Search results for: avenue tree species

Authors: Sharmin Ferdewsi Rakhi, AHM Mohsinul Reza, Brynley Davies, Jianzhong Wang, Youhong Tang, Jian Qin

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Mass production of microalgae has become a focus of research owing to their promising aspects for sustainable food, biofunctional compounds, and biofuel feedstock. However, low lipid content with optimum algal biomass is still a challenge that must be resolved for commercial use. This research aims to determine the effects of light spectral shift and reactive oxygen species (ROS) on growth and lipid biosynthesis in a green microalga, Chlamydomonas reinhardtii. Aggregation Induced Emission (AIE)-based photosensitisers, CN-TPAQ-PF6 ([C₃₂H₂₃N₄]+) with high ROS productivity, was introduced into the algal culture media separately for effective conversion of the green-yellow-light to the red spectra. The intense photon energy and high-photon flux density in the photosystems and ROS supplementation induced photosynthesis and lipid biogenesis. In comparison to the control, maximum algal growth (0.15 g/l) was achieved at 2 µM CN-TPAQ-PF6 exposure. A significant increase in total lipid accumulation (146.87 mg/g dry biomass) with high proportion of 10-Heptadecanoic acid (C17:1) linolenic acid (C18:2), α-linolenic acid (C18:3) was observed. The elevated level of cellular NADP/NADPH triggered the Acetyl-Co-A production in lipid biogenesis cascade. Furthermore, MTT analysis suggested that this nanomaterial is highly biocompatible on HaCat cell lines with 100% cell viability. This study reveals that the AIE-based approach can strongly impact algal biofactory development for sustainable food, healthy lipids and eco-friendly biofuel.

Keywords: microalgae, photosensitiser, lipid, biomass, aggregation-induced-emission, reactive oxygen species

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Authors: Ghada Al-Kafaji, Mohamed Sabry

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Mitochondria are the site of cellular respiration and produce energy in the form of adenosine triphosphate (ATP) via oxidative phosphorylation. They are the major source of intracellular reactive oxygen species (ROS) and are also direct target to ROS attack. Oxidative stress and ROS-mediated disruptions of mitochondrial function are major components involved in the pathogenicity of diabetic complications. In this work, the changes in mitochondrial DNA (mtDNA) copy number, biogenesis, gene expression of mtDNA-encoded subunits of electron transport chain (ETC) complexes, and mitochondrial function in response to hyperglycemia-induced ROS and the effect of direct inhibition of ROS on mitochondria were investigated in an in vitro model of diabetic nephropathy using human renal mesangial cells. The cells were exposed to normoglycemic and hyperglycemic conditions in the presence and absence of Mn(III)tetrakis(4-benzoic acid) porphyrin chloride (MnTBAP) or catalase for 1, 4 and 7 days. ROS production was assessed by the confocal microscope and flow cytometry. mtDNA copy number and PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 transcripts, were all analyzed by real-time PCR. PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 proteins, were analyzed by Western blotting. Mitochondrial function was determined by assessing mitochondrial membrane potential and adenosine triphosphate (ATP) levels. Hyperglycemia-induced a significant increase in the production of mitochondrial superoxide and hydrogen peroxide at day 1 (P < 0.05), and this increase remained significantly elevated at days 4 and 7 (P < 0.05). The copy number of mtDNA and expression of PGC-1a, NRF-1, and TFAM as well as ND2, CYTB, CO1 and ATPase 6 increased after one day of hyperglycemia (P < 0.05), with a significant reduction in all those parameters at 4 and 7 days (P < 0.05). The mitochondrial membrane potential decreased progressively at 1 to 7 days of hyperglycemia with the parallel progressive reduction in ATP levels over time (P < 0.05). MnTBAP and catalase treatment of cells cultured under hyperglycemic conditions attenuated ROS production reversed renal mitochondrial oxidative stress and improved mtDNA, mitochondrial biogenesis, and function. These results show that hyperglycemia-induced ROS caused an early increase in mtDNA copy number, mitochondrial biogenesis and mtDNA-encoded gene expression of the ETC subunits in human mesangial cells as a compensatory response to the decline in mitochondrial function, which precede the mtDNA defect and mitochondrial dysfunction with a progressive oxidative response. Protection from ROS-mediated damage to renal mitochondria induced by hyperglycemia may be a novel therapeutic approach for the prevention/treatment of DN.

Keywords: diabetic nephropathy, hyperglycemia, reactive oxygen species, oxidative stress, mtDNA, mitochondrial dysfunction, manganese superoxide dismutase, catalase

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Authors: Waqas Shafqat Chattha, Muhammad Iqbal, Amir Shakeel

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Transcriptional factors are proteins that play a vital role in regulating the transcription of target genes in different biological processes and are being widely studied in different plant species. In the current era of genomics, plant genomes sequencing has directed to the genome-wide identification, analyses and categorization of diverse transcription factor families and hence provide key insights into their structural as well as functional diversity. The DNA-binding with One Finger (DOF) proteins belongs to C2-C2-type zinc finger protein family. DOF proteins are plant-specific transcription factors implicated in diverse functions including seed maturation and germination, phytohormone signalling, light-mediated gene regulation, cotton-fiber elongation and responses of the plant to biotic as well as abiotic stresses. In this context, a genome-wide in-silico analysis of DOF TF family in diploid cotton species i.e. Gossypium raimondii has enabled us to identify 55 non-redundant genes encoding DOF proteins renamed as GrDofs (Gossypium raimondii Dof). Gene distribution studies have shown that all of the GrDof genes are unevenly distributed across 12 out of 13 G. raimondii chromosomes. The gene structure analysis illustrated that 34 out of 55 GrDof genes are intron-less while remaining 21 genes have a single intron. Protein sequence-based phylogenetic analysis of putative 55 GrDOFs has divided these proteins into 5 major groups with various paralogous gene pairs. Molecular evolutionary studies aided with the conserved domain as well as gene structure analysis suggested that segmental duplications were the principal contributors for the expansion of Dof genes in G. raimondii.

Keywords: diploid cotton , G. raimondii, phylogenetic analysis, transcription factor

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Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

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Authors: Ryan Villafuerte Lansangan

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Assessing students’ understanding in the microscopic level of an abstract subject like chemistry poses a challenge to teachers. Literature reveals that the use of representations serves as an essential avenue of measuring the extent of understanding in the discipline as an alternative to traditional assessment methods. This undertaking explored the representational competence profile of high school students from the University of Santo Tomas High School in understanding selected chemical principles and correlate this with their academic profile in chemistry based on their performance in the academic achievement examination in chemistry administered by the Center for Education Measurement (CEM). The common misconceptions of the students on the selected chemistry principles based on their representations were taken into consideration as well as the students’ views regarding their understanding of the role of chemical representations in their learning. The students’ level of representation task instrument consisting of the main lessons in chemistry with a corresponding scoring guide was prepared and utilized in the study. The study revealed that most of the students under study are unanimously rated as Level 2 (symbolic level) in terms of their representational competence in understanding the selected chemical principles through the use of chemical representations. Alternative misrepresentations were most observed on the students’ representations on chemical bonding concepts while the concept of chemical equation appeared to be the most comprehensible topic in chemistry for the students. Data implies that teachers’ representations play an important role in helping the student understand the concept in a microscopic level. Results also showed that the academic achievement in the chemistry of the students based on the standardized CEM examination has a significant association with the students’ representational competence. In addition, the students’ responses on the students’ views in chemical representations questionnaire evidently showed a good understanding of what a chemical representation or a mental model is by drawing a negative response that these tools should be an exact replica. Moreover, the students confirmed a greater appreciation that chemical representations are explanatory tools.

Keywords: chemical representations, representational competence, academic profile in chemistry, secondary students

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Authors: Tekle Olbamo, Tegegn Tesfaye, Dikaso Unbushe, Belete Jorga

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Bovine trypanosomosis is a haemoprotozoan parasitic disease, mostly transmitted by the tsetse fly (Glossina species) and poses significant losses to the livestock industry in pastoral and agro-pastoral areas. Therefore, the current study was aimed to determine the prevalence of bovine trypanosomosis and its vectorial density in some selected tsetse suppression and non-tsetse suppression areas of South Omo Zonefrom December 2018- November 2019. Dark phase contrast buffy coat, hematocrit techniques, and thin blood smear method were used for determination of prevalence and packed cell volume of trypanosomosis infection, respectively. For entomological investigation, 96 NGU traps were deployed (64 traps in tsetse suppression areas, 32 traps in tsetse non-suppression areas) in vector breeding areas. The overall prevalence of bovine trypanosomosis was 11.05% (142/1284), and overall seasonal prevalence of disease was 14.33% (92/642) and 7.78% (50/642) for dry and wet seasons, respectively. There was a statistically significant difference (P <0.05) in disease prevalence between the two seasons. Trypanosomacongolensewas the dominant parasite species; 80% and 71.64%, followed by Trypanosomavivax. Overall mean packed cell volume indicated parasitaemic animals (23.57±3.13) had significantly lower PCV than aparasitaemic animals (27.80±4.95), and animals examined during dry season (26.22±4.37) had lower mean PCV than animals examined during wet season with the significant association. Entomological study result revealed a total of 2.64 F/T/D and 2.03 F/T/D respectively from tsetse suppression areas and tsetse non-suppression areas during dry season and 0.42 F/T/D and 0.56 F/T/D during the wet season. Glossinapallidipes was the only cyclical vectors collected and identified from current study areas along with numerous mechanical vectors of genus Tabanus, Stomoxys, and Haematopota. Therefore integrated and safe control and prevention effort should be engaged to uphold cattle production and productivity in the area.

Keywords: bovine trypanosomiasis, South Omo, tsetse fly density, epidemiological study

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Authors: Ivan A. Sandoval Salazar, Silvia F. Valderrama

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The microalgae oil emerges as a promising source of raw material for many industrial applications. Thus, this study had as a main focus on the cultivation of the microalgae species Desmodesmus sp. in laboratory scale with a view to maximizing biomass production and triglyceride content in the lipid fraction. Initially, culture conditions were selected to optimize biomass production, which was subsequently subjected to nutritional stress by varying nitrate and phosphate concentrations in order to increase the content and productivity of fatty acids. The culture medium BOLD 3N, nitrate and phosphate, light intensity 250,500 and 1000 μmol photons.m².s⁻¹, photoperiod of 12:12 were evaluated. Under the best conditions of the tests, a maximum cell division of 1.13 div.dia⁻¹ was obtained on the sixth day of culture, beginning of the exponential phase, and a maximum concentration of 8.42x107 cell.mL⁻¹ and dry biomass of 3.49 gL⁻¹ on the 20th day, in the stationary phase. The lipid content in the first stage of culture was approximately 8% after 12 days and at the end of the culture in the stationary phase ranged from 12% to 16% (20 days). In the microalgae grown at 250 μmol fotons.m2.s-1 the fatty acid profile was mostly polyunsaturated (52%). The total of unsaturated fatty acids, identified in this species of microalga, reached values between 70 and 75%, being qualified for use in the food and pharmaceutical industry. In addition, this study showed that the cultivation conditions influenced mainly the production of polyunsaturated fatty acids, with the predominance of γ-linolenic acid. However, in the cultures submitted to the highest the intensity of light (1000 μmol photons.m².s⁻¹) and low concentrations of nitrate and phosphate, saturated and monounsaturated fatty acids, which present greater oxidative stability, were identified mainly (60 to 70 %) being qualified for the production of biodiesel and for oleochemistry.

Keywords: microalgae, Desmodesmus sp, fatty acids, biodiesel

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Authors: Shweta Dhindhwal

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Dopamine is an essential neurotransmitter in the central nervous system of all vertebrates and plays an important role in many processes such as motor function, learning and behavior, and sensory activity. One of the important functions of dopamine is release of pituitary hormones. It is synthesized from the amino acid tyrosine. Two types of dopamine receptors, D1-like and D2-like, have been reported in fish. The dopamine containing neurons are located in the olfactory bulbs, the ventral regions of the pre-optic area and tuberal hypothalamus. Distribution of the dopaminergic system has not been studied in the murrel, Channa punctatus. The present study deals with identification of D2 receptors in the brain of murrel. A phylogenetic tree has been constructed using partial sequence of D2 receptor. Distribution of putative dopaminergic neurons in the brain has been investigated. Also, formalin induced hypertrophy of neurosecretory cells in murrel has been studied.

Keywords: dopamine, fish, pre-optic area, murrel

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Authors: Azza EL-Medany, Jamila EL-Medany

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Lung fibrosis is a common side effect of the chemotherapeutic agent, bleomycin. Current evidence suggests that reactive oxygen species may play a key role in the development of lung fibrosis. The present work studied the effect of green tea extract on bleomycin–induced lung fibrosis in rats. Animals were divided into three groups: (1) Saline control group; (2) bleomycin group in which rats were injected with bleomycin (15mg/kg,i.p.) three times a week for four weeks; (3) bleomycin and green tea group in which green tea extract was given to rats (100mg/kg/day, p.o) a week prior to bleomycin and daily during bleomycin injections for 4 weeks until the end of the experiment. Bleomycin–induced pulmonary injury and lung fibrosis that was indicated by increased lung hydroxyproline content, elevated nitric oxide synthase, myeoloperoxidase (MPO), platelet activating factor (PAF), tumor necrosis factor α (TNF_α), transforming growth factor 1β (TGF1β) and angiotensin converting enzyme (ACE) activity in lung tissues. On the other hand, bleomycin induced a reduction in reduced glutathione concentration (GSH). Moreover, bleomycin resulted in a severe histological changes in lung tissues revealed as lymphocytes and neutrophils infiltration, increased collagen deposition and fibrosis. Co-administration of bleomycin and green tea extract reduced bleomycin–induced lung injury as evaluated by the significant reduction in hydroxyproline content, nitric oxide synthase activity, levels of MPO, PAF, TNF-α, and ACE in lung tissues. Furthermore, green tea extract ameliorated bleomycin– induced reduction in GSH concentration. Finally, histological evidence supported the ability of green tea extract to attenuate bleomycin–induced lung fibrosis and consolidation. Thus, the finding of the present study provides that green tea may serve as a novel target for potential therapeutic treatment of lung fibrosis.

Keywords: bleomycin, lung fibrosis, green tea, oxygen species

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Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: Ajay Kumar, Satwinderjeet Kaur

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Onosma bracteata Wall. (Boraginaceae), is known to be a medicinal plant, useful in the treatment of body swellings, abdominal pain and urinary calculi, etc. The present study focused on the radical scavenging and cancer growth inhibitory properties of isolates from O. bracteata. Obea fraction demonstrated noticeable free radical scavenging ability along with antiproliferative activity in human osteosarcoma MG-63, human neuroblastoma IMR-32, and human lung cancer A549 cell lines using MTT assay with GI50 values of 88.56, 101.61 and 112.7 μg/ml, respectively. The scanning electron and confocal microscopy studies showed morphological alterations including nuclear condensation and formation of apoptotic bodies in osteosarcoma MG-63 cells. Obea fraction in osteosarcoma MG-63 cells augmented the reactive oxygen species (ROS) level and decreased the mitochondrial membrane potential. Flow cytometry analysis revealed the Obea treated cells to be arrested in the G0/G1 phase in a dose dependent manner supported by the observed increase in the early apoptotic cell population. Western blotting analysis showed that the expression of p-NF-kB, COX-2, p-Akt, and Bcl-xL decreased whereas, the expression of GSK-3β, p53, caspase-3 and caspase-9 proteins increased. The downregulation of Bcl-2, Cyclin E, CDK2 and mortalin gene expression and upregulation of p53 genes was unfolded in RT-qPCR studies. The presence of catechin, kaempferol, Onosmin A and epicatechin, as revealed in high-performance liquid chromatography (HPLC) studies, contributes towards the chemopreventive potential of O. bracteata which can be tapped for chemotherapeutic use.

Keywords: apoptosis, confocal microscopy, HPLC, mitochondria membrane potential, reactive oxygen species

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Authors: Zaide Montes Ortiz, Jorge Alberto Molina, Alejandro Reyes

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Insects are extremely successful organisms. A sophisticated olfactory system is in part responsible for their survival and reproduction. The detection of volatile organic compounds can positively or negatively affect many behaviors in insects. Compounds such as carbon dioxide (CO2), ammonium, indol, and lactic acid are essential for many species of mosquitoes like Anopheles gambiae in order to locate vertebrate hosts. For instance, in A. gambiae, the olfactory receptor AgOR2 is strongly activated by indol, which accounts for almost 30% of human sweat. On the other hand, in some insects of agricultural importance, the detection and identification of pheromone receptors (PRs) in lepidopteran species has become a promising field for integrated pest management. For example, with the disruption of the pheromone receptor, BmOR1, mediated by transcription activator-like effector nucleases (TALENs), the sensitivity to bombykol was completely removed affecting the pheromone-source searching behavior in male moths. Then, the detection and identification of olfactory receptors in the genomes of insects is fundamental to improve our understanding of the ecological interactions, and to provide alternatives in the integrated pests and vectors management. Hence, the objective of this study is to propose a bioinformatic workflow to enhance the detection and identification of potential olfactory receptors in genomes of relevant insects. Applying Hidden Markov models (Hmms) and different computational tools, potential candidates for pheromone receptors in Tuta absoluta were obtained, as well as potential carbon dioxide receptors in Rhodnius prolixus, the main vector of Chagas disease. This study showed the validity of a bioinformatic workflow with a potential to improve the identification of certain olfactory receptors in different orders of insects.

Keywords: bioinformatic workflow, insects, olfactory receptors, protein prediction

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Authors: Xiaofei Li, Zhiwei Zhong, Deli Wang

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Large herbivores affect plant growth not only through their direct, consumptive effects, but also through indirect effects that alter species interactions. Indirect effects can be either positive or negative, therefore having the potential to mitigate or enhance the direct impacts of herbivores. However, until recently, we know considerably less about the indirect effects than the direct effects of large herbivores on plants, and few studies have explored multiple indirect pathways simultaneously. Here, we investigated how large domestic herbivores, cattle (Bos taurus), can shape population growth of an intermediately preferred forb species, Artemsisa scoparia, through diverse pathways in a temperate grassland of northeast China. We found that, although exposure to direct consumption of cattle, A. scoparia growth was not inhibited, but rather showed a significant increase in the grazed than ungrazed areas. This unexpected result was due to grazing-induced multiple indirect, positive effects overwhelmed the direct, negative consumption effects of cattle on plant growth. The much more intensive consumption on the dominant Leymus chinensis grass, ground litter removal, and increases in ant nest abundance induced by cattle, exerted significant indirect, positive effects on A. scoparia growth. These pathways benefited A.scoparia growth by lessening interspecific competition, mitigating negative effects of litter accumulation, and increasing soil nutrient availability, respectively. Our results highlight the need to integrate indirect effects into the traditional food web theory, which is based primary on direct, trophic linkages, to fully understand community organization and dynamics. Large herbivores are important conservation and management targets, our results suggest that these mammals should be managed with the understanding that they can affect primary producers through diverse paths.

Keywords: grasslands, large herbivores, plant growth, indirect effects

Procedia PDF Downloads 249

Authors: Shi-Bo Feng, Sheng-Jie Zhang, Jin Zhou

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The relationship between microbial diversity and algal bloom has received considerable attention for decades. Microbes undoubtedly affect annual bloom events and impact the physiology of both partners, as well as shape ecosystem diversity. However, knowledge about interactions and network correlations among broader-spectrum microbes that lead to the dynamics in a complete bloom cycle are limited. In this study, pyrosequencing and network approaches simultaneously assessed the associate patterns among bacteria, archaea, and microeukaryotes in surface water and sediments in response to a natural dinoflagellate (Alexandrium sp.) bloom. In surface water, among the bacterial community, Gamma-Proteobacteria and Bacteroidetes dominated in the initial bloom stage, while Alpha-Proteobacteria, Cyanobacteria, and Actinobacteria become the most abundant taxa during the post-stage. In the archaea biosphere, it clustered predominantly with Methanogenic members in the early pre-bloom period while the majority of species identified in the later-bloom stage were ammonia-oxidizing archaea and Halobacteriales. In eukaryotes, dinoflagellate (Alexandrium sp.) was dominated in the onset stage, whereas multiply species (such as microzooplankton, diatom, green algae, and rotifera) coexistence in bloom collapse stag. In sediments, the microbial species biomass and richness are much higher than the water body. Only Flavobacteriales and Rhodobacterales showed a slight response to bloom stages. Unlike the bacteria, there are small fluctuations of archaeal and eukaryotic structure in the sediment. The network analyses among the inter-specific associations show that bacteria (Alteromonadaceae, Oceanospirillaceae, Cryomorphaceae, and Piscirickettsiaceae) and some zooplankton (Mediophyceae, Mamiellophyceae, Dictyochophyceae and Trebouxiophyceae) have a stronger impact on the structuring of phytoplankton communities than archaeal effects. The changes in population were also significantly shaped by water temperature and substrate availability (N & P resources). The results suggest that clades are specialized at different time-periods and that the pre-bloom succession was mainly a bottom-up controlled, and late-bloom period was controlled by top-down patterns. Additionally, phytoplankton and prokaryotic communities correlated better with each other, which indicate interactions among microorganisms are critical in controlling plankton dynamics and fates. Our results supplied a wider view (temporal and spatial scales) to understand the microbial ecological responses and their network association during algal blooming. It gives us a potential multidisciplinary explanation for algal-microbe interaction and helps us beyond the traditional view linked to patterns of algal bloom initiation, development, decline, and biogeochemistry.

Keywords: microbial community, harmful algal bloom, ecological process, network

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Authors: Anza-Vhudziki Mboyi, Ilunga Kamika, Maggy Momba

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The aim of this study was to ascertain the survival limit and capability of commonly found wastewater protozoan (Aspidisca sp, Trachelophyllum sp, and Peranema sp) and bacterial (Bacillus licheniformis, Brevibacillus laterosporus, and Pseudomonas putida) species to remove COD while exposed to commercial nanomaterials under varying pH conditions. The experimental study was carried out in modified mixed liquor media adjusted to various pH levels (pH 2, 7 and 10), and a comparative study was performed to determine the difference between the cytotoxicity effects of commercial zinc oxide (nZnO) and silver (nAg) nanomaterials (NMs) on the target wastewater microbial communities using standard methods. The selected microbial communities were exposed to lethal concentrations ranging from 0.015 g/L to 40 g/L for nZnO and from 0.015 g/L to 2 g/L for nAg for a period of 5 days of incubation at 30°C (100 r/min). Compared with the absence of NMs in wastewater mixed liquor, the relevant environmental concentration ranging between 10 µg/L and 100 µg/L, for both nZnO and nAg caused no adverse effects, but the presence of 20 g of nZnO/L and 0.65 g of nAg/L significantly inhibited microbial growth. Statistical evidence showed that nAg was significantly more toxic compared to nZnO, but there was an insignificant difference in toxicity between microbial communities and pH variations. A significant decrease in the removal of COD by microbial populations was observed in the presence of NMs with a moderate correlation of r = 0.3 to r = 0.7 at all pH levels. It was evident that there was a physical interaction between commercial NMs and target wastewater microbial communities; although not quantitatively assessed, cell morphology and cell death were observed. Such phenomena suggest the high resilience of the microbial community, but it is the accumulation of NMs that will have adverse effects on the performance in terms of COD removal.

Keywords: bacteria, biological treatment, chemical oxygen demand (COD) and nanomaterials, consortium, pH, protozoan

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Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM

Procedia PDF Downloads 174

Authors: Pureun-Haneul Lee, Byeong-Gon Kim, Sun-Hye Lee, An-Soo Jang

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Background: Nanoparticles may pose adverse health effects due to particulate matter inhalation. Nanoparticle exposure induces cell and tissue damage, causing local and systemic inflammatory responses. The inflammasome is a major regulator of inflammation through its activation of pro-caspase-1, which cleaves pro-interleukin-1β (IL-1β) into its mature form and may signal acute and chronic immune responses to nanoparticles. Objective: The aim of the study was to identify whether nanoparticles exaggerates inflammasome pathway leading to airway inflammation and hyperresponsiveness in an allergic mice model of asthma. Methods: Mice were treated with saline (sham), OVA-sensitized and challenged (OVA), or titanium dioxide nanoparticles. Lung interleukin 1 beta (IL-1β), interleukin 18 (IL-18), NACHT, LRR and PYD domains-containing protein 3 (NLRP3) and caspase-1 levels were assessed with Western Blot. Caspase-1 was checked by immunohistochemical staining. Reactive oxygen species were measured for the marker 8-isoprostane and carbonyl by ELISA. Results: Airway inflammation and hyperresponsiveness increased in OVA-sensitized/challenged mice and these responses were exaggerated by TiO2 nanoparticles exposure. TiO2 nanoparticles treatment increased IL-1β and IL-18 protein expression in OVA-sensitized/challenged mice. TiO2 nanoparticles augmented the expression of NLRP3 and caspase-1 leading to the formation of an active caspase-1 in the lung. Lung caspase-1 expression was increased in OVA-sensitized/challenged mice and these responses were exaggerated by TiO2 nanoparticles exposure. Reactive oxygen species was increased in OVA-sensitized/challenged mice and in OVA-sensitized/challenged plus TiO2 exposed mice. Conclusion: Our data demonstrate that inflammasome pathway activates in asthmatic lungs following nanoparticles exposure, suggesting that targeting the inflammasome may help control nanoparticles-induced airway inflammation and responsiveness.

Keywords: bronchial asthma, inflammation, inflammasome, nanoparticles

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Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

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Authors: Narges Razmjoo, Hamid Sefidari, Michael Strand

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Biomass combustion is a growing technique for heat and power production due to the increasing stringent regulations with CO2 emissions. Grate-fired systems have been regarded as a common and popular combustion technology for burning woody biomass. However, some grate furnaces are not well optimized and may emit significant amount of unwanted compounds such as dust, NOx, CO, and unburned gaseous components. The combustion characteristics inside the fuel bed are of practical interest, as they are directly related to the release of volatiles and affect the stability and the efficiency of the fuel bed combustion. Although numerous studies have been presented on the grate firing of biomass, to the author’s knowledge, none of them have conducted a detailed experimental study within the fuel bed. It is difficult to conduct measurements of temperature and gas species inside the burning bed of the fuel in full-scale boilers. Results from such inside bed measurements can also be applied by the numerical experts for modeling the fuel bed combustion. The current work presents an experimental investigation into the combustion behavior of wet woody biomass (53 %) in a 4 MW reciprocating grate boiler, by focusing on the gas species distribution along the height of the fuel bed. The local concentrations of gases (CO, CO2, CH4, NO, and O2) inside the fuel bed were measured through a glass port situated on the side wall of the furnace. The measurements were carried out at five different heights of the fuel bed, by means of a bent stainless steel probe containing a type-k thermocouple. The sample gas extracted from the fuel bed, through the probe, was filtered and dried and then was analyzed using two infrared spectrometers. Temperatures of about 200-1100 °C were measured close to the grate, indicating that char combustion is occurring at the bottom of the fuel bed and propagates upward. The CO and CO2 concentration varied in the range of 15-35 vol % and 3-16 vol %, respectively, and NO concentration varied between 10-140 ppm. The profile of the gas concentrations distribution along the bed height provided a good overview of the combustion sub-processes in the fuel bed.

Keywords: experimental, fuel bed, grate firing, wood combustion

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Authors: Bhupendra Kumar Poudel, Sadhana Amatya, Tirtha Maiya Shrestha, Bharatmani Pokhrel, Mohan Prasad Amatya

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Background: H. salicifolia is a dense, branched, multipurpose, deciduous, nitrogen fixing, thorny willow-like small to moderate tree, restricted to the Himalaya. Among the two species of Nepal (Hippophae salicifolia and H. tibetana), it has been traditionally used as food additive, anticancer (bark), and treating toothache, tooth inflammation (anti-inflammatory) and radiation injury; while people of Western Nepal have largely undermined its veiled treasure by using it for fuel, wood and soil stabilization only. Therefore, the main objective of this study was to explore biological properties (analgesic, antidiabetic, cytotoxic and anti-inflammatory properties of this plant. Methodology: The transverse section of leaves and stems were viewed under microscope. Extracts obtained from soxhlation subjected to tests for phytochemical and biological studies. Rats (used to study antidiabetic and anti-inflammatory properties) and mice (used to study analgesic, CNS depressant, muscle relaxant and locomotor properties) were assumed to be normally distributed; then ANOVA and post hoc tukey test was used to find significance. The data obtained were analyzed by SPSS 17 and Excel 2007. Results and Conclusion: Pharmacognostical analysis revealed the presence of long stellate trichomes, double layered vascular bundle 5-6 in number and double layered compact sclerenchyma. The preliminary phytochemical screening of the extracts was found to exhibit the positive reaction tests for glycoside, steroid, tannin, flavonoid, saponin, coumarin and reducing sugar. The brine shrimp lethality bioassay tested in 1000, 100 and 10 ppm revealed cytotoxic activity inherent in methanol, water, chloroform and ethyl acetate extracts with LC50 (μg/ml) values of 61.42, 99.77, 292.72 and 277.84 respectively. The cytotoxic activity may be due to presence of tannins in the constituents. Antimicrobial screening of the extracts by cup diffusion method using Staphylococcus aereus, Escherichia coli and Pseudomonas aeruginosa against standard antibiotics (oxacillin, gentamycin and amikacin respectively) portrayed no activity against the microorganisms tested. The methanol extract of the stems and leaves showed various pharmacological properties: and antidiabetic, anti-inflammatory, analgesic [chemical writhing method], CNS depressant, muscle relaxant and locomotor activities in a dose-dependent fashion, indicating the possibility of the presence of different constituents in the stems and leaves responsible for these biological activities. All the effects when analyzed by post hoc tukey test were found to be significant at 95% confidence level. The antidiabetic activity was presumed to be due to flavonoids present in extract. Therefore, it can be concluded that this plant’s secondary metabolites possessed strong antidiabetic, anti-inflammatory and cytotoxic activity which could be isolated for further investigation.

Keywords: Hippophae salicifolia, constituents, antidiabetic, inflammatory, brine shrimp

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Authors: Guilherme Ribeiro, Alexandre Oliveira, Antonio Ferreira, Shyam Visweswaran, Gregory Cooper

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Patient-specific models are instance-based learning algorithms that take advantage of the particular features of the patient case at hand to predict an outcome. We introduce two patient-specific algorithms based on decision tree paradigm that use AUC as a metric to select an attribute. We apply the patient specific algorithms to predict outcomes in several datasets, including medical datasets. Compared to the patient-specific decision path (PSDP) entropy-based and CART methods, the AUC-based patient-specific decision path models performed equivalently on area under the ROC curve (AUC). Our results provide support for patient-specific methods being a promising approach for making clinical predictions.

Keywords: approach instance-based, area under the ROC curve, patient-specific decision path, clinical predictions

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Authors: Fitri Rahmi Fadhilah, Edhyana Sahiratmadja, Ani Melani Maskoen, Ratu Safitri, Supartini Syarif, Herman Susanto

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Cervical cancer is the second most common cancer in women after breast cancer. In Indonesia, the incidence of cervical cancer cases is estimated at 25-40 per 100,000 women per year. Human papillomavirus (HPV) infection is a major cause of cervical cancer, and HPV-16 is the most common genotype that infects the cervical tissue. The major late protein L1 may be associated with infectivity and pathogenicity and its variation can be used to classify HPV isolates. The aim of this study was to determine the phylogenetic tree of HPV 16 L1 gene from cervical cancer patient isolates in Bandung. After confirming HPV-16 by Linear Array Genotyping Test, L1 gene was amplified using specific primers and subject for sequencing. Phylogenetic analysis revealed that HPV 16 from Bandung was in the subgroup of Asia and East Asia, showing the close host-agent relationship among the Asian type.

Keywords: L1 HPV 16, cervical cancer, bandung, phylogenetic

Procedia PDF Downloads 487

Authors: Serkan Yesil

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Cucurbits (the Cucurbitaceae family) include 119 genera and 825 species distributed primarily in tropical and subtropical regions of the world. The major cultivated cucurbit species such as melon (Cucumis melo L.), cucumber (Cucumis sativus L.), squash (Cucurbita pepo L.), and watermelon (Citrullus lanatus (Thunb) Matsum.&Nakai) are important vegetable crops worldwide. Squash is grown for fresh consuming, as well as its seeds are used as a snack in Turkey like some Mediterranean countries and Germany, Hungary, Austria and China. Virus diseases are one of the most destructive diseases on squash which is grown for seeds in Aksaray province. In this study, it was aimed to determine the virus infections in major squash growing areas in Aksaray province. Totally 153 plant samples with common virus symptoms like mosaic, curling, blistering, mottling, distortion, shoestring, stunting and vine decline were collected from squash plants during 2014. In this study, DAS-ELISA method is used for identifying the virus infections on the plant samples. According to the results of the DAS-ELISA 84.96 % of plant samples were infected with Zucchini yellow mosaic Potyvirus (ZYMV), Watermelon mosaic Potyvirus-2 (WMV-2), Cucumber mosaic Cucumovirus (CMV), Papaya ringspot Potyvirus-watermelon strain (PRSV-W) and Squash mosaic Comovirus (SqMV). ZYMV was predominant in the research area with the ratio of 66.01 %. WMV-2 was the second important virus disease in the survey area, it was detected on the samples at the ratio of 57.51 %. Also, mixed infections of those virus infections were detected commonly in squash. Especially, ZYMV+WMV-2 mixed infections were common. Cucumber green mottle mosaic Tobamovirus (CGMMV) was not present in the research area.

Keywords: Aksaray, DAS-ELISA, edible seed squash, WMV-2, ZYMV

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Authors: Hai Zhou, Wenzhi Zhao

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Water is one of the most important factors limiting plant growth and development in desert ecosystems. In order to understand how desert shrubs cope with variation in water sources over time, it is important to understand plant–water relations in desert-oasis ecotone. We selected the typical desert shrubs: Nitraria sibirica, Calligonum mongolicum and Haloxylon ammodendron of 5-, 10-, 20- and 40-year old as the research species, to study the seasonal variation of plant water sources and response to precipitation in the desert-oasis ecotone of Linze, Northwestern China. We examined stable isotopic ratios of oxygen (δ18O) in stem water of desert shrubs as well as in precipitation, groundwater, and soil water in different soil layers and seasons to determine water sources for the shrubs. We found that the N. sibirica and H. ammodendron of 5-, 10-year old showed significant seasonal variation characteristics of δ18O value of stem water and water sources. However, the C. mongolicum and 20- and 40-year H. ammodendron main water sources were from deep soil water and groundwater, and less response to precipitation pulse. After 22.4 mm precipitation, the contribution of shallow soil water (0-50cm) to the use of N. sibirica increased from 6.7% to 36.5%; the C. mongolicum rarely use precipitation that were about 58.29% and 23.51%, absorbed from the deep soil water and groundwater; the contribution of precipitation to use of H. ammodendron had significantly differences among the four ages. The H. ammodendron of 5- and 10-year old about 86.3% and 42.5% water sources absorbed from the shallow soil water after precipitation. However, the contribution to 20- and 40-year old plant was less than 15%. So, the precipitation was one of the main water sources for desert shrubs, but the species showed different water utilization. We conclude that the main water source of the N. sibirica and H. ammodendron of 5-, 10-year was soil water recharged by precipitation, but the deeply rooted H. ammodendron of 20‐ and 40‐year‐old and the C. mongolicum have the ability to exploit a deep and reliable water source.

Keywords: water use pattern, water resource, stable isotope, seasonal change, precipitation pulse

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Authors: Mariam Bibi, Rubab Mehboob, Mehreen Sirshar

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Satisfying the customer requirements is the ultimate goal of producing or developing any product. The quality of the product is decided on the bases of the level of customer satisfaction. There are different techniques which have been reported during the survey which enhance the quality of the product through software defect prediction and by locating the missing software requirements. Some mining techniques were proposed to assess the individual performance indicators in collaborative environment to reduce errors at individual level. The basic intention is to produce a product with zero or few defects thereby producing a best product quality wise. In the analysis of survey the techniques like Genetic algorithm, artificial neural network, classification and clustering techniques and decision tree are studied. After analysis it has been discovered that these techniques contributed much to the improvement and enhancement of the quality of the product.

Keywords: data mining, defect prediction, missing requirements, software quality

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Authors: Sibongiseni Thabethe, Ian Korir

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The effective management of spent fuel pool (SFP) safety has been raised as one of the emerging issues to further enhance nuclear installation safety after the Fukushima accident on March 11, 2011. Before then, SFP safety-related issues have been mainly focused on (a) controlling the configuration of the fuel assemblies in the pool with no loss of pool coolants and (b) ensuring adequate pool storage space to prevent fuel criticality owing to chain reactions of the fission products and the ability for neutron absorption to keep the fuel cool. A probabilistic safety (PSA) assessment was performed using the systems analysis program for hands-on integrated reliability evaluations (SAPHIRE) computer code. Event and fault tree analysis was done to develop a PSA model for the Koeberg SFP. We present preliminary PSA results of events that lead to boiling and cause fuel uncovering, resulting in possible fuel damage in the Koeberg SFP.

Keywords: computer code, fuel assemblies, probabilistic risk assessment, spent fuel pool

Procedia PDF Downloads 152

Authors: Ahmed Abdrabou, Medhat Abdalla

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The studied stele dates back to Third Intermediate Period (1075-664) B.C in an ancient Egypt. It is made of wood and covered with painted gesso layers. This study aims to use a combination of multi spectral imaging {visible, infrared (IR), Visible-induced infrared luminescence (VIL), Visible-induced ultraviolet luminescence (UVL) and ultraviolet reflected (UVR)}, along with portable x-ray fluorescence in order to map and identify the pigments as well as to provide a deeper understanding of the painting techniques. Moreover; the authors were significantly interested in the identification of wood species. Multispectral imaging acquired in 3 spectral bands, ultraviolet (360-400 nm), visible (400-780 nm) and infrared (780-1100 nm) using (UV Ultraviolet-induced luminescence (UVL), UV Reflected (UVR), Visible (VIS), Visible-induced infrared luminescence (VIL) and Infrared photography. False color images are made by digitally editing the VIS with IR or UV images using Adobe Photoshop. Optical Microscopy (OM), potable X-ray fluorescence spectroscopy (p-XRF) and Fourier Transform Infrared Spectroscopy (FTIR) were used in this study. Mapping and imaging techniques provided useful information about the spatial distribution of pigments, in particular visible-induced luminescence (VIL) which allowed the spatial distribution of Egyptian blue pigment to be mapped and every region containing Egyptian blue, even down to single crystals in some instances, is clearly visible as a bright white area; however complete characterization of the pigments requires the use of p. XRF spectroscopy. Based on the elemental analysis found by P.XRF, we conclude that the artists used mixtures of the basic mineral pigments to achieve a wider palette of hues. Identification of wood species Microscopic identification indicated that the wood used was Sycamore Fig (Ficus sycomorus L.) which is recorded as being native to Egypt and was used to make wooden artifacts since at least the Fifth Dynasty.

Keywords: polychrome wooden stele, multispectral imaging, IR luminescence, Wood identification, Sycamore Fig, p-XRF

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Authors: Lucy W. Mburu, Richard Karanja, Simon N. Mwendia

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Over recent years, learners have experienced a constant need to access on demand knowledge that is fully aligned with the paradigm of cloud computing. As motivated by the global sustainable development goal to ensure inclusive and equitable learning opportunities, this research has developed a framework hinged on the knowledge-as-a-service architecture that utilizes knowledge from ambient learning systems. Through statistical analysis and decision tree modeling, the study discovers influential variables for ambient learning among university students. The main aim is to generate a platform for disseminating and exploiting the available knowledge to aid the learning process and, thus, to improve educational support on the ambient learning system. The research further explores how collaborative effort can be used to form a knowledge network that allows access to heterogeneous sources of knowledge, which benefits knowledge consumers, such as the developers of ambient learning systems.

Keywords: actionable knowledge, ambient learning, cloud computing, decision trees, knowledge as a service

Procedia PDF Downloads 143

Authors: Nour S. Abdelrahman, Seunghyun Hong, Hassan A. Arafat, Daniel Choi, Faisal Al Marzooqi

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Abstract—The advancement of lithium extraction methods from water sources, particularly saltwater brine, is gaining prominence in the lithium recovery industry due to its cost-effectiveness. Traditional techniques like recrystallization, chemical precipitation, and solvent extraction for metal recovery from seawater or brine are energy-intensive and exhibit low efficiency. Moreover, the extensive use of organic solvents poses environmental concerns. As a result, there's a growing demand for environmentally friendly lithium recovery methods. Membrane-based separation technology has emerged as a promising alternative, offering high energy efficiency and ease of continuous operation. In our study, we explored the potential of lithium-selective sieve channels constructed from layers of 2D graphene oxide and MXene (transition metal carbides and nitrides), integrated with surface – SO₃₋ groups. The arrangement of these 2D sheets creates interplanar spacing ranging from 0.3 to 0.8 nm, which forms a barrier against multivalent ions while facilitating lithium-ion movement through nano capillaries. The introduction of the sulfonate group provides an effective pathway for Li⁺ ions, with a calculated binding energy of Li⁺ – SO³⁻ at – 0.77 eV, the lowest among monovalent species. These modified membranes demonstrated remarkably rapid transport of Li⁺ ions, efficiently distinguishing them from other monovalent and divalent species. This selectivity is achieved through a combination of size exclusion and varying binding affinities. The graphene oxide channels in these membranes showed exceptional inter-cation selectivity, with a Li⁺/Mg²⁺ selectivity ratio exceeding 104, surpassing commercial membranes. Additionally, these membranes achieved over 94% rejection of MgCl₂.

Keywords: ion permeation, lithium extraction, membrane-based separation, nanotechnology

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Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 138