Search results for: alkaline extraction

Authors: Hilary Rutto

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The investigation was aimed at determining the extent at which the zinc will be extracted from secondary sources generated from galvanising process using dilute sulphuric acid under controlled laboratory conditions of temperature, solid-liquid ratio, and agitation rate. The leaching experiment was conducted for a period of 2 hours and to total zinc extracted calculated in relation to the amount of zinc dissolved at a unit time in comparison to the initial zinc content of the zinc ash. Sulphuric acid was found to be an effective leaching agent with an overall extraction of 91.1% when concentration is at 2M, and solid/liquid ratio kept at 1g/200mL leaching solution and temperature set at 65ᵒC while slurry agitation is at 450rpm. The leaching mechanism of zinc ash with sulphuric acid was conformed well to the shrinking core model.

Keywords: leaching, kinetics, shrinking core model, zinc slag

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Authors: Lamidi Lawal Aduozava

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Masquerade tradition is an indigenous culture of the Anetuno an extraction of the Ebira referred to as Ebira chao. This paper seeks to make aesthetic analysis of the masquerades in terms of their costumes and socio-cultural significance. To this end, the study examined and documented the functions and roles of Anipo and Idowo masquerades in terms of therapeutic, economic, prophetic and divination, entertainment, and funeral functions to the owner community(Eziobe group of families) in Igarra, Edo State of Nigeria, West Africa. For the purpose of data collection, focus group discussion, participatory, visual and observatory methods of data collection were used. All the data collected were aesthetically, descriptively and historically analyzed.

Keywords: Aesthetics, , Costume, , Masquerades, , Significance.

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Authors: Maria Reichenber Arcilla

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Objective: To determine the risk factors for maternal and neonatal complications associated with operative vaginal deliveries. Methods: A retrospective chart review of 435 patients who underwent operative vaginal deliveries was done. Patient profiles – age, parity, AOG, duration of labor – and outcomes – birthweight, maternal and neonatal complications - were tabulated and multivariable analysis and logistic regression were performed using SPSS® Statistics Base. Results and Conclusion: There was no significant difference in the incidence of maternal and neonatal complications between those that underwent vacuum and forceps extraction. Among the variables analysed, parity and duration of labor reached statistical significance. The odds of maternal complications were 3 times higher among nulliparous patients. Neonatal complications were seen in those whose labor lasted more than 9 hours.

Keywords: operative vaginal deliveries, maternal, neonatal, morbidity

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Authors: A. A Warra, S. Fatima

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The experimental investigation revealed that the hexane extract of onion seed oil has acid value, iodine value, peroxide value, saponification value, relative density and refractive index of 0.03±0.01 mgKOH/g, 129.80±0.21 gI2/100g, 3.00± 0.00 meq H2O2 203.00±0.71 mgKOH/g, 0.82±0.01and 1.44±0.00 respectively. The percentage yield was 50.28±0.01%. The colour of the oil was light green. We restricted our GC-MS spectra interpretation to compounds identification, particularly fatty acids and they are identified as palmitic acid, linolelaidic acid, oleic acid, stearic acid, behenic acid, linolenic acid and eicosatetraenoic acid. The pH , foam ability (cm³), total fatty matter, total alkali and percentage chloride of the onion oil soap were 11.03± 0.02, 75.13±0.15 (cm³), 36.66 ± 0.02 %, 0.92 ± 0.02% and 0.53 ± 0.15 % respectively. The texture was soft and the colour was lighter green. The results indicated that the hexane extract of the onion seed oil has potential for cosmetic industries.

Keywords: onion seeds, soxhlet extraction, physicochemical, GC-MS, cold saponification

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Authors: Mounir Zekkaoui, Abdelhadi Fennan

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The software evolution control requires a deep understanding of the changes and their impact on different system heterogeneous artifacts. And an understanding of descriptive knowledge of the developed software artifacts is a prerequisite condition for the success of the evolutionary process. The implementation of an evolutionary process is to make changes more or less important to many heterogeneous software artifacts such as source code, analysis and design models, unit testing, XML deployment descriptors, user guides, and others. These changes can be a source of degradation in functional, qualitative or behavioral terms of modified software. Hence the need for a unified approach for extraction and representation of different heterogeneous artifacts in order to ensure a unified and detailed description of heterogeneous software artifacts, exploitable by several software tools and allowing to responsible for the evolution of carry out the reasoning change concerned.

Keywords: heterogeneous software artifacts, software evolution control, unified approach, meta model, software architecture

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

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Authors: Aiman Alshare, Sahar Qaadan

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A curvature dependent force correction algorithm for planning force controlled grinding process with off-line programming flexibility is designed for ABB industrial robot, in order to avoid the manual interface during the process. The machining path utilizes a spline curve fit that is constructed from the CAD data of the workpiece. The fitted spline has a continuity of the second order to assure path smoothness. The implemented algorithm computes uniform forces normal to the grinding surface of the workpiece, by constructing a curvature path in the spatial coordinates using the spline method.

Keywords: ABB industrial robot, grinding process, offline programming, CAD data extraction, force correction algorithm

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Assia Galleze, Abdurrahim Kocyigit, Nacira Cherif, Nidel Benhalilou, Nabila Attal, Chafia Touil Boukkoffa, Rachida Raache

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Introduction and aims: Chemotherapeutic agents used to inhibit cell division and reduce tumor growth, increase reactive oxygen species levels, which contributes to their genotoxicity [1]. The comet assay is an inexpensive and rapid method to detect the damage at cellular levels and has been used in various cancer populations undergoing chemotherapy [2,3]. The present study aim to assess the oxidative stress and the genotoxicity induced by chemotherapy by the determination of plasma malondialdehyde (MDA) level, protein carbonyl (PC) content, superoxide dismutase (SOD) activity and lymphocyte DNA damage in Algerian children with lymphoma. Materials and Methods: For our study, we selected thirty children with lymphoma treated in university hospital of Beni Messous, Algeria, and fifty unrelated subjects as controls, after obtaining the informed consent in accordance with the Declaration of Helsinki (1964). Plasma levels of MDA, PC and SOD activity were spectrophotometrically measured, while DNA damage was assessed by alkaline comet assay in peripheral blood leukocytes. Results and Discussion: Plasma MDA, PC levels and lymphocyte DNA damage, were found to be significantly higher in lymphoma patients than in controls (p < 0.001). Whereas, SOD activity in lymphoma patients was significantly lower than in healthy controls (p < 0.001). There were significant positive correlations between DNA damage, MDA and PC in patients (r = 0.96, p < 0.001, r = 0.97, p < 0.001, respectively), and negative correlation with SOD (r = 0.87, p < 0.01). Conclusion and Perspective: Our results indicated that, leukocytes DNA damage and oxidative stress were significantly higher in lymphoma patients, suggesting that the direct effect of chemotherapy and the alteration of the redox balance may influence oxidative/antioxidative status.

Keywords: chemotherapy, comet assay, DNA damage, lymphoma

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Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Mao-Sheng Su, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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Climate change is widely recognized as a global crisis, with anthropogenic CO₂ emissions from fossil fuel combustion and industrial processes being major contributors. To address this challenge, carbon capture and sequestration (CCS) technology has emerged as a key strategy for selectively capturing CO₂ from flue gas streams. Among the various solid adsorbents, metal–organic frameworks (MOFs) are notable for their extensive surface area and controllable pore chemistry. The porous MOF structure is comprised of metal ions or clusters coordinated to organic linker compounds. In particular, the pore parameters of MOFs are readily tunable, making them promising materials for CO₂ capture applications. Among these, amine-functionalized MOFs have demonstrated exceptional CO₂ capture abilities because their high uptake capacity and selectivity. In this study, we have investigated the CO₂ capture abilities and adsorption mechanisms of the diamine-appended framework N-Ethylethylenediamine-Mg₂(4,4’-dioxidobiphenyl-3,3’-dicarboxylate) (e-2-Mg₂(dobpdc)) using density functional theory (DFT) calculations. Previous studies have suggested that CO₂ can be captured via both outer- and inner-amine binding sites. Our findings reveal that CO₂ adsorption at the outer amine site is kinetically more favorable compared to the inner amine site, with a lower energy barrier of 1.34 eV for CO₂ physisorption to chemisorption compared to the inner amine, which has an activation barrier of 1.60 eV. Furthermore, we find that CO₂ adsorption is significantly enhanced in an alkaline environment, as deprotonation of the diamine molecule reduces the energy barrier to 0.24 eV. This theoretical study provides detailed insights into CO₂ adsorption in diamine-appended e-2-Mg₂(dobpdc) MOF, offering a deeper understanding of CO₂ capture mechanisms and valuable information for the advancement of effective CO₂ sequestration technologies.

Keywords: DFT, MOFs, CO₂ capture, catalyst

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Sunil Verma

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In today’s world non-renewable sources are depleting quickly, so there is a need to produce efficient and unconventional engines to minimize the use of fuel. Also, there are many fatal accidents happening every year during extraction, distillation, transportation and storage of fuel. Reason for explosions of gaseous fuel is unwanted autoignition. Autoignition characterstics of fuel are mandatory to study to build efficient engines and to avoid accidents. This report is concerned with study of autoignition delay characteristics of iso-octane by using rapid compression machine. The paper clearly explains the dependence of ignition delay characteristics on variation of equivalence ratios from lean to rich mixtures. The equivalence ratio is varied from 0.3 to 1.2.

Keywords: autoignition, iso-octane, combustion, rapid compression machine, equivalence ratio, ignition delay

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Authors: Shiming Li, Qingwang Liu, Honggan Wu, Jianbing Zhang

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Plantation forests are useful for timber production, recreation, environmental protection and social development. Stands height is an important parameter for the estimation of forest volume and carbon stocks. Although lidar is suitable technology for the vertical parameters extraction of forests, but high costs make it not suitable for operational inventory. With the development of computer vision and photogrammetry, aerial photos from unmanned aerial system can be used as an alternative solution for height mapping. Structure-from-motion (SfM) photogrammetry technique can be used to extract DSM and DEM information. Canopy height model (CHM) can be achieved by subtraction DEM from DSM. Our result shows that overlapping aerial photos is a potential solution for plantation forests height mapping.

Keywords: forest height mapping, plantation forests, structure-from-motion photogrammetry, UAS

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Authors: Syed Islam, Yiyun Huang, Sebastian Magierowski, Ebrahim Ghafar-Zadeh

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This paper presents system level CMOS solid-state nanopore techniques enhancement for speedup next generation molecular recording and high throughput channels. This discussion also considers optimum number of base-pair (bp) measurements through channel as an important role to enhance potential read accuracy. Effective power consumption estimation offered suitable rangeof multi-channel configuration. Nanopore bp extraction model in statistical method could contribute higher read accuracy with longer read-length (200 < read-length). Nanopore ionic current switching with Time Multiplexing (TM) based multichannel readout system contributed hardware savings.

Keywords: DNA, nanopore, amplifier, ADC, multichannel

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

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Authors: Isabella Bianco, Gian Andrea Blengini

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The environmental impact related to ornamental stones (such as marbles and granites) is largely debated. Starting from the industrial revolution, continuous improvements of machineries led to a higher exploitation of this natural resource and to a more international interaction between markets. As a consequence, the environmental impact of the extraction and processing of stones has increased. Nevertheless, if compared with other building materials, ornamental stones are generally more durable, natural, and recyclable. From the scientific point of view, studies on stone life cycle sustainability have been carried out, but these are often partial or not very significant because of the high percentage of approximations and assumptions in calculations. This is due to the lack, in life cycle databases (e.g. Ecoinvent, Thinkstep, and ELCD), of datasets about the specific technologies employed in the stone production chain. For example, databases do not contain information about diamond wires, chains or explosives, materials commonly used in quarries and transformation plants. The project presented in this paper aims to populate the life cycle databases with specific data of specific stone processes. To this goal, the methodology follows the standardized approach of Life Cycle Assessment (LCA), according to the requirements of UNI 14040-14044 and to the International Reference Life Cycle Data System (ILCD) Handbook guidelines of the European Commission. The study analyses the processes of the entire production chain (from-cradle-to-gate system boundaries), including the extraction of benches, the cutting of blocks into slabs/tiles and the surface finishing. Primary data have been collected in Italian quarries and transformation plants which use technologies representative of the current state-of-the-art. Since the technologies vary according to the hardness of the stone, the case studies comprehend both soft stones (marbles) and hard stones (gneiss). In particular, data about energy, materials and emissions were collected in marble basins of Carrara and in Beola and Serizzo basins located in the province of Verbano Cusio Ossola. Data were then elaborated through an appropriate software to build a life cycle model. The model was realized setting free parameters that allow an easy adaptation to specific productions. Through this model, the study aims to boost the direct participation of stone companies and encourage the use of LCA tool to assess and improve the stone sector environmental sustainability. At the same time, the realization of accurate Life Cycle Inventory data aims at making available, to researchers and stone experts, ILCD compliant datasets of the most significant processes and technologies related to the ornamental stone sector.

Keywords: life cycle assessment, LCA datasets, ornamental stone, stone environmental impact

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Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

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In this work we present an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods: the parameters of distribution, the moments centered of the different projections and the Barr features. It should be noted that these methods are applied on segments gotten after the division of the binary image of the word in six segments. The classification is achieved by a multi layers perceptron. Detailed experiments are carried and satisfactory recognition results are reported.

Keywords: handwritten word recognition, neural networks, image processing, pattern recognition, features extraction

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Authors: Boukari Nassim

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This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

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Authors: Aminah Salim, Idrees Ahmed Nasir, Abdul Qayyum Rao, Muhammad Ali, Muhammad Sohail Anjum, Ayesha Hameed, Bushra Tabassum, Anwar Khan, Arfan Ali, Mariyam Zameer, Tayyab Husnain

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Risk assessment of transgenic herbicide tolerant sugarcane having CEMB codon optimized cp4EPSPS gene was done in present study. Fifteen days old chicks taken from K&Ns Company were randomly assorted into four groups with eight chicks in each group namely control chicken group fed with commercial diet, non-transgenic group fed with non-experimental sugarcane and transgenic group fed with transgenic sugarcane with minimum and maximum level. Body weights, biochemical analysis for Urea, alkaline phosphatase, alanine transferase, aspartate transferase, creatinine and bilirubin determination and histological examination of chicks fed with four types of feed was taken at fifteen days interval and no significant difference was observed in body weight biochemical and histological studies of all four groups. Protein isolated from the serum sample was analyzed through dipstick and SDS-PAGE, showing the absence of transgene protein in the serum sample of control and experimental groups. Moreover the amplification of cp4EPSPS gene with gene specific primers of DNA isolated from chicks blood and also from commercial diet was done to determine the presence and mobility of any nucleotide fragment of the transgene in/from feed and no amplification was obtained in feed as well as in blood extracted DNA of any group. Also no mRNA expression of cp4EPSPS gene was obtained in any tissue of four groups of chicks. From the results it is clear that there is no deleterious or harmful effect of the CEMB codon optimized transgenic cp4EPSPS sugarcane on the chicks health.

Keywords: chicks, cp4EPSPS, glyphosate, sugarcane

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Authors: Rajkumar Ghosh

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The industrialization of coal mining and related activities has a significant impact on groundwater in the surrounding areas of the Damodar River. The Damodar River basin, located in eastern India, is known as the "Ruhr of India" due to its abundant coal reserves and extensive coal mining and industrial operations. One of the major consequences of collieries on groundwater is the contamination of water sources. Coal mining activities often involve the excavation and extraction of coal through underground or open-pit mining methods. These processes can release various pollutants and chemicals into the groundwater, including heavy metals, acid mine drainage, and other toxic substances. As a result, the quality of groundwater in the Damodar River region has deteriorated, making it unsuitable for drinking, irrigation, and other purposes. The high concentration of heavy metals, such as arsenic, lead, and mercury, in the groundwater has posed severe health risks to the local population. Prolonged exposure to contaminated water can lead to various health problems, including skin diseases, respiratory issues, and even long-term ailments like cancer. The contamination has also affected the aquatic ecosystem, harming fish populations and other organisms dependent on the river's water. Moreover, the excessive extraction of groundwater for industrial processes, including coal washing and cooling systems, has resulted in a decline in the water table and depletion of aquifers. This has led to water scarcity and reduced availability of water for agricultural activities, impacting the livelihoods of farmers in the region. Efforts have been made to mitigate these issues through the implementation of regulations and improved industrial practices. However, the historical legacy of coal industrialization continues to impact the groundwater in the Damodar River area. Remediation measures, such as the installation of water treatment plants and the promotion of sustainable mining practices, are essential to restore the quality of groundwater and ensure the well-being of the affected communities. In conclusion, the coal industrialization in the Damodar River surrounding has had a detrimental impact on groundwater. This research focuses on soil subsidence induced by the over-exploitation of ground water for dewatering open pit coal mines. Soil degradation happens in arid and semi-arid regions as a result of land subsidence in coal mining region, which reduces soil fertility. Depletion of aquifers, contamination, and water scarcity are some of the key challenges resulting from these activities. It is crucial to prioritize sustainable mining practices, environmental conservation, and the provision of clean drinking water to mitigate the long-lasting effects of collieries on the groundwater resources in the region.

Keywords: coal mining, groundwater, soil subsidence, water table, damodar river

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Authors: I. M. Fakai, A. Abdulhamid, I. Sani, F. Bello, E. O. Olusesi

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The phytochemical screening and hepatotoxic effect of Datura metel aqueous seeds extract in Albino Wistar rats were evaluated. Phytochemicals were screened using standard methods. The enzymes activity and liver function indices were also determined using standard methods of analysis. The phytochemicals screening revealed the presence of alkaloid, tannin, glycoside and flavonoid. The organ-body weight decreased significantly (P<0.05) at all the doses of the extract treated groups compared to the control. The activity of alkaline phosphatase decreased significantly (P<0.05) in the liver and increased significantly in the serum at all the doses of the extract treated groups compared to the control. The activity of serum alanine transaminase increased significantly (P<0.05) while there is no significant difference (P>0.05) in the activity liver alanine transaminase at all the doses of the extract treated groups compared to the control. The result also revealed significant increase (P<0.05) in the aspartate transaminase activity in both liver and serum at all doses of the extract treated groups compared to the control. Serum total protein, albumin, globulin, and total bilirubin concentration decreased significantly (P<0.05), while direct bilirubin concentration increased significantly (P<0.05) at all the doses of the extract treated groups compared to the control. The present study therefore revealed that, the present of some phytochemicals in the plant extract attributed the plant to its hepatotoxic effects as revealed in the alteration of marker enzymes and some liver function indices analyzed.

Keywords: datura metel, transaminases, hepatotoxic effect, phytochemicals, rats

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Authors: K. Swapna

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A Series of Alkali-Earth Boro Tellurite (AEBT) glasses doped with different concentrations of Dy³⁺ ions have been prepared by using melt quenching technique and characterized through spectroscopic techniques such as optical absorption, excitation, emission and photoluminescence decay to understand their utility in optoelectronic devices such as lasers and white light emitting diodes (w-LEDs). Raman spectrum recorded for an undoped glass is used to measure the phonon energy of the host glass and various functional groups present in the host glass (AEBT). The intensities of the electronic transitions and the ligand environment around the Dy³⁺ ions were studied by applying Judd-Ofelt (J-O) theory to the recorded absorption spectra of the glasses. The evaluated J-O parameters are subsequently used to measure various radiative parameters such as transition probability (AR), radiative branching ratio (βR) and radiative lifetimes (τR) for the prominent fluorescent levels of Dy³⁺ ions in the as-prepared glasses. The luminescence spectra recorded at 387 nm excitation show three emission transitions (⁴F9/2→⁶H15/2 (blue), ⁴F9/2→⁶H13/2 (yellow) and ⁴F9/2 → ⁶H11/2 (red)) of which the yellow transition observed at 575 nm is found to be highly intense. The experimental branching ratio (βexp) and stimulated emission crosssection (σse) were measured from luminescence spectra. The experimental lifetimes (τexp) measured from the decay spectral profiles are combined with radiative lifetimes to measure quantum efficiencies of the as-prepared glasses. The yellow to blue intensity ratios and chromaticity color coordinates are found to vary with Dy³⁺ ion concentrations. The aforementioned results reveal that these glasses are aptly suitable for w-LEDs and laser devices.

Keywords: glasses, J-O parameters, photoluminescence, I-H model

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Authors: Milad Mirzaei Aminiyan, Abdolreza Akhgar, Farzad Mirzaei Aminiyan

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Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Pistachio is a main crop that accounts for a considerable portion of Iranian agricultural exports. Give that pistachio tree is a tolerant type of tree to saline and alkaline soil and water conditions, but groundwater and irrigation water quality play important roles in main production this crop. For this purpose, 94 well water samples were taken from 25 wells and samples were analyzed. The results showed give that region’s geological, climatic characteristics, statistical analysis, and based on dominant cations and anions in well water samples (piper diagram); four main types of water were found: Na-Cl, K-Cl, Na-SO4, and K-SO4. It seems that most wells in terms of water quality (salinity and alkalinity) and based on Wilcox diagram have critical status. The analysis suggested that more than eighty-seven percentage of the well water samples have high values of EC that these values are higher than into critical limit EC value for irrigation water, which may be due to the sandy soils in this area. Most groundwater were relatively unsuitable for irrigation but it could be used by application of correct management such as removing and reducing the ion concentrations of Cl‾, SO42‾, Na+ and total hardness in groundwater and also the concentrated deep groundwater was required treatment to reduce the salinity and sodium hazard. Given that irrigation water quality in this area was relatively unsuitable for most agriculture production but pistachio tree was adapted to this area conditions. The integrated management of groundwater for irrigation is the way to solve water quality issues not only in Rafsanjan area, but also in other arid and semi-arid areas.

Keywords: groundwater quality, irrigation water quality, salinity, alkalinity, Rafsanjan plain, pistachio

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Authors: Chris Miskelly, Eoin Cunningham, Beatrice Smyth, John. D. Holbrey, Gosia Swadzba-Kwasny, Emily L. Byrne, Yoan Delavoux, Mantian Li.

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Recently, the use of ionic liquids (ILs) for the preparation of lignocellulose derived cellulosic materials as alternatives to petrochemical feedstocks has been the focus of considerable research interest. While the technical viability of IL-based lignocellulose treatment methodologies has been well established, the high cost of reagents inhibits commercial feasibility. This work aimed to assess the technoeconomic viability of the preparation of cellulose rich materials (CRMs) using protic ionic liquids (PILs) synthesized from low cost alkylamines and sulphuric acid. For this purpose, the tertiary alkylamines, triethylamine, and dimethylbutylamine were selected. Bulk scale production cost of the synthesized PILs, triethylammonium hydrogen sulphate and dimetheylbutylammonium hydrogen sulphate, was reported as $0.78 kg-1 to $1.24 kg-1. CRMs were prepared through the treatment of common wheat (Triticum aestivum) straw with these PILs. By controlling treatment parameters, CRMs with a cellulose content of ≥ 80 wt% were prepared. This was achieved using a T. aestivum straw to PIL loading ratio of 1:15 w/w, a treatment duration of 180 minutes, and ethanol as a cellulose antisolvent. Infrared spectra data and decreased onset degradation temperature of CRMs (ΔTONSET ~ 70 °C) suggested the formation of cellulose sulphate esters during treatment. Chemical derivatisation can aid the dispersion of prepared CRMs in non-polar polymer/ composite matrices, but act as a barrier to thermal processing at temperatures above 150 °C. It was also shown that treatment increased the crystallinity of CRMs (ΔCrI ~ 40 %) without altering the native crystalline structure or crystallite size (~ 2.6 nm) of cellulose; peaks associated with the cellulose I crystalline planes (110), (200), and (004) were observed at Bragg angles 16.0 °, 22.5 ° and 35.0 ° respectively. This highlighted the inability of assessed PILs to dissolve crystalline cellulose and was attributed to the high acidity (pKa ~ - 1.92 to - 6.42) of sulphuric acid derived anions. Electron micrographs revealed that the stratified multilayer tissue structure of untreated T. aestivum straw was significantly modified during treatment. T. aestivum straw particles were disassembled during treatment, with prepared CRMs adopting a golden-brown film-like appearance. This work demonstrated the degradation of non-cellulosic fractions of lignocellulose without dissolution of cellulose. It is the first to report on the derivatisation of cellulose during treatment with protic hydrogen sulphate ionic liquids, and the potential implications of this with reference to biopolymer feedstock preparation.

Keywords: cellulose, extraction, protic ionic liquids, esterification, thermal stability, waste valorisation, biopolymer feedstock

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Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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Authors: Xiao Chen, Xiaoying Kong, Min Xu

Abstract:

This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.

Keywords: vehicle classification, signal processing, road traffic model, magnetic sensing

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Authors: Kilari Nikhil, Ankur Tibrewal, Srinivas Kruthiventi S. S.

Abstract:

Conventional speaker identification systems often fall short of capturing the diverse variations present in speech data due to fixed-scale architectures. In this research, we propose a CNN-based architecture, USENet, designed to overcome these limitations. Leveraging two key techniques, our approach achieves superior performance on the VoxCeleb 1 Dataset without any pre-training. Firstly, we adopt a U-net-inspired design to extract features at multiple scales, empowering our model to capture speech characteristics effectively. Secondly, we introduce the squeeze and excitation block to enhance spatial feature learning. The proposed architecture showcases significant advancements in speaker identification, outperforming existing methods, and holds promise for future research in this domain.

Keywords: multi-scale feature extraction, squeeze and excitation, VoxCeleb1 speaker identification, mel-spectrograms, USENet

Procedia PDF Downloads 72