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Chronic infection with the hepatitis C virus (HCV) is now the leading cause of liver-related morbidity and mortality; Currently, alanine aminotransferase ALT measurement is not only widely used in detecting the incidence, development, and prognosis of liver disease with obvious clinical symptoms, but also provides reference on screening the overall health status during health check-ups. Exercise is a low-cost, reliable and sustainable therapy for many chronic diseases. Low-volume high intensity interval training HIT is time efficient while also having wider application to different populations including people at risk for chronic inflammatory diseases. Purpose of this study was to investigate the effect of low volume high intensity interval training on ALT, AST in HCV patients. All practical work was done in outpatient physiotherapy clinic of Suez Canal Authority Hospitals. Forty patients both gender (27 male, 13 female), age ranged (40-60) years old submitted to low volume high intensity interval training on treadmill for two months three sessions per week. Each session consisting of five min warming up, two bouts for 10 min each bout consisting of 30 sec - 1 min of high intensity (75%-85%) HRmax then two to four min active recovery at intensity (40%-60%) HRmax, so the sum of high intensity intervals was one to two min for each session and four to eight min active recovery, and ends with five min cooling down. ALT and AST were measured before starting exercise session and 2 months later after finishing the total exercise sessions through blood samples. Results showed significant decrease in ALT, AST with improvement percentage (18.85%), (23.87%) in the study, so the study concluded that low volume high intensity interval training had a significant effect in lowering the level of circulating liver enzymes (ALT, AST) which means protection of hepatic cells and restoration of its function.

Keywords: alanine aminotransferase (ALT), aspartate aminotransferase (AST), hepatitis C (HCV), low volume high intensity interval training

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Authors: Pagadaplly Girish, P. V. Manohar

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Introduction: Management of distal femur fractures is challenging. Recently, treatment has evolved towards indirect reduction and minimally invasive techniques. Objectives: To assess the fracture union and functional outcome following open reduction and internal fixation of distal femur fractures with locking compression plate and to achieve restoration of the anatomical alignment of fracture fragments and stable internal fixation. Methodology: Patients with distal femur fracture treated by locking compression during Oct 2011 to April 2013 were assessed prospectively. Patients below 18 years and those with neuro-vascular deficits were excluded. Age, sex of the patient, type of fracture, mechanism of injury, type of implant used, operative time and postoperative complications were analysed. The Neer’s scale was used to assess the outcome of the patients. Results: The total number of patients was 30; 28 males and 2 females; mean age was 41.53 years. Road traffic accidents were the major causes of injury followed by falls. The average duration of hospital stay was 21.3 days. The overall complication rate note was 23.33%. The mean range of movement around the knee joint after 6 months of follow-up was 114.330. The average time for the radiological union was 14 weeks. Excellent to good results were noted in 26 patients (86.6%) and average to poor results were observed in 4 (13.33%) patients. Conclusions: The locking compression plate gives a rigid fixation for the fracture. It also provides a good purchase in osteoporotic bones. LCP is simple and a reliable implant appropriate for fixation of femoral fractures with promising results.

Keywords: distal femur fractures, locking compression plate, Neer’s criteria, neuro-vascular deficits

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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: 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: Ashley DelCorno

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GEM Anscombe’s 1958 essay Modern Moral Philosophy and the tradition of virtue ethics that followed has given rise to the restoration (or, more plainly, the resurrection) of Aristotle as something of an authority figure. Alisdair MacIntyre and Martha Nussbaum are proponents, for example, not just of Aristotle’s relevancy but also of his apparent implicit authority. That said, it’s not clear that the schema imagined by virtue ethicists accurately describes moral life or that it does not inadvertently work to impoverish genuine decision-making. If the label ‘virtue’ is categorically denied to some groups (while arbitrarily afforded to others), it can only turn on itself, thus rendering ridiculous its own premise. Likewise, as an inescapable feature of virtue ethics, Aristotelean binaries like ‘virtue/vice’ and ‘voluntary/involuntary’ offer up false dichotomies that may seriously compromise an agent’s ability to conceptualize choices that are truly free and rooted in meaningful criteria. Here, this topic is analyzed through a feminist lens predicated on the known paradoxes of patriarchy. The work of feminist theorists Jacqui Alexander, Katharine Angel, Simone de Beauvoir, bell hooks, Audre Lorde, Imani Perry, and Amia Srinivasan serves as important guideposts, and the argument here is built from a key tenet of black feminist thought regarding scarcity and possibility. Above all, it’s clear that though the philosophical tradition of virtue ethics presents itself as recovering the place of agency in ethics, its premises possess crippling limitations toward the achievement of this goal. These include, most notably, virtue ethics’ binding analysis of history, as well as its axiomatic attachment to obligatory clauses, problematic reading-in of Aristotle and arbitrary commitment to predetermined and competitively patriarchal ideas of what counts as a virtue.

Keywords: feminist history, the limits of utopic imagination, curatorial creation, truth, virtue, freedom

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Authors: Rafla Attia, Claudio Zucca, Bao Quang Le, Sana Dridi, Thouraya Sahli, Taoufik Hermassi

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In Tunisia, landscape change and land degradation are critical issues for landscape conservation, management, and planning. Landscapes are undergoing crucial environmental problems made evident by soil degradation and desertification. Human improper uses of land resources (e.g., unsuitable land uses, unsustainable crop intensification, and poor rangeland management) and climate change are the main factors leading to the landscape transformation and desertification affecting high proportions of the Tunisian lands. Land use planning (LUP) to achieve Land Degradation Neutrality (LDN) must be supported by methodologies and technologies that help identify best solutions and practices and design context-specific sustainable land management (SLM) strategies. Such strategies must include restoration or rehabilitation efforts in areas with high land degradation, as well as prevention of degradation that could be caused by improper land use (LU) and land management (LM). The geoinformatics Land Use Planning for LDN (LUP4LDN) tool has been designed for this purpose. Its aim is to support national and sub-national planners in i) mapping geographic patterns of current land degradation; ii) anticipating further future land degradation expected in areas that are unsustainably managed; and iii) providing an interactive procedure for developing participatory LU-LM transitional scenarios over selected regions of interest and timeframes, visualizing the related expected levels of impacts on ecosystem services via maps and graphs. The tool has been co-developed and piloted with national stakeholders in Tunisia. The piloting implementation assessed how the LUP4LDN tool fits with existing LUP processes and the benefits achieved by using the tool to support land use planning for LDN.

Keywords: land use system, land cover, sustainable land management, land use planning for land degradation neutrality

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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: 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: 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: Niyati Sharma, Om Anand, Sanjeev Kumar Prasad

Abstract:

Assuming future sale value for any of the organizations is one of the major essential characteristics of tactical development. Walmart Sales Forecasting is the finest illustration to work with as a beginner; subsequently, it has the major retail data set. Walmart uses this sales estimate problem for hiring purposes also. We would like to analyzing how the internal and external effects of one of the largest companies in the US can walk out their Weekly Sales in the future. Demand forecasting is the planned prerequisite of products or services in the imminent on the basis of present and previous data and different stages of the market. Since all associations is facing the anonymous future and we do not distinguish in the future good demand. Hence, through exploring former statistics and recent market statistics, we envisage the forthcoming claim and building of individual goods, which are extra challenging in the near future. As a result of this, we are producing the required products in pursuance of the petition of the souk in advance. We will be using several machine learning models to test the exactness and then lastly, train the whole data by Using linear regression and fitting the training data into it. Accuracy is 8.88%. The extra trees regression model gives the best accuracy of 97.15%.

Keywords: random forest algorithm, linear regression algorithm, extra trees classifier, mean absolute error

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

Abstract:

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: D. Manai, J. Alvarez-Marron, M. Inoubli

Abstract:

The southern Tunisian Atlas is a part of the wide Cenozoic intracontinental deformation that affected North Africa as a result of convergence between African and Eurasian plates. The Southern Tunisian Atlas Front (STAF) corresponds to the chotts area that covers several hundreds of Km² and represents a 60 km wide transition between the deformed Tunisian Atlas to the North and the undeformed Saharan platform to the South. It includes three morphostructural alignments, a fold and thrust range in the North, a wide depression in the middle and a monocline to horizontal zone to the south. Four cross-sections have been constructed across the chotts area to illustrate the structure of the Southern Tunisian Atlas Front based on integrated geological and geophysical data including geological maps, petroleum wells, and seismic data. The fold and thrust zone of the northern chotts is interpreted as related to a detachment level near the Triassic-Jurassic contact. The displacement of the basal thrust seems to die out progressively under the Fejej antiform and it is responsible to the south dipping of the southern chotts range. The restoration of the cross-sections indicates that the Southern Tunisian Atlas front is a weakly deformed wide zone developed during the Cenozoic inversion with a maximum calculated shortening in the order of 1000 m. The wide structure of this STAF has been influenced by a pre-existing large thickness of upper Jurassic-Aptian sediments related to the rifting episodes associated to the evolution of Tethys in the Maghreb. During Jurassic to Aptian period, the chotts area corresponded to a highly subsiding basin.

Keywords: Southern Tunisian Atlas Front, subsident sub- basin, wide deformation, balanced cross-sections.

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Authors: Prashant Verma

Abstract:

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: Mário Ernesto Sitoe, Orlando Zacarias

Abstract:

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

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

Abstract:

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

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Authors: Budoor Al Abid

Abstract:

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

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Authors: Ebenezer Amoquandoh, Daniel Bruce Sarpong, Godfred K. Ofosu-Budu, Andreas Fliessbach

Abstract:

Soil quality is at stake globally, but under tropical conditions, the loss of soil fertility may be existential. The current rates of soil nutrient depletion, erosion and environmental degradation in most of Africa’s farmland urgently require methods for soil fertility restoration through affordable agricultural management techniques. The study assessed the effects of locally available organic resources to improve soil fertility, crop yield and profitability compared to business as usual on farms in the Eastern and Greater Accra regions of Ghana. Apart from this, we analyzed the change of farmers’ perceptions and knowledge upon the experience with the new techniques; the effect of using locally available organic resource on farmers’ yield and determined the factors influencing the profitability of farming. Using the Difference in Mean Score and Proportion to estimate the extent to which farmers’ perceptions, knowledge and practices have changed, the study showed that farmers’ perception, knowledge and practice on the use of locally available organic resources have changed significantly. This paves way for the sustainable use of locally available organic resource for soil fertility improvement. The Propensity Score Matching technique and Endogenous Switching Regression model used showed that using locally available organic resources have the potential to increase crop yield. It was also observed that using the Profit Margin, Net Farm Income and Return on Investment analysis, it is more profitable to use locally available organic resources than other soil fertility amendments techniques studied. The results further showed that socioeconomic, farm characteristics and institutional factors are significant in influencing farmers’ decision to use locally available organic resources and profitability.

Keywords: soil fertility, locally available organic resources, perception, profitability, sustainability

Procedia PDF Downloads 148