Search results for: Uputaua therapeutic approach

Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Wang Yunhong

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The present paper is preoccupied with the different styles of three translators in their translating a Chinese classical novel Shuihu Zhuan. Based on a parallel corpus, it adopts a target-oriented approach to look into whether and what stylistic differences and shifts the three translations have revealed. The findings show that the three translators demonstrate different styles concerning their word choices and sentence preferences, which implies that identification of recurrent textual patterns may be a basic step for investigating the style of a translator.

Keywords: corpus, lexical choices, sentence characteristics, style

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Authors: D. O. Miranda, L. R. Azevedo, J. F. C. Cordeiro, A. H. Dos Santos, S. F. Lisboa, F. S. Guimarães, G. S. Bisson

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Background: The Colorectal cancer (CRC) is one of the most common cancers and the fourth leading cause of cancer death in the world. The prevalence of psychiatric-disorders among CRC patients, mainly depression, is high, resulting in impaired quality of life and side effects of primary treatment. High levels of proinflammatory cytokines at tumor microenvironment is a feature of CRC and the literature suggests that those mediators could contribute to the development of psychiatric disorders. Nevertheless, the ability of tumor-associated biological processes to affect the central nervous system (CNS) has only recently been explored in the context of symptoms of depression and is still not well understood. Therefore, the aim of the present study was to test the hypothesis that depressive-like behavior in an experimental model of CCR induced by N-methyl-N-nitro-N-nitrosoguanidine (MNNG) was correlated to proinflammatory profile in the periphery and in the brain. Methods: Colorectal carcinogenesis was induced in adult C57BL/6 mice (n=12) by administration of MNNG (5mg/kg, 0.1ml/intrarectal instillation) 2 times a week, for 2 week. Control group (n=12) received saline (0.1ml/intrarectal instillation). Eight weeks after beginning of MNNG administration animals were submitted to the forced swim test (FST) and the sucrose preference test for evaluation, respectively, of depressive- and anhedonia-like behaviors. After behavioral evaluation, the colon was collected and brain regions dissected (cortex-C, striatum-ST and hippocampus-HIP) for posterior evaluation of cytokine levels (IL-1β, IL-10, IL-17, and CX3CL1) by ELISA. Results: MNNG induced depressive-like behavior, represented by increased immobility time in the FST (Student t test, p < 0.05) and lower sucrose preference (Student t test, p < 0.05). Moreover, there were increased levels of IL-1β, IL-17 and CX3CL1 in the colonic tissue (Student t test, p < 0.05) and in the brain (IL-1 β in the ST and HIP, Student t test, p < 0.05; IL-17 and CX3CL1 in the C and HIP, p < 0.05). IL-10 levels, in contrast, were decreased in both the colon (p < 0.05) and the brain (C and HIP, p < 0.05). Conclusions: The results obtained in the present work support the notion that tumor growth induces neuroinflammation in stress-related brain regions and depressive-like behavior, which could be related to the high incidence of depression in colorectal carcinogenesis. This work have important clinical and research implications, taken into account that cytokine levels may be a marker promissory for the developing depression in CRC patients. New therapeutic strategies to assist in alleviating mental suffering in cancer patients might result from a better understanding of the role of cytokines in the pathophysiology of depression in these subjects.

Keywords: cytokines, brain, depression, colorectal cancer

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Authors: Peter M. Schneider, Batyr Garlyyev, Sebastian A. Watzele, Aliaksandr S. Bandarenka

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Functional nanostructures such as nanoparticles are a promising class of materials for energy applications due to their unique properties. Bottom-up synthetic routes for nanostructured materials often involve multiple synthesis steps and the use of surfactants, reducing agents, or stabilizers. This results in complex and extensive synthesis protocols. In recent years, a novel top-down synthesis approach to form metal nanoparticles has been established, in which bulk metal wires are immersed in an electrolyte (primarily alkali earth metal based) and subsequently subjected to a high alternating potential. This leads to the generation of nanoparticles dispersed in the electrolyte. The main advantage of this facile top-down approach is that there are no reducing agents, surfactants, or precursor solutions. The complete synthesis can be performed in one pot involving one main step with consequent washing and drying of the nanoparticles. More recent studies investigated the effect of synthesis parameters such as potential amplitude, frequency, electrolyte composition, and concentration on the size and shape of the nanoparticles. Here, we investigate the electrochemical erosion of various metal wires such as Ti, Pt, Pd, and Sn in various electrolyte compositions via this facile top-down technique and its experimental optimization to successfully synthesize nanostructured materials for various energy applications. As an example, for Pt and Pd, homogeneously distributed nanoparticles on carbon support can be obtained. These materials can be used as electrocatalyst materials for the oxygen reduction reaction (ORR) and hydrogen evolution reaction (HER), respectively. In comparison, the top-down erosion of Sn wires leads to the formation of nanoparticles, which have great potential as oxygen evolution reaction (OER) support materials. The application of the technique on Ti wires surprisingly leads to the formation of nanowires, which show a high surface area and demonstrate great potential as an alternative support material to carbon.

Keywords: ORR, electrochemistry, electrocatalyst, synthesis

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Authors: Ligang Wang, Theodoros Damartzis, Stefan Diethelm, Jan Van Herle, François Marechal

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Biogas production from anaerobic digestion of organic sludge from wastewater treatment as well as various urban and agricultural organic wastes is of great significance to achieve a sustainable society. Two upgrading approaches for cleaned biogas can be considered: (1) direct H₂ injection for catalytic CO₂ methanation and (2) CO₂ separation from biogas. The first approach usually employs electrolysis technologies to generate hydrogen and increases the biogas production rate; while the second one usually applies commercially-available highly-selective membrane technologies to efficiently extract CO₂ from the biogas with the latter being then sent afterward for compression and storage for further use. A straightforward way of utilizing the captured CO₂ is on-site catalytic CO₂ methanation. From the perspective of system complexity, the second approach may be questioned, since it introduces an additional expensive membrane component for producing the same amount of methane. However, given the circumstance that the sustainability of the produced biogas should be retained after biogas upgrading, renewable electricity should be supplied to drive the electrolyzer. Therefore, considering the intermittent nature and seasonal variation of renewable electricity supply, the second approach offers high operational flexibility. This indicates that these two approaches should be compared based on the availability and scale of the local renewable power supply and not only the technical systems themselves. Solid-oxide electrolysis generally offers high overall system efficiency, and more importantly, it can achieve simultaneous electrolysis of CO₂ and H₂O (namely, co-electrolysis), which may bring significant benefits for the case of CO₂ separation from the produced biogas. When taking co-electrolysis into account, two additional upgrading approaches can be proposed: (1) direct steam injection into the biogas with the mixture going through the SOE, and (2) CO₂ separation from biogas which can be used later for co-electrolysis. The case study of integrating SOE to a wastewater treatment plant is investigated with wind power as the renewable power. The dynamic production of biogas is provided on an hourly basis with the corresponding oxygen and heating requirements. All four approaches mentioned above are investigated and compared thermo-economically: (a) steam-electrolysis with grid power, as the base case for steam electrolysis, (b) CO₂ separation and co-electrolysis with grid power, as the base case for co-electrolysis, (c) steam-electrolysis and CO₂ separation (and storage) with wind power, and (d) co-electrolysis and CO₂ separation (and storage) with wind power. The influence of the scale of wind power supply is investigated by a sensitivity analysis. The results derived provide general understanding on the economic competitiveness of SOE for sustainable biogas upgrading, thus assisting the decision making for biogas production sites. The research leading to the presented work is funded by European Union’s Horizon 2020 under grant agreements n° 699892 (ECo, topic H2020-JTI-FCH-2015-1) and SCCER BIOSWEET.

Keywords: biogas upgrading, solid-oxide electrolyzer, co-electrolysis, CO₂ utilization, energy storage

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Authors: Anusha Atmakuri, R. D. Tyagi, Patrick Drogui

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Landfilling is the most familiar and easy way to dispose solid waste. Landfill is generally received via wastes from municipal near to a landfill. The waste collected is from commercial, industrial, and residential areas and many more. Landfill leachate (LFL) is formed when rainwater passes through the waste placed in landfills and consists of several dissolved organic materials, for instance, aquatic humic substances (AHS), volatile fatty acids (VFAs), heavy metals, inorganic macro components, and xenobiotic organic matters, highly toxic to the environment. These components of LFL put a load on it, hence it necessitates the treatment of LFL prior to its discharge into the environment. Various methods have been used to treat LFL over the years, such as physical, chemical, biological, physicochemical, electrical, and advanced oxidation methods. This study focuses on the combination of biological and electrochemical methods- extracellular polymeric substances and electrocoagulation(EC). The coupling of electro-coagulation process with extracellular polymeric substances (EPS) (as flocculant) as pre and\or post treatment strategy provides efficient and economical process for the decontamination of landfill leachate contaminated with suspended matter, metals (e.g., Fe, Mn) and ammonical nitrogen. Electro-coagulation and EPS mediated coagulation approach could be an economically viable for the treatment of landfill leachate, along with possessing several other advantages over several other methods. This study utilised waste substrates such as activated sludge, crude glycerol and waste cooking oil for the production of EPS using fermentation technology. A comparison of different scenarios for the treatment of landfill leachate is presented- such as using EPS alone as bioflocculant, EPS and EC with EPS being the 1st stage, and EPS and EC with EC being the 1st stage. The work establishes the use of crude EPS as a bioflocculant for the treatment of landfill leachate and wastewater from a site near a landfill, along with EC being successful in removal of some major pollutants such as COD, turbidity, total suspended solids. A combination of these two methods is to be explored more for the complete removal of all pollutants from landfill leachate.

Keywords: landfill leachate, extracellular polymeric substances, electrocoagulation, bioflocculant.

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Authors: Lassi Lehto, Jaakko Kahkonen, Juha Oksanen, Tapani Sarjakoski

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The use of raster-formatted data sets in geospatial analysis is increasing rapidly. At the same time, geographic data are being introduced into disciplines outside the traditional domain of geoinformatics, like climate change, intelligent transport, and immigration studies. These developments call for better methods to deliver raster geodata in an efficient and easy-to-use manner. Data cube technologies have traditionally been used in the geospatial domain for managing Earth Observation data sets that have strict requirements for effective handling of time series. The same approach and methodologies can also be applied in managing other types of geospatial data sets. A cloud service-based geodata cube, called GeoCubes Finland, has been developed to support online delivery and analysis of most important geospatial data sets with national coverage. The main target group of the service is the academic research institutes in the country. The most significant aspects of the GeoCubes data repository include the use of multiple resolution levels, cloud-optimized file structure, and a customized, flexible content access API. Input data sets are pre-processed while being ingested into the repository to bring them into a harmonized form in aspects like georeferencing, sampling resolutions, spatial subdivision, and value encoding. All the resolution levels are created using an appropriate generalization method, selected depending on the nature of the source data set. Multiple pre-processed resolutions enable new kinds of online analysis approaches to be introduced. Analysis processes based on interactive visual exploration can be effectively carried out, as the level of resolution most close to the visual scale can always be used. In the same way, statistical analysis can be carried out on resolution levels that best reflect the scale of the phenomenon being studied. Access times remain close to constant, independent of the scale applied in the application. The cloud service-based approach, applied in the GeoCubes Finland repository, enables analysis operations to be performed on the server platform, thus making high-performance computing facilities easily accessible. The developed GeoCubes API supports this kind of approach for online analysis. The use of cloud-optimized file structures in data storage enables the fast extraction of subareas. The access API allows for the use of vector-formatted administrative areas and user-defined polygons as definitions of subareas for data retrieval. Administrative areas of the country in four levels are available readily from the GeoCubes platform. In addition to direct delivery of raster data, the service also supports the so-called virtual file format, in which only a small text file is first downloaded. The text file contains links to the raster content on the service platform. The actual raster data is downloaded on demand, from the spatial area and resolution level required in each stage of the application. By the geodata cube approach, pre-harmonized geospatial data sets are made accessible to new categories of inexperienced users in an easy-to-use manner. At the same time, the multiresolution nature of the GeoCubes repository facilitates expert users to introduce new kinds of interactive online analysis operations.

Keywords: cloud service, geodata cube, multiresolution, raster geodata

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Authors: Jacqueline Y. Thompson, Sam Watson, Lee Middleton, Karla Hemming

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Introduction: The odds ratio (estimated via logistic regression) is a well-established and common approach for estimating covariate-adjusted binary treatment effects when comparing a treatment and control group with dichotomous outcomes. Its popularity is primarily because of its stability and robustness to model misspecification. However, the situation is different for the relative risk and risk difference, which are arguably easier to interpret and better suited to specific designs such as non-inferiority studies. So far, there is no equivalent, widely acceptable approach to estimate an adjusted relative risk and risk difference when conducting clinical trials. This is partly due to the lack of a comprehensive evaluation of available candidate methods. Methods/Approach: A simulation study is designed to evaluate the performance of relevant candidate methods to estimate relative risks to represent conditional and marginal estimation approaches. We consider the log-binomial, generalised linear models (GLM) with iteratively weighted least-squares (IWLS) and model-based standard errors (SE); log-binomial GLM with convex optimisation and model-based SEs; log-binomial GLM with convex optimisation and permutation tests; modified-Poisson GLM IWLS and robust SEs; log-binomial generalised estimation equations (GEE) and robust SEs; marginal standardisation and delta method SEs; and marginal standardisation and permutation test SEs. Independent and identically distributed datasets are simulated from a randomised controlled trial to evaluate these candidate methods. Simulations are replicated 10000 times for each scenario across all possible combinations of sample sizes (200, 1000, and 5000), outcomes (10%, 50%, and 80%), and covariates (ranging from -0.05 to 0.7) representing weak, moderate or strong relationships. Treatment effects (ranging from 0, -0.5, 1; on the log-scale) will consider null (H0) and alternative (H1) hypotheses to evaluate coverage and power in realistic scenarios. Performance measures (bias, mean square error (MSE), relative efficiency, and convergence rates) are evaluated across scenarios covering a range of sample sizes, event rates, covariate prognostic strength, and model misspecifications. Potential Results, Relevance & Impact: There are several methods for estimating unadjusted and adjusted relative risks. However, it is unclear which method(s) is the most efficient, preserves type-I error rate, is robust to model misspecification, or is the most powerful when adjusting for non-prognostic and prognostic covariates. GEE estimations may be biased when the outcome distributions are not from marginal binary data. Also, it seems that marginal standardisation and convex optimisation may perform better than GLM IWLS log-binomial.

Keywords: binary outcomes, statistical methods, clinical trials, simulation study

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Authors: Mohammad Afzal Khan, Fatimah Alanazi, Hala Abdalrahman Ahmed, Talal Shamma, Kilian Kelly, Mohammed A. Hammad, Abdullah O. Alawad, Abdullah Mohammed Assiri, Dieter Clemens Broering

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Lung transplantation is a life-saving surgical replacement of diseased lungs in patients with end-stage respiratory malfunctions. Despite the remarkable short-term recovery, long-term lung survival continues to face several significant challenges, including chronic rejection and severe toxic side-effects due to global immunosuppression. Stem cell-based immunotherapy has been recognized as a crucial immunoregulatory regimen in various preclinical and clinical studies. Despite initial therapeutic outcomes, conventional stem cells face key limitations. The Cymerus™ manufacturing facilitates the production of a virtually limitless supply of consistent human induced pluripotent stem cell (iPSC)-derived mesenchymal stem cells, which could play a key role in selective immunosuppression and graft repair during rejection. Here, we demonstrated the impact of iPSC-derived human MSCs on the development of immune-tolerance and long-term graft survival in mouse orthotopic airway allografts. BALB/c→C57BL/6 allografts were reconstituted with iPSC-derived MSCs (2 million/transplant/ at d0), and allografts were examined for regulatory T cells (Tregs), oxygenation, microvascular blood flow, airway epithelium and collagen deposition during rejection. We demonstrated that iPSC-derived MSC treatment leads to significant increase in tissue expression of hTSG-6 protein, followed by an upregulation of mouse Tregs and IL-5, IL-10, IL-15 cytokines, which augments graft microvascular blood flow and oxygenation, and thereby maintained a healthy airway epithelium and prevented the subepithelial deposition of collagen at d90 post-transplantation. Collectively, these data confirmed that iPSC-derived MSC-mediated immunosuppression has potential to establish immune-tolerance and rescue allograft from sustained hypoxic/ischemic phase and subsequently limits long-term airway epithelial injury and collagen progression, which therapeutically warrant a study of Cymerus iPSC-derived MSCs as a potential management option for immunosuppression in transplant recipients.

Keywords: stem cell therapy, immunotolerance, regulatory T cells, hypoxia and ischemia, microvasculature

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Authors: Stella Chioma Nwizu

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The National Commission for Adult and Non Formal Education (NMEC) in Nigeria is charged with the reduction of illiteracy rate through the development, monitoring, and supervision of literacy programmes in Nigeria. In spite of various efforts by NMEC to reduce illiteracy, literature still shows that the illiteracy rate is still high. According to NMEC/UNICEF, about 60 million Nigerians are non-literate, and nearly two thirds of them are women. This situation forced the government to search for innovative and better approaches to literacy promotion and delivery. The literacy by radio project was adopted as an innovative intervention to literacy delivery in Nigeria because the radio is the cheapest and most easily affordable medium for non-literates. The project aimed at widening access to literacy programmes for the non-literate marginalized and disadvantaged groups in Nigeria by taking literacy programmes to their door steps. The literacy by radio has worked perfectly well in non-literacy reduction in Cuba. This innovative intervention of literacy by radio is anchored on the diffusion of innovation theory by Rogers. The literacy by radio has been going on for fifteen years and the efficacy and contributions of this innovation need to be investigated. Thus, the purpose of this research is to review the contributions of the literacy by radio in Nigeria. The researcher adopted the survey research design for the study. The population for the study consisted of 2,706 participants and 47 facilitators of the literacy by radio programme in the 10 pilot states in Nigeria. A sample of four states made up of 302 participants and eight facilitators were used for the study. Information was collected through Focus Group Discussion (FGD), interviews and content analysis of official documents. The data were analysed qualitatively to review the contributions of literacy by radio project and determine the efficacy of this innovative approach in facilitating literacy in Nigeria. Results from the field experience showed, among others, that more non-literates have better access to literacy programmes through this innovative approach. The pilot project was 88% successful; not less than 2,110 adults were made literate through the literacy by radio project in 2017. However, lack of enthusiasm and commitment on the part of the technical committee and facilitators due to non-payment of honorarium, poor signals from radio stations, interruption of lectures with adverts, low community involvement in decision making in the project are challenges to the success rate of the project. The researcher acknowledges the need to customize all materials and broadcasts in all the dialects of the participants and the inclusion of more civil rights, environmental protection and agricultural skills into the project. The study recommends among others, improved and timely funding of the project by the Federal Government to enable NMEC to fulfill her obligations towards the greater success of the programme, setting up of independent radio stations for airing the programmes and proper monitoring and evaluation of the project by NMEC and State Agencies for greater effectiveness. In an era of the knowledge-driven economy, no one should be allowed to get saddled with the weight of illiteracy.

Keywords: innovative approach, literacy, project, radio, survey

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Authors: Tahira Hussain, Ilhom Rahamkulov, Muhammad Aasim, Ugur Pirlak, Emre Aksoy, Mehmet Emin Caliskan, Allah Bakhsh

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RNA interference (RNAi) has proved its usefulness in functional genomic research on insects recently and is considered potential strategy in crop improvement for the control of insect pests. The different insect pests incur significant losses to potato yield worldwide, Colorado Potato Beetle (CPB) being most notorious one. The present study focuses to knock down highly specific 20-hydroxyecdysone hormone-receptor complex interaction by using RNAi approach to silence Ecdysone receptor (EcR) gene of CPB in transgenic potato plants expressing dsRNA of EcR gene. The partial cDNA of Ecdysone receptor gene of CPB was amplified using specific primers in sense and anti-sense orientation and cloned in pRNAi-GG vector flanked by an intronic sequence (pdk). Leaf and internodal explants of Lady Olympia, Agria and Granola cultivars of potato were infected with Agrobacterium strain LBA4404 harboring plasmid pRNAi-CPB, pRNAi-GFP (used as control). Neomycin phosphotransferase (nptII) gene was used as a plant selectable marker at a concentration of 100 mg L⁻¹. The primary transformants obtained have shown proper integration of T-DNA in plant genome by standard molecular analysis like polymerase chain reaction (PCR), real-time PCR, Sothern blot. The transgenic plants developed out of these cultivars are being evaluated for their efficacy against larvae as well adults of CPB. The transgenic lines are expected to inhibit expression of EcR protein gene, hindering their molting process, hence leading to increased potato yield.

Keywords: plant mediated RNAi, molecular strategy, ecdysone receptor, insect metamorphosis

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Authors: Niloofar Mobasem, Kambiz Heidarzadeh Hanzaee

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Purpose: The study aimed to measure the customer satisfaction with service recovery through the conflict management framework, especially assessing the role of pre-existing attitudes for measuring the customer response to the service failure. Design/ methodology/ approach: The study is based on the experimental research method. The factorial designs are used in the research that measures the variables in two separate studies. In the first study, the factorial design is 3 conflict management style: cooperative, competitive, avoiding; - 3 service performance: exceed expectation, meet expectation, fail to meet expectation; and in the second study includes: - 3 conflict management style: cooperative, competitive, avoiding; - 2 service performance: exceed expectation, fail to meet expectation; - 2 pre-existing attitude: positive, negative. Finding: The results of study based on a scenario indicate that the conflict management style affected on customer satisfaction by service recovery efforts as well as the pre-existing attitudes affected the customer interpretation for service providers (conflict management style) and those who have positive pre-existing attitudes are interested to response to the cooperative approach in dealing with service failure. Research limitation/ implication: According to all researches, the study has several limitations. The nature of scenario in this study may cause to hit the reality of life. Although, the similar scenario approaches commonly are used for such researches, but the approaches are not without criticism. Practical implications: Given the importance of service recovery, companies can understand the importance of creating customer satisfaction achieved by the positive results due to the service recovery during the shortness or service failure by the mentioned companies. Originality/ value: The study highlights the importance of service failure and providing the education in relation to the service recovery.

Keywords: service recovery, pre-existing attitude, service failure, customer satisfaction

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Authors: Menouni Aziza, Chbihi Kaoutar, El Jaafari Samir

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There is strong evidence connecting epidemics with the disruption of the human-animal-environment interaction. Despite the fact that several cases of emerging and endemic zoonotic diseases indifferent parts of Africa have been documented, there is limited data regarding which specific interventions are effective in preventing and managing the associated risks using a One Health approach. The aim of this study is to better understand perceptions and ongoing research related to interventions in Africa through the implementation of suitable projects and policies. A bibliometric review of the scientific literature on one health studies with a focus on African countries was conducted, followed by a qualitative survey among stakeholders involved in fields related to One Health research or management in the Africa, including veterinary experts, public health professionals, environmentalists and policy makers, to learn about determinants of their perceptions, as well as barriers to and promoters of successful interventions and governance. The project was concluded with an international workshop in March 2023, where a broad range of topics relevant to One Health were discussed. 94% of the respondents were aware of the importance of the One Health approach and strongly endorse it within their respective countries. The top reported barriers to One Health development in Africa included paucity of data, weak linkages and institutional communication between the different departments and the lack of funding. Key areas of improvement identified were the impact evaluation of current initiatives, awareness raising campaigns among citizens targeted at behavioral changes, capacity building of relevant professionals and stakeholders, as well as the implementation of adequate policies and enforcement of national and continental regulations, allowing for better coordination on the African level. All One Health sectors in Africa require strong governance and leadership, as well as inter-ministerial, inter-sectoral, and interdisciplinary cooperation.

Keywords: one health, perceptions, governance, Africa

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Authors: Lakhoua Najeh

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Aims of the work: The aim of this paper is to improve the reliability and the availability of a Packer production line of cigarettes based on two methods: The SADT method (Structured Analysis Design Technique) and the FMECA approach (Failure Mode Effects and Critically Analysis). The first method enables us to describe the functionality of the Packer production line of cigarettes and the second method enables us to establish an FMECA analysis. Methods: The methodology adopted in order to contribute to the improvement of the reliability and the availability of a Packer production line of cigarettes has been proposed in this paper, and it is based on the use of Structured Analysis Design Technique (SADT) and Failure mode, effects, and criticality analysis (FMECA) methods. This methodology consists of using a diagnosis of the existing of all of the equipment of a production line of a factory in order to determine the most critical machine. In fact, we use, on the one hand, a functional analysis based on the SADT method of the production line and on the other hand, a diagnosis and classification of mechanical and electrical failures of the line production by their criticality analysis based on the FMECA approach. Results: Based on the methodology adopted in this paper, the results are the creation and the launch of a preventive maintenance plan. They contain the different elements of a Packer production line of cigarettes; the list of the intervention preventive activities and their period of realization. Conclusion: The diagnosis of the existing state helped us to found that the machine of cigarettes used in the Packer production line of cigarettes is the most critical machine in the factory. Then this enables us in the one hand, to describe the functionality of the production line of cigarettes by SADT method and on the other hand, to study the FMECA machine in order to improve the availability and the performance of this machine.

Keywords: production system, diagnosis, SADT method, FMECA method

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Authors: Anil Kumar Baral

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The research introduces a ground-breaking approach to waste management, emphasizing innovation, education, and transformation. Using Chandragiri Municipality as a case study, the study advocates a shift from traditional to progressive waste management strategies, contributing an inventive waste framework, sustainability advocacy, and a transformative blueprint. The waste composition analysis highlights Chandragiri's representative profile, leading to a comprehensive plan addressing challenges and recommending a transition to a profitable waste treatment model, supported by relevant statistics. The data-driven approach incorporates the official data of waste Composition from Chandragiri Municipality as secondary data and incorporates the primary data from Chandragiri households, ensuring a nuanced perspective. Discussions on implementation, viability, and environmental preservation underscore the dual benefit of sustainability. The study includes a comparative analysis, monitoring, and evaluation framework, examining international relevance and collaboration, and conducting a social and environmental impact assessment. The results indicate the necessity for creative changes in Chandragiri's waste practices, recommending separate treatment centers in wards level rather than Municipal level, composting machines, and a centralized waste treatment plant. Educational reforms involve revising school curricula and awareness campaigns. The transformation's success hinges on reducing waste size, efficient treatment center operation, and ongoing public literacy. The conclusion summarizes key findings, envisioning a future with sustainable waste management practices deeply embedded in the community fabric.

Keywords: innovate, educate, transform, municipality, method

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Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

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Authors: Ching Shya Lee, Mohamed Kheireddine Aroua, Wan Mohd Ashri Wan Daud, Patrick Cognet, Yolande Peres, Mohammed Ajeel

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In recent years, with the decreasing supply of fossil fuel, renewable energy has received a significant demand. Biodiesel which is well known as vegetable oil based fatty acid methyl ester is an alternative fuel for diesel. It can be produced from transesterification of vegetable oils, such as palm oil, sunflower oil, rapeseed oil, etc., with methanol. During the transesterification process, crude glycerol is formed as a by-product, resulting in 10% wt of the total biodiesel production. To date, due to the fast growing of biodiesel production in worldwide, the crude glycerol supply has also increased rapidly and resulted in a significant price drop for glycerol. Therefore, extensive research has been developed to use glycerol as feedstock to produce various added-value chemicals, such as tartronic acid, mesoxalic acid, glycolic acid, glyceric acid, propanediol, acrolein etc. The industrial processes that usually involved are selective oxidation, biofermentation, esterification, and hydrolysis. However, the conversion of glycerol into added-value compounds by electrochemical approach is rarely discussed. Currently, the approach is mainly focused on the electro-oxidation study of glycerol under potentiostatic mode for cogenerating energy with other chemicals. The electro-organic synthesis study from glycerol under galvanostatic mode is seldom reviewed. In this study, the glycerol was converted into various added-value compounds by electrochemical method under galvanostatic mode. This work aimed to study the possible compounds produced from glycerol by electrochemical technique in a one-pot electrolysis cell. The electro-organic synthesis study from glycerol was carried out in a single compartment reactor for 8 hours, over the platinum cathode and anode electrodes under acidic condition. Various parameters such as electric current (1.0 A to 3.0 A) and reaction temperature (27 °C to 80 °C) were evaluated. The products obtained were characterized by using gas chromatography-mass spectroscopy equipped with an aqueous-stable polyethylene glycol stationary phase column. Under the optimized reaction condition, the glycerol conversion achieved as high as 95%. The glycerol was successfully converted into various added-value chemicals such as ethylene glycol, glycolic acid, glyceric acid, acetaldehyde, formic acid, and glyceraldehyde; given the yield of 1%, 45%, 27%, 4%, 0.7% and 5%, respectively. Based on the products obtained from this study, the reaction mechanism of this process is proposed. In conclusion, this study has successfully converted glycerol into a wide variety of added-value compounds. These chemicals are found to have high market value; they can be used in the pharmaceutical, food and cosmetic industries. This study effectively opens a new approach for the electrochemical conversion of glycerol. For further enhancement on the product selectivity, electrode material is an important parameter to be considered.

Keywords: biodiesel, glycerol, electrochemical conversion, galvanostatic mode

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Authors: A. V. Varfolomeeva, N. S. Tkachenko, A. G. Tishchenko

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The problem of violation of internal validity in studies of psychological structures is considered. The role of epistemological attitudes of researchers in the planning of research within the methodology of the system-evolutionary approach is assessed. Alternative programs of psychological research involving representatives of different biological species are presented. On the example of the results of two research series the variants of solving the problem are discussed.

Keywords: epistemological attitudes, experimental design, validity, psychological structure, learning

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Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Maciej Zaręba, Sławomir Lasota

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The monitoring of manufacturing processes is an important issue in nowadays ERP systems. The identification and analysis of appropriate data for the units that take part in the production process are ones of the most crucial problems. In this paper, the authors introduce a new approach towards modelling the relation between production units, signals, and factors possible to obtain from the production system. The main idea for the system is based on the ontology of production units.

Keywords: manufacturing operation management, OWL, ontology implementation, ontology modeling

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Authors: Veronika Efremova

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In recent decades, there have been significant developments in the European Union in the field of collective consumer redress. South East European countries (SEE) covered by this paper, in line with their EU accession priorities and duties under Stabilisation and Association Agreements, have to harmonize their national laws with the relevant EU acquis for consumer protection (Chapter 28: Health and Consumer). In these countries, only minimal compliance is achieved. SEE countries have introduced rudimentary collective redress mechanisms, with modest enforcement of collective redress and case law. This paper is based on comprehensive interdisciplinary research conducted for SEE countries on common principles for injunctive and compensatory collective redress mechanisms, emphasizing cross-national comparisons, underlining issues of commonality and difference aiming to develop recommendations for an adequate enforcement of collective redress. SEE countries are recognized by the sectoral approach for regulating collective redress contrary to the majority of EU Member States with having adopted horizontal approach to collective redress. In most SEE countries, the laws do not recognize compensatory but only injunctive collective redress in consumer protection. All responsible stakeholders for implementation of collective redress in SEE countries, lack information and awareness on collective redress mechanisms and the way they function in practice. Therefore, specific actions are needed in these countries to make the whole system of collective redress for consumer protection operational and efficient. Taking into consideration the various designated stakeholders in collective redress in each SEE countries, there is a need of their mutual coordination and cooperation in order to develop consumer protection system and policies. By putting into practice the national collective redress mechanisms, effective access to justice for all consumers, the principle of rule of law will be secured and appropriate procedural guarantees to avoid abusive litigation will be ensured.

Keywords: collective redress mechanism, consumer protection, commonality and difference, South East Europe

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Authors: Tan Lay Cheng (Cheryl), Low Huiqi

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Background: All children learn at different pace. Individualized learning is an approach that tailors to the individual learning needs of each child. When implementing this approach, educators have to base their lessons on the understanding that all students learn differently and that what works for one student may not work for another. In the current early childhood environment, individualized learning is for children with diverse needs. However, a typical developing child is also able to benefit from individualized learning. This research abstract explores the concept of utilizing DNA-MILE, a patented (in Singapore) DNA-based assessment tool that can be used to measure a variety of factors that can impact learning. The assessment report includes the dominant intelligence of the user or, in this case, the child. From the result, a personalized learning plan that is tailored to each individual student's needs. Methods: A study will be conducted to investigate the effectiveness of DNA-MILE in supporting individualized learning. The study will involve a group of 20 preschoolers who were randomly assigned to either a DNA-MILE-assessed group (experimental group) or a control group. 10 children in each group. The experimental group will receive DNA Mile assessments and personalized learning plans, while the control group will not. The children in the experimental group will be taught using the dominant intelligence (as shown in the DNA-MILE report) to enhance their learning in other domains. The children in the control group will be taught using the curriculum and lesson plan set by their teacher for the whole class. Parents’ and teachers’ interviews will be conducted to provide information about the children before the study and after the study. Results: The results of the study will show the difference in the outcome of the learning, which received DNA Mile assessments and personalized learning plans, significantly outperformed the control group on a variety of measures, including standardized tests, grades, and motivation. Conclusion: The results of this study suggest that DNA Mile can be an effective tool for supporting individualized learning. By providing personalized learning plans, DNA Mile can help to improve learning outcomes for all students.

Keywords: individualized, DNA-MILE, learning, preschool, DNA, multiple intelligence

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Authors: Tereza Dolečková

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Following article provides the comparison of international norms and standards formulating personal expenses, and then it illustrates the national concept of personal expenses of the Ministry of Defence. Then a new salary system of soldiers and the importance of the service appraisal in the context of personal expenses of the Ministry of Defence are explained. The first part of the article includes formulation of the approach to the definition of personal expenses within the international norms and standards and also within the Ministry of Defence of the Czech Republic. The structure of employees of the Ministry of Defence of the Czech Republic in years 2012 – 2014 and the amount of military expenses and the share of salary expenses of the Ministry of total expenses of the Ministry are clarified there, also the comparison of the amount of military expenses in chosen member states of the North Atlantic Treaty Organization is done. The salary system of professional soldiers in connection with the amendment of the Act No. 221/1999 Coll. on Professional Soldiers is clarified in the second part of this article. The amendment significantly regulates the salary items of soldiers but changes are also in the service appraisal of soldiers which reflects one of seven salary items of soldiers – the performance bonus. The aim of this article is to clarify different approach to define personal expenses with emphasis on the Ministry of Defence of the Czech Republic which overlaps to the service appraisal of soldiers of the Army of the Czech Republic and their salary system in connection with personal expenses of the Ministry of Defence of the Czech Republic. The efficient and objective system of the service appraisal and the use of its results are connected to the principles of the career advancement; only the best soldiers can advance in the system of the service careers to higher positions. That is why it is necessary to improve the service appraisal so it would provide the maximum information about the performance of a soldier and it would also motivate the soldier in his development. The attention should be paid to the service appraisal of the soldiers of the Army of the Czech Republic to achieve as much objectivity as possible.

Keywords: career, human resource management and development, personal expenses, salary system of soldiers, service appraisal of soldiers, the Army of the Czech Republic

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Authors: Acha Mildred Endam

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Gentrification brings changes in socio-economic and environmental aspects in cities. This is a concern for local governments and urban residents, as rapid urbanization poses a challenge to SDGs 11 and 13. This paper aims to: (1) examine the dominant gentrification actions that counteract the drive towards green urbanism; (2) evaluate policy actions and institutions created to promote green urbanism; (3) explore the constraints that hinder development proponents from achieving the goal of green urbanism. A mixed research design (survey and exploratory) was used, along with snowball sampling techniques, to administer the questionnaire. Structured interviews and focus group discussions were also conducted to assess the efforts and success rate of planning and development proponents in achieving green urbanism. Secondary data provided the basis for a literature review on activities that promote brown cities, which hinder green urbanism. The results of the study revealed that gentrification in Bamenda is mainly focused on upgrading infrastructure within the city centre. This transition is accompanied by unsustainable architectural developments, sprawl into peri-urban ecosystems, and climate-incompatible developments. Efforts to achieve green urbanization in Bamenda are insignificant. Socio-economic and policy actions of residents do not reflect a move towards sustainable cities, which is a common theme in most development agendas. This undermines the ecology, health, and general well-being of its inhabitants, increasing vulnerability. The study suggests that there is a need to learn from the few green cities in Africa and adopt a holistic approach towards green urbanization. This approach should include green transportation, preservation of green spaces, and retrofitting brown buildings to green buildings, through synergies, motivation and subsidization through green governance.

Keywords: environmental sustainability, green urbanism, green governace, retrofitting

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Authors: Himanshu Singh, Rishi Kant, Shantanu Bhattacharya

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This paper adopts a top-down approach for mathematical modeling to predict the size reduction from micro to nano-scale through persistent etching. The process is simulated using a finite difference approach. Previously, various researchers have simulated the etching process for 1-D and 2-D substrates. It consists of two processes: 1) Convection-Diffusion in the etchant domain; 2) Chemical reaction at the surface of the particle. Since the process requires analysis along moving boundary, partial differential equations involved cannot be solved using conventional methods. In 1-D, this problem is very similar to Stefan's problem of moving ice-water boundary. A fixed grid method using finite volume method is very popular for modelling of etching on a one and two dimensional substrate. Other popular approaches include moving grid method and level set method. In this method, finite difference method was used to discretize the spherical diffusion equation. Due to symmetrical distribution of etchant, the angular terms in the equation can be neglected. Concentration is assumed to be constant at the outer boundary. At the particle boundary, the concentration of the etchant is assumed to be zero since the rate of reaction is much faster than rate of diffusion. The rate of reaction is proportional to the velocity of the moving boundary of the particle. Modelling of the above reaction was carried out using Matlab. The initial particle size was taken to be 50 microns. The density, molecular weight and diffusion coefficient of the substrate were taken as 2.1 gm/cm3, 60 and 10-5 cm2/s respectively. The etch-rate was found to decline initially and it gradually became constant at 0.02µ/s (1.2µ/min). The concentration profile was plotted along with space at different time intervals. Initially, a sudden drop is observed at the particle boundary due to high-etch rate. This change becomes more gradual with time due to declination of etch rate.

Keywords: particle size reduction, micromixer, FDM modelling, wet etching

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Authors: El Asnaoui Khalid, Aksasse Brahim, Ouanan Mohammed

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This paper presents an unsupervised color image segmentation method. It is based on a hierarchical analysis of 2-D histogram in RGB color space. This histogram minimizes storage space of images and thus facilitates the operations between them. The improved segmentation approach shows a better identification of objects in a color image and, at the same time, the system is fast.

Keywords: image segmentation, hierarchical analysis, 2-D histogram, classification

Procedia PDF Downloads 363

Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Omran M. Kenshel, Alan J. O'Connor

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Estimating the service life of Reinforced Concrete (RC) bridge structures located in corrosive marine environments of a great importance to their owners/engineers. Traditionally, bridge owners/engineers relied more on subjective engineering judgment, e.g. visual inspection, in their estimation approach. However, because financial resources are often limited, rational calculation methods of estimation are needed to aid in making reliable and more accurate predictions for the service life of RC structures. This is in order to direct funds to bridges found to be the most critical. Criticality of the structure can be considered either form the Structural Capacity (i.e. Ultimate Limit State) or from Serviceability viewpoint whichever is adopted. This paper considers the service life of the structure only from the Structural Capacity viewpoint. Considering the great variability associated with the parameters involved in the estimation process, the probabilistic approach is most suited. The probabilistic modelling adopted here used Monte Carlo simulation technique to estimate the Reliability (i.e. Probability of Failure) of the structure under consideration. In this paper the authors used their own experimental data for the Correlation Length (CL) for the most important deterioration parameters. The CL is a parameter of the Correlation Function (CF) by which the spatial fluctuation of a certain deterioration parameter is described. The CL data used here were produced by analyzing 45 chloride profiles obtained from a 30 years old RC bridge located in a marine environment. The service life of the structure were predicted in terms of the load carrying capacity of an RC bridge beam girder. The analysis showed that the influence of SV is only evident if the reliability of the structure is governed by the Flexure failure rather than by the Shear failure.

Keywords: Chloride-induced corrosion, Monte-Carlo simulation, reinforced concrete, spatial variability

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Authors: Said Ghalem

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Honey is primarily composed of sugars: glucose and fructose. Depending honey, it's either fructose or glucose predominates. More the fructose concentration and the less the glycemic index (GI) is high. Thus, changes in the insulin response shows a decrease of the amount of insulin secreted at an increased fructose honey. Honey is also a compound that can reduce the lipid in the blood. Several studies on animals, but which remain to be checked in humans, have shown that the honey can have interesting effects when combined with other molecules: associated with Metformin (a medicine taken by diabetics), it shows the benefits and effects of diabetes preserves the tissue; associated ginger, it increases the antioxidant activity and thus avoids neurologic complications, neuropathic. Molecular modeling techniques are widely used in chemistry, biology, and the pharmaceutical industry. Most of the currently existing drugs target enzymes. Inhibition of DPP-4 is an important approach in the treatment of type 2 diabetes. We have chosen for the inhibition of DPP-4 the following molecules: Linagliptin (BI1356), Sitagliptin (Januvia), Vildagliptin, Saxagliptin, Alogliptin, and Metformin (Glucophage), that are involved in the disease management of type 2 diabetes and added to honey. For this, we used software Molecular Operating Environment. A Wistar rat study was initiated in our laboratory with a well-studied protocol; after sacrifice, according to international standards and respect for the animal This theoretical approach predicts the mode of interaction of a ligand with its target. The honey can have interesting effects when combined with other molecules, it shows the benefits and effects of honey preserves the tissue, it increases the antioxidant activity, and thus avoids neurologic complications, neuropathic or macrovascular. The organs, especially the kidneys of Wistar, shows that the parameters to renal function let us conclude that damages caused by diabetes are slightly perceptible than those observed without the addition of a high concentration of fructose honey.

Keywords: honey, molecular modeling, DPP4 enzyme, metformin

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Authors: Xianlu Zeng

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China has undergone rapid economic growth over the last three decades. During this time, China-focused study has become one of the most popular areas of research. However, even though China has one of the oldest legal traditions in the world, there is limited research available regarding the development and operation of China’s juvenile justice system. This article will provide general information about China’s juvenile justice tradition along with a review of its reformation in 2013. A discussion is presented that provides some thoughts about how successful these reforms have been and where China may need to head.

Keywords: China, history, juvenile justice, legal traditions

Procedia PDF Downloads 481