Search results for: naturally regenerated acacia forest

Authors: Amberkar Mohanbabu Vittalrao, Avin, Meena Kumari Kamalkishore, Padmanabha Udupa, Vinaykumar Bavimane, Honnegouda

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Objective: To evaluate the hepato-protective activity of Tinospora cordiofolia (Tc) against paracetamol induced hepatic damage in rats. Methods: The plant stem (test drug) was procured locally, shade dried, powdered and extracted with water. Silymarin was used as standard hepatoprotective drugs and 2% gum acacia as a control (vehicle) against paracetamol (PCT) induced hepatotoxicity. Results and Discussion: The hepato-protective activity of aqueous stem extract was assessed by paracetamol induced hepatotoxicity preventive model in rats. Alteration in the levels of biochemical markers of hepatic damage like AST, ALT, ALP and lipid peroxides were tested in both paracetamol treated and untreated groups. Paracetamol (3g/kg) had enhanced the AST, ALT, ALP and the lipid peroxides in the serum. Treatment of silymarin and aqueous stem extract of Tc (200 and 400mg/kg) extract showed significant hepatoprotective activity by altering biochemical marker levels to the near normal. Preliminary phytochemical tests were done. Aqueous Tc extract showed presence of phenolic compound and flavonoids. Our findings suggested that Tc extract possessed hepatoprotective activity in a dose dependent manner. Conclusions: Tc was found to possess significant hepatoprotective property when treated with PCT. This was evident by decreasing the liver enzymes significantly when treated with PCT as compared to PCT only treated group (P < 0.05). Hence Tinospora cardiofolia could be a good, promising, preventive agent against PCT induced hepatotoxicity.

Keywords: Tinospora cardiofolia, hepatoprotection, paracetamol, silymarin

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Authors: Stephen Dankwa, Zheng Wenfeng, Xiaolu Li

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

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

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Authors: Saloni Khandelwal

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

Keywords: Aravalli, ecosystem, LULC, Rajasthan

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Authors: Jelka Pleadin, Nina Kudumija, Ana Vulic, Manuela Zadravec, Tina Lesic, Mario Skrivanko, Irena Perkovic, Nada Vahcic

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Products of animal origin, such as meat and meat products, can contribute to human mycotoxins’ intake coming as a result of either indirect transfer from farm animals exposed to naturally contaminated grains and feed (carry-over effects) or direct contamination with moulds or naturally contaminated spice mixtures used in meat production. Ochratoxin A (OTA) is mycotoxin considered to be of the outermost importance from the public health standpoint in connection with meat products. The aim of this study was to investigate the occurrence of OTA in different traditional meat products circulating on Croatian markets during 2018, produced by a large number of households situated in eastern and north Croatian regions using a variety of technologies. Concentrations of OTA were determined in traditional meat products (n = 70), including dry fermented sausages (Slavonian kulen, Slavonian sausage, Istrian sausage and domestic sausage; n = 28), dry-cured meat products (pancetta, pork rack and ham; n = 22) and cooked sausages (liver sausages, black pudding sausages and pate; n = 20). OTA was analyzed by use of quantitative screening immunoassay method (ELISA) and confirmed for positive samples (higher than the limit of detection) by liquid chromatography tandem mass spectrometry (LC-MS/MS) method. Whereas the bacon samples contaminated with OTA were not found, its level in dry fermented sausages ranged from 0.22 to 2.17 µg/kg and in dry-cured meat products from 0.47 to 5.35 µg/kg, with in total 9% of positive samples. Besides possible primary contamination of these products arising due to improper manufacturing or/and storage conditions, observed OTA contamination could also be the consequence of secondary contamination that comes as a result of contaminated feed the animals were fed on. OTA levels obtained in cooked sausages ranged from 0.32 to 4.12 µg/kg (5% of positives) and could probably be linked to the contaminated raw materials (liver, kidney and spices) used in the sausages production. The results showed an occasional OTA contamination of traditional meat products, pointing that to avoid such contamination on households these products should be produced and processed under standardized and well-controlled conditions. Further investigations should be performed in order to identify mycotoxin-producing moulds on the surface of the products and to define preventative measures that can reduce the contamination of traditional meat products during their production on households and period of storage.

Keywords: Croatian households, ochratoxin-A, traditional cooked sausages, traditional dry-cured meat products

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: M. F. Nawaz, S. Gul, T. H. Farooq, M. T. Siddiqui, M. Asif, I. Ahmad, N. K. Niazi

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In Pakistan, major demands of fuel wood and timber wood are fulfilled by agroforestry. However, the information regarding economic significance of agroforestry and its productivity in Pakistan is still insufficient and unreliable. Survey of field conditions to examine the agroforestry status at local level helps us to know the future trends and to formulate the policies for sustainable wood supply. The objectives of this research were to examine the actual status and potential of agroforestry and to point out the barriers that are faced by farmers in the adoption of agroforestry. Research was carried out in Chiniot district, Pakistan because it is the famous city for furniture industry that is largely dependent on farm trees. A detailed survey of district Chiniot was carried out from 150 randomly selected farmer respondents using multi-objective oriented and pre-tested questionnaire. It was found that linear tree planting method was more adopted (45%) as compared to linear + interplanting (42%) and/or compact planting (12.6%). Chi-square values at P-value <0.5 showed that age (11.35) and education (17.09) were two more important factors in the quick adoption of agroforestry as compared to land holdings (P-value of 0.7). The major reason of agroforestry adoption was to obtain income, fodder and fuelwood. The most dominant species in farmlands was shisham (Dalbergia sissoo) but since last five years, mostly farmers were growing Sufeida (Eucalyptus camaldulensis), kikar (Acacia nilotica) and popular (Populus deltoides) on their fields due to “Shisham die-back” problem. It was found that agro-forestry can be increased by providing good quality planting material to farmers and improving wood markets.

Keywords: agroforestry, trees, services, agriculture, farmers

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Authors: Stellina Jolly

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July 18th to August 19th 2013 has gone down in the history of India for undertaking the country’s first environment referendum. The Supreme Court had ruled that the Vedanta Group's bauxite mining project in the Niyamgiri Hills of Orissa will have to get clearance from the gram sabha, which will consider the cultural and religious rights of the tribals and forest dwellers living in Rayagada and Kalahandi districts. In the Niyamgiri hills, people of small tribal hamlets were asked to voice their opinion on bauxite mining in their habitat. The ministry has reiterated its stand that mining cannot be allowed on the Niyamgiri hills because it will affect the rights of the Dongria Kondhs. The tribal person who occupies the Niyamgiri Hills in Eastern India accomplished their first success in 2010 in their struggle to protect and preserve their existence, culture and land against Vedanta a London-based mining giant. In August, 2010 Government of India revoked permission for Vedanta Resources to mine bauxite from hills in Orissa State where the Dongria Kondh live as forest dwellers. This came after various protests and reports including amnesty report wherein it highlighted that an alumina refinery in eastern India operated by a subsidiary of mining company. Vedanta was accused of causing air and water pollution that threatens the health of local people and their access to water. The abuse of human rights by corporate is not a new issue it has occurred in Africa, Asia and other parts of the world. Paper focuses on the instances and extent of human right especially in terms of environment violations by corporations. Further Paper details on corporations and sustainable development. Paper finally comes up with certain recommendation including call for a declaration by United Nations on Corporate environment Human Rights Liability.

Keywords: environment, corporate, human rights, sustainable development

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Authors: Hamidreza Fallah Lajimi, Elham Karami, Alireza Arab, Fatemeh Alinasab

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Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with Four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering, business engineering

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Authors: Zarine Avetisyan

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The process of speech production and transmission naturally implies the occurrence of certain defective assumptions and erroneous formulations which may be both spontaneous, caused by haste, carelessness, etc., or deliberate. Whether deliberate or not, fallacies always act by way of “faux pas”. In the latter case, we deal with fake or deceptive arguments which are the focus of the given paper. The paper departs from the assumption that fallacies are arguments that prove nothing. Additionally and more importantly, political discourse becomes the main domain for scholarly “cultivation” while pinning down fallacies. The fallacy of telling the truth but deliberately omitting important key details in order to falsify the larger picture called “the half truth” captures special attention in the given paper.

Keywords: break in the information chain, fallacy, half truth, political discourse

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Authors: Neelima Meravi, Santosh Prajapati

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The present study was conducted over a period of three years on fly ash dyke. The physicochemical analysis of fly ash (pH, WHC, BD, porosity, EC% OC & available P, heavy metal content etc.) was performed before and after the growth of plant species. Fly ash was analyzed after concentrated nitric acid digestion by atomic absorption spectrophotometer AAS-7000b(Shimadzu) for heavy metals. The dyke was colonized by the propagules of native species over a period of time, and it was observed that fly ash was contaminated by heavy metals and plants were able to ameliorate the metal concentration of dyke. The growth of plant species also improved the condition of fly ash so that it can be used for agricultural purposes. Phytosociological studies of the fly ash dyke were performed so that these plants may be used for reclamation of fly ash for subsequent use in agriculture.

Keywords: fly ash, heavy metals, IVI, phytosociology, reclamation

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Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

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Authors: Jian-Jun Gao

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Repetition is used for a variety of functions in conversation. When young children first learn to speak, they often repeat words from the adult’s recent utterance with the learning and social function. The objective of this study was to ascertain whether the repetitions are equivalent in indicating attention to new words and the initial repeat of information in conversation. Based on the observation of naturally occurring language use in Taiwan Corpus of Child Mandarin (TCCM), the results in this study provided empirical support to the previous findings that children are more likely to repeat new words they are offered than to repeat new information. When children get older, there would be a drop in the repetition of both new words and new information.

Keywords: acquisition, corpus, mandarin, new words, new information, repetition

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Authors: Raheleh Farzanmanesh, Christopher J. Weston

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Mangroves are forest ecosystems located in the inter-tidal regions of tropical and subtropical coastlines that provide many valuable economic and ecological benefits for millions of people, such as preventing coastal erosion, providing breeding, and feeding grounds, improving water quality, and supporting the well-being of local communities. In addition, mangroves capture and store high amounts of carbon in biomass and soils that play an important role in combating climate change. The decline in mangrove area has prompted government and private sector interest in mangrove conservation and restoration projects to achieve multiple Sustainable Development Goals, from reducing poverty to improving life on land. Mangrove aboveground biomass plays an essential role in the global carbon cycle, climate change mitigation and adaptation by reducing CO2 emissions. However, little information is available about the effectiveness of mangrove sustainable management on mangrove change area and aboveground biomass (AGB). Here, we proposed a method for mapping, modeling, and assessing mangrove area and AGB in two Global Environment Facility (GEF) blue forests projects based on Sentinel-2 Level 1C imagery during their conservation lifetime. The SVR regression model was used to estimate AGB in Tahiry Honko project in Madagascar and the Abu Dhabi Blue Carbon Demonstration Project (Abu Dhabi Emirates. The results showed that mangrove forests and AGB declined in the Tahiry Honko project, while in the Abu Dhabi project increased after the conservation initiative was established. The results provide important information on the impact of mangrove conservation activities and contribute to the development of remote sensing applications for mapping and assessing mangrove forests in blue carbon initiatives.

Keywords: blue carbon, mangrove forest, REDD+, aboveground biomass, Sentinel-2

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Authors: Kazuyoshi Mori

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In this paper, we consider the number of parameters for the parametrization of stabilizing controllers for RHinf systems with size 2 × 2. Fortunately, any plant of this model can admit doubly coprime factorization. Thus we can use the Youla parameterization to parametrize the stabilizing contollers . However, Youla parameterization does not give itself the minimal number of parameters. This paper shows that the minimal number of parameters is four. As a result, we show that the Youla parametrization naturally gives the parameterization of stabilizing controllers with minimal numbers.

Keywords: RHinfo, parameterization, number of parameters, multi-input, multi-output systems

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Authors: J. R. Mudakavi, K. Puttanna

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Chromium in the environment is considered as one of the most toxic elements probably next only to mercury and arsenic. It is acutely toxic, mutagenic and carcinogenic in the environment. Chromium contamination of soil and underground water due to industrial activities is a very serious problem in several parts of India covering Karnataka, Tamil Nadu, Andhra Pradesh etc. Functionally modified Activated Carbon Fabrics (ACF) offer targeted chromium removal from drinking water and industrial effluents. Activated carbon fabric is a light weight adsorbing material with high surface area and low resistance to fluid flow. We have investigated surface modification of ACF using various acids in the laboratory through batch as well as through continuous flow column experiments with a view to develop the optimum conditions for chromium removal. Among the various acids investigated, phosphoric acid modified ACF gave best results with a removal efficiency of 95% under optimum conditions. Optimum pH was around 2 – 4 with 2 hours contact time. Continuous column experiments with an effective bed contact time (EBCT) of 5 minutes indicated that breakthrough occurred after 300 bed volumes. Adsorption data followed a Freundlich isotherm pattern. Nickel adsorbs preferentially and sulphate reduces chromium adsorption by 50%. The ACF could be regenerated up to 52.3% using 3 M NaOH under optimal conditions. The process is simple, economical, energy efficient and applicable to industrial effluents and drinking water.

Keywords: activated carbon fabric, hexavalent chromium, adsorption, drinking water

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Authors: Abishek Rajkumar

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Antibiotic resistance can occur naturally given the selective pressure placed on antibiotics. Within a large population of bacteria, there is a significant chance that some of those bacteria can develop resistance via mutations or genetic recombination. However, a growing public health concern has arisen over the fact that antibiotic resistance has increased significantly over the past few decades. This is because humans have been over-consuming and producing antibiotics, which has ultimately accelerated the antibiotic resistance seen in these bacteria. The product of all of this is an ongoing race between scientists and the bacteria as bacteria continue to develop resistance, which creates even more demand for an antibiotic that can still terminate the newly resistant strain of bacteria. This paper will focus on a myriad of aspects of antibiotic resistance in bacteria starting with how it occurs on a molecular level and then focusing on the antibiotic concentrations and how they affect the resistance and fitness seen in bacteria.

Keywords: antibiotic, molecular, mutation, resistance

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Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

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During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

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Authors: Tuğrul Varol, Halil Barış Özel

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In this study which has been conducted in Akçasu Forest Range District of Devrek Forest Directorate; 3 methods (cover removal with human force, cover removal with Hitachi F20 Excavator, and cover removal with agricultural equipment mounted on a Ferguson 240S agriculture tractor) utilized in weed control efforts in regeneration of degraded oriental beech forests have been compared. In this respect, 3 methods have been compared by determining certain work hours and standard durations of unit areas (1 hectare). For this purpose, evaluating the tasks made with human and machine force from the aspects of duration, productivity and costs, it has been aimed to determine the most productive method in accordance with the actual ecological conditions of research field. Within the scope of the study, the time studies have been conducted for 3 methods used in weed control efforts. While carrying out those studies, the performed implementations have been evaluated by dividing them into business stages. Also, the actual data have been used while calculating the cost accounts. In those calculations, the latest formulas and equations which are also used in developed countries have been utilized. The variance of analysis (ANOVA) was used in order to determine whether there is any statistically significant difference among obtained results, and the Duncan test was used for grouping if there is significant difference. According to the measurements and findings carried out within the scope of this study, it has been found during living cover removal efforts in regeneration efforts in demolished oriental beech forests that the removal of weed layer in 1 hectare of field has taken 920 hours with human force, 15.1 hours with excavator and 60 hours with an equipment mounted on a tractor. On the other hand, it has been determined that the cost of removal of living cover in unit area (1 hectare) was 3220.00 TL for man power, 788.70 TL for excavator and 2227.20 TL for equipment mounted on a tractor. According to the obtained results, it has been found that the utilization of excavator in weed control effort in regeneration of degraded oriental beech regions under actual ecological conditions of research field has been found to be more productive from both of aspects of duration and costs. These determinations carried out should be repeated in weed control efforts in degraded forest fields with different ecological conditions, it is compulsory for finding the most efficient weed control method. These findings will light the way of technical staff of forestry directorate in determination of the most effective and economic weed contol method. Thus, the more actual data will be used while preparing the weed control budgets, and there will be significant contributions to national economy. Also the results of this and similar studies are very important for developing the policies for our forestry in short and long term.

Keywords: artificial regeneration, weed control, oriental beech, productivity, mechanization, man power, cost analysis

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Authors: Phusit Phukamchanoad, Chutchai Ditchareon, Suwaree Yordchim

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This research was to study on background and social and cultural context of Kamchanoad community for sustainable tourism management. All data was collected through in-depth interview with village headmen, community committees, teacher, monks, Kamchanoad forest field officers and respected senior citizen above 60 years old in the community who have lived there for more than 40 years. Altogether there were 30 participants for this research. After analyzing the data, content from interview and discussion, Kamchanoad has both high land and low land in the region as well as swamps that are very capable of freshwater animals’ conservation. Kamchanoad is also good for agriculture and animal farming. 80% of Kamchanoad’s land are forest, freshwater and rice farms. Kamchanoad was officially set up as community in 1994 as “Baan Nonmuang”. Inhabitants in Kamchanoad make a living by farming based on sufficiency economy. They have rice farm, eucalyptus farm, cassava farm and rubber tree farm. Local people in Kamchanoad still believe in the myth of Srisutto Naga. They are still religious and love to preserve their traditional way of life. In order to understand how to create successful tourism business in Kamchanoad, we have to study closely on local culture and traditions. Outstanding event in Kamchanoad is the worship of Grand Srisutto, which is on the full-moon day of 6th month or Visakhabucha Day. Other big events are also celebration at the end of Buddhist lent, Naga firework, New Year celebration, Boon Mahachart, Songkran, Buddhist Lent, Boon Katin and Loy Kratong. Buddhism is the main religion in Kamchanoad. The promotion of tourism in Kamchanoad is expected to help spreading more income for this region. More infrastructures will be provided for local people as well as funding for youth support and people activities.

Keywords: social and culture area, tourism management, Kamchanoad Community, Udon Thani Province

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Authors: Gul Jan

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It is the first quantitative ethno-botanical analysis and conservation issues of medicinal flora of Alpine and Sub-alpine, Hindikush region of Pakistan. The objective of the study aims to report, compare the uses and highlight the ethno-Botanical significance of medicinal plants for treatment of various diseases. A total of 250 (242 males and 8 females) local informants including 10 Local Traditional Healers were interviewed. Information was collected through semi-structured interviews, analyzed and compared by quantitative ethno-botanical indices such as Jaccard index (JI), Informant Consensus Factor (ICF), use value (UV) and Relative frequency of citation (RFC).Thorough survey indicated that 57 medicinal plants belongs to 43 families were investigated to treat various illnesses. The highest ICF is recorded for digestive system (0.69%), Circolatory system (0.61%), urinary tract system, (0.53%) and respiratory system (0.52%). Used value indicated that, Achillea mellefolium (UV = 0.68), Aconitum violaceum (UV = 0.69), Valeriana jatamansi (UV = 0.63), Berberis lyceum (UV = 0.65) and are exceedingly medicinal plant species used in the region. In comparison, highest similarity index is recorded in these studies with JI 17.72 followed by 16.41. According to DMR output, Pinus williciana ranked first due to multipurpose uses among all species and was found most threatened with higher market value. Unwise used of natural assets pooled with unsuitable harvesting practices have exaggerated pressure on plant species of the research region. The main issues causative to natural variety loss found were over grazing of animals, forest violation, wild animal hunting, fodder, plant collection as medicine, fuel wood, forest fire, and invasive species negatively affect the natural resources. For viable utilization, in situ and ex situ conservation, skillful collecting, and reforestation project may be the resolution. Further wide field management research is required.

Keywords: quantitative analysis, conservations issues, medicinal flora, alpine and sub-alpine, Hindukush region

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Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

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Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

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Authors: Messaouda Belaid, Salima Kebbouche-Gana

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The negative effect of the Varroa bee colony is very important. They cause morphological and physiological changes, causing a decrease in performance of individuals and long-term death of the colony. Indirectly, they weaken the bees become much more sensitive to the different pathogenic organisms naturally present in the colony. This work aims to research secondary infections of microbial origin occurred in the worker bee nurse due to parasitism by Varroa destructor. The feeding behaviour of Varroa may causes damaging host integument. The results show that the microbial contamination enable to be transmitted into honeybee heamocoel are Bacillus sp, Pseudomonas sp, Enterobacter, Aspergillus.

Keywords: honeybee, Apis mellifera intermissa, microbial contamination, Varroa destructor

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Authors: R. Vishnu, K. S. Reddy, Amrendra Kumar

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The present guideline for the construction of flexible pavement in India, IRC 37: 2012 recommends to use viscous grade VG 40 bitumen in both wearing and binder bituminous layers. However, most of the bitumen production plants in India are unable to produce the air-blown VG40 grade bitumen. This requires plant’s air-blowing technique modification, and often the manufactures finds it as uneconomical. In this context, stiffer grade bitumen can be produced if bitumen is modified. Gilsonite, which is naturally occurring asphalt have been found to be used for increasing the stiffness of binders. The present study evaluates the physical, rheological characteristics of Gilsonite modified binders and the performance characteristics of these binders when used in the mix.

Keywords: bitumen, gilsonite, stiffness, laboratory evaluation

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Authors: Philip Vercoe, Ali Hardan

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Samples of 29 Australian wild natives and exotic plants were tested in vitro batch rumen culture system for their methanogenic characteristics and potential usage as feed or antimicrobial to enhance sustainable livestock ruminant production system. The plants were tested for their in vitro rumen fermentation end products properties which include: methane production, total gas pressure, concentrations of total volatile fatty acids, ammonia, and acetate to propionate ratio. All of the plants were produced less methane than the positive control (i.e., oaten chaff) in vitro. Nearly 50 % of plants inhibiting methane by over 50% in comparison to the control. Eremophila granitica had the strongest inhibitory effect about 92 % on methane production comparing with oaten chaff. The exotic weed Arctotheca calendula (Capeweed) had the highest concentration of volatile fatty acids production as well as the highest in total gas pressure among all plants and the control. Some of the acacia species have the lowest production of total gas pressure. The majority of the plants produced more ammonia than the oaten chaff control. The plant species that produced the most ammonia was Codonocarpus cotinifolius, producing over 3 times as much methane as oaten chaff control while the lowest was Eremophila galeata. There was strong positive correlation between methane production and total gas production as well as between total gas production and the concentration of VFA produced with R² = 0.74, R² = 0.84, respectively. While there was weak positive correlation between methane production and the acetate to propionate ratio as well as between the concentration of VFA produced and methane production with R² = 0.41, R² = 0.52, respectively.

Keywords: in vitro Rumen Fermentation, methane, wild Australian native plants, forages

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Authors: Ali Moharrek, Hosein Mobli, Ali Jafari, Ahmad Tabataee Far

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Biomass is a material generally produced by plants living on soil or water and their derivatives. The remains of agricultural and forest products contain biomass which is changeable into fuel. Besides, you can obtain biogas and ethanol from the charcoal produced from biomass through specific actions. this technology was designed for as a useful Native Fuel and Technology in Energy disasters Management Due to the sudden interruption of the flow of heat energy One of the problems confronted by mankind in the future is the limitations of fossil energy which necessitates production of new energies such as biomass. In order to produce biomass from the remains of the plants, different methods shall be applied considering factors like cost of production, production technology, area of requirement, speed of work easy utilization, ect. In this article we are focusing on designing a biomass briquetting portable machine. The speed of installation of the machine on a tractor is estimated as 80 MF 258. Screw press is used in designing this machine. The needed power for running this machine which is estimated as 17.4 kW is provided by the power axis of tractor. The pressing speed of the machine is considered to be 375 RPM Finally the physical and mechanical properties of the product were compared with utilized material which resulted in appropriate outcomes. This machine is designed for Gathering Raw materials of the ground by Head Section. During delivering the raw materials to Briquetting section, they Crushed, Milled & Pre Heated in Transmission section. This machine is a Combine Portable Tractor unit machine and can use all type of Agriculture, Forest & Livestock Animals Resides as Raw material to make Bio fuel. The Briquetting Section was manufactured and it successfully made bio fuel of Sawdust. Also this machine made a biofuel with Ethanol of sugarcane Wastes. This Machine is using P.T.O power source for Briquetting and Hydraulic Power Source for Pre Processing of Row Materials.

Keywords: biomass, briquette, screw press, sawdust, animal wastes, portable, tractors

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Authors: Sang-Wook Lee, So-Yeon Jeon, Min-Gi Cho, Dae-Young Shin, Sung-Ho Hwang

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Hydraulic system of excavator gets working energy from hydraulic pump which is connected to output shaft of engine. Recently, main control valve (MCV) which is composed of several independent metering valve (IMV) has been introduced for better energy efficiency of the hydraulic system so that fuel efficiency of the excavator can be improved. Excavator with IMV has 5 operating modes depending on the quantity of regeneration flow. In this system, the hydraulic pump is controlled to supply demanded flow which is needed to operate each mode. Because the regenerated flow supply energy to actuators, the hydraulic pump consumes less energy to make same motion than one that does not regenerate flow. The horse power control is applied to the hydraulic pump of excavator for maintaining engine start under a heavy load and this control makes the flow of hydraulic pump reduced. When excavator is in complex operation such as loading or unloading soil, the hydraulic pump discharges small quantity of working fluid in high pressure. At this operation, the engine of excavator does not run at optimal operating line (OOL). The engine needs to be operated on OOL to improve fuel efficiency and by controlling hydraulic pump the engine can drive on OOL. By continuous mode changing of IMV, the hydraulic pump is controlled to make engine runs on OOL. The simulation result of this study shows that fuel efficiency of excavator with IMV can be improved by considering engine OOL and continuous mode changing algorithm.

Keywords: continuous mode changing, engine fuel consumption, excavator, fuel efficiency, IMV

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Authors: Elise M. Shauf

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Beryllium can be found naturally in some fruits and vegetables (carrots, garden peas, kidney beans, pears) at very low concentrations, but is typically not clinically significant due to the low-level exposure and limited absorption of beryllium by the stomach and intestines. However, acute or chronic beryllium exposure can result in harmful toxic and carcinogenic biological effects. Beryllium can be both a workplace hazard and an environmental pollutant, therefore determining the presence of beryllium at trace levels can be essential to protect workers as well as the environment. Analysis of gallein, C₂₀H₁₂O₇, to determine if it is usable as a fluorescent dye for beryllium detection. The primary detection method currently in use includes hydroxybenzoquinoline sulfonates (HBQS), for which alternative indicators are desired. Unfortunately, gallein does not have the desired aspects needed as a dye for beryllium detection due to the peak shift properties.

Keywords: beryllium detection, fluorescent, gallein dye, indicator, spectroscopy

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Shima Naderi, Abbas Abbaszadeh Shahri

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Energy resources are reachable and affordable in Iran, thus surplus access to fossil fuels besides high level of economic growth leads to serious environmental critical such as pollutants and greenhouse gases in the atmosphere, increase in average degrease and lack of water sources specially in Tehran as a capital city of Iran. As building sector consumes a huge portion of energy, taking actions towards alternative sources of energy as well as conserving non-renewable energy resources and architectural energy saving methods are the fundamental basis for achieving sustainability`s goals. This study tries to explore implantation of both high technologies and traditional issues for reduction of energy demands in buildings of Tehran and introduce some factors and instructions for achieving this purpose. Green and energy efficient buildings such as ZEBs make it possible to preserve natural resources for the next generations by reducing pollution and increasing ecosystem self-recovery. However ZEB is not widely spread in Iran because of its low economic efficiency, it is not viable for a private entrepreneur without the governmental supports. Therefore executing of Architectural Energy Efficiency can be a better option. It is necessary to experience a substructure expansion with respect to traditional residential building style. Renewable energies and passive design which are the substantial part of the history of architecture in Iran can be regenerated and employed as an essential part of designing energy efficient buildings.

Keywords: architectural energy efficiency, passive design, renewable energies, zero energy buildings

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Authors: Fidelia A. Orji, Julita Vassileva

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This research aims to develop machine learning models for students' academic performance and study strategy prediction, which could be generalized to all courses in higher education. Key learning attributes (intrinsic, extrinsic, autonomy, relatedness, competence, and self-esteem) used in building the models are chosen based on prior studies, which revealed that the attributes are essential in students’ learning process. Previous studies revealed the individual effects of each of these attributes on students’ learning progress. However, few studies have investigated the combined effect of the attributes in predicting student study strategy and academic performance to reduce the dropout rate. To bridge this gap, we used Scikit-learn in python to build five machine learning models (Decision Tree, K-Nearest Neighbour, Random Forest, Linear/Logistic Regression, and Support Vector Machine) for both regression and classification tasks to perform our analysis. The models were trained, evaluated, and tested for accuracy using 924 university dentistry students' data collected by Chilean authors through quantitative research design. A comparative analysis of the models revealed that the tree-based models such as the random forest (with prediction accuracy of 94.9%) and decision tree show the best results compared to the linear, support vector, and k-nearest neighbours. The models built in this research can be used in predicting student performance and study strategy so that appropriate interventions could be implemented to improve student learning progress. Thus, incorporating strategies that could improve diverse student learning attributes in the design of online educational systems may increase the likelihood of students continuing with their learning tasks as required. Moreover, the results show that the attributes could be modelled together and used to adapt/personalize the learning process.

Keywords: classification models, learning strategy, predictive modeling, regression models, student academic performance, student motivation, supervised machine learning

Procedia PDF Downloads 128