Search results for: twin therapeutic approach
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 15228

Search results for: twin therapeutic approach

13248 Generating 3D Battery Cathode Microstructures using Gaussian Mixture Models and Pix2Pix

Authors: Wesley Teskey, Vedran Glavas, Julian Wegener

Abstract:

Generating battery cathode microstructures is an important area of research, given the proliferation of the use of automotive batteries. Currently, finite element analysis (FEA) is often used for simulations of battery cathode microstructures before physical batteries can be manufactured and tested to verify the simulation results. Unfortunately, a key drawback of using FEA is that this method of simulation is very slow in terms of computational runtime. Generative AI offers the key advantage of speed when compared to FEA, and because of this, generative AI is capable of evaluating very large numbers of candidate microstructures. Given AI generated candidate microstructures, a subset of the promising microstructures can be selected for further validation using FEA. Leveraging the speed advantage of AI allows for a better final microstructural selection because high speed allows for the evaluation of many more candidate microstructures. For the approach presented, battery cathode 3D candidate microstructures are generated using Gaussian Mixture Models (GMMs) and pix2pix. This approach first uses GMMs to generate a population of spheres (representing the “active material” of the cathode). Once spheres have been sampled from the GMM, they are placed within a microstructure. Subsequently, the pix2pix sweeps over the 3D microstructure (iteratively) slice by slice and adds details to the microstructure to determine what portions of the microstructure will become electrolyte and what part of the microstructure will become binder. In this manner, each subsequent slice of the microstructure is evaluated using pix2pix, where the inputs into pix2pix are the previously processed layers of the microstructure. By feeding into pix2pix previously fully processed layers of the microstructure, pix2pix can be used to ensure candidate microstructures represent a realistic physical reality. More specifically, in order for the microstructure to represent a realistic physical reality, the locations of electrolyte and binder in each layer of the microstructure must reasonably match the locations of electrolyte and binder in previous layers to ensure geometric continuity. Using the above outlined approach, a 10x to 100x speed increase was possible when generating candidate microstructures using AI when compared to using a FEA only approach for this task. A key metric for evaluating microstructures was the battery specific power value that the microstructures would be able to produce. The best generative AI result obtained was a 12% increase in specific power for a candidate microstructure when compared to what a FEA only approach was capable of producing. This 12% increase in specific power was verified by FEA simulation.

Keywords: finite element analysis, gaussian mixture models, generative design, Pix2Pix, structural design

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13247 Mechanical Characterization of Porcine Skin with the Finite Element Method Based Inverse Optimization Approach

Authors: Djamel Remache, Serge Dos Santos, Michael Cliez, Michel Gratton, Patrick Chabrand, Jean-Marie Rossi, Jean-Louis Milan

Abstract:

Skin tissue is an inhomogeneous and anisotropic material. Uniaxial tensile testing is one of the primary testing techniques for the mechanical characterization of skin at large scales. In order to predict the mechanical behavior of materials, the direct or inverse analytical approaches are often used. However, in case of an inhomogeneous and anisotropic material as skin tissue, analytical approaches are not able to provide solutions. The numerical simulation is thus necessary. In this work, the uniaxial tensile test and the FEM (finite element method) based inverse method were used to identify the anisotropic mechanical properties of porcine skin tissue. The uniaxial tensile experiments were performed using Instron 8800 tensile machine®. The uniaxial tensile test was simulated with FEM, and then the inverse optimization approach (or the inverse calibration) was used for the identification of mechanical properties of the samples. Experimentally results were compared to finite element solutions. The results showed that the finite element model predictions of the mechanical behavior of the tested skin samples were well correlated with experimental results.

Keywords: mechanical skin tissue behavior, uniaxial tensile test, finite element analysis, inverse optimization approach

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13246 A Stepped Care mHealth-Based Approach for Obesity with Type 2 Diabetes in Clinical Health Psychology

Authors: Gianluca Castelnuovo, Giada Pietrabissa, Gian Mauro Manzoni, Margherita Novelli, Emanuele Maria Giusti, Roberto Cattivelli, Enrico Molinari

Abstract:

Diabesity could be defined as a new global epidemic of obesity and being overweight with many complications and chronic conditions. Such conditions include not only type 2 diabetes, but also cardiovascular diseases, hypertension, dyslipidemia, hypercholesterolemia, cancer, and various psychosocial and psychopathological disorders. The financial direct and indirect burden (considering also the clinical resources involved and the loss of productivity) is a real challenge in many Western health-care systems. Recently the Lancet journal defined diabetes as a 21st-century challenge. In order to promote patient compliance in diabesity treatment reducing costs, evidence-based interventions to improve weight-loss, maintain a healthy weight, and reduce related comorbidities combine different treatment approaches: dietetic, nutritional, physical, behavioral, psychological, and, in some situations, pharmacological and surgical. Moreover, new technologies can provide useful solutions in this multidisciplinary approach, above all in maintaining long-term compliance and adherence in order to ensure clinical efficacy. Psychological therapies with diet and exercise plans could better help patients in achieving weight loss outcomes, both inside hospitals and clinical centers and during out-patient follow-up sessions. In the management of chronic diseases clinical psychology play a key role due to the need of working on psychological conditions of patients, their families and their caregivers. mHealth approach could overcome limitations linked with the traditional, restricted and highly expensive in-patient treatment of many chronic pathologies: one of the best up-to-date application is the management of obesity with type 2 diabetes, where mHealth solutions can provide remote opportunities for enhancing weight reduction and reducing complications from clinical, organizational and economic perspectives. A stepped care mHealth-based approach is an interesting perspective in chronic care management of obesity with type 2 diabetes. One promising future direction could be treating obesity, considered as a chronic multifactorial disease, using a stepped-care approach: -mhealth or traditional based lifestyle psychoeducational and nutritional approach. -health professionals-driven multidisciplinary protocols tailored for each patient. -inpatient approach with the inclusion of drug therapies and other multidisciplinary treatments. -bariatric surgery with psychological and medical follow-up In the chronic care management of globesity mhealth solutions cannot substitute traditional approaches, but they can supplement some steps in clinical psychology and medicine both for obesity prevention and for weight loss management.

Keywords: clinical health psychology, mhealth, obesity, type 2 diabetes, stepped care, chronic care management

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13245 MiR-103 Inhibits Osteoblast Proliferation Mainly through Suppressing Cav 1.2 Expression in Simulated Microgravity

Authors: Zhongyang Sun, Shu Zhang, Manjiang Xie

Abstract:

Emerging evidence indicates that microRNAs (miRNAs) play important roles in modulating osteoblast function and bone formation. However, the influence of miRNA on osteoblast proliferation and the possible mechanisms underlying remain to be defined. In this study, we aimed to investigate whether miR-103 regulates osteoblast proliferation under simulated microgravity condition through regulating Cav1.2, the primary subunit of L-type voltage sensitive calcium channels (LTCCs). We first investigated the effect of simulated microgravity on osteoblast proliferation and the outcomes clearly demonstrated that the mechanical unloading inhibits MC3T3-E1 osteoblast-like cells proliferation. Using quantitative Real-Time PCR (qRT-PCR), we provided data showing that miR-103 was up-regulated in response to simulated microgravity. In addition, we observed that up-regulation of miR-103 inhibited and down-regulation of miR-103 promoted osteoblast proliferation under simulated microgravity condition. Furthermore, knocking-down or over-expressing miR-103, respectively, up- or down-regulated the level of Cav1.2 expression and LTCCs currents, suggesting that miR-103 acts as an endogenous attenuator of Cav1.2 in osteoblasts under the condition of simulated microgravity. More importantly, we showed that the effect of miR-103 on osteoblast proliferation was diminished in simulated microgravity, when co-transfecting miR-103 mimic or inhibitor with Cav1.2 siRNA. Taken together, our data suggest that miR-103 inhibits osteoblast proliferation mainly through suppression of Cav1.2 expression under simulated microgravity condition. This work may provide a novel mechanism of microgravity-induced detrimental effects on osteoblast, identifying miR-103 as a novel possible therapeutic target in bone remodeling disorders in this mechanical unloading.

Keywords: microRNA, osteoblasts, cell proliferation, Cav1.2, simulated microgravity

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13244 IL-21 Production by CD4+ Effector T Cells and Frequency of Circulating Follicular Helper T Cells Are Increased in Type 1 Diabetes Patients

Authors: Ferreira RC, Simons HZ, Thompson WS, Cutler AJ, Dopico XC, Smyth DJ, Mashar M, Schuilenburg H, Walker NM, Dunger DB, Wallace C, Todd JA, Wicker LS, Pekalski ML

Abstract:

Type 1 diabetes is caused by autoimmune destruction of insulin-secreting beta cells in the pancreas. T cells are known to play an important role in this immune-mediated destruction; however, there is no general consensus regarding alterations in cytokine production or T cell subsets in peripheral blood of patients with type 1 diabetes. Using polychromatic flow cytometry of peripheral blood mononuclear cells (PBMCs), we assessed production of the proinflammatory cytokines IL-21, IFN-γ and IL-17 by memory CD4 T effector (Teff) cells in 69 patients with type 1 diabetes and 61 healthy donors. We found a 21.9% (95% CI 5.8, 40.2; p = 3.9 × 10(-3)) higher frequency of IL-21(+) CD45RA(-) memory CD4(+) Teffs in patients with type 1 diabetes (geometric mean 5.92% [95% CI 5.44, 6.44]) compared with healthy donors (geometric mean 4.88% [95% CI 4.33, 5.50]). In a separate cohort of 30 patients with type 1 diabetes and 32 healthy donors, we assessed the frequency of circulating T follicular helper (Tfh) cells in whole blood. Consistent with the increased production of IL-21, we also found a 14.9% increase in circulating Tfh cells in the patients with type 1 diabetes (95% CI 2.9, 26.9; p = 0.016). Analysis of IL-21 production by PBMCs from a subset of 46 of the 62 donors immunophenotyped for Tfh showed that frequency of Tfh cells was associated with the frequency of IL-21+ cells (r2 = 0.174, p = 0.004). These results indicate that increased IL-21 production is likely to be an aetiological factor in the pathogenesis of type 1 diabetes that could be considered as a potential therapeutic target.

Keywords: T follicular helper cell, IL-21, IL-17, type 1 diabetes

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13243 Establishing a Surrogate Approach to Assess the Exposure Concentrations during Coating Process

Authors: Shan-Hong Ying, Ying-Fang Wang

Abstract:

A surrogate approach was deployed for assessing exposures of multiple chemicals at the selected working area of coating processes and applied to assess the exposure concentration of similar exposed groups using the same chemicals but different formula ratios. For the selected area, 6 to 12 portable photoionization detector (PID) were placed uniformly in its workplace to measure its total VOCs concentrations (CT-VOCs) for 6 randomly selected workshifts. Simultaneously, one sampling strain was placed beside one of these portable PIDs, and the collected air sample was analyzed for individual concentration (CVOCi) of 5 VOCs (xylene, butanone, toluene, butyl acetate, and dimethylformamide). Predictive models were established by relating the CT-VOCs to CVOCi of each individual compound via simple regression analysis. The established predictive models were employed to predict each CVOCi based on the measured CT-VOC for each the similar working area using the same portable PID. Results show that predictive models obtained from simple linear regression analyses were found with an R2 = 0.83~0.99 indicating that CT-VOCs were adequate for predicting CVOCi. In order to verify the validity of the exposure prediction model, the sampling analysis of the above chemical substances was further carried out and the correlation between the measured value (Cm) and the predicted value (Cp) was analyzed. It was found that there is a good correction between the predicted value and measured value of each measured chemical substance (R2=0.83~0.98). Therefore, the surrogate approach could be assessed the exposure concentration of similar exposed groups using the same chemicals but different formula ratios. However, it is recommended to establish the prediction model between the chemical substances belonging to each coater and the direct-reading PID, which is more representative of reality exposure situation and more accurately to estimate the long-term exposure concentration of operators.

Keywords: exposure assessment, exposure prediction model, surrogate approach, TVOC

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13242 Endothelial Progenitor Cell Biology in Ankylosing Spondylitis

Authors: Ashit Syngle, Inderjit Verma, Pawan Krishan

Abstract:

Aim: Endothelial progenitor cells (EPCs) are unique populations which have reparative potential in overcoming the endothelial damage and reducing cardiovascular risk. Patients with ankylosing spondylitis (AS) have increased risk of cardiovascular morbidity and mortality. The aim of this study was to investigate the endothelial progenitor cell population in AS patients and its potential relationships with disease variables. Methods: Endothelial progenitor cells were measured in peripheral blood samples from 20 AS and 20 healthy controls by flow cytometry on the basis of CD34 and CD133 expression. Disease activity was evaluated by using Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). Functional ability was monitored by using Bath Ankylosing Spondylitis Functional Index (BASFI). Results: EPCs were depleted in AS patients as compared to the healthy controls (CD34+/CD133+: 0.027 ± 0.010 % vs. 0.044 ± 0.011 %, p<0.001). EPCs depletion were significantly associated with disease duration (r=-0.52, p=0.01) and BASDAI (r=-0.45, p=0.04). Conclusion: This is the first study to demonstrate endothelial progenitor cells depletion in AS patients. EPCs depletion inversely correlates with disease duration and disease activity, suggesting the pivotal role of inflammation in depletion of EPCs. EPC would possibly also serve as a therapeutic target for preventing cardiovascular disease in AS.

Keywords: ankylosing spondylitis, endothelial progenitor cells, inflammation, vascular damage

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13241 A Case for Q-Methodology: Teachers as Policymakers

Authors: Thiru Vandeyar

Abstract:

The present study set out to determine how Q methodology may be used as an inclusive education policy development process. Utilising Q-methodology as a strategy of inquiry, this qualitative instrumental case study set out to explore how teachers, as a crucial but often neglected human resource, may be included in developing policy. A social constructivist lens and the theoretical moorings of Proudford’s emancipatory approach to educational change anchored in teachers’ ‘writerly’ interpretation of policy text was employed. Findings suggest that Q-method is a unique research approach to include teachers’ voices in policy development. Second, that beliefs, attitudes, and professionalism of teachers to improve teaching and learning using ICT are integral to policy formulation. The study indicates that teachers have unique beliefs about what statements should constitute a school’s information and communication (ICT) policy. Teachers’ experiences are an extremely valuable resource in and should not be ignored in the policy formulation process.

Keywords: teachers, q-methodology, education policy, ICT

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13240 Body of Dialectics: Exploring a Dynamic-Adaptational Model of Physical Self-Integrity and the Pursuit of Happiness in a Hostile World

Authors: Noam Markovitz

Abstract:

People with physical disabilities constitute a very large and simultaneously a diverse group of general population, as the term physical disabilities is extensive and covers a wide range of disabilities. Therefore, individuals with physical disabilities are often faced with a new, threatening and stressful reality leading possibly to a multi-crisis in their lives due to the great changes they experience in somatic, socio-economic, occupational and psychological level. The current study seeks to advance understanding of the complex adaptation to physical disabilities by expanding the dynamic-adaptational model of the pursuit of happiness in a hostile world with a new conception of physical self-integrity. Physical self-integrity incorporates an objective dimension, namely physical self-functioning (PSF), and a subjective dimension, namely physical self-concept (PSC). Both of these dimensions constitute an experience of wholeness in the individual’s identification with her or his physical body. The model guiding this work is dialectical in nature and depicts two systems in the individual’s sense of happiness: subjective well-being (SWB) and meaning in life (MIL). Both systems serve as self-adaptive agents that moderate the complementary system of the hostile-world scenario (HWS), which integrates one’s perceived threats to one’s integrity. Thus, in situations of increased HWS, the moderation may take a form of joint activity in which SWB and MIL are amplified or a form of compensation in which one system produces a stronger effect while the other system produces a weaker effect. The current study investigated PSC in relations to SWB and MIL through pleasantness and meanings that are physically or metaphorically grounded in one’s body. In parallel, PSC also relates to HWS by activating representations of inappropriateness, deformation and vulnerability. In view of possibly dialectical positions of opposing and complementary forces within the current model, the current field study that aims to explore PSC as appearing in an independent, cross-sectional, design addressing the model’s variables in a focal group of people with physical disabilities. This study delineated the participation of the PSC in the adaptational functions of SWB and MIL vis-à-vis HWS-related life adversities. The findings showed that PSC could fully complement the main variables of the pursuit of happiness in a hostile world model. The assumed dialectics in the form of a stronger relationship between SWB and MIL in the face of physical disabilities was not supported. However, it was found that when HWS increased, PSC and MIL were strongly linked, whereas PSC and SWB were weakly linked. This highlights the compensatory role of MIL. From a conceptual viewpoint, the current investigation may clarify the role of PSC as an adaptational agent of the individual’s positive health in complementary senses of bodily wholeness. Methodologically, the advantage of the current investigation is the application of an integrative, model-based approach within a specially focused design with a particular relevance to PSC. Moreover, from an applicative viewpoint, the current investigation may suggest how an innovative model may be translated to therapeutic interventions used by clinicians, counselors and practitioners in improving wellness and psychological well-being, particularly among people with physical disabilities.

Keywords: older adults, physical disabilities, physical self-concept, pursuit of happiness in a hostile-world

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13239 Chitosan Modified Halloysite Nanomaterials for Efficient and Effective Vaccine Delivery in Farmed Fish

Authors: Saji George, Eng Khuan Seng, Christof Luda

Abstract:

Nanotechnology has been recognized as an important tool for modern agriculture and has the potential to overcome some of the pressing challenges faced by aquaculture industry. A strategy for optimizing nanotechnology-based therapeutic delivery platform for immunizing farmed fish was developed. Accordingly, a compositional library of nanomaterials of natural chemistry (Halloysite (clay), Chitosan, Hydroxyapatite, Mesoporous Silica and a composite material of clay-chitosan) was screened for their toxicity and efficiency in delivering models antigens in cellular and zebrafish embryo models using high throughput screening platforms. Through multi-parametric optimization, chitosan modified halloysite (clay) nanomaterial was identified as an optimal vaccine delivery platform. Further, studies conducted in juvenile seabass showed the potential of clay-chitosan in delivering outer membrane protein of Tenacibaculum maritimum- TIMA (pathogenic bacteria) to and its efficiency in eliciting immune responses in fish. In short, as exemplified by this work, the strategy of using compositional nanomaterial libraries and their biological profiling using high-throughput screening platform could fasten the discovery process of nanomaterials with potential applications in food and agriculture.

Keywords: nanotechnology, fish-vaccine, drug-delivery, halloysite-chitosan

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13238 Impact of Popular Passive Physiological Diversity Drivers on Thermo-Physiology

Authors: Ilango Thiagalingam, Erwann Yvin, Gabriel Crehan, Roch El Khoury

Abstract:

An experimental investigation is carried out in order to evaluate the relevance of a customization approach of the passive thermal mannikin. The promise of this approach consists in the following assumption: physiological differences lead to distinct thermo-physiological responses that explain a part of the thermal appraisal differences between people. Categorizing people and developing an appropriate thermal mannikin for each group would help to reduce the actual dispersion on the subjective thermal comfort perception. The present investigation indicates that popular passive physiological diversity drivers such as sex, age and BMI are not the correct parameters to consider. Indeed, very little or no discriminated global thermo-physiological responses arise from the physiological classification of the population using these parameters.

Keywords: thermal comfort, thermo-physiology, customization, thermal mannikin

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13237 Diversity for Safety and Security of Autonomous Vehicles against Accidental and Deliberate Faults

Authors: Anil Ranjitbhai Patel, Clement John Shaji, Peter Liggesmeyer

Abstract:

Safety and security of autonomous vehicles (AVs) is a growing concern, first, due to the increased number of safety-critical functions taken over by automotive embedded systems; second, due to the increased exposure of the software-intensive systems to potential attackers; third, due to dynamic interaction in an uncertain and unknown environment at runtime which results in changed functional and non-functional properties of the system. Frequently occurring environmental uncertainties, random component failures, and compromise security of the AVs might result in hazardous events, sometimes even in an accident, if left undetected. Beyond these technical issues, we argue that the safety and security of AVs against accidental and deliberate faults are poorly understood and rarely implemented. One possible way to overcome this is through a well-known diversity approach. As an effective approach to increase safety and security, diversity has been widely used in the aviation, railway, and aerospace industries. Thus, the paper proposes fault-tolerance by diversity model takes into consideration the mitigation of accidental and deliberate faults by application of structure and variant redundancy. The model can be used to design the AVs with various types of diversity in hardware and software-based multi-version system. The paper evaluates the presented approach by employing an example from adaptive cruise control, followed by discussing the case study with initial findings.

Keywords: autonomous vehicles, diversity, fault-tolerance, adaptive cruise control, safety, security

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13236 Environmental Impact of Gas Field Decommissioning

Authors: Muhammad Ahsan

Abstract:

The effective decommissioning of oil and gas fields and related assets is one of the most important challenges facing the oil and gas industry today and in the future. Decommissioning decisions can no longer be avoided by the operators and the industry as a whole. Decommissioning yields no return on investment and carries significant regulatory liabilities. The main objective of this paper is to provide an approach and mechanism for the estimation of emissions associated with decommissioning of Oil and Gas fields. The model uses gate to gate approach and considers field life from development phase up to asset end life. The model incorporates decommissioning processes which includes; well plugging, plant dismantling, wellhead, and pipeline dismantling, cutting and temporary fabrication, new manufacturing from raw material and recycling of metals. The results of the GHG emissions during decommissioning phase are 2.31x10-2 Kg CO2 Eq. per Mcf of the produced natural gas. Well plug and abandonment evolved to be the most GHG emitting activity with 84.7% of total field decommissioning operational emissions.

Keywords: LCA (life cycle analysis), gas field, decommissioning, emissions

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13235 Key Success Factors of Customer Relationship Management: An Empirical Study of Tunisian Firms

Authors: Khlif Hamadi

Abstract:

Customer Relationship Management has become the main interest of researchers and practitioners especially in the domains of Management and Information Systems (IS). This paper is an overview of success factors that could facilitate successful adoption of CRM. There are 2 factors: the organizational climate and the capacity for innovation. The survey was developed with 200 CRM users. Empirical research is in the positivist paradigm based on the hypothetico-deductive method. Indeed, the approach adopted is the quantitative approach based on a questionnaire complied by Tunisian companies operating in different sectors of activity. For the data analyses, the structural equations method was used to conduct our exploratory and confirmatory analysis. The results revealed that the creative organizational climate and high innovation capacity positively influence the success of CRM practice.

Keywords: CRM practices, innovation capacity, organizational climate, the structural equation

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13234 Shopping Behaviour of Ethnic Groups in Indian Culture

Authors: Hari Govindmishra, Sarabjot Singh

Abstract:

The study offers an approach to understand different determinants of shopping behaviour, and the effect of ethnicity on shopping behaviour. The results reveal that the Indian culture is composite in nature and because of which there is no difference between different ethnic groups in their preference for three shopping behaviour determinants, viz., status consciousness, need for touch and companion opinion. The research model investigates the relevant relationship between these constructs by using a structural equation modelling approach, which reveals that status consciousness, need for touch and companion opinion are significant determinants of shopping behaviour. Consequently, the shopping behaviour managers have to understand the collective nature of Indian ethnic consumers in their shopping behaviour.

Keywords: ethnic groups, status consciousness, companion opinion, need for touch, shopping behaviour

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13233 Fuzzy Multi-Component DEA with Shared and Undesirable Fuzzy Resources

Authors: Jolly Puri, Shiv Prasad Yadav

Abstract:

Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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13232 Recidivism in Brazil: Exploring the Case of the Association of Protection and Assistance to Convicts Methodology

Authors: Robyn Heitzman

Abstract:

The traditional method of punitive justice in Brazil has failed to prevent high levels of recidivism. Combined with overcrowding, a lack of resources, and human rights abuses, the conventional prison approach in Brazil is being questioned; one alternative approach is the association of protection and assistance to convicts (APAC) method. Justice -according to the principles of the APAC methodology- is served through education, reformation, and human development. The model has reported relatively low levels of recidivism and has been internationally recognised for its progress. Through qualitative research such as interviews and case studies, this paper explains why, applying the theory of restorative justice, the APAC methodology yields lower rates of recidivism compared to the traditional models of prisons in Brazil. 

Keywords: Brazil, justice, prisons, restorative

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13231 Antihypertensive Activity of Alcoholic Extract of Citrus Paradise Juice in One Clip One Kidney Hypertension Model in Rats

Authors: Lokesh Bhatt, Jayesh Rathod

Abstract:

Hypertension is one of the most prevalent cardiovascular disorder. It is responsible for several other cardiovascular disorders. Although many drugs are available for the treatment of hypertension, still a large population has uncontrolled blood pressure. Thus there is an unmet need for new therapeutic approaches for the same. Fruit juice of Citrus paradise contains several flavonoids with vasodilatory activity. We hypothesized that alcoholic extract of Citrus paradise, which contains flavonoids, might attenuate hypertension. The objective of the present study was to evaluate the antihypertensive activity of alcoholic extract of Citrus paradise fruit juice in rats. Hypertension was induced using one clip one kidney model in rats. The renal artery was occluded for 4 h after removal of one kidney. Once stabilized, the ganglionic blockade was performed followed by removal of the arterial clip from the kidney. Removal of clip resulted in an increase in blood pressure which is due to release of renin from the kidney. Alcoholic extract of Citrus paradise fruit juice was then administered at 50 mg/kg and 100 mg/kg dose by intravenous injection. Blood pressure was monitored continuously. Alcoholic extract of Citrus paradise fruit juice reduced hypertension in dose-dependent manner. Antihypertensive activity was found to be associated with vasodilation. The results of the present study showed antihypertensive potential of alcoholic extract of Citrus paradise fruit juice.

Keywords: citrus paradise, alcoholic extract, one clip one kidney model, vasodilation

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13230 Structural Testing and the Finite Element Modelling of Anchors Loaded Against Partially Confined Surfaces

Authors: Ali Karrech, Alberto Puccini, Ben Galvin, Davide Galli

Abstract:

This paper summarises the laboratory tests, numerical models and statistical approach developed to investigate the behaviour of concrete blocks loaded in shear through metallic anchors. This research is proposed to bridge a gap in the state of the art and practice related to anchors loaded against partially confined concrete surfaces. Eight concrete blocks (420 mm x 500 mm x 1000 mm) with 150 and/or 250 deep anchors were tested. The stainless-steel anchors of diameter 16 mm were bonded with HIT-RE 500 V4 injection epoxy resin and were subjected to shear loading against partially supported edges. In addition, finite element models were constructed to validate the laboratory tests and explore the influence of key parameters such as anchor depth, anchor distance from the edge, and compressive strength on the stability of the block. Upon their validation experimentally, the numerical results were used to populate, develop and interpret a systematic parametric study based on the Design of Experiment approach through the Box-Behnken design and Response Surface Methodology. An empirical model has been derived based on this approach, which predicts the load capacity with the desirable intervals of confidence.

Keywords: finite element modelling, design of experiment, response surface methodology, Box-Behnken design, empirical model, interval of confidence, load capacity

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13229 Number of Parametrization of Discrete-Time Systems without Unit-Delay Element: Single-Input Single-Output Case

Authors: Kazuyoshi Mori

Abstract:

In this paper, we consider the parametrization of the discrete-time systems without the unit-delay element within the framework of the factorization approach. In the parametrization, we investigate the number of required parameters. We consider single-input single-output systems in this paper. By the investigation, we find, on the discrete-time systems without the unit-delay element, three cases that are (1) there exist plants which require only one parameter and (2) two parameters, and (3) the number of parameters is at most three.

Keywords: factorization approach, discrete-time system, parameterization of stabilizing controllers, system without unit-delay

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13228 Epidemiology of Primary Bronchopulmonary Cancer in Tunisia

Authors: Melliti Rihab, Zaeid Sonia, Khechine Wiem, Daldoul Amira

Abstract:

Introduction: Lung cancer is the leading cause of cancer death. Its incidence is increasing, and its prognosis remains pejorative. We present the clinical, pathological, and therapeutic characteristics of bronchopulmonary cancer (BPC) in Tunisia. Methods: Retrospective study including patients followed in the oncology department of the University Hospital of Monastir between April 2014 and December 2021 suffering from lung cancer. Results: These are 117 patients, including 86.3% men and 13.7% women (sex ratio 6.3). The average age was 64 years ± 9 (37-83), with 95.7% being over 50 years old. Patients were smokers in 82% of cases. The clinical signs were dominated by chest pain (27.5%) and dyspnea in 21.1% of cases. In 6 patients, an episode of COVID-19 infection revealed the diagnosis. Half of the patients had a PS between 0 and 1. Small cell lung cancer was present in 18 patients (15.4%). The majority of non small cell lung cancer was of the adenocarcinoma type (68.7%). The diagnosis was late (stage IV) in 62.4% of cases. BPC was metastatic to bone (52%), contralateral lung (25.9%), and brain (27.3%). Patients were oligometastatic in 26% of cases. Surgery and radiotherapy were performed respectively in 14.5% and 23.1% of cases. Three-quarters of the patients had had nutrition (75.2%). The ROS1 mutation was present in 1 patient. PDL-1 expression was >40% in 2 patients. Survival was mean eight months ± 7.4. Conclusion: Lung cancer is diagnosed at a late stage in Tunisia. The lack of molecular study for non-small cell PBC and the lack of marketing authorization for tyrosine kinase inhibitors in Tunisia make the management incomplete.

Keywords: SCLC, NCSLC, ROS1, PDL1

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13227 Modern Seismic Design Approach for Buildings with Hysteretic Dampers

Authors: Vanessa A. Segovia, Sonia E. Ruiz

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The use of energy dissipation systems for seismic applications has increased worldwide, thus it is necessary to develop practical and modern criteria for their optimal design. Here, a direct displacement-based seismic design approach for frame buildings with hysteretic energy dissipation systems (HEDS) is applied. The building is constituted by two individual structural systems consisting of: 1) A main elastic structural frame designed for service loads and 2) A secondary system, corresponding to the HEDS, that controls the effects of lateral loads. The procedure implies to control two design parameters: A) The stiffness ratio (α=K_frame/K_(total system)), and B) The strength ratio (γ= V_damper / V_(total system)). The proposed damage-controlled approach contributes to the design of a more sustainable and resilient building because the structural damage is concentrated on the HEDS. The reduction of the design displacement spectrum is done by means of a damping factor (recently published) for elastic structural systems with HEDS, located in Mexico City. Two limit states are verified: Serviceability and near collapse. Instead of the traditional trial-error approach, a procedure that allows the designer to establish the preliminary sizes of the structural elements of both systems is proposed. The design methodology is applied to an 8-story steel building with buckling restrained braces, located in soft soil of Mexico City. With the aim of choosing the optimal design parameters, a parametric study is developed considering different values of α and γ. The simplified methodology is for preliminary sizing, design, and evaluation of the effectiveness of HEDS, and it constitutes a modern and practical tool that enables the structural designer to select the best design parameters.

Keywords: damage-controlled buildings, direct displacement-based seismic design, optimal hysteretic energy dissipation systems, hysteretic dampers

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13226 Multidimensional Item Response Theory Models for Practical Application in Large Tests Designed to Measure Multiple Constructs

Authors: Maria Fernanda Ordoñez Martinez, Alvaro Mauricio Montenegro

Abstract:

This work presents a statistical methodology for measuring and founding constructs in Latent Semantic Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations present on Item Response Theory. More precisely, we propose initially reducing dimensionality with specific use of Principal Component Analysis for the linguistic data and then, producing axes of groups made from a clustering analysis of the semantic data. This approach allows the user to give meaning to previous clusters and found the real latent structure presented by data. The methodology is applied in a set of real semantic data presenting impressive results for the coherence, speed and precision.

Keywords: semantic analysis, factorial analysis, dimension reduction, penalized logistic regression

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13225 State of the Art and Future Perspectives of Virtual Reality, Augmented Reality, and Mixed Reality in Cardiovascular Care

Authors: Adisu Mengesha Assefa

Abstract:

The field of cardiovascular care is being transformed by the incorporation of Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), collectively known as Extended Reality (XR), into medical education, procedural planning, and patient care. This review examines the state-of-the-art applications of XR in cardiology, emphasizing its role in enhancing the precision of interventional procedures and understanding complex anatomical structures. XR technologies complement conventional imaging methods by enabling immersive three-dimensional interaction that facilitates both preoperative planning and intraoperative guidance. Despite these promising developments, challenges such as harmonizing data, integrating various imaging systems, and addressing the prevalence of cybersickness remain. Ethical considerations, including maintaining physician focus and ensuring patient safety, are crucial when implementing XR in clinical settings. This review summarizes the existing literature and highlights the need for more rigorous future studies to validate therapeutic benefits and ensure safe application. By examining both the potential and the challenges, this paper aims to delineate the current and future roles of XR in cardiovascular care, emphasizing the necessity for continued innovation and ethical oversight to improve patient outcomes.

Keywords: virtual reality, augmented reality, mixed reality, cardiovascular care, education, preprocedural planning, intraoperative guidance, postoperative patient rehabilitation

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13224 Identifying the True Extend of Glioblastoma Based on Preoperative FLAIR Images

Authors: B. Shukir, L. Szivos, D. Kis, P. Barzo

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Glioblastoma is the most malignant brain tumor. In general, the survival rate varies between (14-18) months. Glioblastoma consists a solid and infiltrative part. The standard therapeutic management of glioblastoma is maximum safe resection followed by chemo-radiotherapy. It’s hypothesized that the pretumoral hyperintense region in fluid attenuated inversion recovery (FLAIR) images includes both vasogenic edema and infiltrated tumor cells. In our study, we aimed to define the sensitivity and specificity of hyperintense FLAIR images preoperatively to examine how well it can define the true extent of glioblastoma. (16) glioblastoma patients included in this study. Hyperintense FLAIR region were delineated preoperatively as tumor mask. The infiltrative part of glioblastoma considered the regions where the tumor recurred on the follow up MRI. The recurrence on the CE-T1 images was marked as the recurrence masks. According to (AAL3) and (JHU white matter labels) atlas, the brain divided into cortical and subcortical regions respectively. For calculating specificity and sensitivity, the FLAIR and the recurrence masks overlapped counting how many regions affected by both . The average sensitivity and specificity was 83% and 85% respectively. Individually, the sensitivity and specificity varied between (31-100)%, and (100-58)% respectively. These results suggest that despite FLAIR being as an effective radiologic imaging tool its prognostic value remains controversial and probabilistic tractography remain more reliable available method for identifying the true extent of glioblastoma.

Keywords: brain tumors, glioblastoma, MRI, FLAIR

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13223 Role of ABC-Type Efflux Transporters in Antifungal Resistance of Candida auris

Authors: Mohamed Mahdi Alshahni, Takashi Tamura, Koichi Makimura

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Objective: The objective of this study is to evaluate roles of ABC-type efflux transporters in the resistance of Candida auris against common antifungal agents. Material and Methods: A wild-type C. auris strain and its antifungal resistant derivative strain that is generated through induction by antifungal agents were used in this study. The strains were cultured onto media containing beauvericin alone or in combination with azole agents. Moreover, expression levels of four ABC-type transporter’s homologs in those strains were analyzed by real time PCR with or without antifungal stress by fluconazole or voriconazole. Results: Addition of beauvericin helped to partially restore the susceptibility of the resistant strain against fluconazole, suggesting participation of ABC-type transporters in the resistance mechanism. Real time PCR results showed that mRNA levels of three out of the four analyzed transporters in the resistant strain were more than 2-fold higher than their counterparts in the wild-type strain under negative control and antifungal agent-containing conditions. Conclusion: C. auris is an emerging multidrug-resistant pathogen causing human mortality worldwide. Providing effective treatment has been hampered by the resistance to antifungal drugs, demanding understanding the resistance mechanism in order to devise new therapeutic strategies. Our data suggest a partial contribution of ABC-type transporters to the resistance of this pathogen.

Keywords: resistance, C. auris, transporters, antifungi

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13222 Comparison of Machine Learning-Based Models for Predicting Streptococcus pyogenes Virulence Factors and Antimicrobial Resistance

Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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13221 Synthesis and Surface Engineering of Lanthanide Nanoparticles for NIR Luminescence Imaging and Photodynamic Therapy

Authors: Syue-Liang Lin, C. Allen Chang

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Luminescence imaging is an important technique used in biomedical research and clinical diagnostic applications in recent years. Concurrently, the development of NIR luminescence probes / imaging contrast agents has helped the understanding of the structural and functional properties of cells and animals. Photodynamic therapy (PDT) is used clinically to treat a wide range of medical conditions, but the therapeutic efficacy of general PDT for deeper tumor was limited by the penetration of excitation source. The tumor targeting biomedical nanomaterials UCNP@PS (upconversion nanoparticle conjugated with photosensitizer) for photodynamic therapy and near-infrared imaging of cancer will be developed in our study. Synthesis and characterization of biomedical nanomaterials were completed in this studies. The spectrum of UCNP was characterized by photoluminescence spectroscopy and the morphology was characterized by Transmission Electron Microscope (TEM). TEM and XRD analyses indicated that these nanoparticles are about 20~50 nm with hexagonal phase. NaYF₄:Ln³⁺ (Ln= Yb, Nd, Er) upconversion nanoparticles (UCNPs) with core / shell structure, synthesized by thermal decomposition method in 300°C, have the ability to emit visible light (upconversion: 540 nm, 660 nm) and near-infrared with longer wavelength (downconversion: NIR: 980 nm, 1525 nm) by absorbing 800 nm NIR laser. The information obtained from these studies would be very useful for applications of these nanomaterials for bio-luminescence imaging and photodynamic therapy of deep tumor tissue in the future.

Keywords: Near Infrared (NIR), lanthanide, core-shell structure, upconversion, theranostics

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13220 The Use of Drones in Measuring Environmental Impacts of the Forest Garden Approach

Authors: Andrew J. Zacharias

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The forest garden approach (FGA) was established by Trees for the Future (TREES) over the organization’s 30 years of agroforestry projects in Sub-Saharan Africa. This method transforms traditional agricultural systems into highly managed gardens that produce food and marketable products year-round. The effects of the FGA on food security, dietary diversity, and economic resilience have been measured closely, and TREES has begun to closely monitor the environmental impacts through the use of sensors mounted on unmanned aerial vehicles, commonly known as 'drones'. These drones collect thousands of pictures to create 3-D models in both the visible and the near-infrared wavelengths. Analysis of these models provides TREES with quantitative and qualitative evidence of improvements to the annual above-ground biomass and leaf area indices, as measured in-situ using NDVI calculations.

Keywords: agroforestry, biomass, drones, NDVI

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13219 Fair Federated Learning in Wireless Communications

Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

Procedia PDF Downloads 75