Search results for: intelligent computational techniques

Authors: Jacob Lewis Watts, Adam F. A. Pellegrini

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Prairies, grasslands, and forests cover an expansive portion of the world’s surface and contribute significantly to Earth’s carbon cycle. The largest driver of carbon dynamics in some of these ecosystems is fire. As the global climate changes, most fire-dominated ecosystems will experience increased fire frequency and intensity, leading to increased carbon flux into the atmosphere and soil nutrient depletion. The plant communities associated with different fire regimes are important for reassimilation of carbon lost during fire and soil recovery. More frequent fires promote conservative plant functional traits aboveground; however, belowground fine root traits are poorly explored and arguably more important drivers of ecosystem function as the primary interface between the soil and plant. The root economic spectrum (RES) hypothesis describes single-dimensional covariation between important fine-root traits along a range of plant strategies from acquisitive to conservative – parallel to the well-established leaf economic spectrum (LES). However, because of the paucity of root trait data, the complex nature of the rhizosphere, and the phylogenetic conservatism of root traits, it is unknown whether the RES hypothesis accurately describes plant nutrient and water acquisition strategies. This project utilizesplants grown in common garden conditions in the Cambridge University Botanic Garden and a meta-analysis of long-term fire manipulation experiments to examine the belowground physiological traits of fire-adapted and non-fire-adapted herbaceous species to 1) test the RES hypothesis and 2) describe the effect of fire regimes on fine root functional traits – which in turn affect carbon and nutrient cycling. A suite of morphological, chemical, and biological root traits (e.g. root diameter, specific root length, percent N, percent mycorrhizal colonization, etc.) of 50 herbaceous species were measuredand tested for phylogenetic conservatism and RES dimensionality. Fire-adapted and non-fire-adapted plants traits were compared using phylogenetic PCA techniques. Preliminary evidence suggests that phylogenetic conservatism may weaken the single-dimensionality of the RES, suggesting that there may not be a single way that plants optimize nutrient and water acquisition and storage in the complex rhizosphere; additionally, fire-adapted species are expected to be more conservative than non-fire-adapted species, which may be indicative of slower carbon cycling with increasing fire frequency and intensity.

Keywords: climate change, fire regimes, root economic spectrum, fine roots

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Authors: Dewan Ahsan

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Denmark is well ahead in generating electricity from renewable sources. The offshore wind sector is playing the pivotal role to achieve this target. Though there is a rapid growth of offshore wind sector in Denmark, still there is a dearth of synchronization in OHS (occupational health and safety) regulation and standards. Therefore, this paper attempts to ascertain: i) what are the major challenges of the company specific OHS standards? ii) why does the offshore wind industry need a standardized OHS management system? and iii) who can play the key role in this process? To achieve these objectives, this research applies the interview and survey techniques. This study has identified several key challenges in OHS management system which are; gaps in coordination and communication among the stakeholders, gaps in incident reporting systems, absence of a harmonized OHS standard and blame culture. Furthermore, this research has identified eleven key stakeholders who are actively involve with the offshore wind business in Denmark. As noticed, the relationships among these stakeholders are very complex specially between operators and sub-contractors. The respondent technicians are concerned with the compliance of various third-party OHS standards (e.g. ISO 31000, ISO 29400, Good practice guidelines by G+) which are applying by various offshore companies. On top of these standards, operators also impose their own OHS standards. From the technicians point of angle, many of these standards are not even specific for the offshore wind sector. So, it is a big challenge for the technicians and sub-contractors to comply with different company specific standards which also elevate the price of their services offer to the operators. For instance, when a sub-contractor is competing for a bidding, it must fulfill a number of OHS requirements (which demands many extra documantions) set by the individual operator and/the turbine supplier. According to sub-contractors’ point of view these extra works consume too much time to prepare the bidding documents and they also need to train their employees to pass the specific OHS certification courses to accomplish the demand for individual clients and individual project. The sub-contractors argued that in many cases these extra documentations and OHS certificates are inessential to ensure the quality service. So, a standardized OHS management procedure (which could be applicable for all the clients) can easily solve this problem. In conclusion, this study highlights that i) development of a harmonized OHS standard applicable for all the operators and turbine suppliers, ii) encouragement of technicians’ active participation in the OHS management, iii) development of a good safety leadership, and, iv) sharing of experiences among the stakeholders (specially operators-operators-sub contractors) are the most vital strategies to overcome the existing challenges and to achieve the goal of 'zero accident/harm' in the offshore wind industry.

Keywords: green energy, offshore, safety, Denmark

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Authors: Lami Mohammed, Hussain J. Al Faifi, Abdel Aziz Al Bassam, Osama M. K. Kassem

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The Neoproterozoic basement rocks of the Ar Rayn terrane have been identified as parts of the Eastern Arabian Shield. It focuses on the petrological and finite strain properties to display the tectonic setting of the Al Amar suture for high deformed volcanic and granitoids rocks. The volcanic rocks are classified into two major series: the eastern side cycle, which includes dacite, rhyodacite, rhyolite, and ignimbrites, and the western side cycle, which includes andesite and pyroclastics. Granitoids rocks also contain monzodiorite, tonalite, granodiorite, and alkali-feldspar granite. To evaluate the proportions of shear contributions in penetratively deformed rocks. Asymmetrical porphyroclast and sigmoidal structural markers along the suture's strike, namely the Al Amar, are expected to reveal strain factors. The Rf/phi and Fry techniques are used to characterize quartz and feldspar porphyroclast, biotite, and hornblende grains in Abt schist, high deformed volcanic rock, and granitoids. The findings exposed that these rocks had experienced shape flattening, finite strain accumulation, and overall volume loss. The magnitude of the strain appears to increase across the nappe contacts with neighboring lithologies. Subhorizontal foliation likely developed in tandem with thrusting and nappe stacking, almost parallel to tectonic contacts. The ductile strain accumulation that occurred during thrusting along the Al Amar suture mostly includes a considerable pure shear component. Progressive thrusting by overlaid transpression and oblique convergence is shown by stacked nappes and diagonal stretching lineations along the thrust axes. The subhorizontal lineation might be the result of the suture's most recent activity. The current study's findings contradict the widely accepted model that links orogen-scale structures in the Arabian Shield to oblique convergence with dominant simple shear deformation. A significant pure shear component/crustal thickening increment should have played a significant role in the evolution of the suture and thus in the Shield's overall deformation history. This foliation was primarily generated by thrusting nappes together, showing that nappe stacking was linked to substantial vertical shortening induced by the active Al Amar suture on a massive scale.

Keywords: petrology, finite strain analysis, al amar region, ar-rayn terrane, Arabian shield

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Authors: Ashoke Priyadarshana Premananda

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As per the suggestions of previously conducted research in Counseling Psychology, the necessity of forming culture- friendly approaches has been strongly emphasized by a number of scholars in the field. In response to that, Multicultural-model of Buddhist Based Cognitive Behavioral Therapy (MMBCBT) has been formed as a culture-friendly therapeutic approach to address psychological disturbances (depression) in late adulthood. Elderly population in the world is on the rise by leaps and bounds, and forming a culture-based therapeutic model which is blended with Buddhist teachings has been the major objective of the study. Buddhist teachings and cultural applications, which were mapped onto Cognitive Behavioral Therapy (CBT) in the West, ultimately resulted in MMBCBT. Therefore, MMBCBT is a blend of cultural therapeutic techniques and the essence of certain Buddhist teachings extracted from five crucial suttas, which include CBT principles. In the process of mapping, MeghiyaSutta, GirimānandaSutta, SallekhaSutta, DvedhāvitakkaSutta, and Vitakka- SaṇṭhānaSutta have been taken into consideration mainly because of their cognitive behavioral content. The practical components of Vitakka- Saṇṭhānasutta (Aññanimittapabbaṃ) and Sallekhasutta (SallekhaPariyāya and CittuppādaPariyāya) have been used in the model while mindfulness of breathing was also carried out with the participants. Basically, multi-cultural therapeutic approaches of MMBCBT aim at modifying behavior (behavioral modification), whereas the rest is centered to the cognitive restructuring process. Therefore, MMBCBT is endowed with Behavioral Therapy (BT) and Cognitive Therapy(CT). In order to find out the validation of MMBCBT as a newly formed approach, it was then followed by mixed research (quantitative and qualitative research) with a sample selected from the elderly population following the purposive sampling technique. 40 individuals were selected from three elderly homes as per the purposive sampling technique. Elderly people identified to be depressed via Geriatric Depression Scale underwent MMBCBT for two weeks continuously while action research was being conducted simultaneously. Additionally, a Focus Group interview was carried out to support the action research. As per the research findings, people who identified depressed prior to the exposure to MMBCBT were found to be showing positive changes after they were exposed to the model. “Paired Sample t test” showed that the Multicultural Model of Buddhist based Cognitive Behavioral Therapy reduced depression of elderly people (The mean value (x̄) of the sample (level of depression) before the model was 10.7 whereas the mean value after the model was 7.5.). Most importantly, MMBCBT has been found to be effectively used with people from all walks of life despite religious diversities.

Keywords: buddhist psychotherapy, cognitive behavioral therapy in buddhism, counseling in cultural context, gerontology, and buddhism

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Authors: Bijad Alqahtani, Graham Arnold, Weijie Wang

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Background—Tai Chi Chuan (TCC) is a type of traditional Chinese martial art and is considered a benefiting physical fitness. Advanced techniques of motion analysis have been routinely used in the clinical assessment. However, so far, little research has been done on the biomechanical assessment of TCC players in terms of gait and balance using motion analysis. Objectives—The aim of this study was to investigate whether TCC improves the lower limb conditions and balance ability using the state of the art motion analysis technologies, i.e. motion capture system, electromyography and force platform. Methods—Twenty TCC (9 male, 11 female) with age between (42-77) years old and weight (56.2-119 Kg), and eighteen Non-TCC participants (7 male, 11 female), weight (50-110 Kg) with age (43- 78) years old at the matched age as a control group were recruited in this study. Their gait and balance were collected using Vicon Nexus® to obtain the gait parameters, and kinematic parameters of hip, knee, and ankle joints in three planes of both limbs. Participants stood on force platforms to perform a single leg balance test. Then, they were asked to walk along a 10 m walkway at their comfortable speed. Participants performed 5 trials of single-leg balance for the dominant side. Also, the participants performed 3 trials of four square step balance and 10 trials of walking. From the recorded trials, three good ones were analyzed using the Vicon Plug-in-Gait model to obtain gait parameters, e.g. walking speed, cadence, stride length, and joint parameters, e.g. joint angle, force, moments, etc. Result— The temporal-spatial variables of TCC subjects were compared with the Non-TCC subjects, it was found that there was a significant difference (p < 0.05) between the groups. Moreover, it was observed that participants of TCC have significant differences in ankle, hip, and knee joints’ kinematics in the sagittal, coronal, and transverse planes such as ankle angle (19.90±19.54 deg) for TCC while (15.34±6.50 deg) for Non-TCC, and knee angle (14.96±6.40 deg) for TCC while (17.63±5.79 deg) for Non-TCC in the transverse plane. Also, the result showed that there was a significant difference between groups in the single-leg balance test, e.g. maintaining single leg stance time in the TCC participants showed longer duration (20.85±10.53 s) in compared to Non-TCC people group (13.39±8.78 s). While the result showed that there was no significant difference between groups in the four square step balance. Conclusion—Our result showed that there are significant differences between Tai Chi Chuan and Non-Tai Chi Chuan participants in the various aspects of gait analysis and balance test, as a consequence of these findings some of biomechanical parameters such as joints kinematics, gait parameters and single leg stance balance test, the Tai Chi Chuan could improve the lower limb conditions and could reduce a risk of fall for the elderly with ageing.

Keywords: gait analysis, kinematics, single leg stance, Tai Chi Chuan

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Authors: Robert Pečenko, Karin Tomažič, Igor Planinc, Sabina Huč, Tomaž Hozjan

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Timber is favourable structural material due to high strength to weight ratio, recycling possibilities, and green credentials. Despite being flammable material, it has relatively high fire resistance. Everyday engineering practice around the word is based on an outdated design of timber structures considering standard fire exposure, while modern principles of performance-based design enable use of advanced non-standard fire curves. In Europe, standard for fire design of timber structures EN 1995-1-2 (Eurocode 5) gives two methods, reduced material properties method and reduced cross-section method. In the latter, fire resistance of structural elements depends on the effective cross-section that is a residual cross-section of uncharred timber reduced additionally by so called zero strength layer. In case of standard fire exposure, Eurocode 5 gives a fixed value of zero strength layer, i.e. 7 mm, while for non-standard parametric fires no additional comments or recommendations for zero strength layer are given. Thus designers often implement adopted 7 mm rule also for parametric fire exposure. Since the latest scientific evidence suggests that proposed value of zero strength layer can be on unsafe side for standard fire exposure, its use in the case of a parametric fire is also highly questionable and more numerical and experimental research in this field is needed. Therefore, the purpose of the presented study is to use advanced calculation methods to investigate the thickness of zero strength layer and parametric charring rates used in effective cross-section method in case of parametric fire. Parametric studies are carried out on a simple solid timber beam that is exposed to a larger number of parametric fire curves Zero strength layer and charring rates are determined based on the numerical simulations which are performed by the recently developed advanced two step computational model. The first step comprises of hygro-thermal model which predicts the temperature, moisture and char depth development and takes into account different initial moisture states of timber. In the second step, the response of timber beam simultaneously exposed to mechanical and fire load is determined. The mechanical model is based on the Reissner’s kinematically exact beam model and accounts for the membrane, shear and flexural deformations of the beam. Further on, material non-linear and temperature dependent behaviour is considered. In the two step model, the char front temperature is, according to Eurocode 5, assumed to have a fixed temperature of around 300°C. Based on performed study and observations, improved levels of charring rates and new thickness of zero strength layer in case of parametric fires are determined. Thus, the reduced cross section method is substantially improved to offer practical recommendations for designing fire resistance of timber structures. Furthermore, correlations between zero strength layer thickness and key input parameters of the parametric fire curve (for instance, opening factor, fire load, etc.) are given, representing a guideline for a more detailed numerical and also experimental research in the future.

Keywords: advanced numerical modelling, parametric fire exposure, timber structures, zero strength layer

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Authors: Radhika Jain

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The nursing community in India face unique challenges ranging from lack of adequate career progression, low social status attached to the profession, poor nurse-to-patient ratio leading to heavy workload resulting in stress and burnout, lack of general recognition and the responsibility of often having to deal with the ire of the patients and their families. This study explores how a combination of Playback Theatre and Expressive Arts could be used as a very powerful tool to understand the concerns, and consequently as a self-care tool to bring about the sense of well-being and emotional awareness for the nurses. For the purpose of this study, Playback Theatre was used as an entry tool to understand the thoughts, feelings and concerns. Playback theatre is a unique improvisational form of theatre developed by Jonathan Fox and Jo Salas in 1975, in which audience share their own stories from their lives and the performers play them back through a range of improv techniques such as metaphor, poetry, music and movement. Playback Theatre helped in first warming them up to the idea of sharing and then gave them the confidence of a safe space to collectively go deeper into their emotional experiences. As the next step, structured sessions of Expressive Arts were conducted with the same set of nurses, for them to work on the issues and concerns they have (and which they shared during the Playback performance). These sessions were to enable longer engagements as many of the concerns expressed were related to perceptions and beliefs that have been ingrained over a period of time and hence it needs a longer engagement to be worked on in detail. The Expressive Art sessions helped in this regard. Expressive arts therapy combines psychology and the creative process to promote emotional growth and healing. The study was conducted at two places: one a geriatric centre and the other, a palliative care centre. The study revealed that concerns and challenges would not be identical across the nursing community or across similar types of health care organizations but would be specific to each organization or centre as the circumstances and set-up at each place would be different. At the geriatric centre, stress and burnout emerged as the main concerns while at the palliative care centre, the main concern that came up was around the difficulty the nurses faced in expressing emotions and in communicating their feelings. The objective analysis of the results of the study indicated how longer-term engagements using Expressive Arts as the modality helped the nurses have better awareness of their emotions and helped them develop tools of self-care tools while also tapping into their emotions to express and experience. The process of eliciting the main concerns from the nurses using a Playback Theatre performance and then following that with subsequent sessions of expressive arts helped the nurses in the way nurses approached their job and the reduced level of overwhelm that they felt.

Keywords: palliative care, nurses, self-care, expressive arts, playback theatre

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Authors: E. Rommes, Els Toonen, Rahil Roodsaz, Suborna Camellia, Farhana Alam, Saad Khan, Jhalok Ranjon Talukder, Tanveer Hassan, Syeda Farjana Ahmed, Sabina Faiz Rashid

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In Bangladesh, a country in which adults (both parents and teachers) find it particularly hard to speak with youth about sexuality, adolescents seem to struggle with various insecurities about their sexual feelings, thoughts, behavior and physical characteristics. On the basis of a large number of interviews and focus groups with rural and urban Bangla adolescent girls and boys of lower and middle class as part of the large-scale three-year project ‘Breaking the Shame’, we have identified ten sexual themes or ‘myths’ that youth struggle with most. These encompass amongst others beliefs and insecurities on masturbation, discharge, same-sex behavior and feelings, the effects of watching porn and gender norms. We argue that the Internet is a particularly suitable medium to ‘debunk’ those myths, as youth can consult it anonymously and privately and so avoid social shame. Moreover, amongst the myths, we have identified two kinds which may need different debunking techniques. One kind of myth concerns scientifically uncontested, generally biological related information, such as the effects of having sex with a pregnant woman, questions on the effects of a penile or vaginal discharge or questions on the effects of masturbation. The second kind of myths concerns more diverse information sources and deals with e.g. religious or culturally specific norms, such as on the meaning and existence of homosexuality or gender appropriate norms of behavior in Bangladesh. For addressing both kinds of myths, expert information including a wealth of references to information resources needs to be provided, which the Internet is very suitable for. For the second kind of myths, adolescents also need to learn how to deal with sometimes conflicting norms and information sources, and they need to develop and reflect on their own opinions as part of their identity formation. On the basis of a literature review, we thus distinguish general information needs from identity formation needs, which includes the need to be able to relate information and opinions to one’s own opinions and situation. Hence, we argue that youth not only need abstract expert information to be able to debunk sexual myths, but also the option to discuss this information with other adolescents and compare their own situation and opinions with other peers, who in that way serve as ‘warm experts’ for each other. In this paper, we will describe the outcomes of our qualitative study above. In addition, we will present our findings of an intervention by presenting youth with general, uncontested information on the Internet with additional peer discussion options to compare the debunking effects on different kinds of myths.

Keywords: peer discussion, intervention, sexual myths, shame

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Sakinah Idris, Femke Ten Hoeve, Kirstin Greaves-Lord

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Background: Social skills interventions are considered to be efficacious if social skills are improved as a result of an intervention. Nevertheless, the objective assessment of social skills is hindered by a lack of sensitive and validated measures. To measure the change in social skills after an intervention, questionnaires reported by parents, clinicians and/or teachers are commonly used. Observations are the most ecologically valid method of assessing improvements in social skills after an intervention. For this purpose, The Program for the Educational and Enrichment of Relational Skills (PEERS) was developed for adolescents, in order to teach them the age-appropriate skills needed to participate in society. It is an evidence-based intervention for adolescents with ASD that taught ecologically valid social skills techniques. Objectives: The current study aims to describe the development and psychometric evaluation of the Dutch Contextual Assessment of Social Skills (CASS), an observational outcome measure of social skills for adolescents with Autism Spectrum Disorder (ASD). Methods: 64 adolescents (M = 14.68, SD = 1.41, 71% boys) with ASD performed the CASS before and after a social skills intervention (i.e. PEERS or the active control condition). Each adolescent completed a 3-minute conversation with a confederate. The conversation was prompt as a natural introduction between two-unfamiliar, similar ages, opposite-sex peers who meet for the first time. The adolescent and the confederate completed a brief questionnaire about the conversation (Conversation Rating Scale). Results: Results indicated sufficient psychometric properties. The Dutch CASS has a high level of internal consistency (Cronbach's α coefficients = 0.84). Data supported the convergent validity (i.e., significant correlated with the Social Skills Improvement System (SSiS). The Dutch CASS did not significantly correlate with the autistic mannerism subscale from Social Responsiveness Scale (SRS), thus proved the divergent validity. Based on scorings made by raters who were kept blind to the time points, reliable change index was computed to assess the change in social skills. With regard to the content validity, only the learning objectives of the first two meetings of PEERS about conversational skills relatively matched with rating domains of the CASS. Due to this underrepresentation, we found an existing observational measure (TOPICC) that covers some of the other learning objectives of PEERS. TOPICC covers 22% of the learning objectives of PEERS about conversational skills, meanwhile, CASS is 45%. Unfortunately, 33% of the learning objectives of PEERS was not covered by CASS or TOPICC. Conclusion: Recommendations are made to improve the psychometric properties and content validity of the Dutch CASS.

Keywords: autism spectrum disorder, observational, PEERS, social skills

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Authors: Ezinne K. Okoro, Takahiko Katoh, Yoko Kawamura, Stanley C. Meribe

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HIV infection in children is largely as a result of vertical transmission (mother to child transmission [MTCT]). Thus, elimination of mother to child transmission of HIV/AIDS is critical in eliminating HIV infection in children. In Nigeria, drawbacks such as; limited pediatric screening, limited human capital, insufficient advocacy and poor understanding of ART guidelines, have impacted efforts at combating the disease, even as treatment services are free. Prevention of Mother to Child Transmission (PMTCT) program relies on health workers who not only counsel pregnant women on first contact but can competently provide HIV-positive pregnant women with accurate information about the PMTCT program such as feeding techniques and drug adherence. In developing regions like Nigeria where health care delivery faces a lot of drawbacks, it becomes paramount to address these issues of poor PMTCT coverage by conducting a baseline assessment of the knowledge, practices and perceptions related to HIV prevention amongst healthcare workers in Nigeria. A descriptive cross-sectional study was conducted amongst 250 health workers currently employed in health facilities in Abuja, Nigeria where PMTCT services were offered with the capacity to carry out early infant diagnosis testing (EID). Data was collected using a self-administered, pretested, structured questionnaire. This study showed that the knowledge of PMTCT of HIV was poor (30%) among healthcare workers who offer this service day-to-day to pregnant women. When PMTCT practices were analyzed in keeping with National PMTCT guidelines, over 61% of the respondents reported observing standard practices and the majority (58%) had good attitudes towards caring for patients with HIV/AIDS. Although 61% of the respondents reported being satisfied with the quality of service being rendered, 63% reported not being satisfied with their level of knowledge. Predictors of good knowledge were job designation and level of educational attainment. Health workers who were more satisfied with their working conditions and those who had worked for a longer time in the PMTCT service were more likely to observe standard PMTCT practices. With over 62% of the healthcare workers suggesting that more training would improve the quality of service being rendered, this is a strong pointer to stakeholders to consider a ‘healthcare worker-oriented approach’ when planning and conducting PMTCT training for healthcare workers. This in turn will increase pediatric ARV coverage, the knowledge and effectiveness of the healthcare workers in carrying out appropriate PMTCT interventions and culminating in the reduction/elimination of HIV transmission to newborns.

Keywords: attitudes, HIV/AIDS, healthcare workers, knowledge, mother to child transmission, Nigeria, perceptions

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Authors: Lara Bettinelli, Bernhard Glatz, Josef Fink

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Planning engineers and researchers use various calculation models with different levels of complexity, calculation efficiency and accuracy in dynamic calculations of railway bridges under high-speed traffic. When choosing a vehicle model to depict the dynamic loading on the bridge structure caused by passing high-speed trains, different goals are pursued: On the one hand, the selected vehicle models should allow the calculation of a bridge’s vibrations as realistic as possible. On the other hand, the computational efficiency and manageability of the models should be preferably high to enable a wide range of applications. The commonly adopted and straightforward vehicle model is the moving load model (MLM), which simplifies the train to a sequence of static axle loads moving at a constant speed over the structure. However, the MLM can significantly overestimate the structure vibrations, especially when resonance events occur. More complex vehicle models, which depict the train as a system of oscillating and coupled masses, can reproduce the interaction dynamics between the vehicle and the bridge superstructure to some extent and enable the calculation of more realistic bridge accelerations. At the same time, such multi-body models require significantly greater processing capacities and precise knowledge of various vehicle properties. The European standards allow for applying the so-called additional damping method when simple load models, such as the MLM, are used in dynamic calculations. An additional damping factor depending on the bridge span, which should take into account the vibration-reducing benefits of the vehicle-bridge interaction, is assigned to the supporting structure in the calculations. However, numerous studies show that when the current standard specifications are applied, the calculation results for the bridge accelerations are in many cases still too high compared to the measured bridge accelerations, while in other cases, they are not on the safe side. A proposal to calculate the additional damping based on extensive dynamic calculations for a parametric field of simply supported bridges with a ballasted track was developed to address this issue. In this contribution, several different approaches to determine the additional damping of the supporting structure considering the vehicle-bridge interaction when using the MLM are compared with one another. Besides the standard specifications, this includes the approach mentioned above and two additional recently published alternative formulations derived from analytical approaches. For a bridge catalogue of 65 existing bridges in Austria in steel, concrete or composite construction, calculations are carried out with the MLM for two different high-speed trains and the different approaches for additional damping. The results are compared with the calculation results obtained by applying a more sophisticated multi-body model of the trains used. The evaluation and comparison of the results allow assessing the benefits of different calculation concepts for the additional damping regarding their accuracy and possible applications. The evaluation shows that by applying one of the recently published redesigned additional damping methods, the calculation results can reflect the influence of the vehicle-bridge interaction on the design-relevant structural accelerations considerably more reliable than by using normative specifications.

Keywords: Additional Damping Method, Bridge Dynamics, High-Speed Railway Traffic, Vehicle-Bridge-Interaction

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Authors: Wedad Albalawi

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The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques, and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then, dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is an arbitrary nonempty closed subset of the real numbers. Then, the dynamic inequalities on time scales have received a lot of attention in the literature and has become a major field in pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on Hardy and Coposon inequalities, using Steklov operator on time scale in double integrals to obtain special cases of time-scale inequalities of Hardy and Copson on high dimensions. The advantage of this study is that it uses the one-dimensional classical Hardy inequality to obtain higher dimensional on time scale versions that will be applied in the solution of the Cauchy problem for the wave equation. In addition, the obtained inequalities have various applications involving discontinuous domains such as bug populations, phytoremediation of metals, wound healing, maximization problems. The proof can be done by introducing restriction on the operator in several cases. The concepts in time scale version such as time scales calculus will be used that allows to unify and extend many problems from the theories of differential and of difference equations. In addition, using chain rule, and some properties of multiple integrals on time scales, some theorems of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of hardy, inequality of coposon, steklov operator

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Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

Procedia PDF Downloads 53

Authors: Mmatladi D. Mnguni, Mustapha Mohammed, George Y. Mahama, Alhassan L. Abdulai, Felix D. Dakora

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Industrial-based nitrogen (N) fertilizers are justifiably credited for the current state of food production across the globe, but their continued use is not sustainable and has an adverse effect on the environment. The search for greener and sustainable technologies has led to an increase in exploiting biological systems such as legumes and organic amendments for plant growth promotion in cropping systems. Although the benefits of legume rotation with cereal crops have been documented, the full benefits of soybean-sorghum rotation systems have not been properly evaluated in Africa. This study explored the benefits of soybean-sorghum rotation through assessing N₂ fixation and water-use efficiency of soybean in rotation with sorghum with and without organic and inorganic amendments. The field trials were conducted from 2017 to 2020. Sorghum was grown on plots previously cultivated to soybean and vice versa. The succeeding sorghum crop received fertilizer amendments [organic fertilizer (5 tons/ha as poultry litter, OF); inorganic fertilizer (80N-60P-60K) IF; organic + inorganic fertilizer (OF+IF); half organic + inorganic fertilizer (HIF+OF); organic + half inorganic fertilizer (OF+HIF); half organic + half inorganic (HOF+HIF) and control] and was arranged in a randomized complete block design. The soybean crop succeeding fertilized sorghum received a blanket application of triple superphosphate at 26 kg P ha⁻¹. Nitrogen fixation and water-use efficiency were respectively assessed at the flowering stage using the ¹⁵N and ¹³C natural abundance techniques. The results showed that the shoot dry matter of soybean plants supplied with HOF+HIF was much higher (43.20 g plant-1), followed by OF+HIF (36.45 g plant⁻¹), and HOF+IF (33.50 g plant⁻¹). Shoot N concentration ranged from 1.60 to 1.66%, and total N content from 339 to 691 mg N plant⁻¹. The δ¹⁵N values of soybean shoots ranged from -1.17‰ to -0.64‰, with plants growing on plots previously treated to HOF+HIF exhibiting much higher δ¹⁵N values, and hence lower percent N derived from N₂ fixation (%Ndfa). Shoot %Ndfa values varied from 70 to 82%. The high %Ndfa values obtained in this study suggest that the previous year’s organic and inorganic fertilizer amendments to sorghum did not inhibit N₂ fixation in the following soybean crop. The amount of N-fixed by soybean ranged from 106 to 197 kg N ha⁻¹. The treatments showed marked variations in carbon (C) content, with HOF+HIF treatment recording the highest C content. Although water-use efficiency varied from -29.32‰ to -27.85‰, shoot water-use efficiency, C concentration, and C:N ratio were not altered by previous fertilizer application to sorghum. This study provides strong evidence that previous HOF+HIF sorghum residues can enhance N nutrition and water-use efficiency in nodulated soybean.

Keywords: ¹³C and ¹⁵N natural abundance, N-fixed, organic and inorganic fertilizer amendments, shoot %Ndfa

Procedia PDF Downloads 146

Authors: Amparo Camacho

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ABET accredited programs must assess the development of student learning outcomes (SOs) in engineering programs. Different institutions implement different strategies for this assessment, and they are usually designed “in house.” This paper presents a proposal for including standardized tests to complement the ABET assessment model in an engineering college made up of six distinct engineering programs. The engineering college formulated a model of quality assurance in education to be implemented throughout the six engineering programs to regularly assess and evaluate the achievement of SOs in each program offered. The model uses diverse techniques and sources of data to assess student performance and to implement actions of improvement based on the results of this assessment. The model is called “Assessment Process Model” and it includes SOs A through K, as defined by ABET. SOs can be divided into two categories: “hard skills” and “professional skills” (soft skills). The first includes abilities, such as: applying knowledge of mathematics, science, and engineering and designing and conducting experiments, as well as analyzing and interpreting data. The second category, “professional skills”, includes communicating effectively, and understanding professional and ethnical responsibility. Within the Assessment Process Model, various tools were used to assess SOs, related to both “hard” as well as “soft” skills. The assessment tools designed included: rubrics, surveys, questionnaires, and portfolios. In addition to these instruments, the Engineering College decided to use tools that systematically gather consistent quantitative data. For this reason, an in-house exam was designed and implemented, based on the curriculum of each program. Even though this exam was administered during various academic periods, it is not currently considered standardized. In 2017, the Engineering College included three standardized tests: one to assess mathematical and scientific reasoning and two more to assess reading and writing abilities. With these exams, the college hopes to obtain complementary information that can help better measure the development of both hard and soft skills of students in the different engineering programs. In the first semester of 2017, the three exams were given to three sample groups of students from the six different engineering programs. Students in the sample groups were either from the first, fifth, and tenth semester cohorts. At the time of submission of this paper, the engineering college has descriptive statistical data and is working with various statisticians to have a more in-depth and detailed analysis of the sample group of students’ achievement on the three exams. The overall objective of including standardized exams in the assessment model is to identify more precisely the least developed SOs in order to define and implement educational strategies necessary for students to achieve them in each engineering program.

Keywords: assessment, hard skills, soft skills, standardized tests

Procedia PDF Downloads 268

Authors: S. Trafela, X. Xua, K. Zuzek Rozmana

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In this study, we used an accurate and precise method to measure the electrochemically active surface areas (Aecsa) of nickel electrodes. Calculated Aecsa is really important for the evaluation of an electro-catalyst’s activity in electrochemical reaction of different organic compounds. The method involves the electrochemical formation of Ni(OH)₂ and NiOOH in the presence of adsorbed oxalate in alkaline media. The studies were carried out using cyclic voltammetry with polycrystalline nickel as a reference material and electrodeposited nickel nanowires, homogeneous and heterogeneous nickel films. From cyclic voltammograms, the charge (Q) values for the formation of Ni(OH)₂ and NiOOH surface oxides were calculated under various conditions. At sufficiently fast potential scan rates (200 mV s⁻¹), the adsorbed oxalate limits the growth of the surface hydroxides to a monolayer. Although the Ni(OH)₂/NiOOH oxidation peak overlaps with the oxygen evolution reaction, in the reverse scan, the NiOOH/ Ni(OH)₂ reduction peak is well-separated from other electrochemical processes and can be easily integrated. The values of these integrals were used to correlate experimentally measured charge density with an electrochemically active surface layer. The Aecsa of the nickel nanowires, homogeneous and heterogeneous nickel films were calculated to be Aecsa-NiNWs = 4.2066 ± 0.0472 cm², Aecsa-homNi = 1.7175 ± 0.0503 cm² and Aecsa-hetNi = 2.1862 ± 0.0154 cm². These valuable results were expanded and used in electrochemical studies of formaldehyde oxidation. As mentioned nickel nanowires, heterogeneous and homogeneous nickel films were used as simple and efficient sensor for formaldehyde detection. For this purpose, electrodeposited nickel electrodes were modified in 0.1 mol L⁻¹ solution of KOH in order to expect electrochemical activity towards formaldehyde. The investigation of the electrochemical behavior of formaldehyde oxidation in 0.1 mol L⁻¹ NaOH solution at the surface of modified nickel nanowires, homogeneous and heterogeneous nickel films were carried out by means of electrochemical techniques such as cyclic voltammetric and chronoamperometric methods. From investigations of effect of different formaldehyde concentrations (from 0.001 to 0.1 mol L⁻¹) on electrochemical signal - current we provided catalysis mechanism of formaldehyde oxidation, detection limit and sensitivity of nickel electrodes. The results indicated that nickel electrodes participate directly in the electrocatalytic oxidation of formaldehyde. In the overall reaction, formaldehyde in alkaline aqueous solution exists predominantly in form of CH₂(OH)O⁻, which is oxidized to CH₂(O)O⁻. Taking into account the determined (Aecsa) values we have been able to calculate the sensitivities: 7 mA mol L⁻¹ cm⁻² for nickel nanowires, 3.5 mA mol L⁻¹ cm⁻² for heterogeneous nickel film and 2 mA mol L⁻¹ cm⁻² for heterogeneous nickel film. The detection limit was 0.2 mM for nickel nanowires, 0.5 mM for porous Ni film and 0.8 mM for homogeneous Ni film. All of these results make nickel electrodes capable for further applications.

Keywords: electrochemically active surface areas, nickel electrodes, formaldehyde, electrocatalytic oxidation

Procedia PDF Downloads 143

Authors: Y. Roumila, D. Meziani, R. Bagtache, K. Abdmeziem, M. Trari

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Heterogeneous photocatalysis over semiconductors has proved its effectiveness in the treatment of wastewaters since it works under soft conditions. It has emerged as a promising technique, giving rise to less toxic effluents and offering the opportunity of using sunlight as a sustainable and renewable source of energy. Many compounds have been used as photocatalysts. Though synthesized ones are intensively used, they remain expensive, and their synthesis involves special conditions. We thus thought of implementing a natural material, a phosphate ore, due to its low cost and great availability. Our work is devoted to the removal of hazardous organic pollutants, which cause several environmental problems and health risks. Among them, dye pollutants occupy a large place. This work relates to the study of the photodegradation of methyl violet (MV) and rhodamine B (RhB), in single and binary systems, under UV light and sunlight irradiation. Methyl violet is a triarylmethane dye, while RhB is a heteropolyaromatic dye belonging to the Xanthene family. In the first part of this work, the natural compound was characterized using several physicochemical and photo-electrochemical (PEC) techniques: X-Ray diffraction, chemical, and thermal analyses scanning electron microscopy, UV-Vis diffuse reflectance measurements, and FTIR spectroscopy. The electrochemical and photoelectrochemical studies were performed with a Voltalab PGZ 301 potentiostat/galvanostat at room temperature. The structure of the phosphate material was well characterized. The photo-electrochemical (PEC) properties are crucial for drawing the energy band diagram, in order to suggest the formation of radicals and the reactions involved in the dyes photo-oxidation mechanism. The PEC characterization of the natural phosphate was investigated in neutral solution (Na₂SO₄, 0.5 M). The study revealed the semiconducting behavior of the phosphate rock. Indeed, the thermal evolution of the electrical conductivity was well fitted by an exponential type law, and the electrical conductivity increases with raising the temperature. The Mott–Schottky plot and current-potential J(V) curves recorded in the dark and under illumination clearly indicate n-type behavior. From the results of photocatalysis, in single solutions, the changes in MV and RhB absorbance in the function of time show that practically all of the MV was removed after 240 mn irradiation. For RhB, the complete degradation was achieved after 330 mn. This is due to its complex and resistant structure. In binary systems, it is only after 120 mn that RhB begins to be slowly removed, while about 60% of MV is already degraded. Once nearly all of the content of MV in the solution has disappeared (after about 250 mn), the remaining RhB is degraded rapidly. This behaviour is different from that observed in single solutions where both dyes are degraded since the first minutes of irradiation.

Keywords: environment, organic pollutant, phosphate ore, photodegradation

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Authors: I. Inuaeyen, L. Phil, O. Eni

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Fossil fuels have been the main source of global energy for many decades, accounting for about 80% of global energy need. This is beginning to change however with increasing concern about greenhouse gas emissions which comes mostly from fossil fuel combustion. Greenhouse gases such as carbon dioxide are responsible for stimulating climate change. As a result, there has been shift towards more clean and renewable energy sources of energy as a strategy for stemming greenhouse gas emission into the atmosphere. The production of bio-products such as bio-fuel, bio-electricity, bio-chemicals, and bio-heat etc. using biomass materials in accordance with the bio-refinery concept holds a great potential for reducing high dependence on fossil fuel and their resources. The bio-refinery concept promotes efficient utilisation of biomass material for the simultaneous production of a variety of products in order to minimize or eliminate waste materials. This will ultimately reduce greenhouse gas emissions into the environment. In Nigeria, cassava solid waste from cassava processing facilities has been identified as a vital feedstock for bio-refinery process. Cassava is generally a staple food in Nigeria and one of the most widely cultivated foodstuff by farmers across Nigeria. As a result, there is an abundant supply of cassava waste in Nigeria. In this study, the aim is to explore opportunities for converting cassava waste to a range of bio-products such as butanol, ethanol, electricity, heat, methanol, furfural etc. using a combination of biochemical, thermochemical and chemical conversion routes. . The best process scenario will be identified through the evaluation of economic analysis, energy efficiency, life cycle analysis and social impact. The study will be carried out by developing a model representing different process options for cassava waste conversion to useful products. The model will be developed using Aspen Plus process simulation software. Process economic analysis will be done using Aspen Icarus software. So far, comprehensive survey of literature has been conducted. This includes studies on conversion of cassava solid waste to a variety of bio-products using different conversion techniques, cassava waste production in Nigeria, modelling and simulation of waste conversion to useful products among others. Also, statistical distribution of cassava solid waste production in Nigeria has been established and key literatures with useful parameters for developing different cassava waste conversion process has been identified. In the future work, detailed modelling of the different process scenarios will be carried out and the models validated using data from literature and demonstration plants. A techno-economic comparison of the various process scenarios will be carried out to identify the best scenario using process economics, life cycle analysis, energy efficiency and social impact as the performance indexes.

Keywords: bio-refinery, cassava waste, energy, process modelling

Procedia PDF Downloads 351

Authors: Sabrina Neururer, Marco Schweitzer, Werner Hackl, Bernhard Tilg, Patrick Raudaschl, Andreas Huber, Bernhard Pfeifer

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History and the current outbreak of Covid-19 have shown the deadly potential of infectious diseases. However, infectious diseases also have a serious impact on areas other than health and healthcare, such as the economy or social life. These areas are strongly codependent. Therefore, disease control measures, such as social distancing, quarantines, curfews, or lockdowns, have to be adopted in a very considerate manner. Infectious disease modeling can support policy and decision-makers with adequate information regarding the dynamics of the pandemic and therefore assist in planning and enforcing appropriate measures that will prevent the healthcare system from collapsing. In this work, an agent-based simulation package named “survival” for simulating infectious diseases is presented. A special focus is put on SARS-Cov-2. The presented simulation package was used in Austria to model the SARS-Cov-2 outbreak from the beginning of 2020. Agent-based modeling is a relatively recent modeling approach. Since our world is getting more and more complex, the complexity of the underlying systems is also increasing. The development of tools and frameworks and increasing computational power advance the application of agent-based models. For parametrizing the presented model, different data sources, such as known infections, wastewater virus load, blood donor antibodies, circulating virus variants and the used capacity for hospitalization, as well as the availability of medical materials like ventilators, were integrated with a database system and used. The simulation result of the model was used for predicting the dynamics and the possible outcomes and was used by the health authorities to decide on the measures to be taken in order to control the pandemic situation. The survival package was implemented in the programming language Java and the analytics were performed with R Studio. During the first run in March 2020, the simulation showed that without measures other than individual personal behavior and appropriate medication, the death toll would have been about 27 million people worldwide within the first year. The model predicted the hospitalization rates (standard and intensive care) for Tyrol and South Tyrol with an accuracy of about 1.5% average error. They were calculated to provide 10-days forecasts. The state government and the hospitals were provided with the 10-days models to support their decision-making. This ensured that standard care was maintained for as long as possible without restrictions. Furthermore, various measures were estimated and thereafter enforced. Among other things, communities were quarantined based on the calculations while, in accordance with the calculations, the curfews for the entire population were reduced. With this framework, which is used in the national crisis team of the Austrian province of Tyrol, a very accurate model could be created on the federal state level as well as on the district and municipal level, which was able to provide decision-makers with a solid information basis. This framework can be transferred to various infectious diseases and thus can be used as a basis for future monitoring.

Keywords: modelling, simulation, agent-based, SARS-Cov-2, COVID-19

Procedia PDF Downloads 158

Authors: Eric Bang

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Interactions between receptors and ligands are crucial for many essential biological processes, including neurotransmission and metabolism. Ligand-receptor analyses that examine cell behavior and interactions often utilize cell type-specific RNA expressions from single-cell RNA sequencing (scRNA-seq) data. Using CellPhoneDB, a public repository consisting of ligands, receptors, and ligand-receptor interactions, the cell-cell interactions were explored in a specific scRNA-seq dataset from kidney tissue and portrayed the results with dot plots and heat maps. Depending on the type of cell, each ligand-receptor pair was aligned with the interacting cell type and calculated the positori probabilities of these associations, with corresponding P values reflecting average expression values between the triads and their significance. Using single-cell data (sample kidney cell references), genes in the dataset were cross-referenced with ones in the existing CellPhoneDB dataset. For example, a gene such as Pleiotrophin (PTN) present in the single-cell data also needed to be present in the CellPhoneDB dataset. Using the single-cell transcriptomics data via slide-seq and reference data, the CellPhoneDB program defines cell types and plots them in different formats, with the two main ones being dot plots and heat map plots. The dot plot displays derived measures of the cell to cell interaction scores and p values. For the dot plot, each row shows a ligand-receptor pair, and each column shows the two interacting cell types. CellPhoneDB defines interactions and interaction levels from the gene expression level, so since the p-value is on a -log10 scale, the larger dots represent more significant interactions. By performing an interaction analysis, a significant interaction was discovered for myeloid and T-cell ligand-receptor pairs, including those between Secreted Phosphoprotein 1 (SPP1) and Fibronectin 1 (FN1), which is consistent with previous findings. It was proposed that an effective protocol would involve a filtration step where cell types would be filtered out, depending on which ligand-receptor pair is activated in that part of the tissue, as well as the incorporation of the CellPhoneDB data in a streamlined workflow pipeline. The filtration step would be in the form of a Python script that expedites the manual process necessary for dataset filtration. Being in Python allows it to be integrated with the CellPhoneDB dataset for future workflow analysis. The manual process involves filtering cell types based on what ligand/receptor pair is activated in kidney cells. One limitation of this would be the fact that some pairings are activated in multiple cells at a time, so the manual manipulation of the data is reflected prior to analysis. Using the filtration script, accurate sorting is incorporated into the CellPhoneDB database rather than waiting until the output is produced and then subsequently applying spatial data. It was envisioned that this would reveal wherein the cell various ligands and receptors are interacting with different cell types, allowing for easier identification of which cells are being impacted and why, for the purpose of disease treatment. The hope is this new computational method utilizing spatially explicit ligand-receptor association data can be used to uncover previously unknown specific interactions within kidney tissue.

Keywords: bioinformatics, Ligands, kidney tissue, receptors, spatial transcriptome

Procedia PDF Downloads 124

Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

Procedia PDF Downloads 104

Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

Procedia PDF Downloads 387

Authors: Sahar Nasr, Lin Li, Edwin Wang

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Bladder cancer (BLCA) is known as the 13th cause of death among cancer patients worldwide, and ~575,000 new BLCA cases are diagnosed each year. Urothelial carcinoma (UC) is the most prevalent subtype among BLCA patients, which can be categorized into muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC). Currently, various therapeutic options are available for UC patients, including (1) transurethral resection followed by intravesical instillation of chemotherapeutics or Bacillus Calmette-Guérin for NMIBC patients, (2) neoadjuvant platinum-based chemotherapy (NAC) plus radical cystectomy is the standard of care for localized MIBC patients, and (3) systematic chemotherapy for metastatic UC. However, conventional treatments may lead to several challenges for treating patients. As an illustration, some patients may suffer from recurrence of the disease after the first line of treatment. Recently, immune checkpoint therapy (ICT) has been introduced as an alternative treatment strategy for the first or second line of treatment in advanced or metastatic BLCA patients. Although ICT showed lucrative results for a fraction of BLCA patients, ~80% of patients were not responsive to it. Therefore, novel treatment methods are required to augment the ICI response rate within BLCA patients. It has been shown that the infiltration of T-cells into the tumor microenvironment (TME) is positively correlated with the response to ICT within cancerous patients. Therefore, the goal of this study is to enhance the infiltration of cytotoxic T-cells into TME through the identification of target genes within the tumor that are responsible for the non-T-cell inflamed TME and their inhibition. BLCA bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and immune score for TCGA samples were used to determine the Pearson correlation score between the expression of different genes and immune score for each sample. The genes with strong negative correlations were selected (r < -0.2). Thereafter, the correlation between the expression of each gene and survival in BLCA patients was calculated using the TCGA data and Cox regression method. The genes that are common in both selected gene lists were chosen for further analysis. Afterward, BLCA bulk and single-cell RNA-sequencing data were ranked based on the expression of each selected gene and the top and bottom 25% samples were used for pathway enrichment analysis. If the pathways related to the T-cell infiltration (e.g., antigen presentation, interferon, or chemokine pathways) were enriched within the low-expression group, the gene was included for downstream analysis. Finally, the selected genes will be used to calculate the correlation between their expression and the infiltration rate of the activated CD+8 T-cells, natural killer cells and the activated dendric cells. A list of potential target genes has been identified and ranked based on the above-mentioned analysis and criteria. SUN-1 got the highest score within the gene list and other identified genes in the literature as benchmarks. In conclusion, inhibition of SUN1 may increase the tumor-infiltrating lymphocytes and the efficacy of ICI in BLCA patients. BLCA tumor cells with and without SUN-1 CRISPR/Cas9 knockout will be injected into the syngeneic mouse model to validate the predicted SUN-1 effect on increasing tumor-infiltrating lymphocytes.

Keywords: data analysis, gene expression analysis, gene identification, immunoinformatic, functional genomics, transcriptomics

Procedia PDF Downloads 139

Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

Procedia PDF Downloads 51

Authors: Saqib Aziz, Brad Alexander, Christoph Gengnagel, Stefan Weinzierl

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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full-scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the building information modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit, the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models, which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: acoustical design, additive manufacturing, computational design, multimodal optimization

Procedia PDF Downloads 142

Authors: Neha Batra Bali, Monika Tomar, Vinay Gupta

Abstract:

A reagentless biosensor for detection of urea based on ZnO-CuO composite thin film is presented in following work. Biosensors have immense potential for varied applications ranging from environmental to clinical testing, health care, and cell analysis. Immense growth in the field of biosensors is due to the huge requirement in today’s world to develop techniques which are both cost effective and accurate for prevention of disease manifestation. The human body comprises of numerous biomolecules which in their optimum levels are essential for functioning. However mismanaged levels of these biomolecules result in major health issues. Urea is one of the key biomolecules of interest. Its estimation is of paramount significance not only for healthcare sector but also from environmental perspectives. If level of urea in human blood/serum is abnormal, i.e., above or below physiological range (15-40mg/dl)), it may lead to diseases like renal failure, hepatic failure, nephritic syndrome, cachexia, urinary tract obstruction, dehydration, shock, burns and gastrointestinal, etc. Various metal nanoparticles, conducting polymer, metal oxide thin films, etc. have been exploited to act as matrix to immobilize urease to fabricate urea biosensor. Amongst them, Zinc Oxide (ZnO), a semiconductor metal oxide with a wide band gap is of immense interest as an efficient matrix in biosensors by virtue of its natural abundance, biocompatibility, good electron communication feature and high isoelectric point (9.5). In spite of being such an attractive candidate, ZnO does not possess a redox couple of its own which necessitates the use of electroactive mediators for electron transfer between the enzyme and the electrode, thereby causing hindrance in realization of integrated and implantable biosensor. In the present work, an effort has been made to fabricate a matrix based on ZnO-CuO composite prepared by pulsed laser deposition (PLD) technique in order to incorporate redox properties in ZnO matrix and to utilize the same for reagentless biosensing applications. The prepared bioelectrode Urs/(ZnO-CuO)/ITO/glass exhibits high sensitivity (70µAmM⁻¹cm⁻²) for detection of urea (5-200 mg/dl) with high stability (shelf life ˃ 10 weeks) and good selectivity (interference ˂ 4%). The enhanced sensing response obtained for composite matrix is attributed to the efficient electron exchange between ZnO-CuO matrix and immobilized enzymes, and subsequently fast transfer of generated electrons to the electrode via matrix. The response is encouraging for fabricating reagentless urea biosensor based on ZnO-CuO matrix.

Keywords: biosensor, reagentless, urea, ZnO-CuO composite

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Authors: Maryam Mohammadi, Mohammadjavad Mahdavinejad, Mojtaba Ansari

Abstract:

The main driving force for increasing movement towards the design of High-Performance Buildings (HPB) are building codes and rating systems that address the various components of the building and their impact on the environment and energy conservation through various methods like prescriptive methods or simulation-based approaches. The methods and tools developed to meet these needs, which are often based on building performance simulation tools (BPST), have limitations in terms of compatibility with the integrated design process (IDP) and HPB design, as well as use by architects in the early stages of design (when the most important decisions are made). To overcome these limitations in recent years, efforts have been made to develop Design Decision Support Systems, which are often based on artificial intelligence. Numerous needs and steps for designing and developing a Decision Support System (DSS), which complies with the early stages of energy-efficient architecture design -consisting of combinations of different methods in an integrated package- have been listed in the literature. While various review studies have been conducted in connection with each of these techniques (such as optimizations, sensitivity and uncertainty analysis, etc.) and their integration of them with specific targets; this article is a critical and holistic review of the researches which leads to the development of applicable systems or introduction of a comprehensive framework for developing models complies with the IDP. Information resources such as Science Direct and Google Scholar are searched using specific keywords and the results are divided into two main categories: Simulation-based DSSs and Meta-simulation-based DSSs. The strengths and limitations of different models are highlighted, two general conceptual models are introduced for each category and the degree of compliance of these models with the IDP Framework is discussed. The research shows movement towards Multi-Level of Development (MOD) models, well combined with early stages of integrated design (schematic design stage and design development stage), which are heuristic, hybrid and Meta-simulation-based, relies on Big-real Data (like Building Energy Management Systems Data or Web data). Obtaining, using and combining of these data with simulation data to create models with higher uncertainty, more dynamic and more sensitive to context and culture models, as well as models that can generate economy-energy-efficient design scenarios using local data (to be more harmonized with circular economy principles), are important research areas in this field. The results of this study are a roadmap for researchers and developers of these tools.

Keywords: integrated design process, design decision support system, meta-simulation based, early stage, big data, energy efficiency

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Authors: Robert Pellerin, Michel Gamache, Remi Trudeau, Nathalie Perrier

Abstract:

The context of large engineering projects is particularly favorable to the appearance of engineering changes and contractual modifications. These elements are potential causes for claims. In this paper, we investigate one of the critical components of the claim management process: the calculation of the impacts of changes in terms of losses of productivity due to the need to accelerate some project activities. When project changes are initiated, delays can arise. Indeed, project activities are often executed in fast-tracking in an attempt to respect the completion date. But the acceleration of project execution and the resulting rework can entail important costs as well as induce productivity losses. In the past, numerous methods have been proposed to quantify the duration of delays, the gains achieved by project acceleration, and the loss of productivity. The calculation related to those changes can be divided into two categories: direct cost and indirect cost. The direct cost is easily quantifiable as opposed to indirect costs which are rarely taken into account during the calculation of the cost of an engineering change or contract modification despite several research projects have been made on this subject. However, proposed models have not been accepted by companies yet, nor they have been accepted in court. Those models require extensive data and are often seen as too specific to be used for all projects. These techniques are also ignoring the resource constraints and the interdependencies between the causes of delays and the delays themselves. To resolve this issue, this research proposes a simulation model that mimics how major engineering changes or contract modifications are handled in large construction projects. The model replicates the use of overtime in a reactive scheduling mode in order to simulate the loss of productivity present when a project change occurs. Multiple tests were conducted to compare the results of the proposed simulation model with statistical analysis conducted by other researchers. Different scenarios were also conducted in order to determine the impact the number of activities, the time of occurrence of the change, the availability of resources, and the type of project changes on productivity loss. Our results demonstrate that the number of activities in the project is a critical variable influencing the productivity of a project. When changes occur, the presence of a large number of activities leads to a much lower productivity loss than a small number of activities. The speed of reducing productivity for 30-job projects is about 25 percent faster than the reduction speed for 120-job projects. The moment of occurrence of a change also shows a significant impact on productivity. Indeed, the sooner the change occurs, the lower the productivity of the labor force. The availability of resources also impacts the productivity of a project when a change is implemented. There is a higher loss of productivity when the amount of resources is restricted.

Keywords: engineering changes, indirect costs overtime, productivity, scheduling, simulation

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Authors: Mihai Palade, Gina Cecilia Pistol, Mariana Stancu, Veronica Chedea, Ionelia Taranu

Abstract:

Nutrition is an important determinant of general health status, with especially focus on prevention and/or attenuation of the inflammatory-associated pathologies. People with chronic kidney disease can experience chronic inflammation that can lead to cardiovascular disease and even an increased rate of death. There are important links between chronic kidney diseases, inflammation and nutritional strategies that may prevent or protect against undesirable inflammation and oxidative stress. The grape by-products either seeds or pomace are rich in polyphenols which may be beneficial in prevention of inflammatory, antioxidant and antimicrobial processes. As a model for studying the impact of grape seeds on renal inflammation and oxidative stress, we used in this study weaned piglets. After a feeding trial of 30 days with a control diet and an experimental diet containing 5% grape seed (GS), kidney samples were collected. In renal tissues were determined the expression and activity of important markers of immune respose and oxidative stress: pro-inflammatory cytokines (TNF-alpha, IL-1 beta, IL-6, IL-8, IFN-gamma), anti-inflammatory cytokines (IL-4, IL-10), anti-oxidant enzymes (catalase CAT, superoxide dismutase SOD, glutathione peroxidise GPx) and important mediators belonging to nuclear receptors (NF-kB1, Nrf-2 and PPAR-gamma). Gene expression was evaluated by qPCR, whereas protein concentration was determined using proteomic techniques (ELISA). The activity of anti-oxidant enzymes was determined using specific kits. Our results showed that GS enriched in polyphenols does not have effect on TNF-alpha, IL-6 and IL-1 beta gene expression and protein concentration in kidney. By contrast, the gene expression and protein level of IL-8 and IFN-gamma were decreased in GS kidney. Anti-inflammatory cytokines IL-4 and IL-10 gene levels were increased in kidneys collected from GS piglets in comparison with controls, with no modification of protein levels between the two groups. The activities of anti-oxidant enzymes CAT and GPx were increased in kidney by GS, whereas SOD activity was unmodified in comparison with control samples. Also, the GS diet was associated with no modulation of mRNAs for nuclear receptors NF-kB1, Nrf-2 and PPAR-gamma gene expressions in kidneys. In conclusion, our results demonstrated that GS enriched in bioactive compounds such polyphenols could modulate inflammation and oxidative stress markers in kidney tissues. Further studies are necessary to elucidate the mechanism of action of GS compounds in case kidney inflammation associated with oxidative stress, and signalling molecules involved in these mechanisms.

Keywords: animal model, kidney inflammation, oxidative stress, grape seed

Procedia PDF Downloads 280