Search results for: reduced order macro models

Authors: Ahmed A. Abdel-Khalek, Reham A. Mohamed

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The kinetics of oxidation of binary complex [CrIII(DMG)2(H2O)4 ]+ to Cr(VI) by periodate has been investigated spectrophotometrically where, [DMG= Dimethylglyoxime] at 370nm under pseudo first order reaction conditions in aqueous medium over 20- 40ºC range, PH 2-3, and I=0.07 mol dm-3. The reaction is first order with respect to both [IO4-] and Cr(III), and the reaction increased with PH increased. Thermodymanic activation parameters have been calculated. It is suggested that electron transfer proceeds through an inner sphere mechanism via coordination of IO4- to Cr (III). The reaction obeys the following rate law Rate= {k1 K5+ k2 K6 K2 } [Cr III (DMG)2(H2O)4 ]+ [H5IO6].

Keywords: chromium, dimethylglyoxime, kinetics, oxidation, periodate

Procedia PDF Downloads 425

Authors: Beyene Daniel, Herbert Ntuli

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Agritourism in Eritrea is increasingly threatened by climate change, manifesting through rising temperatures, shifting rainfall patterns, and resource scarcity. This study employs quantitative methods to assess the economic and environmental impacts of climate change on agritourism, utilizing metrics such as annual income fluctuations, changes in visitor numbers, and energy consumption patterns. The methodology relies on secondary data sourced from the World Bank, government reports, and academic publications to analyze the economic viability of integrating solar energy into agritourism operations. Key variables include the Benefits from Renewable Energy (BRE), encompassing cost savings from reduced energy expenses and the monetized value of avoided greenhouse gas emissions. Using a net present value (NPV) framework, the research compares the impact of solar energy against traditional fossil fuel sources by evaluating the Value of Reduced Greenhouse Gas Emissions (CO2) and the Value of Health-Related Costs (VHRC) due to air pollution. The preliminary findings of this research are of utmost importance. They indicate that the adoption of solar energy can enhance energy independence by up to 40%, reduce operational costs by 25%, and stabilize agritourism activities in climate-sensitive regions. This research aims to provide actionable insights for policymakers and stakeholders, supporting the sustainable development of agritourism in Eritrea and contributing to broader climate adaptation strategies. By employing a comprehensive cost-benefit analysis, the study highlights the economic advantages and environmental benefits of transitioning to renewable energy in the face of climate change.

Keywords: climate change, renewable energy, resilience, cost-benefit analysis

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Authors: Milda A. Cruz-Huaranga, Natalí Carbo-Bustinza, Javier Linkolk López-Gonzales, K. Depaz, Gina M. Tito T., Soledad Torres-Calderón

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The objective of this study was to improve water quality in the “La Mansión” pond in order to irrigate green spaces on the Peruvian Union University campus (Lima, Peru) using the aquatic species Eichhornia Crassipes. Furthermore, tree trimming and cleaning activities were performed that reduced water pollution caused by organic deposits and feathers from wild birds. The impaired waterbody is located on the campus of the Peruvian Union University, 580 meters above sea level, with a volume of 6,405.336 m3, an area of 3,050.16 m2, 256.81 m perimeter, and 0.12 m3/s input flow. Seven 1.8 m2 floating systems were implemented, with 12 common water hyacinth plants in each system. Before implementing this system, a water quality analysis was performed to analyse the physical-chemical, microbiological, and organoleptic parameters. The pre-analysis revealed the pond’s critical condition, with electrical conductivity: 556 mg/l; phosphate: < 0.5; pH: 7.06; total solids: 412 mg/l; arsenic: <0.01; lead: 0.115; BOD5: 14; COD: 16.94; dissolved oxygen: 13; total coliforms: 24000 MCL/100 ml; and thermo-tolerant coliforms: 11000 MCL/100 ml. After implementing the system, the following results were obtained: EC: 495 mg/l; DO:9.2 mg/l; TS: 235 mg/l; BOD5: 7.7; COD: 8.47; Pb: 0.001 mg/l; TC: 460 MCL/100 ml; FC: 240 MCL/100 ml. Thus, we confirmed that the system is 78.79% efficient regarding the Peruvian ECA (Environmental Quality Standards) established for water according to DS #015-2015-MINAM. Therefore, the water is suitable for plant irrigation. Finally, we concluded that treating wastewater with the species Eichhornia Crassipes is efficient since an improvement was achieved in the impaired waterbody.

Keywords: Eichhornia crassipes, plantlets, cleaning, impaired waterbody, pond

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Authors: Siegfried Berhimpon, Jein Dangeubun, Sandra Baulu, Rene Ch. Kepel

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In Indonesia, macro-alga is known as seaweeds or rumput laut and sea grass or lamun, and have been used as vegetables and medicine since long time ago. This studies have been done, to collect data about utilization of seaweed and sea grass as food or medicine in Eastern Indonesia. Six regencies in two provinces have been chosen as sampling areas i.e. South-East Maluku, West-East Maluku, and Aru in province of Maluku; and Sangihe, Sitaro, and Minahasa in province of North Sulawesi. The results shown that in the pass, seaweeds and sea grass have been widely used as food and medicine, and there are similarity between one area and other areas in species and in the way to prepare or to cook the food. Ten species of alga and 2 species of sea grass were consumed as vegetables and desert, and one species of sea grass was used for traditional medicine. Nowadays, because of easier to get terrestrial vegetables, the people in the coastal area rarely consumed marine vegetables, and if there are no attempt to promote and to socialize the custom, the habits trend to disappear. Environmental degradation was another caused has been identified. Seaweed contained high content of Iodine and dietary fiber, therefore, this food can overcomes the problem of iodine deficiency, and to supply an exotic high-fiber foods. In addition, by consuming seaweeds, marine culture industry will be developed, especially in the number of species seaweeds to be cultivated.

Keywords: ethno-botany, seaweed, sea grass, exotic food

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Authors: Annur Suhadi, Haris B. Harahap, Zaim Arrosyidi, Epan, Darmapala

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Oilfields under waterflood often face the problem of plugging injectors either by internal filtration or external filter cake built up inside pore throats. The content of suspended solids shall be reduced to required level of filtration since corrective action of plugging is costly expensive. The performance of nutshell filters, where filtration takes place, is good using pecan and walnut shells. Candlenut shells were used instead of pecan and walnut shells since they were abundant in Indonesia, Malaysia, and East Africa. Physical and chemical properties of walnut, pecan, and candlenut shells were tested and the results were compared. Testing, using full-scale nutshell filters, was conducted to determine the oil content, turbidity, and suspended solid removal, which was based on designed flux rate. The performance of candlenut shells, which were deeply bedded in nutshell filters for filtration process, was monitored. Cleaned water outgoing nutshell filters had total suspended solids of 17 ppm, while oil content could be reduced to 15.1 ppm. Turbidity, using candlenut shells, was below the specification for injection water, which was less than 10 Nephelometric Turbidity Unit (NTU). Turbidity of water, outgoing nutshell filter, was ranged from 1.7-5.0 NTU at various dates of operation. Walnut, pecan, and candlenut shells had moisture content of 8.98 wt%, 10.95 wt%, and 9.95 wt%, respectively. The porosity of walnut, pecan, and candlenut shells was significantly affected by moisture content. Candlenut shells had property of toluene solubility of 7.68 wt%, which was much higher than walnut shells, reflecting more crude oil adsorption. The hardness of candlenut shells was 2.5-3 Mohs, which was close to walnut shells’ hardness. It was advantage to guarantee the cleaning filter cake by fluidization process during backwashing.

Keywords: candlenut shells, filtration, nutshell filter, pecan shells, walnut shells

Procedia PDF Downloads 115

Authors: Yazidu Saidi Mbalamula

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Free Basic Education (FBE) policy implementation in Secondary Schools has been one of thrilled undertaking both to the government and household in Tanzania. On the one hand, the government has achieved citizenry acceptance to responsibility and accountability, and on the other hand, the household has been relieved from social costs that were unbearable and deprived many Tanzanians access to basic education and secondary education in particular. Specifically, this study presents a descriptive survey conducted in two districts of Kagera region located at the northern part of Tanzania. Three objectives were pursued to identify achievements realized and challenges in the FBE implementation, and also stakeholders’ proposals were explored on how to improve FBE implementation. A sample of 91 respondents, including school managers, teachers, students, and parents, were involved in the study. Both questionnaires and interviews were used whereby the quantitative data were analyzed using Statistical Package for Social Sciences (SPSS), and content analysis was used to analyze the qualitative data. The results show that implementation of free education policy in secondary schools had far positive impact on the improvement of school management, school attendance, reduced school drop-out, reduced parents-school managers conflicts, and increased enrollment rates. Notwithstanding that, the political machinery remains instrumental to instigate policy reforms in education sector. Nevertheless, the alienating interests of politibureau, often top-down and blanketed by superficial government redness, can hardly be feasible to wield such huge programme given staggering stakeholders’ awareness of the actual requirements and unlatching resources to back up policy implementation. The study recommends that further studies on stakeholders’ conceptions on the FBE and equity of financing of basic education in Tanzania.

Keywords: capitation grant, CCM, free basic education, kagera, education policy

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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Authors: Asaiel Alohaly

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A theoretical framework for corporate governance is needed to bridge the gap between the corporate governance of private companies and State-owned Enterprises (SOEs). The two dominant models, being shareholder and stakeholder, do not always address the specific requirements and challenges posed by ‘hybrid’ companies; namely, previously national bodies that have been privatised bffu t where the government retains significant control or holds a majority of shareholders. Thus, an exploratory theoretical study is needed to identify how ‘hybrid’ companies should be defined and why the state model should be acknowledged since it is the less conspicuous model in comparison with the shareholder and stakeholder models. This research focuses on ‘the state model of corporate governance to understand the complex ownership, control pattern, goals, and corporate governance of these hybrid companies. The significance of this research lies in the fact that there is a limited available publication on the state model. The outcomes of this research are as follows. It became evident that the state model exists in the ecosystem. However, corporate governance theories have not extensively covered this model. Though, there is a lot being said about it by OECD and the World Bank. In response to this gap between theories and industry practice, this research argues for the state model, which proceeds from an understanding of the institutionally embedded character of hybrid companies where the government is either a majority of the total shares or a controlling shareholder.

Keywords: corporate governance, control, shareholders, state model

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Authors: Kyeong Hoon Park, Taiji Mazuda

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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.

Keywords: base-isolation, bilinear model, high damping rubber, loading test

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Authors: S. Jalaja, A. M. Vijaya Prakash

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Recursive combination of an algorithm based on Karatsuba multiplication is exploited to design a generalized transpose and parallel Finite Impulse Response (FIR) Filter. Mid-range Karatsuba multiplication and Carry Save adder based on Karatsuba multiplication reduce time complexity for higher order multiplication implemented up to n-bit. As a result, we design modified N-tap Transpose and Parallel Symmetric FIR Filter Structure using Karatsuba algorithm. The mathematical formulation of the FFA Filter is derived. The proposed architecture involves significantly less area delay product (APD) then the existing block implementation. By adopting retiming technique, hardware cost is reduced further. The filter architecture is designed by using 90 nm technology library and is implemented by using cadence EDA Tool. The synthesized result shows better performance for different word length and block size. The design achieves switching activity reduction and low power consumption by applying with and without retiming for different combination of the circuit. The proposed structure achieves more than a half of the power reduction by adopting with and without retiming techniques compared to the earlier design structure. As a proof of the concept for block size 16 and filter length 64 for CKA method, it achieves a 51% as well as 70% less power by applying retiming technique, and for CSA method it achieves a 57% as well as 77% less power by applying retiming technique compared to the previously proposed design.

Keywords: carry save adder Karatsuba multiplication, mid range Karatsuba multiplication, modified FFA and transposed filter, retiming

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Authors: Ella Tyuryumina, Alexey Neznanov

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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

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Authors: Chih-Hua Chang

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This study uses a three-dimensional (3D) fully nonlinear model to simulate the wave generation problem caused by the movement of the seabed. The numerical model is first simplified into two dimensions and then compared with the existing two-dimensional (2D) experimental data and the 2D numerical results of other shallow-water wave models. Results show that this model is different from the earlier shallow-water wave models, with the phase being closer to the experimental results of wave propagation. The results of this study are also compared with those of the 3D experimental results of other researchers. Satisfactory results can be obtained in both the waveform and the flow field. This study assesses the application of the model to simulate the wave caused by the circular (radius r0) terrain rising or falling (moving distance bm). The influence of wave-making parameters r0 and bm are discussed. This study determines that small-range (e.g., r0 = 2, normalized by the static water depth), rising, or sinking terrain will produce significant wave groups in the far field. For large-scale moving terrain (e.g., r0 = 10), uplift and deformation will potentially generate the leading solitary-like waves in the far field.

Keywords: seismic wave, wave generation, far-field waves, seabed deformation

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Authors: Faci Youcef

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In the present work, an experimental study is carried out using the digital image correlation (DIC) technique to analyze the damage and behavior of woven composite carbon/epoxy under tensile loading. The tension mechanisms associated with failure modes of bolted joints in advanced composites are studied, as well as displacement distribution and strain distribution. The evolution value of bolt angle inclination during tensile tests was studied. In order to compare the distribution of displacements and strains along the surface, figures of image mapping are made. Several factors that are responsible for the failure of fiber-reinforced polymer composite materials are observed. It was found that strain concentrations observed in the specimens can be used to identify full-field damage onset and to monitor damage progression during loading. Moreover, there is an interaction between laminate pattern, laminate thickness, fastener size and type, surface strain concentrations, and out-of-plane displacement. Conclusions include a failure analysis associated with bolt angle inclinations and supported by microscopic visualizations of the composite specimen. The DIC results can be used to develop and accurately validate numerical models.

Keywords: Carbone, woven, damage, digital image, bolted joint, the inclination of angle

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Authors: Behrang Ekrami, Amin Tamadon

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Persian fallow deer (Dama dama mesopotamica) is belonging to the family Cervidae and is only found in a few protected areas in the northwest, north, and southwest of Iran. The aims of this study were analysis of inbreeding and morphometric parameters of semen in male Persian fallow deer to investigate the cause of reduced fertility of this endangered species in Dasht-e-Naz National Refuge, Sari, Iran. The Persian fallow deer semen was collected from four adult bucks randomly during the breeding and non-breeding season from five dehorned and horned deer's BY an artificial vagina. Twelve blood samples was taken from Persian fallow deer and mitochondrial DNA was extracted, amplified, extracted, sequenced, and then were considered for genetic analysis. The Persian fallow deer semen, both with normal and abnormal spermatozoa, is similar to that of domestic ruminants but very smaller and difficult to observe at the primary observation. The post-mating season collected ejaculates contained abnormal spermatozoa, debris and secretion of accessory glands in horned bucks and accessory glands secretion free of any spermatozoa in dehorned or early velvet budding bucks. Microscopic evaluation in all four bucks during the mating season showed the mean concentration of 9×106 spermatozoa/ml. The mean ±SD of age, testes length and testes width was 4.60±1.52 years, 3.58±0.32 and 1.86±0.09 cm, respectively. The results identified 1120 loci (assuming each nucleotide as locus) in which 377 were polymorphic. In conclusion, reduced fertility of male Persian fallow deer may be caused by inbreeding of the protected herd in a limited area of Dasht-e-Naz National Refuge.

Keywords: Persian fallow deer, spermatozoa, reproductive characteristics, morphometric parameters

Procedia PDF Downloads 581

Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

Procedia PDF Downloads 86

Authors: Sulyman Abdulhakeem Olarewaju, S. O. Malomo, M. T. Yakubu, J. O. Akolade

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The ameliorative effect of Celosia argentea var. cristata leaf extract against cadmium (Cd) induced oxidative stress and toxicity in selected tissues of rats was investigated. Toxicity coupled with oxidative stress was induced in rats by oral administration of Cd (8 mg/kg b. wt). Preliminary quantitative phytochemical and in vitro antioxidant analyses showed that the methanolic extract of C. argentea leaves was constituted by polyphenols (5.72%), saponins (3.20%), tannins (0.65%) and cadenolides (0.006%). IC50 of 9800, 7406, and 45.04 μg/ml were recorded for inhibition of linoleic acid oxidation, 2, 2-diphenyl-1-picrylhydrazyl and hydrogen peroxide radicals respectively. Simultaneous administration of C. argentea leaf extract with Cd significantly attenuated Cd-induced elevation of serum enzyme markers such as aspartate and alanine transaminase, alkaline and acid phosphatase as well as γ-glutaryltransferase in a dose-dependent fashion, while their reduced level in the liver were significantly increased. Higher levels of enzymatic antioxidants; superoxide dismutase and catalase activities were observed in the liver, brain, kidney and testes of the Cd-induced rats treated with C. argentea extract, while lipid peroxidation expressed in malondialdehyde concentrations were lower when compared to values in rats administered Cd only. Other Cd-induced toxicity and stress markers in the serum viz. reduced uric acid and albumin levels as well as elevated total and unconjugated bilirubin were attenuated by the extract and their values compared favorably with those animals co-administered cadmium with ascorbic acid. Data from the study showed that oral administration of extract from the leaf C. argentea may ameliorate Cd-induced oxidative stress and toxicity in rats.

Keywords: toxicity, cadmium, celosia, antioxidants, oxidative stress

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Authors: Williams A. Adu, Cynthia A. Danquah, Paul P. S. Ossei, Selase Ativui, Michael Ofori, James Asenso, George Owusu

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Background Silicosis is an occupational disease of the lung that is caused by chronic exposure to silica dust. There is a higher frequency of co-existence of silicosis with tuberculosis (TB), ultimately resulting in lung fibrosis and respiratory failure. Chronic intake of synthetic drugs has resulted in undesirable side effects. Diosgenin is a steroidal saponin that has been shown to exert a therapeutic effect on lung injury. Therefore, we investigated the ability of diosgenin to reduce the susceptibility of silica-induced TB in rats. Method Silicosis was induced by intratracheal instillation of 50 mg/kg crystalline silica in Sprague Dawley rats. Different doses of diosgenin (1, 10, and 100 mg/kg), Mycobacterium smegmatis and saline were administered for 30 days. Afterwards, 5 of the rats from each group were sacrificed, and the 5 remaining rats in each group, except the control, received Mycobacterium smegmatis. Treatment of diosgenin continued until the 50th day, and the rats were sacrificed at the end of the experiment. The result was analysed using a one-way analysis of variance (ANOVA) with a Graph-pad prism Result At a half-maximal inhibition concentration of 48.27 µM, diosgenin inhibited the growth of Mycobacterium smegmatis. There was a marked decline in the levels of immune cell infiltration and cytokines production. Lactate dehydrogenase and total protein levels were significantly reduced compared to control. There was an increase in the survival rate of the treatment group compared to the control. Conclusion Diosgenin ameliorated silica-induced pulmonary tuberculosis by declining the levels of inflammatory and pro-inflammatory cytokines and, in effect, significantly reduced the susceptibility of rats to pulmonary TB.

Keywords: silicosis, tuberculosis, diosgenin, fibrosis, crystalline silica

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Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

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Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: T. A. Faria, C. C. Toniolo, L. F. Ribeiro

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In order to satisfy the costumer’s needs, many sectors of industry and services has been spending major effort to make its processes more efficient. Facing a situation, when its production cannot cover the demand, the traditional way to achieve the production required involves, mostly, adding shifts, workforce, or even more machines. This paper narrates how lean manufacturing supported a dramatic increase of productivity at a rail welding plant in Brazil in order to meet the demand for the next years.

Keywords: productivity, lean manufacturing, rail welding, value stream mapping

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Authors: M. A. Tayfun, M. A. Alkhalidi

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The exact theoretical expression describing the probability distribution of nonlinear sea-surface elevations derived from the second-order narrowband model has a cumbersome form that requires numerical computations, not well-disposed to theoretical or practical applications. Here, the same narrowband model is re-examined to develop a simpler closed-form approximation suitable for theoretical and practical applications. The salient features of the approximate form are explored, and its relative validity is verified with comparisons to other readily available approximations, and oceanic data.

Keywords: ocean waves, probability distributions, second-order nonlinearities, skewness coefficient, wave steepness

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Authors: Thendiyath Roshni, Stefano Pagliara

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Block ramps (BR) or rock chutes are eco-friendly natural river restoration structures. BR are made of ramp of rocks and flows over BR develop turbulence and helps in the entrainment of ambient air. These act as natural aerators in river flow and therefore leads to oxygenation of water. As many of the hydraulic structures in rivers, hinders the natural path for aquatic habitat. However, flows over BR ascertains a natural rocky flow and ensures safe and natural movement for aquatic habitat. Hence, BR is considered as a better alternative for drop structures. As water quality is concerned, turbulent and aerated flows over BR or macro-roughness conditions improves aeration and thereby oxygenation. Hence, the objective of this paper is to study the oxygenation in the turbulent flows over BR. Experimental data were taken for a slope (S) of 27.5% for three discharges (Q = 9, 15 and 21 lps) conditions. Air concentration were measured with the help of air concentration probe for three different discharges in the uniform flow region. Oxygen concentration is deduced from the air concentration as ambient air is entrained in the flows over BR. Air concentration profiles and oxygen profiles are plotted in the uniform flow region for three discharges and found that air concentration and oxygen concentration does not show any remarkable variation in properties in the longitudinal profile in uniform flow region. An empirical relation is developed for finding the average oxygen concentration (Oₘ) for S = 27.5% in the uniform flow region for 9 < Q < 21 lps. The results show that as the discharge increases over BR, there is a reduction of oxygen concentration in the uniform flow region.

Keywords: aeration, block ramps, oxygenation, turbulent flows

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Majid Mardaniyan Ghahfarokhi, Abdolhamid Habibi, Majid Mohammad Shahi

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The combination of exercise and diet as the most important strategy to reduce weight and control obesity-related factors, including Irisin, Insulin, and Glucose was raised. The aim of this study was to investigate the effect of aerobic exercise combined with four different diets on serum levels of Irisin, Insulin, and Glucose in overweight men. Methods: In this quasi-experimental study, 8 overweight men (BMI 29.23±0.47) with average age of (23±1.6) voluntarily participated in 4 sessions by one-week interval. The study was done in exercise physiology lab. In each session, subjects performed a 30 minutes treadmill test with 60-70% of maximum heart rate, after consuming a high carbohydrate, high-fat, high-protein and normal diet. For biochemical measurement, three blood samples were taken in fasting state, two hours after meals and after exercise Results: Statistical analysis of data showed that the serum levels of Irisin after consumption all four diets had been reduced which this reduce as a result of high-fat diet that were significantly (p ≤ 0/038). Serum concentration of Insulin and Glucose increased after consuming four diets. However, increase in serum Insulin and Glucose was significant only after consuming high-carbohydrate diet (Respectively p ≤ 0/001, p ≤ 0/042). In addition, during exercise after consuming all four regular diet, high carbohydrate, high-protein and high-fat, Irisin significant increased significantly (Respectively p ≤ 0/021, p ≤ 0/049, p ≤ 0/001, P ≤ 0/003), Insulin decreased significantly (Respectively p ≤ 0/002, p ≤ 0/001, p ≤ 0/001, p ≤ 0/002) and Glucose were significantly reduced (Respectively p ≤ 0/001, p ≤ 0/001, P ≤ 0/001, p ≤ 0/002). After aerobic activity following the consumption of a high protein diet the highest increase in irisin levels, and after aerobic exercise following consumption of high carbohydrate diet the greatest decrease in insulin and glucose levels were observed. Conclusion: It seems that diet alone and exercises following different consumption diets can have a significant effect on Irisin, Insulin, and Glucose serum levels in overweight young men.

Keywords: acute aerobic exercise, diet, irisin, overweight

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Authors: Abigail Tan, Heng Liang Tan, Vanessa Ding, James Hui, Eng Hin Lee, Andre Choo

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Introduction: Comparative oncology investigates the similarities in spontaneous carcinogenesis between humans and animals, in order to identify treatments that can benefit these patients. Companion animals (CA), like canines and felines, are of special interest when it comes to studying human cancers due to their exposure to the same environmental factors and develop tumours with similar features. The purpose of this study is to explore the cross-reactivity of monoclonal antibodies (mAbs) across cancers in humans and CA. Material and Methods: A panel of CA mAbs generated in the lab was screened on multiple human cancer cell lines through flow cytometry to identify for positive binders. Shortlisted candidates were then characterised by biochemical and functional assays e.g., antibody-drug conjugate (ADC) and western blot assays, including glycan studies. Results: Candidate mAb KP52 was generated from whole-cell immunisation using feline mammary carcinoma. KP52 showed strong positive binding to human cancer cells, such as breast cancer and ovarian cancer. Furthermore, KP52 demonstrated strong killing ( > 50%) as an ADC with Saporin as the payload. Western blot results revealed the molecular weight of the antigen targets to be approximately 45kD and 50kD under reduced conditions. Glycan studies suggest that the epitope is glycan in nature, specifically an O-linked glycan. Conclusion: Candidate mAb KP52 has a therapeutic potential as an ADC against feline mammary cancer, human ovarian cancer, human mammary cancer, human pancreatic cancer, and human gastric cancer.

Keywords: ADC, comparative oncology, mAb, therapeutic

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Authors: Tooraj Karimi, Mohammadreza Sadeghi Moghadam

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Grey set theory has the advantage of using fewer data to analyze many factors, and it is therefore more appropriate for system study rather than traditional statistical regression which require massive data, normal distribution in the data and few variant factors. So, in this paper grey clustering and entropy of coefficient vector of grey evaluations are used to analyze energy consumption in buildings of the Oil Ministry in Tehran. In fact, this article intends to analyze the results of energy audit reports and defines most favorable characteristics of system, which is energy consumption of buildings, and most favorable factors affecting these characteristics in order to modify and improve them. According to the results of the model, ‘the real Building Load Coefficient’ has been selected as the most important system characteristic and ‘uncontrolled area of the building’ has been diagnosed as the most favorable factor which has the greatest effect on energy consumption of building. Grey clustering in this study has been used for two purposes: First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, grey clustering with variable weights has been used to classify all buildings in three categories named ‘no standard deviation’, ‘low standard deviation’ and ‘non- standard’. Entropy of coefficient vector of Grey evaluations is calculated to investigate greyness of results. It shows that among the 38 buildings surveyed in terms of energy consumption, 3 cases are in standard group, 24 cases are in ‘low standard deviation’ group and 11 buildings are completely non-standard. In addition, clustering greyness of 13 buildings is less than 0.5 and average uncertainly of clustering results is 66%.

Keywords: energy audit, grey set theory, grey incidence matrixes, grey clustering, Iran oil ministry

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Authors: Marina Sofia, Alexios Giannakopoulos, Antonia Touloudi, Dimitris C Chatzopoulos, Zoi Athanasakopoulou, Vassiliki Spyrou, Charalambos Billinis

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Fertility of dairy cattle can be affected by heat stress when the ambient temperature increases above 30°C and the relative humidity ranges from 35% to 50%. The present study was conducted on dairy cattle farms during summer months in Greece and aimed to identify the serological profile against pathogens that could affect fertility and to associate the positive serological results at herd level with temperature factors. A total of 323 serum samples were collected from clinically healthy dairy cows of 8 herds, located in Central and Northern Greece. ELISA tests were performed to detect antibodies against selected pathogens that affect fertility, namely Chlamydophila abortus, Coxiella burnetii, Neospora caninum, Toxoplasma gondii and Infectious Bovine Rhinotracheitis Virus (IBRV). Eleven climatic variables were derived from the WorldClim version 1.4. and ArcGIS V.10.1 software was used for analysis of the spatial information. Five different MaxEnt models were applied to associate the temperature variables with the locations of seropositive Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV herds (one for each pathogen). The logistic outputs were used for the interpretation of the results. ROC analyses were performed to evaluate the goodness of fit of the models’ predictions. Jackknife tests were used to identify the variables with a substantial contribution to each model. The seropositivity rates of pathogens varied among the 8 herds (0.85-4.76% for Chl. abortus, 4.76-62.71% for N. caninum, 3.8-43.47% for C. burnetii, 4.76-39.28% for T. gondii and 47.83-78.57% for IBRV). The variables of annual temperature range, mean diurnal range and maximum temperature of the warmest month gave a contribution to all five models. The regularized training gains, the training AUCs and the unregularized training gains were estimated. The mean diurnal range gave the highest gain when used in isolation and decreased the gain the most when it was omitted in the two models for seropositive Chl.abortus and IBRV herds. The annual temperature range increased the gain when used alone and decreased the gain the most when it was omitted in the models for seropositive C. burnetii, N. caninum and T. gondii herds. In conclusion, antibodies against Chl. abortus, C. burnetii, N. caninum, T. gondii and IBRV were detected in most herds suggesting circulation of pathogens that could cause infertility. The results of the spatial analyses demonstrated that the annual temperature range, mean diurnal range and maximum temperature of the warmest month could affect positively the possible pathogens’ presence. Acknowledgment: This research has been co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH–CREATE–INNOVATE (project code: T1EDK-01078).

Keywords: dairy cows, seropositivity, spatial analysis, temperature factors

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Authors: Nozar Kishi, Babak Kamrani, Filmon Habte

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Natural hazards such as earthquakes and tropical storms, are very frequent and highly destructive in Japan. Japan experiences, every year on average, more than 10 tropical cyclones that come within damaging reach, and earthquakes of moment magnitude 6 or greater. We have developed stochastic catastrophe models to address the risk associated with the entire suite of damaging events in Japan, for use by insurance, reinsurance, NGOs and governmental institutions. KCC’s (Karen Clark and Company) catastrophe models are procedures constituted of four modular segments: 1) stochastic events sets that would represent the statistics of the past events, hazard attenuation functions that could model the local intensity, vulnerability functions that would address the repair need for local buildings exposed to the hazard, and financial module addressing policy conditions that could estimates the losses incurring as result of. The events module is comprised of events (faults or tracks) with different intensities with corresponding probabilities. They are based on the same statistics as observed through the historical catalog. The hazard module delivers the hazard intensity (ground motion or wind speed) at location of each building. The vulnerability module provides library of damage functions that would relate the hazard intensity to repair need as percentage of the replacement value. The financial module reports the expected loss, given the payoff policies and regulations. We have divided Japan into regions with similar typhoon climatology, and earthquake micro-zones, within each the characteristics of events are similar enough for stochastic modeling. For each region, then, a set of stochastic events is developed that results in events with intensities corresponding to annual occurrence probabilities that are of interest to financial communities; such as 0.01, 0.004, etc. The intensities, corresponding to these probabilities (called CE, Characteristics Events) are selected through a superstratified sampling approach that is based on the primary uncertainty. Region specific hazard intensity attenuation functions followed by vulnerability models leads to estimation of repair costs. Extensive economic exposure model addresses all local construction and occupancy types, such as post-linter Shinand Okabe wood, as well as concrete confined in steel, SRC (Steel-Reinforced Concrete), high-rise.

Keywords: typhoon, earthquake, Japan, catastrophe modelling, stochastic modeling, stratified sampling, loss model, ERM

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Authors: Qian Huiya, Feng Lin

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The progressive collapse of reinforced concrete (RC) structures will cause huge casualties and property losses. Therefore, it is necessary to evaluate the ability of structures against progressive collapse accurately. This paper numerically investigated the effect of storey number on the mechanism and quantitative contribution of the Vierendeel action (VA) in progressive collapse under corner column removal scenario. First, finite element (FE) models of multi-storey RC frame structures were developed using LS-DYNA. Then, the accuracy of the modeling technique was validated by test results conducted by the authors. Last, the validated FE models were applied to investigated the structural behavior of the RC frames with different storey numbers from one to six storeys. Results found the multi-storey substructure formed additional plastic hinges at the beam ends near the corner column in the second to top storeys, and at the lower end of the corner column in the first storey. The average ultimate resistance of each storey of the multi-storey substructures were increased by 14.0% to 18.5% compared with that of the single-storey substructure experiencing no VA. The contribution of VA to the ultimate resistance was decreased with the increase of the storey number.

Keywords: progressive collapse, reinforced concrete structure, storey number, Vierendeel action

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

Procedia PDF Downloads 149