Search results for: deep soil mixing column

Authors: J. Aliyu, A. O. Raji, A. A. Ibrahim

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The study was carried out to assess the fertility, early and late embryonic mortalities as well as hatchability by strain, season and hen’s weight in Nigerian indigenous chickens reared on deep litter. Four strains (normal feathered, naked neck, frizzle and dwarf) of hens maintained at a mating ratio of 1 cock to 4 hens, fed breeders mash and water ad libitum were used in a three year experiment. The data generated were subjected to analysis of variance using the SAS package and the means, where significant, were separated using the least significant difference (LSD). There were significant effects (P < 0.05) of strain on all the traits studied. Fertility was generally high (84.29 %) in all the strains. Early embryonic mortality was significantly lowest (P < 0.01) in naked neck which had the highest late embryonic mortality (P < 0.001). Hatchability was significantly highest (P < 0.01) in normal feathered (80.23 %) and slightly depressed in frizzle (74.95 %) and dwarf (72.27 %) while naked neck had the lowest (60.80 %). Season of the year had significant effects on early embryonic mortality. Dry hot season significantly (P < 0.05) depressed fertility while early embryonic mortality was depressed in the wet season (15.33 %). Early and late embryonic mortalities significantly increased (P < 0.05) with increasing weight of hen. Dwarf, frizzle and normal feathered hens could be used to improve hatchability as well as reduce early and late embryonic mortalities in Nigerian indigenous chickens.

Keywords: chicken, fertility, hatchability, indigenous, strain

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Authors: B. S. Choudri

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Introduction: Climate change is a major threat to rural livelihoods and to food security in the developing world, including Oman. The aim of this study is to provide a basis for policymakers and researchers in order to understand the impacts of climate change on agriculture and developing adaptation strategies in Oman. Methodology: The data was collected from different agricultural areas across the country with the help of a questionnaire survey among farmers, discussion with community, and observations at the field level. Results: The analysis of data collected from different areas within the country shows a shift in the sowing period of major crops and increased temperatures over recent years. Farmer community is adopting through diversification of crops, use of heat-tolerant species, and improved measures of soil and water conservation. Agriculture has been the main livelihood for most of the farmer communities in rural areas in the country. Conclusions: In order to reduce the effects of climate change at the local and farmer communities, risk reduction would be important along with an in-depth analysis of the vulnerability. Therefore, capacity building of local farmers and providing them with scientific knowledge, mainstreaming adaptation into development activities would be essential with additional funding and subsidies.

Keywords: agriculture, climate change, vulnerability, adaptation

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Authors: Nor Ruba’Yah Binti Abd Rahim, Norsyahidah Binti Jaafar

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Translating Malay idiomatic expressions into other languages presents unique challenges due to the deep cultural nuances and linguistic intricacies embedded within these expressions. This study examined these challenges through a two-pronged methodology: a comparative analysis using survey questionnaires and a quiz administered to 50 semester 6 students who are taking Translation 1 course, and in-depth interviews with their lecturers. The survey aimed to capture students’ experiences and difficulties in translating selected Malay idioms into English, highlighting common errors and misunderstandings. Complementing this, interviews with lecturers provided expert insights into the nuances of these expressions and effective translation strategies. The findings revealed that literal translations often fail to convey the intended meanings, underscoring the importance of cultural competence and contextual awareness. The study also identified key factors that contribute to successful translations, such as the translator’s familiarity with both source and target cultures and their ability to adapt expressions creatively. This research contributed to the field of translation studies by offering practical recommendations for improving the translation of idiomatic expressions, thereby enhancing cross-cultural communication. The insights gained from this study are valuable for translators, educators, and students, emphasizing the need for a nuanced approach that respects the cultural richness of the source language while ensuring clarity in the target language.

Keywords: idiomatic expressions, cultural competence, translation strategies, cross-cultural communication, students’ difficulties

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Authors: S. Taghvamanesh

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Modern landfills are highly engineered containment systems that are designed to reduce the environmental and human health impacts of solid waste (trash). In modern landfills, waste is contained by a liner system. The primary goal of the liner system is to isolate the landfill contents from the environment, thereby protecting the soil and groundwater from pollution caused by the leachate of a landfill. Landfill leachate is the most serious threat to groundwater. Therefore, it is necessary to design a system that prevents the penetration of this dangerous substance into the environment. These layers are made up of two basic elements: clay and geosynthetics. Hydraulic conductivity and flexibility are two desirable properties of these materials. There are three different types of liner systems that will be discussed in this paper. According to available data, the current article analyzed materials and methods for constructing liner layers made of distinct leachates, including various harmful components and heavy metals from all around the world. Also, this study attempted to gather data on leachates for each of the sites discussed. In conclusion, every landfill requires a specific type of liner, which depends on the type of leachate that it produces daily. It should also be emphasized that, based on available data, this article focused on the number of landfills that each country or continent possesses.

Keywords: landfill, liner layer, impervious layer, barrier layer

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Authors: Angelica Corcoran, Fredrik Lind, Pavleta Knutsson, Henrik Thunman

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Solid waste volumes are at current predominately deposited on landfill. Furthermore, the impending climate change requires new solutions for a sustainable future energy mix. Currently, solid waste is globally utilized to small extent as fuel during combustion for heat and power production. Due to its variable composition and size, solid waste is considered difficult to combust and requires a technology with high fuel flexibility. One of the commercial technologies used for combustion of such difficult fuels is circulating fluidized beds (CFB). In a CFB boiler, fine particles of a solid material are used as 'bed material', which is accelerated by the incoming combustion air that causes the bed material to fluidize. The chosen bed material has conventionally been silica sand with the main purpose of being a heat carrier, as it transfers heat released by the combustion to the heat-transfer surfaces. However, the release of volatile compounds occurs rapidly in comparison with the lateral mixing in the combustion chamber. To ensure complete combustion a surplus of air is introduced, which decreases the total efficiency of the boiler. In recent years, the concept of partly or entirely replacing the silica sand with an oxygen carrier as bed material has been developed. By introducing an oxygen carrier to the combustion chamber, combustion can be spread out both temporally and spatially in the boiler. Specifically, the oxygen carrier can take up oxygen from the combustion air where it is in abundance and release it to combustible gases where oxygen is in deficit. The concept is referred to as oxygen carrier aided combustion (OCAC) where the natural ore ilmenite (FeTiO3) has been the oxygen carrier used. The authors have validated the oxygen buffering ability of ilmenite during combustion of biomass in Chalmers 12-MWth CFB boiler in previous publications. Furthermore, the concept has been demonstrated on full industrial scale during combustion of municipal solid waste (MSW) in E.ON’s 75 MWth CFB boiler. The experimental campaigns have showed increased mass transfer of oxygen inside the boiler when combustion both biomass and MSW. As a result, a higher degree of burnout is achieved inside the combustion chamber and the plant can be operated at a lower surplus of air. Moreover, the buffer of oxygen provided by the oxygen carrier makes the system less sensitive to disruptions in operation. In conclusion, combusting difficult fuels with OCAC results in higher operation stability and an increase in boiler efficiency.

Keywords: OCAC, ilmenite, combustion, CFB

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: S. Z. A. Zaidi, A. Crosky

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Biocomposites is a field that has gained much scientific attention due to the current substantial consumption of non-renewable resources and the environmentally harmful disposal methods required for traditional polymer composites. Research on natural fiber reinforced polyhydroxyalkanoates (PHAs) has gained considerable momentum over the past decade. There is little work on PHAs reinforced with unidirectional (UD) natural fibers and little work on using epoxidized natural rubber (ENR) as a toughening agent for PHA-based biocomposites. In this work, we prepared polyhydroxybutyrate-co-valerate (PHBV) biocomposites reinforced with UD 30 wt.% flax fibers and evaluated the use of ENR with 50% epoxidation (ENR50) as a toughening agent for PHBV biocomposites. Quasi-unidirectional flax/PHBV composites were prepared by hand layup, powder impregnation followed by compression molding.  Toughening agents – polybutylene adiphate-co-terephthalate (PBAT) and ENR50 – were cryogenically ground into powder and mechanically mixed with main matrix PHBV to maintain the powder impregnation process. The tensile, flexural and impact properties of the biocomposites were measured and morphology of the composites examined using optical microscopy (OM) and scanning electron microscopy (SEM). The UD biocomposites showed exceptionally high mechanical properties as compared to the results obtained previously where only short fibers have been used. The improved tensile and flexural properties were attributed to the continuous nature of the fiber reinforcement and the increased proportion of fibers in the loading direction. The improved impact properties were attributed to a larger surface area for fiber-matrix debonding and for subsequent sliding and fiber pull-out mechanisms to act on, allowing more energy to be absorbed. Coating cryogenically ground ENR50 particles with PHBV powder successfully inhibits the self-healing nature of ENR-50, preventing particles from coalescing and overcoming problems in mechanical mixing, compounding and molding. Cryogenic grinding, followed by powder impregnation and subsequent compression molding is an effective route to the production of high-mechanical-property biocomposites based on renewable resources for high-obsolescence applications such as plastic casings for consumer electronics.

Keywords: natural fibers, natural rubber, polyhydroxyalkanoates, unidirectional

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Authors: Faezeh Zaefarian1, Sajedeh Golmohammadzadeh, Mohammad Rezvani

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Weed management decisions for weed species can be derived from knowledge of seed germination biology. Experiments were conducted in laboratory and greenhouse to determine the effects of light, temperature, salt and water stress, seed burial depth on seed germination and seedling emergence of Papaver rhoeas and P.dubium and to assay the response of these species to commonly available POST herbicides. Germination of the Papaver seeds was influenced by the tested temperatures (day/night temperatures of 20 and 25 °C) and light. The concentrations of sodium chloride, ranging from 0 to 80 mM, influence germination of seeds. The osmotic potential required for 50% inhibition of maximum germination of P. rhoeas was -0.27 MPa and for P. dubium species was 0.25 MPa. Seedling emergence was greatest for the seeds placed at 1 cm and emergence declined with increased burial depth in the soil. No seedlings emerged from a burial depth of 6 cm. The herbicide 2,4-D at 400 g ai ha-1 provided excellent control of both species when applied at the four-leaf and six-leaf stages. However, at the six-leaf stage, percent control was reduced. The information gained from this study could contribute to developing components of integrated weed management strategies for Papaver species.

Keywords: germination, papaver species, planting depth, POST herbicides

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Authors: M. El-Eraki, A. A. Mohamed, A. A. El-Kenawy, M. S. Toni, S. I. Mustafa

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The aim of this paper is to study the ground vibrations using Nakamura technique to evaluate the relation between the ground conditions and the earthquake characteristics. Microtremor measurements were carried out at 55 sites in and around Zagazig city. The signals were processed using horizontal to vertical spectral ratio (HVSR) technique to estimate the fundamental frequencies of the soil deposits and its corresponding H/V amplitude. Seismic measurements were acquired at nine sites for recording the surface waves. The recorded waveforms were processed using the multi-channel analysis of surface waves (MASW) method to infer the shear wave velocity profile. The obtained fundamental frequencies were found to be ranging from 0.7 to 1.7 Hz and the maximum H/V amplitude reached 6.4. These results together with the average shear wave velocity in the surface layers were used for the estimation of the thickness of the upper most soft cover layers (depth to bedrock). The sediment thickness generally increases at the northeastern and southwestern parts of the area, which is in good agreement with the local geological structure. The results of this work showed the zones of higher potential damage in the event of an earthquake in the study area.

Keywords: ambient vibrations, fundamental frequency, surface waves, zagazig

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Authors: Bulent Topcuoglu

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Repeated amendments of organic matter and intensive use of fertilizers, metal-enriched chemicals and biocides may cause soil and environmental pollution in greenhouses. Specially, the impact of heavy metal pollution of soils on food metal content and underground water quality has become a public concern. Due to potential toxicity of heavy metals to human life and environment, determining the chemical form of heavy metals in greenhouse soils is an important approach of chemical characterization and can provide useful information on its mobility and bioavailability. A sequential extraction procedure was used to estimate the availability of heavy metals (Zn, Cd, Ni, Pb and Cr) in greenhouse soils of Antalya Aksu. Zn was predominantly associated with Fe-Mn oxide fraction, major portion of Cd associated with carbonate and organic matter fraction, a major portion of (>65 %) Ni and Cr were largely associated with Fe-Mn oxide and residual fractions and Pb was largely associated with organic matter and Fe-Mn oxide fractions. Results of the present study suggest that the mobility and bioavailability of metals probably increase in the following order: Cr < Pb < Ni < Cd < Zn. Among the elements studied, Zn and Cd appeared to be the most readily soluble and potentially bioavailable metals and these metals may carry a potential risk for metal transfer in food chain and contamination to ground water.

Keywords: metal speciation, metal mobility, greenhouse soils, biosystems engineering

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Authors: O. B. Citil, V. Sariyel, M. Akoz

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In this study, total fatty acid composition of muscle lipids of Cyprinus carpio L. living in Suğla Dam Lake, Altinapa Dam Lake, Eğirdir Lake and Burdur Lake were determined using GC. During this study, for the summer season of July was taken from each region of the land and they were stored in deep-freeze set to -20 degrees until the analysis date. At the end of the analyses, 30 different fatty acids were found in the composition of Cyprinus carpio L. which lives in different lakes. Cyprinus carpio Suğla Dam Lake of polyunsaturated fatty acids (PUFAs), were higher than other lakes. Cyprinus carpio L. was the highest in the major SFA palmitic acid. Polyunsaturated fatty acids (PUFA) of carp, the most abundant fish species in all lakes, were found to be higher than those of saturated fatty acids (SFA) in all lakes. Palmitic acid was the major SFA in all lakes. Oleic acid was identified as the major MUFA. Docosahexaenoic acid (DHA) was the most abundant in all lakes. ω3 fatty acid composition was higher than the percentage of the percentage ω6 fatty acids in all lake. ω3/ω6 rates of Cyprinus carpio L. Suğla Dam Lake, Altinapa Dam Lake, Eğirdir Lake and Burdur Lake, 2.12, 1.19, 2.15, 2.87, and 2.82, respectively. Docosahexaenoic acid (DHA) was the major PUFA in Eğirdir and Burdur lakes, whereas linoleic acid (LA) was the major PUFA in Altinapa and Suğla Dam Lakes. It was shown that the fatty acid composition in the muscle of carp was significantly influenced by different lakes.

Keywords: Cyprinus carpio L., fatty acid, composition, gas chromatography

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Authors: Natalia Kartushina

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Foreign (second) language (L2) learning is highly promoted in modern society. Students are encouraged to study abroad (SA) to achieve the most effective learning outcomes. However, L2 learning has side effects for native language (L1) production, as L1 sounds might show a drift from the L1 norms towards those of the L2, and this, even after a short period of L2 learning. L1 assimilatory drift has been attributed to a strong perceptual association between similar L1 and L2 sounds in the mind of L2 leaners; thus, a change in the production of an L2 target leads to the change in the production of the related L1 sound. However, nowadays, it is quite common that speakers acquire two languages from birth, as, for example, it is the case for many bilingual communities (e.g., Basque and Spanish in the Basque Country). Yet, it remains to be established how FL learning affects native production in individuals who have two native languages, i.e., in simultaneous or very early bilinguals. Does FL learning (here a third language, L3) affect bilinguals’ both languages or only one? What factors determine which of the bilinguals’ languages is more susceptible to change? The current study examines the effects of L3 (English) learning on the production of vowels in the two native languages of simultaneous Spanish-Basque bilingual adolescents enrolled into the Erasmus SA English program. Ten bilingual speakers read five Spanish and Basque consonant-vowel-consonant-vowel words two months before their SA and the next day after their arrival back to Spain. Each word contained the target vowel in the stressed syllable and was repeated five times. Acoustic analyses measuring vowel openness (F1) and backness (F2) were performed. Two possible outcomes were considered. First, we predicted that L3 learning would affect the production of only one language and this would be the language that would be used the most in contact with English during the SA period. This prediction stems from the results of recent studies showing that early bilinguals have separate phonological systems for each of their languages; and that late FL learner (as it is the case of our participants), who tend to use their L1 in language-mixing contexts, have more L2-accented L1 speech. The second possibility stated that L3 learning would affect both of the bilinguals’ languages in line with the studies showing that bilinguals’ L1 and L2 phonologies interact and constantly co-influence each other. The results revealed that speakers who used both languages equally often (balanced users) showed an F1 drift in both languages toward the F1 of the English vowel space. Unbalanced speakers, however, showed a drift only in the less used language. The results are discussed in light of recent studies suggesting that the amount of language use is a strong predictor of the authenticity in speech production with less language use leading to more foreign-accented speech and, eventually, to language attrition.

Keywords: language-contact, multilingualism, phonetic drift, bilinguals' production

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Authors: Ebert Brea

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We propose a novel direct search algorithm for identifying at least a local minimum of mixed integer nonlinear unconstrained optimization problems. The Mixed Integer Randomized Pattern Search Algorithm (MIRPSA), so-called by the author, is based on a randomized pattern search, which is modified by the MIRPSA for finding at least a local minimum of our problem. The MIRPSA has two main operations over the randomized pattern search: moving operation and shrinking operation. Each operation is carried out by the algorithm when a set of conditions is held. The convergence properties of the MIRPSA is analyzed using a Markov chain approach, which is represented by an infinite countable set of state space λ, where each state d(q) is defined by a measure of the qth randomized pattern search Hq, for all q in N. According to the algorithm, when a moving operation is carried out on the qth randomized pattern search Hq, the MIRPSA holds its state. Meanwhile, if the MIRPSA carries out a shrinking operation over the qth randomized pattern search Hq, the algorithm will visit the next state, this is, a shrinking operation at the qth state causes a changing of the qth state into (q+1)th state. It is worthwhile pointing out that the MIRPSA never goes back to any visited states because the MIRPSA only visits any qth by shrinking operations. In this article, we describe the MIRPSA for mixed integer nonlinear unconstrained optimization problems for doing a deep study of its convergence properties using Markov chain viewpoint. We herein include a low dimension case for showing more details of the MIRPSA, when the algorithm is used for identifying the minimum of a mixed integer quadratic function. Besides, numerical examples are also shown in order to measure the performance of the MIRPSA.

Keywords: direct search, mixed integer optimization, random search, convergence, Markov chain

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Authors: Ke Yang, QiHan, Bauke de Veirs

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This study addresses the need for coordinated management of natural resources in urban agglomeration. Using ecosystem services theory, The study explore the relationship between land use in the Beijing-Tianjin-Hebei (B-T-H) region and the Food-Water-Energy (F-W-E) nexus from 2000 to 2030. We assess ecosystem services using the InVEST: Habitat Quality (HQ), Water Yield (WY), Carbon Sequestration (CS), Soil Retention (SDR), and Food Production (FP). The study find an annual expansion of construction land alongside a significant decline in cultivated land. Additionally, HQ, CS, and per capita FP decline annually until 2020 and are expected to persist through 2030. In contrast, WY and SDR grow annually but may decline by 2030. Spearman coefficient analysis reveals synergies between HQ and CS, SDR and CS, and SDR and HQ, with trade-offs between CS and WY and HQ and WY. Utilizing the K-means clustering analysis method, we introduce county-based spatial planning for the F-W-E system, offering valuable insights and recommendations for sustainable resource management.

Keywords: food-water-energy (F-W-E), ecosystem services, trade-offs and synergies, ecosystem service bundle, county-based

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Authors: Anna Kowalik-Klimczak, Maciej żYcki, Monika łOżYńska, Wioletta Barszcz, Jolanta Drabik

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The rapidly changing fashion trends generate huge amounts of leather and textile waste globally. The complexity of these types of waste makes recycling difficult in economic terms. Pyrolysis is suggested for this purpose, which transforms heterogeneous and complex waste into added-value products e.g. active carbons and soil fertilizer. The possibility of using pyrolysis for the valorization of leather and textile waste has been analyzed in this paper. In the first stage, leather and textile waste were subjected to TG/DTG thermogravimetric and DSC calorimetric analysis. These analyses provided basic information about thermochemical transformations and degradation rates during the pyrolysis of these types of waste and enabled the selection of the pyrolysis temperature. In the next stage, the effect of gas type using pyrolysis was investigated on the physicochemical properties, composition, structure, and formation of the specific surfaces of carbonized materials produced by means of a thermal treatment without oxygen access to the reaction chamber. These studies contribute some data about the thermal management and pyrolytic processing of leather and textile waste into useful carbonized materials, according to the circular economy model.

Keywords: pyrolysis, leather and textiles waste, composition and structure of carbonized materials, valorisation of waste, circular economy model

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Authors: Kiran Fatima, Kashif Ali

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Staphylococcus aureus is an opportunistic human as well as animal pathogen that causes a variety of diseases. A total of 70 staphylococci isolates were obtained from soil, water, yogurt, and clinical samples. The likely staphylococci clinical isolates were identified phenotypically by different biochemical tests. Molecular identification was done by PCR using species-specific 16S rRNA primer pairs, and finally, 50 isolates were found to be positive as Staphylococcus aureus, sciuri, xylous and cohnii. Screened isolates were further analyzed by several microbiological diagnostics tests, including gram staining, coagulase, capsule, hemolysis, fermentation of glucose, lactose, maltose, and sucrose tests enzymatic reactions. It was found that 78%, 81%, and 51% of isolates were positive for gelatin hydrolysis, protease, and lipase activities, respectively. Antibiogram analysis of isolated Staphylococcus aureus strains with respect to different antimicrobial agents revealed resistance patterns ranging from 57 to 96%. Our study also shows 70% of strains to be MRSA, 54.3% as VRSA, and 54.3% as both MRSA and VRSA. All the identified isolates were subjected to detection of mecA, nuc, and hlb genes, and 70%, 84%, and 40% were found to harbour mecA, nuc, and hlb genes, respectively. The current investigation is highly important and informative for the high-level multidrug-resistant Staphylococcus aureus infections inclusive also of methicillin and vancomycin.

Keywords: MRSA, VRSA, mecA, MSSA

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Fadlan Atmaja Nursiwan, Ugi Kurnia Gusti

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Garba Hill, located in Tekana Village, South Sumatera Province is comprised to South Sumatra Basin and classified as back arc basin. This area is entered as an active margin of Sundaland which experiences subduction several times since Mesozoic to recent time. The traces of Mesozoic subduction in the southern part of Sumatra island are exposed in Garba Hill area. The aim of this investigation is to study the tectonic changes in the first phase in Mesozoic era at the active margin of Sundaland which causes the rocks assemblage in Garba hill consist of continental and oceanic plate rocks which the correlation between those rocks show indistinct relation. This investigation is conducted by field observation in Tekana village and Lubar Village, Muara Dua, South Sumatra along with laboratory analysis included fossil and geochemistry analysis of radiolarian chert, petrography analysis of granite and basalt, and structural modelling. Fossil and geochemistry analysis of radiolarian chert and geochemistry of granite rocks shown the relation between the two rocks and Mesozoic subduction of Woyla terrane on western margin of Sundaland. Petrography analysis from granite and basalt depict the tectonic affinity of rocks. Moreover, structural analysis showed the changes of lineation direction from N-S to WNW-ESE.

Keywords: granite, mesozoic, radiolarian, subduction traces

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Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

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The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

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Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

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The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Mohammad Hossein Badamchi

Abstract:

As Leo Strauss demonstrates in his works, Political Philosophy in the western tradition is an epistemic-naturalistic tradition insofar Hanna Arendt mentioning the deep conflict between philosophy and politics, opposed to be named “political philosopher” prefer the title “political thinker” for herself. In fact, the Western political philosophy’s tendency to derive politics from natural law and epistemic argumentations makes a paradox between the actual “the political” and the theoretical “natural politics” in the western tradition. In this paper, we want to show that Hanna Arendt, in her exploration to find a new realm of the non-naturalistic way of thinking about the political is walking on a completely different tradition of political philosophy which was first established by Al-Farabi, the founder of Islamic political philosophy around thousand years after Greek Philosophy. Despite Aristotelian Polis which is a Natural community based on true natural rationality to reach the natural purposes of mankind, Al-Farabi’s Madine (his reconstructed concept of Aristotelian Polis) is completely constructed against natural cities, which are formulated by necessity logic of natural arguments and natural deception of humanity. In fact, Farabi considers the natural understanding of politics as Ignorant ideologies used by governments to suppress people. Madine in Farabi’s work is not a natural institution but is a collaborative constitution founded by citizens. So despite Aristotelian thinking, here we don’t have just A Polis that is the one true polis, but we have various multiple Madines among one, is virtuous not by definition but by real action of citizens and civil relations. Al-Farabi’s political philosophy is not a Naturalistic-epistemic Political Philosophy but is a Phronetic Political Philosophy which Hanna Arendt wants to establish outside of western contemplative anti-active political philosophy tradition.

Keywords: al-farabi, hanna arendt, natural politics, the political, political philosophy

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Authors: Orsolya Kegyes-Brassai, Zsolt Szilvágyi, Ákos Wolf, Richard P. Ray

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Local ground conditions have a substantial influence on the seismic response of structures. Their inclusion in seismic hazard assessment and structural design can be realized at different levels of sophistication. However, response results based on more advanced calculation methods e.g. nonlinear or equivalent linear site analysis tend to show significant discrepancies when compared to simpler approaches. This project's main objective was to compare results from several 1-D response programs to Eurocode 8 design spectra. Data from in-situ site investigations were used for assessing local ground conditions at several locations in Hungary. After discussion of the in-situ measurements and calculation methods used, a comprehensive evaluation of all major contributing factors for site response is given. While the Eurocode spectra should account for local ground conditions based on soil classification, there is a wide variation in peak ground acceleration determined from 1-D analyses versus Eurocode. Results show that current Eurocode 8 design spectra may not be conservative enough to account for local ground conditions typical for Hungary.

Keywords: 1-D site response analysis, multichannel analysis of surface waves (MASW), seismic CPT, seismic hazard assessment

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Authors: Daniel Rosero, Johan S. Arana, Sebastian Arango, Alejandro Cruz, Isabel Gomez-Gutierrez, Peter Thomson

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Santiago de Cali is located in the southwestern Colombia in a high seismic hazard zone. About 50% of the city is on the banks of the Cauca River, which is the second most important hydric affluent in the country and whose alluvial deposits contain potentially liquefiable sands. Among the methods used to study a site's liquefaction potential is the finite elements method which use constitutive models to simulate the soil response for different load types. Among the different constitutive models, the Modified UBCSand stands out to study the seismic behavior of sands, and especially the liquefaction phenomenon. In this paper, the dynamic behavior of a potentially liquefiable sand of Santiago de Cali is studied by cyclic triaxial and CPTu tests. Subsequently, the behavior of the sand is simulated using the Modified UBCSand constitutive model, whose parameters are calibrated using the results of cyclic triaxial and CPTu tests. The above with the aim of analyze the constitutive model applicability for studying the geotechnical problems associated to liquefaction in the city.

Keywords: constitutive model, cyclic triaxial test, dynamic behavior, liquefiable sand, modified ubcsand

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Authors: Mohd Iqbal Malik

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Ethical philosophy of Quran pinnacled virtue and economics as the part and parcel of human life. Human beings are to be imagined by the sign of morals. Soul and morality are both among the essences of human personality. Islam lays the foundation of ethics by installation of making a momentous variance between virtue and vice. It suggests for the distribution of wealth in-order to terminate accumulation of economic resources. Quran claims for the ambiguous pavement to attain virtue by saying, ‘Never will you attain the good (reward) until you spend (in the way of Allah) from that which you love. And whatever you spend indeed, Allah knows of it.’ The essence of Quran is to eliminate all the deep-seated approaches through which the wealth of nations is being accumulated within few hands. The paper will study the Quranic Philosophy Of Islamic Economic System. In recent times, to get out of the human resource development mystery of Muslims, Ismail Al-Raji Faruqi led the way in the so-called ‘Islamization’ of knowledge. Rahman and Faruqi formed opposite opinions on this project. Al-Faruqi thought of the Islamization of knowledge in terms of introducing Western learning into received Islamic values and vice versa. This proved to be a mere peripheral treatment of Islamic values in relation to Western knowledge. It is true that out of the programme of Islamization of knowledge arose Islamic universities in many Muslim countries. Yet the academic programmes of these universities were not founded upon a substantive understanding and application of the tawhidi epistemology.

Keywords: ethical philosophy, modern Islamic finance, knowledge of finance, Islamic banking

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Sangram Shamrao Patil, Hara Mohan Jena

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Phthalates are among the most common organic pollutant since they have become widespread in the environment and found in sediments, natural waters, soils, plants, landfill leachates, biota including human tissue and aquatic organisms. Diethyl phthalate (DEP) is a low molecular weight phthalate which has wide applications as plasticizer and become a major cause of environmental pollution. Environmental protection agency (EPA) listed DEP as priority pollutant because of its toxicity and they recommended human health ambient water quality criterion for diethyl phthalate (DEP) as 4 mg/l. Therefore, wastes containing phthalates require proper treatment before being discharged into the environment. Biodegradation is attractive and efficient treatment method as it is cost effective and produces non-toxic end products. In the present study, a DEP degrading aerobic bacterium was isolated from soil contaminated with plastic industry wastewater. Morphological and biochemical characteristics of isolate were performed. 16S rRNA sequencing and phylogenetic analysis of isolate was carried out and it was identified as Empedobacter brevis. Isolate has been found to tolerate up to 1650 mg/l of DEP. This study will be significant for exploring an application of microbes for remediation of phthalates and development of a suitable bioreactor.

Keywords: diethyl phthalate, plasticizer, pollutant, biodegradation

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Authors: Rushva Parihar, Anushka Barua

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The negative repercussions of a warming planet are already visible, with biodiversity loss, water scarcity, and extreme weather events becoming ever so frequent. The agriculture sector is perhaps the most impacted, and modern agriculture has failed to defend farmers from the effects of climate change. This, coupled with the added pressure of higher demands for food production caused due to population growth, has only compounded the impact. Traditional agricultural practices that are routed in indigenous knowledge have long safeguarded the delicate balance of the ecosystem through sustainable production techniques. This paper uses secondary data to explore these traditional processes (like Beejamrita, Jeevamrita, sheep penning, earthen bunding, and others) from around the world that have been developed over centuries and focuses on how they can be used to tackle contemporary issues arising from climate change (such as nutrient and water loss, soil degradation, increased incidences of pests). Finally, the resulting framework has been applied to the context of Indian agriculture as a means to combat climate change and improve food security, all while encouraging documentation and transfer of local knowledge as a shared resource among farmers.

Keywords: sustainable food systems, traditional agricultural practices, climate smart agriculture, climate change, indigenous knowledge

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 154