Search results for: Uputaua therapeutic approach

Authors: Fatemeh Yazdandoust

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Sustainability is a growing concern in architecture and urban planning due to the environmental impact of the built environment. Ecological challenges persist despite the proliferation of sustainable design strategies, prompting a critical reevaluation of existing approaches. This study examines sustainable design practices, focusing on the origins and processes of production, environmental impact, and socioeconomic dimensions. It also discusses ‘cleantech’ initiatives, which often prioritize profitability over ecological stewardship. The study advocates for a paradigm shift in urban design towards greater adaptability, complexity, and inclusivity, embracing porosity, incompleteness, and seed planning. This holistic approach emphasizes citizen participation and bottom-up interventions, reimagining urban spaces as evolving ecosystems. The study calls for a reimagining of sustainability that transcends conventional green design concepts, promoting a more resilient and inclusive built environment through an open system approach grounded in adaptability, diversity, and equity principles.

Keywords: sustainability, clean-tech, open system design, sustainable design

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Authors: Eddy K. Mukadi

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The aim of this study was to provide contributing elements to improve the management of the asthma crisis in the intensive care unit of the General Reference Hospital of Kinshasa. This was a descriptive study of all patients in the intensive care unit presenting with the asthma attack during the period from February 5, 2013 to February 5, 2014. The main data were obtained from consultation registry and medical records. A total of 35 patients, 21 of whom were male (majority) compared to 14 female. Average age of patients was 46.48 plus or minus 16.98 with extremes ranging from 21-75 years. The clinic was dominated by dyspnea in 100% of cases, followed by rales with 91.4% of cases. In spite of the control of the crisis obtained after the treatment with B2 mimetic by inhalation was introduced A 91.5%; 88% corticosteroids; 80% oxygen, the therapeutic principle recommended for the management of asthma attacks was not respected in the majority of cases. This is why we suggest that improving the quality of care to be administered to patients will yield more adequate results.

Keywords: asthma crisis, intensive care, general hospital, Kinshasa

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Authors: Mesnan Silalahi, Dana Indra Sensuse, Indra Budi

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Many research have revealed the fact of the complexity of ontology building process that there is a need to have a new approach which addresses the socio-technical aspects in the collaboration to reach a consensus. Meta-design approach is considered applicable as a method in the methodological model in a socio-technical ontology engineering. Principles in the meta-design framework is applied in the construction phases on the ontology. A portal is developed to support the meta-design principles requirements. To validate the methodological model semantic web applications were developed and integrated in the portal and also used as a way to show the usefulness of the ontology. The knowledge based system will be filled with data of Indonesian medicinal plants. By showing the usefulness of the developed ontology in a web semantic application, we motivate all stakeholders to participate in the development of knowledge based system of medicinal plants in Indonesia.

Keywords: socio-technical, metadesign, ontology engineering methodology, semantic web application

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Authors: Geetha Baskaran, Andrzej Barjiela, Rong Qu

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Motivation: Nurse scheduling is a complex combinatorial optimization problem. It is also known as NP-hard. It needs an efficient re-scheduling to minimize some trade-off of the measures of violation by reducing selected constraints to soft constraints with measurements of their violations. Problem Statement: In this paper, we extend our novel approach to solve the nurse scheduling problem by transforming it through Information Granulation. Approach: This approach satisfies the rules of a typical hospital environment based on a standard benchmark problem. Generating good work schedules has a great influence on nurses' working conditions which are strongly related to the level of a quality health care. Domain transformation that combines the strengths of operation research and artificial intelligence was proposed for the solution of the problem. Compared to conventional methods, our approach involves judicious grouping (information granulation) of shifts types’ that transforms the original problem into a smaller solution domain. Later these schedules from the smaller problem domain are converted back into the original problem domain by taking into account the constraints that could not be represented in the smaller domain. An Integer Programming (IP) package is used to solve the transformed scheduling problem by expending the branch and bound algorithm. We have used the GNU Octave for Windows to solve this problem. Results: The scheduling problem has been solved in the proposed formalism resulting in a high quality schedule. Conclusion: Domain transformation represents departure from a conventional one-shift-at-a-time scheduling approach. It offers an advantage of efficient and easily understandable solutions as well as offering deterministic reproducibility of the results. We note, however, that it does not guarantee the global optimum.

Keywords: domain transformation, nurse scheduling, information granulation, artificial intelligence, simulation

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Authors: N. N. Mosola, K. F. Moeketsi, R. Sehobai, N. Pule

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The Internet brings increasing use of Information and Communications Technology (ICT) services and facilities. Consequently, new computing paradigms emerge to provide services over the Internet. Although there are several benefits stemming from these services, they pose several risks inherited from the Internet. For example, cybercrime, identity theft, malware etc. To thwart these risks, this paper proposes a holistic approach. This approach involves multidisciplinary interactions. The paper proposes a top-down and bottom-up approach to deal with cyber security concerns in developing countries. These concerns range from regulatory and legislative areas, cyber awareness, research and development, technical dimensions etc. The main focus areas are highlighted and a cybersecurity model solution is proposed. The paper concludes by combining all relevant solutions into a proposed cybersecurity model to assist developing countries in enhancing a cyber-safe environment to instill and promote a culture of cybersecurity.

Keywords: cybercrime, cybersecurity, computer emergency response team, computer security incident response team

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Authors: Sharat Chandra, Zilong Wang, Ru-Rong Ji, Andrey Bortsov

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Chronic pain (CP) therapeutic approaches have limited efficacy. As a result, doctors are prescribing opioids for chronic pain, leading to opioid overuse, abuse, and addiction epidemic. Therefore, the development of effective and safe CP drugs remains an unmet medical need. Voltage-gated sodium (Nav) channels act as cardiovascular and neurological disorder’s molecular targets. Nav channels selective inhibitors are hard to design because there are nine closely-related isoforms (Nav1.1-1.9) that share the protein sequence segments. We are targeting the Nav1.7 found in the peripheral nervous system and engaged in the perception of pain. The objective of this project was to screen a 1.5 million compound library for identification of inhibitors for Nav1.7 with analgesic effect. In this study, we designed a protocol for identification of isoform-selective inhibitors of Nav1.7, by utilizing the prior information on isoform-selective antagonists. First, a similarity search was performed; then the identified hits were docked into a binding site on the fourth voltage-sensor domain (VSD4) of Nav1.7. We used the FTrees tool for similarity searching and library generation; the generated library was docked in the VSD4 domain binding site using FlexX and compounds were shortlisted using a FlexX score and SeeSAR hyde scoring. Finally, the top 25 compounds were tested with molecular dynamics simulation (MDS). We reduced our list to 9 compounds based on the MDS root mean square deviation plot and obtained them from a vendor for in vitro and in vivo validation. Whole-cell patch-clamp recordings in HEK-293 cells and dorsal root ganglion neurons were conducted. We used patch pipettes to record transient Na⁺ currents. One of the compounds reduced the peak sodium currents in Nav1.7-HEK-293 stable cell line in a dose-dependent manner, with IC50 values at 0.74 µM. In summary, our computer-aided analgesic discovery approach allowed us to develop pre-clinical analgesic candidate with significant reduction of time and cost.

Keywords: chronic pain, voltage-gated sodium channel, isoform-selective antagonist, similarity search, virtual screening, analgesics development

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Authors: Maryam Nimehforush, Hamid Vahidkia

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The International Court of Justice, as well as international law in general, may not excel in methodology. In contrast to how it interprets treaties, the Court rarely explains how it determines the existence, content, and scope of customary international law rules it uses. The Court's jurisprudence only mentions the inductive and deductive methods of law determination sporadically. Both the Court and legal literature have not extensively discussed their approach to determining customary international law. Surprisingly, the question of the Court's methodology has not garnered much attention despite the fact that interpreting and shaping the law have always been intertwined. This article seeks to redirect focus to the method used by the Court in deciding the customs of international law it enforces, emphasizing the importance of methodology in the evolution of customary international law. The text begins by giving explanations for the concepts of ‘induction’ and ‘deduction’ and explores how the Court utilizes them. It later examines when the Court employs inductive and deductive reasoning, the varied types and purposes of deduction, and the connection between the two approaches. The text questions the different concepts of inductive and deductive tradition and proves that the primary approach utilized by the Court is not induction or deduction but instead, assertion.

Keywords: ICJ, law, international, induction, deduction, assertion

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Authors: Deepak Kumar Mittal, Alok Kumar Jena, Deepmala Joshi

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The present study was carried out to observe the hepatoprotective effect and antioxidant activity of the aqueous extract of the roots of Polygonum bistorta (PB) (200 mg/kg) and Zingiber roseum (ZR) (250 mg/kg) in rats treated with carbon tetrachloride (0.15 ml/kg, i.p.). Extract of PB and ZR at the tested doses restored the levels of liver homogenate enzymes, glutathione peroxidase, glutathione-S-transferase, superoxide dismutase and catalase enzymes, significantly. The activities of MTT assay significantly recovered the damage and supported the biochemical observations. This study suggests that Zingiber roseum has a higher protective effect on liver, compared to Polygonum bistorta, against carbon tetrachloride-induced hepatotoxicity and possesses antioxidant activities. Also, extracts exhibited moderate anticancer activity towards cell viability at higher concentration.

Keywords: Polygonum bistorta, Zingiber roseum, hepatoprotective effect, carbon tetrachloride, anti-cancerous

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Authors: Chin-Chen Chang, I-Ta Lee, Tsung-Ta Ke, Wen-Kai Tai

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Common methods for resizing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image resizing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

Keywords: energy map, visual saliency, gradient map, seam carving

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Mohamed Fadzlee Sulaiman, Mohd Zabri Adil Talib, Aswami Fadillah Mohd Ariffin

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Each individual organization has their own mechanism to build up cyber defense capability in protecting their information infrastructures from data breaches and cyber espionage. But, we can not deny the possibility of failing to detect and stop cyber attacks especially for those targeting credential information and intellectual property (IP). In this paper, we would like to share the modern approach of effective digital forensic methodology in order to identify the artifacts in tracing the trails of evidence while mitigating the infection from the target machine/s. This proposed approach will suit the digital forensic investigation to be conducted while resuming the business critical operation after mitigating the infection and minimizing the risk from the identified attack to transpire. Therefore, traditional digital forensics methodology has to be improvised to be proactive which not only focusing to discover the root caused and the threat actor but to develop the relevant mitigation plan in order to prevent from the same attack.

Keywords: digital forensic, detection, eradication, targeted attack, malware

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Authors: C. E. Sutton, A. Varvani-Farahani

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Fatigue damage and life prediction of particle metal matrix composites (PMMCs) under uniaxial and multiaxial loading conditions were investigated. Three PMM composite materials of Al6061/Al2O3/20p-T6, Al6061/Al2O3/22p-T6 and Al6061/SiC/17w-T6 tested under tensile, torsion, and combined tension-torsion fatigue cycling were evaluated with various fatigue damage models. The fatigue damage models of Smith-Watson-Topper (S. W. T.), Ellyin, Brown-Miller, Fatemi-Socie, and Varvani were compared for their capability to assess the fatigue damage of materials undergoing various loading conditions. Fatigue life predication results were then evaluated by implementing material-dependent coefficients that factored in the effects of the particle reinforcement in the earlier developed Varvani model. The critical plane-energy approach incorporated the critical plane as the plane of crack initiation and early stage of crack growth. The strain energy density was calculated on the critical plane incorporating stress and strain components acting on the plane. This approach successfully evaluated fatigue damage values versus fatigue lives within a narrower band for both uniaxial and multiaxial loading conditions as compared with other damage approaches studied in this paper.

Keywords: fatigue damage, life prediction, critical plane approach, energy approach, PMM composites

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Authors: Ahmad Sanusi Azmi, Amiruddin Mohd Sobali, Zulhilmi Mohamed Nor, Mohd Yusuf Ismail, Amran Abdul Halim

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The non-Muslim communities’ reactions to the denials of the prophethood of Muḥammad in the ninth century created an impact on the development of Islamic prophetology. Vigorous refutations from non-Muslim community, specifically the Jews, Christians and Brahmins urged Muslims to develop a solid mechanism in defense of the status of their beloved prophet. One of the works that has been recognized as an apparatus to defend the Prophet Muḥammad veracity is al-Dīn wa al-Dawla composed by Ibn Rabban, a physician of the Caliph’s court. This study analyses the novelty of his approaches in exploring Sīra Nabawiyya and defending the prophethood of Muḥammad. The study employed a descriptive, comparative and critical approach where it analyses and extracts the author original approach in explaining the legitimacy of Muḥammad’s prophethood and enlightening the Prophet’s biography. The study in its finding argues that most of Ibn Rabban arguments in this work are actually developed from the foundations of Biblical scripture. His style of interpreting Biblical passages indicates a possible dependence on Ibn al-Layth’s letter. However, the way in which he presents Qur’ānic references seems not to be in accordance with Ibn al-Layth’s perspective. This is where the novelty of his approach is distinguished. As a result, the study also affirms that Ibn Rabban imposes his own standards of selection and interpretation of Qur’ānic verses when he applies it as reference to the Prophet life.

Keywords: Sīra Nabawiyya, Ibn Rabban, al-Dīn wa al-Dawla, Christian, Dalāil Nubuwwa

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Authors: Tong-Chien Wu, Ching-Liang Hsieh, Yi-Wen Lin

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There are accumulating evidences surrounding the therapeutic effect of electroacupuncture (EA). Local EA can reliably attenuate inflammatory pain in mouse with unclear mechanisms. However, the effect of EA on distal and contralateral acupoint for pain control has been rarely studied and the result was controversial. Here in our study, we found that inflammatory hindpaw pain in mouth, which was induced by injecting the complete Freund’s adjuvant (CFA) 2 days ago can be alleviated immediately after 2Hz 15mins EA treatment at contralateral forefoot acupoint LI4 through both mechanic and thermal behavior test, while sham acupoint group is not. The efficacy was observed to be more obvious after the second round of EA treatment on the following day. This analgesic effect is produced by applying EA to a site remote from the painful area. The present study provides a powerful experimental animal model that can be used for investigating the unique physiological mechanisms involved in acupuncture analgesia.

Keywords: remote electroacupuncture, distal EA, pain control, anti-inflammation

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Diabetic nephropathy (DN) is a major complication of diabetes, with fibrosis and propionate metabolism playing critical roles in its progression. Identifying biomarkers linked to these pathways may provide novel insights into DN diagnosis and treatment. This study aims to identify biomarkers associated with fibrosis and propionate metabolism in DN. Analyze the biological pathways and regulatory mechanisms of these biomarkers. Develop a machine learning model to predict DN-related biomarkers and validate their functional roles. Publicly available transcriptome datasets related to DN (GSE96804 and GSE104948) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/gds), and 924 propionate metabolism-related genes (PMRGs) and 656 fibrosis-related genes (FRGs) were identified. The analysis began with the extraction of DN-differentially expressed genes (DN-DEGs) and propionate metabolism-related DEGs (PM-DEGs), followed by the intersection of these with fibrosis-related genes to identify key intersected genes. Instead of relying on traditional models, we employed a combination of deep neural networks (DNNs) and ensemble methods such as Gradient Boosting Machines (GBM) and XGBoost to enhance feature selection and biomarker discovery. Recursive feature elimination (RFE) was coupled with these advanced algorithms to refine the selection of the most critical biomarkers. Functional validation was conducted using convolutional neural networks (CNN) for gene set enrichment and immunoinfiltration analysis, revealing seven significant biomarkers—SLC37A4, ACOX2, GPD1, ACE2, SLC9A3, AGT, and PLG. These biomarkers are involved in critical biological processes such as fatty acid metabolism and glomerular development, providing a mechanistic link to DN progression. Furthermore, a TF–miRNA–mRNA regulatory network was constructed using natural language processing models to identify 8 transcription factors and 60 miRNAs that regulate these biomarkers, while a drug–gene interaction network revealed potential therapeutic targets such as UROKINASE–PLG and ATENOLOL–AGT. This integrative approach, leveraging deep learning and ensemble models, not only enhances the accuracy of biomarker discovery but also offers new perspectives on DN diagnosis and treatment, specifically targeting fibrosis and propionate metabolism pathways.

Keywords: diabetic nephropathy, deep neural networks, gradient boosting machines (GBM), XGBoost

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Authors: Nidhi Gadura

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To ensure student success in a non majors biology course, a flipped classroom pedagogical approach is developed and implemented. All students are assigned online lectures to listen to before they come to class. A three hour lecture is split into one hour of online component, one hour of in class lecture and one hour of worksheets done by students in the classroom. This deviation from a traditional 3 hour in class lecture has resulted in increased student interest in science as well as better understanding of difficult scientific concepts. A pre and post survey was given to measure the interest rates and grades were used to measure the success rates. While the overall grade average did not change dramatically, students reported a better appreciation of biology. Also, students overwhelmingly like the use of worksheets in class to help them understand the concepts. They liked the fact that they could listen to lectures at their own pace on line and even repeat if needed. The flipped classroom approach turned out to work really well our non science majors and the author is ready to implement this in other classrooms.

Keywords: flipped classroom, non science majors, pedagogy, technological pedagogical model

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Authors: Meitham Amereh, Mohsen Akbari, Ben Nadler

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Cancer has been recognized as one of the most challenging problems in biology and medicine. Aggressive tumors are a lethal type of cancers characterized by high genomic instability, rapid progression, invasiveness, and therapeutic resistance. Their behavior involves complicated molecular biology and consequential dynamics. Although tremendous effort has been devoted to developing therapeutic approaches, there is still a huge need for new insights into the dark aspects of tumors. As one of the key requirements in better understanding the complex behavior of tumors, mathematical modeling and continuum physics, in particular, play a pivotal role. Mathematical modeling can provide a quantitative prediction on biological processes and help interpret complicated physiological interactions in tumors microenvironment. The pathophysiology of aggressive tumors is strongly affected by the extracellular cues such as stresses produced by mechanical forces between the tumor and the host tissue. During the tumor progression, the growing mass displaces the surrounding extracellular matrix (ECM), and due to the level of tissue stiffness, stress accumulates inside the tumor. The produced stress can influence the tumor by breaking adherent junctions. During this process, the tumor stops the rapid proliferation and begins to remodel its shape to preserve the homeostatic equilibrium state. To reach this, the tumor, in turn, upregulates epithelial to mesenchymal transit-inducing transcription factors (EMT-TFs). These EMT-TFs are involved in various signaling cascades, which are often associated with tumor invasiveness and malignancy. In this work, we modeled the tumor as a growing hyperplastic mass and investigated the effects of mechanical stress from surrounding ECM on tumor invasion. The invasion is modeled as volume-preserving inelastic evolution. In this framework, principal balance laws are considered for tumor mass, linear momentum, and diffusion of nutrients. Also, mechanical interactions between the tumor and ECM is modeled using Ciarlet constitutive strain energy function, and dissipation inequality is utilized to model the volumetric growth rate. System parameters, such as rate of nutrient uptake and cell proliferation, are obtained experimentally. To validate the model, human Glioblastoma multiforme (hGBM) tumor spheroids were incorporated inside Matrigel/Alginate composite hydrogel and was injected into a microfluidic chip to mimic the tumor’s natural microenvironment. The invasion structure was analyzed by imaging the spheroid over time. Also, the expression of transcriptional factors involved in invasion was measured by immune-staining the tumor. The volumetric growth, stress distribution, and inelastic evolution of tumors were predicted by the model. Results showed that the level of invasion is in direct correlation with the level of predicted stress within the tumor. Moreover, the invasion length measured by fluorescent imaging was shown to be related to the inelastic evolution of tumors obtained by the model.

Keywords: cancer, invasion, mathematical modeling, microfluidic chip, tumor spheroids

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Emily Hickmann, Peggy Richter, Maren Kaehlig, Hannes Schlieter

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Patient engagement is a cornerstone of high-quality care and essential for patients with chronic diseases to achieve improved health outcomes. Through digital transformation, possibilities to engage patients in their personal healthcare have multiplied. However, the exploitation of this potential is still lagging. To support the transmission of patient engagement theory into practice, this paper’s objective is to give a state-of-the-art overview of patient engagement tools and methods. A systematic literature review was conducted. Overall, 56 tools and methods were extracted and synthesized according to the four attributes of patient engagement, i.e., personalization, access, commitment, and therapeutic alliance. The results are discussed in terms of their potential to be implemented in digital health solutions under consideration of the “computers are social actors” (CASA) paradigm. It is concluded that digital health can catalyze patient engagement in practice, and a broad future research agenda is formulated.

Keywords: chronic diseases, digitalization, patient-centeredness, patient empowerment, patient engagement

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Authors: Amar Aliche, Hocine Hammoum, Karima Bouzelha, Arezki Ben Abderrahmane

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Traditionally, the dimensioning of storage tanks is conducted with a deterministic approach based on partial coefficients of safety. These coefficients are applied to take into account the uncertainties related to hazards on properties of materials used and applied loads. However, the use of these safety factors in the design process does not assure an optimal and reliable solution and can sometimes lead to a lack of robustness of the structure. The reliability theory based on a probabilistic formulation of constructions safety can respond in an adapted manner. It allows constructing a modelling in which uncertain data are represented by random variables, and therefore allows a better appreciation of safety margins with confidence indicators. The work presented in this paper consists of a mecano-reliability analysis of a concrete storage tank placed on ground. The classical method of Monte Carlo simulation is used to evaluate the failure probability of concrete tank by considering the seismic acceleration as random variable.

Keywords: reliability approach, storage tanks, monte carlo simulation, seismic acceleration

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Authors: Babatunde Osabiya

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Cybersecurity has emerged as a pressing policy problem in recent years, affecting individuals, businesses, and governments worldwide. This research paper aims to critically review the literature on cybersecurity policy and apply policy theory to propose a policy approach that balances the freedom to access and use technology with the human rights risks and threats posed by cyber. Drawing on various credible sources, the paper examines the scale and seriousness of cyber threats, highlighting the growing threat posed by cybercriminals, hackers, and nation-states. The paper also identifies the key challenges facing policymakers, including the need for more significant investment in cybersecurity research and development and the importance of balancing the benefits of technological innovation with the risks to privacy, security, and human rights. To address these challenges, the paper proposes a policy approach emphasizing investing in cybersecurity research and development to maintain a technological edge over potential adversaries. This approach also highlights the need for greater collaboration between government, industry, and civil society to develop effective cybersecurity policies and practices that protect the rights and freedoms of people while mitigating the risks posed by cyber threats. This paper will contribute to the growing body of literature on cybersecurity policy and offers a policy framework for addressing this critical policy challenge.

Keywords: security risk, legal framework, cyber security and policy, national security

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Authors: Salihah Alghamdi, Surajit Ray

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Space-time data can be observed over irregularly shaped manifolds, which might have complex boundaries or interior gaps. Most of the existing methods do not consider the shape of the data, and as a result, it is difficult to model irregularly shaped data accommodating the complex domain. We used a method that can deal with space-time data that are distributed over non-planner shaped regions. The method is based on partial differential equations and finite element analysis. The model can be estimated using a penalized least squares approach with a regularization term that controls the over-fitting. The model is regularized using two roughness penalties, which consider the spatial and temporal regularities separately. The integrated square of the second derivative of the basis function is used as temporal penalty. While the spatial penalty consists of the integrated square of Laplace operator, which is integrated exclusively over the domain of interest that is determined using finite element technique. In this paper, we applied a spatio-temporal regression model with partial differential equations regularization (ST-PDE) approach to analyze a remote sensing data measuring the greenness of vegetation, measure by an index called enhanced vegetation index (EVI). The EVI data consist of measurements that take values between -1 and 1 reflecting the level of greenness of some region over a period of time. We applied (ST-PDE) approach to irregular shaped region of the EVI data. The approach efficiently accommodates the irregular shaped regions taking into account the complex boundaries rather than smoothing across the boundaries. Furthermore, the approach succeeds in capturing the temporal variation in the data.

Keywords: irregularly shaped domain, partial differential equations, finite element analysis, complex boundray

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Authors: Marcin Michalak

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Biclustering is the way of two-dimensional data analysis. For several years it became possible to express such issue in terms of Boolean reasoning, for processing continuous, discrete and binary data. The mathematical backgrounds of such approach — proved ability of induction of exact and inclusion–maximal biclusters fulfilling assumed criteria — are strong advantages of the method. Unfortunately, the core of the method has quite high computational complexity. In the paper the basics of Boolean reasoning approach for biclustering are presented. In such context the problems of computation parallelization are risen.

Keywords: Boolean reasoning, biclustering, parallelization, prime implicant

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Authors: Mara J. Richman, Zsolt Unoka, Robert Dudas, Zsolt Demetrovics

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Borderline personality disorder (BPD) is characterized by deficits in emotion regulation and effective liability. Of this domain, ruminative behaviors have been considered a core feature of emotion dysregulation difficulties. Taking this into consideration, a meta-analysis was performed to assess how BPD symptoms correlate with rumination, while also considering clinical moderator variables such as comorbidity, GAF score, and type of BPD symptom and demographic moderator variables such as age, gender, and education level. Analysis of correlation across rumination domains for the entire sample revealed a medium overall correlation. When assessing types of rumination, the largest correlation was among pain rumination followed by anger, depressive, and anxious rumination. Furthermore, affective instability had the strongest correlation with increased rumination, followed by unstable relationships, identity disturbance, and self-harm/ impulsivity, respectively. Demographic variables showed no significance. Clinical implications are considered and further therapeutic interventions are discussed in the context of rumination.

Keywords: borderline personality disorder, meta-analysis, rumination, symptoms

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Authors: Seyed Habib A. Rahmati, Mohsen Sadegh Amalnick

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Different terms of the statistical process control (SPC) has sketch in the fuzzy environment. However, measurement system analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through a new method introduces the measures in fuzzy environment. In this method, which works based on Buckley approach, imprecision and vagueness nature of the real world measurement are considered simultaneously. To do so, fuzzy version of the gauge capability (Cg and Cgk) are introduced. The method is also explained through example clearly.

Keywords: measurement, SPC, MSA, gauge capability (Cg and Cgk)

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Authors: Hajer Taktak, Faouzi Moussa

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With the ubiquitous computing’s emergence and the evolution of enterprises’ needs, one of the main challenges is to build context-aware applications based on Web services. These applications have become particularly relevant in the pervasive computing domain. In this paper, we introduce our approach that optimizes the use of Web services with context notions when dealing with contextual environments. We focus particularly on making Web services autonomous and natively context-aware. We implement and evaluate the proposed approach with a pedagogical example of a context-aware Web service treating temperature values. 

Keywords: context-aware, CXF framework, ubiquitous computing, web service

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Authors: Fabio Oettl, Sebastian Hoerbrand, Tobias Wittmeir, Johannes Schilp

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By combining the additive manufacturing (AM)- process with digital concepts, like the digital twin (DT) or the downsized and basing concept of the digital part file (DPF), the competitiveness of additive manufacturing is enhanced and new use cases like decentral production are enabled. But in literature, one can´t find any quantitative approach for valuing the usage of a DT or DPF in AM. Out of this fact, such an approach will be developed within this paper in order to further promote or dissuade the usage of these concepts. The focus is set on the production as an early lifecycle phase, which means that the AM-production process gets analyzed regarding the potential advantages of using DPF in AM. These advantages are transferred to a monetary value with this approach. By calculating the costs of the DPF, an overall monetary value is a result. Thereon a tool, based on a simulation environment is constructed, where the algorithms are transformed into a program. The results of applying this tool show that an overall value of 20,81 € for the DPF can be realized for one special use case. For the future application of the DPF there is the recommendation to integrate especially sustainable information because out of this, a higher value of the DPF can be expected.

Keywords: additive manufacturing, digital concept costs, digital part file, digital twin, monetary value estimation

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Authors: Zakir H. Shaik, Punam L. Vartak

Abstract:

Management By Objectives (MBO) is a management technique in which objectives of an organisation are conveyed to the employees to establish the individual goals. These objectives and goals are then monitored and assessed jointly by management and the employee time to time. This tool can be used for planning, monitoring as well as for performance appraisal. The success of an organisation is largely dependent on its’s Vision. Thus, it is of paramount importance to achieve the realm of vision through a mission which is well crafted within the organisation to address the objectives. The success of the mission depends upon how realistic and action oriented philosophical approach, an organisation caters to; and how the individual goals are set to track and meet the objectives. Thus, focused and passionate efforts of the team, assigned for the mission, are an absolute obligation for achieving the vision of any organisation. Any construction site is generally a controlled disorder having huge investments, resources and logistics involved. The Construction progression is time-consuming with many isolated as well as interconnected activities. Traditional MBO approach can be unsuccessful if planning and control is non-realistic and inflexible. Moreover, the Construction Industry is far behind understanding these concepts. It is important to address the employee engagement in defining and creating awareness to achieve the targets. Besides, current economic environment and competitive world demands refined management tools to achieve profit, growth and survival of the business. Therefore, the necessity of rational MBO becomes vital part towards the success of an organisation. This paper details about the philosophical assumptions to develop the grounded theory in lieu of achieving objectives through RATIONAL MBO approach in Construction Contracting Organisations. The goals and objectives of the Construction Contracting Organisations can be achieved efficiently by adopting this RATIONAL MBO approach, as those are based on realistic, logical and balanced assumptions.

Keywords: growth, leadership, management by objectives, Management By Objectives (MBO), profit, rational

Procedia PDF Downloads 153

Authors: Yuxi Wang, Xuan Gao

Abstract:

Traditional Chinese medicine has been used in the treatment of coronary heart disease (CHD) for centuries, and in recent years, the research data on the efficacy of traditional Chinese medicine through clinical trials has gradually increased to explore its real efficacy and internal pharmacology. However, due to the complexity of traditional Chinese medicine prescriptions, the efficacy of each component is difficult to clarify, and pharmacological research is challenging. This study aims to systematically review and clarify the clinical efficacy of traditional Chinese medicine in the treatment of coronary heart disease through a meta-analysis. Based on PubMed, CNKI database, Wanfang data, and other databases, eleven randomized controlled trials and 1091 CHD subjects were included. Two researchers conducted a systematic review of the papers and conducted a meta-analysis supporting the positive therapeutic effect of traditional Chinese medicine in the treatment of CHD.

Keywords: coronary heart disease, Chinese medicine, treatment, meta-analysis

Procedia PDF Downloads 123

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

Abstract:

Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 163