Search results for: meta cognition

Authors: Kuni Vergauwen, Ivan P. J. Huijnen, Astrid Depuydt, Jasmine Van Regenmortel, Mira Meeus

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A lower activity level and imbalanced activity pattern are frequently observed in persons with chronic fatigue syndrome (CFS) / myalgic encephalomyelitis (ME) due to debilitating fatigue and post-exertional malaise (PEM). Identification of measurement instruments to evaluate the activity level and pattern is therefore important. The objective is to identify measurement instruments suited to evaluate the activity level and/or pattern in patients with CFS/ME and review their psychometric properties. A systematic literature search was performed in the electronic databases PubMed and Web of Science until 12 October 2016. Articles including relevant measurement instruments were identified and included for further analysis. The psychometric properties of relevant measurement instruments were extracted from the included articles and rated based on the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. The review was performed and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 49 articles and 15 unique measurement instruments were found, but only three instruments were evaluated in patients with CFS/ME: the Chronic Fatigue Syndrome-Activity Questionnaire (CFS-AQ), Activity Pattern Interview (API) and International Physical Activity Questionnaire-Short Form (IPAQ-SF), three self-report instruments measuring the physical activity level. The IPAQ-SF, CFS-AQ and API are all equally capable of evaluating the physical activity level, but none of the three measurement instruments are optimal to use. No studies about the psychometric properties of activity monitors in patients with CFS/ME were found, although they are often used as the gold standard to measure the physical activity pattern. More research is needed to evaluate the psychometric properties of existing instruments, including the use of activity monitors.

Keywords: chronic fatigue syndrome, data collection, physical activity, psychometrics

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Authors: Sweeti, Anoop Kant Godiyal, Neha Singh, Sneh Anand, B. K. Panigrahi, Jayasree Santhosh

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This work is about developing a tool for visualization and segmentation of Electroencephalograph (EEG) signals based on frequency domain features. Change in the frequency domain characteristics are correlated with change in mental state of the subject under study. Proposed algorithm provides a way to represent the change in the mental states using the different frequency band powers in form of segmented EEG signal. Many segmentation algorithms have been suggested in literature having application in brain computer interface, epilepsy and cognition studies that have been used for data classification. But the proposed method focusses mainly on the better presentation of signal and that’s why it could be a good utilization tool for clinician. Algorithm performs the basic filtering using band pass and notch filters in the range of 0.1-45 Hz. Advanced filtering is then performed by principal component analysis and wavelet transform based de-noising method. Frequency domain features are used for segmentation; considering the fact that the spectrum power of different frequency bands describes the mental state of the subject. Two sliding windows are further used for segmentation; one provides the time scale and other assigns the segmentation rule. The segmented data is displayed second by second successively with different color codes. Segment’s length can be selected as per need of the objective. Proposed algorithm has been tested on the EEG data set obtained from University of California in San Diego’s online data repository. Proposed tool gives a better visualization of the signal in form of segmented epochs of desired length representing the power spectrum variation in data. The algorithm is designed in such a way that it takes the data points with respect to the sampling frequency for each time frame and so it can be improved to use in real time visualization with desired epoch length.

Keywords: de-noising, multi-channel data, PCA, power spectra, segmentation

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Authors: David Polcari, Samuel C. Perry, Loredano Pollegioni, Matthias Geissler, Janine Mauzeroll

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ᴅ-serine acts as an endogenous co-agonist for N-methyl-ᴅ-aspartate receptors in neuronal synapses. This makes it a key component in the development and function of a healthy brain, especially given its role in several neurodegenerative diseases such as Alzheimer’s disease and dementia. Despite such clear research motivations, the primary site and mechanism of ᴅ-serine release is still currently unclear. For this reason, we are developing a biosensor for the detection of ᴅ-serine utilizing a microelectrode in combination with a ᴅ-amino acid oxidase enzyme, which produces stoichiometric quantities of hydrogen peroxide in response to ᴅ-serine. For the fabrication of a biosensor with good selectivity, we use a permselective poly(meta-phenylenediamine) film to ensure only the target molecule is reacted, according to the size exclusion principle. In this work, we investigated the effect of the electrodeposition conditions used on the biosensor’s response time and selectivity. Careful optimization of the fabrication process allowed for enhanced biosensor response time. This allowed for the real time sensing of ᴅ-serine in a bulk solution, and also provided in means to map the efflux of ᴅ-serine in real time. This was done using scanning electrochemical microscopy (SECM) with the optimized biosensor to measure localized release of ᴅ-serine from an agar filled glass capillary sealed in an epoxy puck, which acted as a model system. The SECM area scan simultaneously provided information regarding the rate of ᴅ-serine flux from the model substrate, as well as the size of the substrate itself. This SECM methodology, which provides high spatial and temporal resolution, could be useful to investigate the primary site and mechanism of ᴅ-serine release in other biological samples.

Keywords: ᴅ-serine, enzymatic biosensor, microelectrode, scanning electrochemical microscopy

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Authors: Marziye Hadian, Alireza Jabbari

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Background: Each year, tropical diseases affect large numbers of tropical or subtropical populations and give rise to irreparable financial and human damage. Among these diseases, some are known as Neglected Tropical Disease (NTD) that may cause unusual dangers; however, they have not been appropriately accounted for. Taking into account the priority of eradication of the disease, this study explored the causes of failure to eradicate neglected tropical diseases. Method: This study was a systematized review that was conducted in January 2021 on the articles related to neglected tropical diseases on databases of Web of Science, PubMed, Scopus, Science Direct, Ovid, Pro-Quest, and Google Scholar. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines as well as Critical Appraisal Skills Program (CASP) for articles and AACODS (Authority, Accuracy, Coverage, Objectivity, Date, Significance) for grey literature (provides five criteria for judging the quality of grey information) were integrated. Finding: The challenges in controlling and eradicating neglected tropical diseases in four general themes are as follows: shortcomings in disease management policies and programs, environmental challenges, executive challenges in policy disease and research field and 36 sub-themes. Conclusion: To achieve the goals of eradicating forgotten tropical diseases, it seems indispensable to free up financial, human and research resources, proper management of health infrastructure, attention to migrants and refugees, clear targeting, prioritization appropriate to local conditions and special attention to political and social developments. Reducing the number of diseases should free up resources for the management of neglected tropical diseases prone to epidemics as dengue, chikungunya and leishmaniasis. For the purpose of global support, targeting should be accurate.

Keywords: neglected tropical disease, NTD, preventive, eradication

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Authors: Annalakshmi G., Sakthivel Murugan S.

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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

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Authors: Darren Edwards, Thomas Pinna

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Background: Interoception and heart rate variability have been found to predict outcomes of mental health and well-being. However, these have usually been investigated independently of one another. Objectives: This review aimed to explore the associations between interoception and heart rate variability (HRV) with emotion regulation (ER) and ER strategies within the existing literature and utilizing systematic review methodology. Methods: The process of article retrieval and selection followed the preferred reporting items for systematic review and meta-analyses (PRISMA) guidelines. Databases PsychINFO, Web of Science, PubMed, CINAHL, and MEDLINE were scanned for papers published. Preliminary inclusion and exclusion criteria were specified following the patient, intervention, comparison, and outcome (PICO) framework, whilst the checklist for critical appraisal and data extraction for systematic reviews of prediction modeling studies (CHARMS) framework was used to help formulate the research question, and to critically assess for bias in the identified full-length articles. Results: 237 studies were identified after initial database searches. Of these, eight studies were included in the final selection. Six studies explored the associations between HRV and ER, whilst three investigated the associations between interoception and ER (one of which was included in the HRV selection too). Overall, the results seem to show that greater HRV and interoception are associated with better ER. Specifically, high parasympathetic activity largely predicted the use of adaptive ER strategies such as reappraisal, and better acceptance of emotions. High interoception, instead, was predictive of effective down-regulation of negative emotions and handling of social uncertainty, there was no association with any specific ER strategy. Conclusions: Awareness of one’s own bodily feelings and vagal activation seem to be of central importance for the effective regulation of emotional responses.

Keywords: emotional regulation, vagal tone, interoception, chronic conditions, health and well-being, psychological flexibility

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Authors: Seongjun Kim, Jinwooung Kim, Sung-Ah Kim

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The development of information and communication technology also affects human cognition and thinking, especially in the field of design, new techniques are being tried. In architecture, new design methodologies such as machine learning or data-driven design are being applied. In particular, these methodologies are used in analyzing the factors related to the value of real estate or analyzing the feasibility in the early planning stage of the apartment housing. However, since the value of apartment buildings is often determined by external factors such as location and traffic conditions, rather than the interior elements of buildings, data is rarely used in the design process. Therefore, although the technical conditions are provided, the internal elements of the apartment are difficult to apply the data-driven design in the design process of the apartment. As a result, the designers of apartment housing were forced to rely on designer experience or modular design alternatives rather than data-driven design at the design stage, resulting in a uniform arrangement of space in the apartment house. The purpose of this study is to propose a methodology to support the designers to design the apartment unit plan with high consumer preference by deriving the correlation and importance of the floor plan elements of the apartment preferred by the consumers through the machine learning and reflecting this information from the early design process. The data on the pre-sale competition rate and the elements of the floor plan are collected as data, and the correlation between pre-sale competition rate and independent variables is analyzed through machine learning. This analytical model can be used to review the apartment unit plan produced by the designer and to assist the designer. Therefore, it is possible to make a floor plan of apartment housing with high preference because it is possible to feedback apartment unit plan by using trained model when it is used in floor plan design of apartment housing.

Keywords: apartment unit plan, data-driven design, design methodology, machine learning

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Authors: Ramy Bakir

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Advancements in the field of nanoscience and nanotechnology have had a sweeping effect on the manufacturing industry in the last two decades, and have specifically allowed for the enhancement of a multitude of applications in the field of building technology. Research carried out in the architectural field in the past decade highlights how those enhancements have improved the structural and environmental performance of buildings, and/or how they developed the aesthetic value of façade or interior treatments. In developing countries, such as Egypt, the actual use of those nano-enhanced applications and their benefits rarely manifest. Hence this paper investigates the socio-technical relationship between the architectural design process and nanotechnology in Cairo using participant observation within an ethnographic study. The study focused on the socio-cultural context of an environmental design process in a specific design firm, and the role of nano-enhanced applications in it, and provided a thick description of the design decisions made within the preliminary stages of the design process of a residential building in Cairo, Egypt. Using Grounded Theory, and through the analysis and coding of the qualitative data collected, this paper was able to identify specific socio-cultural issues influencing individual architect cognition, clarifying how the context of the design process of the studied project affected the design team members’ responses to nano-enhanced materials. This paper presents those findings within a framework of the three identified statuses of response to nanotechnology and classifies the socio-cultural reasons influencing them. In doing so, the paper aims to shed more light on the relation between nanotechnology and architects in their natural environment, and hence allow both to benefit more from a clearer understanding of how the socio-cultural context, along with the benefits of using nanotechnology, influences the design decisions made.

Keywords: nanotechnology, design process, socio-cultural context, nano-enhanced applications

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Authors: Shruti Malviya, Chris Bowler

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Analysis of microbial eukaryotic diversity is fundamental to understanding ecosystems’ structure, biology, and ecology. Diatoms (Stramenopiles, Bacillariophyceae) are one of the most diverse and ecologically prominent groups of phytoplankton. This study was performed to enhance the understanding of global biodiversity patterns and structure of planktonic diatom communities across the world's oceans. We used the metabarcoding data set generated from the biological samples and associated environmental data collected during the Tara Oceans (2009-2013) global circumnavigation covering all major oceanic provinces. A total of ~18 million diatom V9-18S rDNA tags from 126 sampling stations, constituting 631 size-fractionated plankton communities were generated. Using ~250,000 unique diatom metabarcodes, the global diatom distribution and diversity across size classes, genus and ecological niches was assessed. Notably, our analysis revealed: (i) a new estimate of the total number of planktonic diatom species, (ii) a considerable unknown diversity and exceptionally high diversity in the open ocean, and (iii) complex diversity patterns across oceanic provinces. Also, co-occurrence of several ribotypes in locations separated by great geographic distances (equatorial stations) demonstrated a widespread but not ubiquitous distribution. This work provides a comprehensive perspective on diatom distribution and diversity in the world’s oceans and elaborates interconnections between associated theories and underlying drivers. It shows how meta-barcoding approaches can provide a framework to investigate environmental diversity at a global scale, which is deemed as an essential step in answering various ecological research questions. Consequently, this work also provides a reference point to explore how microbial communities will respond to environmental conditions.

Keywords: diatoms, Tara Oceans, biodiversity, metabarcoding

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Authors: Jawaher F. Alsharef, Abdullah A. Ghaddaf, Mohammed S. Alomari, Abdullah A. Al Qurashi, Ahmed S. Abdulhamid, Mohammed S. Alshehri, Majed Alosaimi

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Botulinum toxin type A (BTX-A) is the most popular therapeutic agent for muscle relaxation and pain control. Lately, BTX-A injection received great interest as a part of multimodal pain management for lower limb lengthening and deformity correction. This systematic review aimed to determine the role of BTX-A injection in pain management for during lower limb lengthening and/or deformity correction. We searched Medline, Embase, and CENTRAL. We included randomized controlled trials (RCTs) that compared the BTX-A injection to placebo for individuals undergoing lower limb lengthening and/or deformity correction. We sought to evaluate the following outcomes: pain on visual analogue scale (VAS), range of motion parameters, average opioid consumption, and adverse events. The standardized mean difference (SMD) was used to represent continuous outcomes while risk ratio (RR) was used to represent dichotomous outcomes. A total of 4 RCTs that enrolled 257 participants (337 limbs) deemed eligible. Adjuvant BTX-A injection showed a significant reduction in post-operative pain compared to placebo (SMD=–0.28, 95% CI –0.53 to –0.04). No difference was found between BTX-A injection and placebo in terms of range of motion parameters, average opioid consumption, or adverse events after surgical limb lengthening and/or deformity correction (RR= 0.77, 95% CI –0.58 to 1.03). Conclusions: Adjuvant BTX-A injection conferred a discernible reduction in post-operative pain during surgical limb lengthening and/or deformity without increasing the risk of adverse events.

Keywords: botulinum toxin type A, limb lengthening, distraction osteogenesis, deformity correction, pain management

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Authors: Jim Shih-Chiao Chin , Tsai Lin Hsu, Shui Lien Chen

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This article extends the relation between company’s employee and customers in market. According to the previous researches, most researchers analyzed and focused on customers’ brand perception. In the recently, some scholars star to explore the brand management from company viewpoint. The aim of this study is to explore whether consumers perception would be affected by the firm brand. This research would like to examine the relationship between individual consumers and corporate brands in the business-to-consumers sector. First, the study develops a framework that the connection with consumer and company. Second, this article uses three dimensions, brand knowledge, brand commitment, and brand equity to measure employees’ loyalty of brand and applies brand relationship quality to gauge the level of brand’s importance in consumer’s mind. This paper uses SPSS 20.0 and AMOS 20.0 to test consumers’ minds toward the brand equity which the company provides. There are totally 862 valid questionnaires returned, and 431 participants are consumers; the other 431 participants are employees. Those questionnaires are one-by-one to consumer and employee so those are 431 pairs questionnaires. Based on 431 pairs of consumers and company’s employees, analyzed results show that brand knowledge and brand commitment play important roles influencing brand equity. The results also demonstrate the extra-role brand equity positively impact on the brand relationship quality of consumers. In addition, the findings reveal that the company can improve brand relationship quality of consumers by enhancing extra-role brand equity. There is a sufficient evidence denote that brand relationship quality not only shows about the brand of customers’ thought but also implies company how to build the brand to impress on consumers. These findings provide the degree of the brand in consumers’ cognition. The brand-owner employee can reference the conclusion to creative new strategic to the next time or can be one of the company’s competitive advantages. Those results and conclusions are contributed to management practice and future.

Keywords: brand knowledge, brand commitment, brand equity, brand relationship quality

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Authors: Lai Gwen Chan, Yining Ong, Audrey Yoke Poh Wong

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Background. The efficacy of electroconvulsive therapy (ECT) as a form of treatment to a range of mental disorders is well-established. However, ECT is often associated with either temporary or persistent cognitive side-effects, resulting in the failure of wider prescription. Of which, retrograde amnesia is the most commonly reported cognitive side-effect. Most studies found a recalling deficit in autobiographical memories to be short-term, although a few have reported more persistent amnesic effects. Little is known about ECT-related amnesic effects in Asian population. Hence, this study aims to resolve conflicting findings, as well as to better elucidate the effects of ECT on cognitive functioning in a local sample. Method: 12 patients underwent bilateral ECT under the care of Psychological Medicine Department, Tan Tock Seng Hospital, Singapore. Participants’ cognition and level of functioning were assessed at four time-points: before ECT, between the third and fourth induced seizure, at the end of the whole course of ECT, and two months after the index course of ECT. Results: It was found that Global Assessment of Functioning scores increased significantly at the completion of ECT. Case-by-case analyses also revealed an overall improvement in Personal Semantic and Autobiographical memory two months after the index course of ECT. A transient dip in both personal semantic and autobiographical memory scores was observed in one participant between the third and fourth induced seizure, but subsequently resolved and showed better performance than at baseline. Conclusions: The findings of this study suggest that ECT is an effective form of treatment to alleviate the severity of symptoms of the diagnosis. ECT does not affect attention, language, executive functioning, personal semantic and autobiographical memory adversely. The findings suggest that Asian patients may respond to bilateral ECT differently from Western samples.

Keywords: electroconvulsive therapy (ECT), autobiographical memory, cognitive impairment, psychiatric disorder

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Authors: J. DeBoard, R. Dietrich, J. Hughes, K. Yurko, G. Harms

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Alzheimer’s disease (AD) is a predominant type of dementia and is likely a major cause of neural network impairment. The pathogenesis of this neurodegenerative disorder has yet to be fully elucidated. There are currently no known cures for the disease, and the best hope is to be able to detect it early enough to impede its progress. Beyond age and genetics, another prevalent risk factor for AD might be traumatic brain injury (TBI), which has similar neurodegenerative hallmarks. Our research focuses on obtaining information and methods to be able to predict when neurodegenerative effects might occur at a clinical level by observation of events at a cellular and molecular level in model mice. First, we wish to introduce our evidence that brain damage can be observed via brain imaging prior to the noticeable loss of neuromuscular control in model mice of AD. We then show our evidence that some blood biomarkers might be able to be early predictors of AD in the same model mice. Thus, we were interested to see if we might be able to predict which mice might show long-term neurodegenerative effects due to differing degrees of TBI and what level of TBI causes further damage and earlier death to the AD model mice. Upon application of TBIs via an apparatus to effectively induce extremely mild to mild TBIs, wild-type (WT) mice and AD mouse models were tested for cognition, neuromuscular control, olfactory ability, blood biomarkers, and brain imaging. Experiments are currently still in process, and more results are therefore forthcoming. Preliminary data suggest that neuromotor control diminishes as well as olfactory function for both AD and WT mice after the administration of five consecutive mild TBIs. Also, seizure activity increases significantly for both AD and WT after the administration of the five TBI treatment. If future data supports these findings, important implications about the effect of TBI on those at risk for AD might be possible.

Keywords: Alzheimer's disease, blood biomarker, neurodegeneration, neuromuscular control, olfaction, traumatic brain injury

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Authors: Liang Wang, Wei Zhang

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Nowadays, sustainable development has increasingly become an important research topic of engineering education. Existing research on Engineering Education for Sustainable Development (EESD) has highlighted the importance of perceptions for ethical responsibility to address sustainable development in practice. However, whether and how the professional engineering experience affects those perceptions has not been proved, especially in a Chinese context. Our study fills this gap by investigating the perceptions bias of EESD between experienced engineers and engineering students. We specifically examined what EESD means for experienced engineers and engineering students using a triple-dimensional model to understand if there are obvious differences between the two groups. Our goal is to make the benefits of these experiences more accessible in school context. The data (n=438) came from a questionnaire created and adapted from previously published studies containing 288 students from mechanical or civil engineering and 150 civil engineers with rich working experience, and the questionnaire was distributed during Fall 2020. T-test was used to find the difference in different dimensions between the two groups. The statistical results show that there is a significant difference in the perceptions of EESD between experienced engineers and inexperienced engineering students in China. Experienced engineers tend to consider sustainable development from ecological, economic, and social perspectives, while engineering students' answers focus more on ecology and ignore economic and social dimensions to some extend. The findings provide empirical evidence that professional experience is helpful to cultivate the cognition and ability of sustainable development in engineering education. The results of this work indicate that more practical content should be added to engineering education to promote sustainable development. In addition, for the design of engineering courses and professional practice systems for sustainable development, we should not only pay attention to the ecological aspects but also emphasize the coordination of ecological, economic, and socially sustainable development (e.g., engineer's ethical responsibility).

Keywords: engineering education, sustainable development, experienced engineers, engineering students

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Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

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Authors: R. R. Billones, N. Lukkahatai, L. N. Saligan

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Mindfulness based interventions (MBIs) have been used in medically unexplained symptoms (MUS). This systematic review describes the literature investigating the general effect of MBIs on MUS and identifies the effects of specific MBIs on specific MUS conditions. The preferred reporting items for systematic reviews and meta-analysis guidelines (PRISMA) and the modified Oxford quality scoring system (JADAD) were applied to the review, yielding an initial 1,556 articles. The search engines included PubMed, ScienceDirect, Web of Science, Scopus, EMBASE, and PsychINFO using the search terms: mindfulness, or mediations, or mindful or MBCT or MBSR and medically unexplained symptoms or MUS or fibromyalgia or FMS. A total of 24 articles were included in the final systematic review. MBIs showed large effects on socialization skills for chronic fatigue syndrome (d=0.65), anger in fibromyalgia (d=0.61), improvement of somatic symptoms (d=1.6) and sleep (d=1.12) for painful conditions, physical health for chronic back pain (d=0.51), and disease intensity for irritable bowel disease/syndrome (d=1.13). A manualized MBI that applies the four fundamental elements present in all types of interventions were critical to efficacy. These elements were psycho-education sessions specific to better understand the medical symptoms, the practice of awareness, the non-judgmental observance of the experience at the moment, and the compassion to ones’ self. The effectiveness of different mindfulness interventions necessitates giving attention to improve the gaps that were identified related to home-based practice monitoring, competency training of mindfulness teachers, and sound psychometric properties to measure the mindfulness practice.

Keywords: mindfulness-based interventions, medically unexplained symptoms, mindfulness-based cognitive therapy, mindfulness-based stress reduction, fibromyalgia, irritable bowel syndrome

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Authors: Ersilio Tushaj

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The efficient solution that satisfies the optimal condition is an important issue in the structural engineering design problem. The new codes of structural design consist in design methodology that looks after the exploitation of the total resources of the construction material. In recent years some non-deterministic or meta-heuristic structural optimization algorithms have been developed widely in the research community. These methods search the optimum condition starting from the simulation of a natural phenomenon, such as survival of the fittest, the immune system, swarm intelligence or the cooling process of molten metal through annealing. Among these techniques the most known are: the genetic algorithms, simulated annealing, evolution strategies, particle swarm optimization, tabu search, ant colony optimization, harmony search and big bang crunch optimization. In this study, five of these algorithms are applied for the optimum weight design of a steel truss structure with variable geometry but fixed topology. The design process selects optimum distances and size sections from a set of commercial steel profiles. In the formulation of the design problem are considered deflection limitations, buckling and allowable stress constraints. The approach is repeated starting from different initial populations. The design problem topology is taken from an existing steel structure. The optimization process helps the engineer to achieve good final solutions, avoiding the repetitive evaluation of alternative designs in a time consuming process. The algorithms used for the application, the results of the optimal solutions, the number of iterations and the minimal weight designs, will be reported in the paper. Based on these results, it would be estimated, the amount of the steel that could be saved by applying structural analysis combined with non-deterministic optimization methods.

Keywords: structural optimization, non-deterministic methods, truss structures, steel truss

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Authors: Indira Makhazhan, Azamat Taigarayev, Perizat Yerlan, Batyrbay Gulbike, Samal Abzhanova

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Aitys is a competitional performance of two or more poets creating instantly the lyrics of music concerning the social issues accompanied with the traditional instrument dombra. It is an unique music genre, because it is not practical to create music and lyrics spontaneous in anywhere else. This research study tends to approach to this particular music genre Aitys and identify its significance not only in the sense of the Kazakh cultural heritage, but also from the perspective of personal development as the improvisational , oratory, public performance skills within the ability to think critically over the social problems and represent them in convenient to public form. Through conducting this research, this paper aims to reveal the importance and beneficence of aitys in terms of both prevalence of cultural heritage and its function in personal development of the singer. In order to answer to the research question, we conducted a survey and an in-depth interview with the students of Nazarbayev University. In the survey it was asked to answer the general questions about aitys and its importance, whereas in the interview part, we asked their opinion on the importance of aitys in improving the personal skills. The results of findings was more surprising than it was expected. They agreed that the aitys lessons, workshops and concerts have high outcomes in terms improvements of improvisational, oratory, and leadership skills. Students of NU as a representors of young generation have shown a great interest in aitys, and even more interested in the topics/social issues, where the poets have to defend their usually controversial position. To conclude, the research study has focused on the importance of the aitys in personal development of different leadership skills. The given research lead us to think about the aitys as a part of cognitive musicology, where within the learning of music it represents the process of cognition as well.

Keywords: aitys, cultural heritage, Kazakh language, musicology, personal development

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Authors: Hadeel Seraj, Mohammed Khoshhal, Mustafa Alhamoud, Hassan Alhashim, Anas Alsaif, Amro Abukhashabah

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Central serous chorioretinopathy (CSCR) is an idiopathic retinal disease characterized by localized serous detachment of the neurosensory retina at the macula. To date, there is no high-quality evidence of recent updates on treating acute CSCR, focusing on photodynamic therapy (PDT) and anti-vascular endothelial growth factor (anti-VEGF). Hence, this review aims to systematically review the latest treatment strategies for acute CSCR. Methodology: The following electronic databases were used for a comprehensive and systematic literature review: MEDLINE, EMBASE, and Cochrane. In addition, we analyzed studies comparing PDT with placebo, anti-VEGF with placebo, or PDT with anti-VEGF in treating acute CSC eyes with no previous intervention. Results: Seven studies were included, with a total of 292 eyes. The overall positive results were significantly higher among patients who received PDT compared to control groups (OR = 7.96, 95% CI, 3.02 to 20.95, p < 0.001). The proportions of positive results were 81.0% and 97.1% among patients who received anti-VEGF and PDT, respectively, with no statistically significant differences between the groups. In addition, there were no significant differences between anti-VEGF and control groups. In contrast, PDT was significantly associated with lower recurrence odds than the control groups (OR = 0.12, 95% CI, 0.04 to 0.39, p = 0.042). Conclusion: According to our findings, PDT showed higher positive results than Anti-VEGF in acute CSCR. In addition, PDT was significantly associated with a lower recurrence rate than the control group. However, the analysis needs to be confirmed and updated by large-scale, well-designed RCTs.

Keywords: central serous chorioretinopathy, Acute CSCR, photodynamic therapy, anti-vascular endothelial growth factor

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Authors: Hammache Nadir

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The scientific study of human learning and memory is now more than 125 years old. Psychologists have conducted thousands of experiments, correlational analyses, and field studies during this time, in addition to other research conducted by those from neighboring fields. A huge knowledge base has been carefully built up over the decades. Given this backdrop, we may ask ourselves: What great changes in education have resulted from this huge research base? How has the scientific study of learning and memory changed practices in education from those of, say, a century ago? Have we succeeded in building a translational educational science to rival medical science (in which biological knowledge is translated into medical practice) or types of engineering (in which, e.g., basic knowledge in chemistry is translated into products through chemical engineering)? The answer, I am afraid, is rather mixed. Psychologists and psychological research have influenced educational practice, but in fits and starts. After all, some of the great founders of American psychology—William James, Edward L. Thorndike, John Dewey, and others—are also revered as important figures in the history of education. And some psychological research and ideas have made their way into education—for instance, computer-based cognitive tutors for some specific topics have been developed in recent years—and in years past, such practices as teaching machines, programmed learning, and, in higher education, the Keller Plan were all important. These older practices have not been sustained. Was that because they failed or because of a lack of systematic research showing they were effective? At any rate, in 2012, we cannot point to a well-developed translational educational science in which research about learning and memory, thinking and reasoning, and related topics is moved from the lab into controlled field trials (like clinical trials in medicine) and the tested techniques, if they succeed, are introduced into broad educational practice. We are just not there yet, and one question that arises is how we could achieve a translational educational science.

Keywords: affective, education, cognition, pshychology

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Authors: Huang Ying

Abstract:

The present study was to investigate factors affecting children's improvement through the first two years of elementary school on a population-based sample of children with autism in Taiwan. All the children were diagnosed with autism spectrum disorder (ASD) by clinical psychologists according to DSM-IV. Children's development was assessed by the Vineland Adaptive Behavior Scales-Chinese version (VABS-C) on the first and the third grade. Children's improvement was measured by the difference between the standardized total score of the third and the first year. In Taiwan, school-age children with special-education needs will be arranged into different classes, including normal classes (NC), resource classes (RC), and special classes (SC) by the government. Therefore, type of class was one of the independent variables. Moreover, as early intervention is considered to be crucial, the earliest age when intervention begins was collected from parents. Attention was also included in the analysis. Teachers were asked to evaluate children's attention with a 3-item Likert Scale. The frequency of paying attention to the class or the task was recorded and scores were summed up. Additionally, standardized scores of the VABS-C in the first grade were used as pretest scores representing children's developmental level at the beginning of elementary school. Multiple regression was conducted with improvement as the dependent variable. Results showed that children in special classes had smaller improvement compared to those in normal or resource classes. Attention positively predicted improvement yet the effect of earliest intervention age was not significant. Furthermore, scores in the first grade negatively predicted improvement, which indicated that children with higher developmental levels would make less progress in the following years. Results were to some degree consistent with previous findings through meta-analysis that the effectiveness of conventional intervention methods lacked sufficient evidence to support.

Keywords: attention, early intervention, elementary school, special education in Taiwan

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Authors: Atsebaha Gebrekidan Kahsay, Tsehaye Asmelash, Enquebaher Kassaye

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Background: Salmonella remains a global public health problem with a significant burden in sub-Saharan African countries. Human restricted cause of typhoid and paratyphoid fever are S. Typhi and S. Paratyphi, whereas S. Enteritidis and S. Typhimurium is the causative agent of invasive nontyphoidal diseases among humans and animals are their reservoir. The antibiotic resistance of Salmonella is another public health threat around the globe. To come up with full information about human and animal salmonellosis, we made a systematic review of the prevalence, serotypes, and antibiotic resistance of Salmonella in Ethiopia. Methods: This systematic review used Google Scholar and PubMed search engines to search articles from Ethiopia that were published in English in peer-reviewed international journals from 2010 to 2022. We used keywords to identify the intended research articles and used a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist to ensure the inclusion and exclusion criteria. Frequencies and percentages were analyzed using Microsoft Excel. Results: Two hundred seven published articles were searched, and 43 were selected for a systematic review, human (28) and animals (15). The prevalence of Salmonella in humans and animals was 434 (5.2%) and 641(10.1%), respectively. Fourteen serotypes were identified from animals, and S. Typhimurium was among the top five. Among the ciprofloxacin-resistant isolates in human studies, 16.7% was the highest, whereas, for ceftriaxone, 100% resistance was reported. Conclusions: The prevalence of Salmonella among diarrheic patients and food handlers (5.2%) was lower than the prevalence in food animals (10.1%). We did not find serotypes of Salmonella in human studies, although fourteen serotypes were included in food-animal studies, and S. Typhimurium was among the top five. Salmonella species from some human studies revealed a non-susceptibility to ceftriaxone. We recommend further study about invasive nontyphoidal Salmonella and predisposing factors among humans and animals in Ethiopia.

Keywords: antibiotic resistance, prevalence, systematic review, serotypes, Salmonella, Ethiopia

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Authors: Gertrude I. Hewapathirana, Loi A. Nguyen, Mohammed M. Mostafa

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Artificial intelligence (AI) technologies and tools are swiftly integrating into many functions of all organizations as a competitive drive to enhance innovations, productivity, efficiency, faster and precise decision making to keep up with rapid changes in the global business arena. Despite increasing research on AI technologies in production, manufacturing, and information management, AI in human resource disciplines is still lagging. Though a few research studies on HR informatics, recruitment, and HRM in general, how to integrate AI in other HR functional disciplines (e.g., compensation, training, mentoring and coaching, employee motivation) is rarely researched. Many inconsistencies of research hinder developing up-to-date knowledge on AI in HR disciplines. Therefore, exploring eight research questions, using bibliometric network analysis combined with a meta-analysis of published research literature. The authors attempt to generate knowledge on the role of AI in improving the efficiency of HR functional disciplines. To advance the knowledge for the benefit of researchers, academics, policymakers, and practitioners, the study highlights the types of AI innovations and outcomes, trends, gaps, themes and topics, fast-moving disciplines, key players, and future directions.AI in HR informatics in high tech firms is the dominant theme in many research publications. While there is increasing attention from researchers and practitioners, there are many gaps between the promise, potential, and real AI applications in HR disciplines. A higher knowledge gap raised many unanswered questions regarding legal, ethical, and morale aspects of AI in HR disciplines as well as the potential contributions of AI in HR disciplines that may guide future research directions. Though the study provides the most current knowledge, it is limited to peer-reviewed empirical, theoretical, and conceptual research publications stored in the WoS database. The implications for theory, practice, and future research are discussed.

Keywords: artificial intelligence, human resources, bibliometric analysis, research directions

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Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

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In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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Authors: Sarah Ullrich, Juliane Rolle, Christian Beste, Nicole Wolff

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Inhibition and cognitive flexibility are essential parts of executive functions in our daily lives, as they enable the avoidance of unwanted responses or selectively switch between mental processes to generate appropriate behavior. There is growing interest in improving inhibition and response selection through brief mindfulness-based meditations. Arguably, open-monitoring meditation (OMM) improves inhibitory and flexibility performance by optimizing cognitive control and information processing. Yet, the underlying neurophysiological processes have been poorly studied. Using the Simon-Go/Nogo paradigm, the present work examined the effect of a single 15-minute smartphone app-based OMM on inhibitory performance and response selection in meditation novices. We used both behavioral and neurophysiological measures (event-related potentials, ERPs) to investigate which subprocesses of response selection and inhibition are altered after OMM. The study was conducted in a randomized crossover design with N = 32 healthy adults. We thereby investigated Go and Nogo trials in the paradigm. The results show that as little as 15 minutes of OMM can improve response selection and inhibition at behavioral and neurophysiological levels. More specifically, OMM reduces the rate of false alarms, especially during Nogo trials regardless of congruency. It appears that OMM optimizes conflict processing and response inhibition compared to no meditation, also reflected in the ERP N2 and P3 time windows. The results may be explained by the meta control model, which argues in terms of a specific processing mode with increased flexibility and inclusive decision-making under OMM. Importantly, however, the effects of OMM were only evident when there was the prior experience with the task. It is likely that OMM provides more cognitive resources, as the amplitudes of these EKPs decreased. OMM novices seem to induce finer adjustments during conflict processing after familiarization with the task.

Keywords: EEG, inhibition, meditation, Simon Nogo

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Authors: Hiroko Komatsu, Kaori Yagasaki

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Background: Cancer-related cognitive impairment is a common problem seen in cancer patients undergoing chemotherapy. Physical activity may show beneficial effects on the cognitive function in such patients. Therefore, we have developed a self-directed home yoga program for cancer patients with cognitive symptoms during chemotherapy. This program involves a DVD presenting a combination of yoga courses based on patient preferences to be practiced at home. This study was performed to examine the feasibility of this program. In addition, we also examined changes in cognitive function and quality of life (QOL) in these patients participating in the program. Methods: This prospective feasibility study was conducted in a 500-bed general hospital in Tokyo, Japan. The study population consisted of breast cancer patients undergoing chemotherapy as the initial therapy. This feasibility study used a convenience sample with estimation of recruitment rate in a single facility with the availability of trained nurses and physicians to ensure safe yoga intervention. The aim of the intervention program was to improve cognitive function by means of both physical and mental activation via yoga, consisting of physical practice, breathing exercises, and meditation. Information on the yoga program was provided as a booklet, with an instructor-guided group yoga class during the orientation, and a self-directed home yoga program on DVD with yoga logs. Results: The recruitment rate was 44.7%, and the study population consisted of 18 women with a mean age of 43.9 years. This study showed high rates of retention, adherence, and acceptability of the yoga program. Improvements were only observed in the cognitive aspects of fatigue, and there were serious adverse events during the program. Conclusion: The self-directed home yoga program discussed here was both feasible and safe for breast cancer patients showing cognitive symptoms during chemotherapy. The patients also rated the program as useful, interesting, and satisfactory. Participation in the program was associated with improvements in cognitive fatigue but not cognitive function.

Keywords: yoga, cognition, breast cancer, chemotherapy, quality of life

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Authors: Aryan Sood, Shruti Pathak, Dipanshu Chaudhary, Shreyanshi, Yogesh Pal

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In this comprehensive meta-analysis, the study delves into the widespread issue of body shaming, revealing its pervasive impact on various aspects of human life and its profound implications for mental health. The paper first explores the origins of body shaming, including societal norms, media influences, and interpersonal dynamics. It highlights the various forms it takes and its detrimental effects on self-esteem, body image, and psychological well-being. Particularly among adolescents and teenagers in today's social media-driven world, the pressure to conform to idealized beauty standards is significant, leading to negative consequences for their development and health. The research emphasizes the long-lasting mental health effects of body shaming, including depression, body dysmorphia, low self-esteem, and eating disorders. The study also discusses the emergence of body positivity movements as a means to challenge societal norms and promote inclusivity and empathy. Furthermore, the research addresses body shaming in the workplace and presents strategies to combat it, stressing the importance of awareness campaigns, education, and policy changes. In conclusion, the study underscores the critical need for a culture of acceptance and support, the promotion of positive body image, and efforts to mitigate the severe mental health toll that body shaming takes on individuals and communities. Overall, this research provides a comprehensive overview of body shaming, its root causes, and its far-reaching impacts on mental health and well-being. It highlights the urgency of addressing this issue in various contexts, from adolescence to the workplace, and offers solutions, such as awareness campaigns and societal changes, to foster a more inclusive and empathetic future.

Keywords: body shaming, mental health, age, gender, societal norms, appearance-based discrimination, cyberbullying, self-esteem, social media, depression, acceptance

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Authors: Sandeep Goyal, Sandeep Saluja

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Natural antioxidants have major role in maintenance of health. Green tea extract principally contains epigallocatechin-3-gallate (EGCG), as its abundant antioxidant constituent. Green tea is consumed daily worldwide as antioxidant to combat CNS diseases and has traditional importance also. EGCG has neuroprotective potential in various animal models of Parkinson disease, Alzheimer’s disease etc. but its exact mechanism has not been ruled out. The present study has been designed to investigate the anti-inflammatory, antioxidant and mitochondrial modulating mechanism of neuroprotective effect of epigallocatechin-3-gallate against rodent model of rotenone induced Parkinson’s disease (PD). The behavioural alterations were assessed by using open field test apparatus, Chatilon’s grip strength test apparatus and elevated plus maze for determining the locomotor activity, grip strength and cognition respectively. Biochemically, various parameters to assess oxidative stress, neuroinflammation and neurochemical estimations were performed on rat brain homogenates. A histological examination of rat brain striatum was done to check the neurodegeneration. Epigallocatechin-3-gallate (EGCG) at 10 & 20 mg/kg, were investigated for their neuroprotective potential along with levodopa as a standard agent. Minocycline, a microglial activation inhibitor, was administered alone and in combination with EGCG. EGCG and minocycline produced ameliorative effect against rotenone induced PD like symptoms by significantly reduced behavioral, biochemical and histological alterations. Results of our study reveal the neuroprotective effect of EGCG and minocycline against rotenone induced PD. Results of our study indicate that EGCG exerted neuroprotective effect against rotenone induced PD via its antioxidant, anti-inflammatory and mitochondrial modulating mechanisms and substantiate its previously reported and traditional claims for its use in CNS diseases.

Keywords: antioxidants, neurotoxicity, rotenone, EGCG

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Authors: Yi-Hsiu Lai

Abstract:

The present study aimed to elucidate the nature of semantic processing in Chinese. Language and cognition related to the issue of aging are examined from the perspective of picture naming and category fluency tasks. Twenty Chinese-speaking adults (ranging from 25 to 45 years old) and twenty Chinese-speaking seniors (ranging from 65 to 75 years old) in Taiwan participated in this study. Each of them individually completed two tasks: a picture naming task and a category fluency task. Instruments for the naming task were sixty black-and-white pictures: thirty-five object and twenty-five action pictures. Category fluency task also consisted of two semantic categories – objects (or nouns) and actions (or verbs). Participants were asked to report as many items within a category as possible in one minute. Scores of action fluency and of object fluency were a summation of correct responses in these two categories. Category effects (actions vs. objects) and age effects were examined in these tasks. Objects were further divided into two major types: living objects and non-living objects. Actions were also categorized into two major types: action verbs and process verbs. Reaction time to each picture/question was additionally calculated and analyzed. Results of the category fluency task indicated that the content of information in Chinese seniors was comparatively deteriorated, thus producing smaller number of semantic-lexical items. Significant group difference was also found in the results of reaction time. Category Effect was significant for both Chinese adults and seniors in the semantic fluency task. Findings in the present study helped characterize the nature of semantic processing in Chinese-speaking adults and seniors and contributed to the issue of language and aging.

Keywords: semantic processing, aging, Chinese, category effects

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Authors: Joana Margarida Bôto, Belmira Neto, Vera Miguéis, Manuela Meireles, Ada Rocha

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The Mediterranean diet has been recognized as a sustainable model of living with benefits for the environment and human health. However, a complete assessment of its sustainability, encompassing all dimensions and aspects, to our best knowledge, has not yet been realized. This systematic literature review aimed to fill this gap by identifying and describing the indicators used to assess the sustainability of the Mediterranean diet, looking at several dimensions, and presenting the results from their application. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines methodology was used, and searches were conducted in PubMed, Scopus, Web of Science, and GreenFile. There were identified thirty-two articles evaluating the sustainability of the Mediterranean diet. The environmental impact was quantified in twenty-five of these studies, the nutritional quality was evaluated in seven studies, and the daily cost of the diet was assessed in twelve studies. A total of thirty-three indicators were identified and separated by four dimensions of sustainability, specifically, the environmental dimension (ten indicators, namely carbon, water, and ecological footprint), the nutritional dimension (eight indicators, namely Health score and Nutrient Rich Food Index), the economic dimension (one indicator, the dietary cost), the sociocultural dimension (six indicators – with no results). Only eight of the studies used combined indicators. The Mediterranean diet was considered in all articles as a sustainable dietary pattern with a lower impact than Western diets. The carbon footprint ranged between 0.9 and 6.88 kg CO₂/d per capita, the water footprint between 600 and 5280 m³/d per capita, and the ecological footprint between 2.8 and 53.42 m²/d per capita. The nutritional quality was high, obtaining 122 points using the Health score and 12.95 to 90.6 points using the Nutrient Rich Food Index. The cost of the Mediterranean diet did not significantly differ from other diets and varied between 3.33 and 14.42€/d per capita. A diverse approach to evaluating the sustainability of the Mediterranean diet was found.

Keywords: Mediterranean diet, sustainability, environmental indicators, nutritional indicators

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