Search results for: language function

Authors: Mariko Hara, Mari Aoki, Takako Ito, Masao Sugita

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Social distancing measures due to the COVID-19 crisis had a severe impact on music and art practices based in community settings. They had to re-think how to connect with their dispersed community using online tools. As the social distancing continues, there is an urgent need to investigate the possibilities of online community music and art practices. Are they sustainable actions that can have positive impacts on the community and the quality of lives of people over time? The Online Lindgren Café (hereafter ‘OLC’) is a monthly online literature event which started in June 2020. In the OLC, up to 14 members meet online to discuss the works of Astrid Lindgren and similar authors. Members come from various places in Japan and Norway, with a variety of expertise from music therapy, music education, psychotherapy, music sociology, storytelling, and theatre, and their family members join them. In these meetings, music and arts activities emerged in response to interests among the members. The resources and experiences of the members helped to develop these activities further. This paper first introduces one of the music and art activities in one specific event, a collaborative picture book-making with music, which was initiated and led by the second author. The third author chose the music, and the activity itself was recorded. This is followed by the description of a reflecting event, where the recording of the collaborative picture book-making activity was shared to facilitate further creations (drawings, haiku, and fabric weaving) as well as group reflections on the trajectories of the Online Lindgren Café. Finally, we will discuss the preliminary findings using the data collected at the reflecting event. Key findings suggest that the resource-driven approach of the OLC leveled the relationships among the intergenerational, multi-cultural, and interdisciplinary members. This enabled the members to set aside their professional and/or predominant identities, which allowed them to discover their own and others’ resources. The relaxed, unstructured, and liminal phenomenon at OLC can be regarded as a form of communitas, where members gain a sense of liberation and belonging in a different way from in-person communications. Participation from one’s home, as well as a video conferencing function that allowed the members to position themselves among the other participants in equal-sized windows, seems to have enabled members to feel safe to express themselves openly at the same time feel a sense of belonging. Furthermore, in the OLC, music and arts activities acted to inclusively connect and re-connect dispersed, intergenerational members with each other. For instance, in a music and drawing activity, music acted as a means for each member to engage in their own ‘drawing space’ while still feeling connected with the others. The positive experiences from these activities inspired the members to use similar approaches outside of the OLC. The finding suggests that, because of its resource-driven approach supported by the music and arts activities, the OLC could be developed further as a permeable and sustainable action even after any current social distancing measures are lifted.

Keywords: communitas, COVID-19, musical affordances, online community of practices, resource-driven approach

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Authors: Heichia Wang, Yalan Chao

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Social inequality is a persistent problem. One of the ways to solve this problem is through education. At present, vulnerable groups are often less geographically accessible to educational resources. However, compared with educational resources, communication equipment is easier for vulnerable groups. Now that information and communication technology (ICT) has entered the field of education, today we can accept the convenience that ICT provides in education, and the mobility that it brings makes learning independent of time and place. With mobile learning, teachers and students can start discussions in an online chat room without the limitations of time or place. However, because liquidity learning is quite convenient, people tend to solve problems in short online texts with lack of detailed information in a lack of convenient online environment to express ideas. Therefore, the ICT education environment may cause misunderstanding between teachers and students. Therefore, in order to better understand each other's views between teachers and students, this study aims to clarify the essays of the analysts and classify the students into several types of learning questions to clarify the views of teachers and students. In addition, this study attempts to extend the description of possible omissions in short texts by using external resources prior to classification. In short, by applying a short text classification, this study can point out each student's learning problems and inform the instructor where the main focus of the future course is, thus improving the ICT education environment. In order to achieve the goals, this research uses convolutional neural network (CNN) method to analyze short discussion content between teachers and students in an ICT education environment. Divide students into several main types of learning problem groups to facilitate answering student problems. In addition, this study will further cluster sub-categories of each major learning type to indicate specific problems for each student. Unlike most neural network programs, this study attempts to extend short texts with external resources before classifying them to improve classification performance. In short, by applying the classification of short texts, we can point out the learning problems of each student and inform the instructors where the main focus of future courses will improve the ICT education environment. The data of the empirical process will be used to pre-process the chat records between teachers and students and the course materials. An action system will be set up to compare the most similar parts of the teaching material with each student's chat history to improve future classification performance. Later, the function of short text classification uses CNN to classify rich chat records into several major learning problems based on theory-driven titles. By applying these modules, this research hopes to clarify the main learning problems of students and inform teachers that they should focus on future teaching.

Keywords: ICT education improvement, social equality, short text analysis, convolutional neural network

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Authors: Britt Erni, Aldara Vazquez Fernandez, Roland Maurer

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Visuospatial perspective taking (VSPT) is a process that allows to integrate spatial information from different points of view, and to transform the mental images we have of the environment to properly orient our movements and anticipate the location of landmarks during navigation. VSPT is also related to egocentric perspective transformations (imagined rotations or translations of one's point of view) and to infer the visuospatial experiences of another person (e.g. if and how another person sees objects). This process is deeply related to a wide-ranging capacity called the theory of mind (ToM), an essential cognitive function that allows us to regulate our social behaviour by attributing mental representations to individuals in order to make behavioural predictions. VSPT is often considered in the literature as the starting point of the development of the theory of mind. VSPT and ToM include several levels of knowledge that have to be assessed by specific tasks. Unfortunately, the lack of tasks assessing these functions in clinical neuropsychology leads to underestimate, in brain-damaged patients, deficits of these functions which are essential, in everyday life, to regulate our social behaviour (ToM) and to navigate in known and unknown environments (VSPT). Therefore, this study aims to create and standardize a VSPT task in order to explore the cognitive requirements of VSPT and ToM, and to specify their relationship in healthy adults and thereafter in brain-damaged patients. Two versions of a computerized VSPT task were administered to healthy participants (M = 28.18, SD = 4.8 years). In both versions the environment was a 3D representation of 10 different geometric shapes placed on a circular base. Two sets of eight pictures were generated from this: of the environment with an avatar somewhere on its periphery (locations) and of what the avatar sees from that place (views). Two types of questions were asked: a) identify the location from the view, and b) identify the view from the location. Twenty participants completed version 1 of the task and 20 completed the second version, where the views were offset by ±15° (i.e., clockwise or counterclockwise) and participants were asked to choose the closest location or the closest view. The preliminary findings revealed that version 1 is significantly easier than version 2 for accuracy (with ceiling scores for version 1). In version 2, participants responded significantly slower when they had to infer the avatar's view from the latter's location, probably because they spent more time visually exploring the different views (responses). Furthermore, men significantly performed better than women in version 1 but not in version 2. Most importantly, a sensitive task (version 2) has been created for which the participants do not seem to easily and automatically compute what someone is looking at yet which does not involve more heavily other cognitive functions. This study is further completed by including analysis on non-clinical participants with low and high degrees of schizotypy, different socio-educational status, and with a range of older adults to examine age-related and other differences in VSPT processing.

Keywords: mental transformation, spatial cognition, theory of mind, visuospatial perspective taking

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Jong H. Kim, Kathleen L. Chan, Luisa W. Cheng

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Control of fungal pathogens, such as foodborne mycotoxin producers, is problematic as effective antimycotic agents are often very limited. Mycotoxin contamination significantly interferes with the safe production of foods or crops worldwide. Moreover, expansion of fungal resistance to commercial drugs or fungicides is a global human health concern. Therefore, there is a persistent need to enhance the efficacy of commercial antimycotic agents or to develop new intervention strategies. Disruption of the cellular antioxidant system should be an effective method for pathogen control. Such disruption can be achieved with safe, redox-active compounds. Natural phenolic derivatives are potent redox cyclers that inhibit fungal growth through destabilization of the cellular antioxidant system. The goal of this study is to identify novel, redox-active compounds that disrupt the fungal antioxidant system. The identified compounds could also function as sensitizing agents to conventional antimycotics (i.e., chemosensitization) to improve antifungal efficacy. Various benzo derivatives were tested against fungal pathogens. Gene deletion mutants of the yeast Saccharomyces cerevisiae were used as model systems for identifying molecular targets of benzo analogs. The efficacy of identified compounds as potent antifungal agents or as chemosensitizing agents to commercial drugs or fungicides was examined with methods outlined by the Clinical Laboratory Standards Institute or the European Committee on Antimicrobial Susceptibility Testing. Selected benzo derivatives possessed potent antifungal or antimycotoxigenic activity. Molecular analyses by using S. cerevisiae mutants indicated antifungal activity of benzo derivatives was through disruption of cellular antioxidant or cell wall integrity system. Certain benzo analogs screened overcame tolerance of Aspergillus signaling mutants, namely mitogen-activated protein kinase mutants, to fludioxonil fungicide. Synergistic antifungal chemosensitization greatly lowered minimum inhibitory or fungicidal concentrations of test compounds, including inhibitors of mitochondrial respiration. Of note, salicylaldehyde is a potent antimycotic volatile that has some practical application as a fumigant. Altogether, benzo derivatives targeting cellular antioxidant system of fungi (along with cell wall integrity system) effectively suppress fungal growth. Candidate compounds possess the antifungal, antimycotoxigenic or chemosensitizing capacity to augment the efficacy of commercial antifungals. Therefore, chemogenetic approaches can lead to the development of novel antifungal intervention strategies, which enhance the efficacy of established microbe intervention practices and overcome drug/fungicide resistance. Chemosensitization further reduces costs and alleviates negative side effects associated with current antifungal treatments.

Keywords: antifungals, antioxidant system, benzo derivatives, chemosensitization

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Authors: Ayesha Mushtaq

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Asthma is a pulmonary disease in which blockade of the airway takes place due to inflammation as a response to certain allergens. Breathing troubles, cough, and dyspnea are one of the few symptoms. Several studies have indicated a significant effect on asthma due to changes in dietary routines. Certain food items, such as oily foods and other materials, are known to cause an increase in the symptoms of asthma. Low dietary intake of fruits and vegetables may be important in relation to asthma prevalence. The objective of this study is to assess and compare the nutritional status of asthmatic and non-asthmatic patients. The significance of this study lies in the factor that it will help nutritionists to arrange a feasible dietary routine for asthmatic patients. This research was conducted at the Pulmonology Department of the Pakistan Institute of Medical Science Islamabad. About thirty hundred thirty-four million people are affected by asthma worldwide. Pakistan is on the verge of being an uplifted urban population and asthma cases are increasingly high these days. Several studies suggest an increase in the Asthmatic patient population due to improper diet. This is a cross-sectional study aimed at assessing the nutritious standing of Asthmatic and non-asthmatic patients. This research took place at the Pakistan Institute of Medical Sciences (PIMS), Islamabad, Pakistan. The research included asthmatic and non-asthmatic patients coming to the pulmonology department clinic at the Pakistan Institute of Medical Sciences (PIMS). These patients were aged between 20-60 years. A questionnaire was developed for these patients to estimate their dietary plans in these patients. The methodology included four sections. The first section was the Socio-Demographic profile, which included age, gender, monthly income and occupation. The next section was anthropometric measurements which included the weight, height and body mass index (BMI) of an individual. The next section, section three, was about the biochemical attributes, such as for biochemical profiling, pulmonary function testing (PFT) was performed. In the next section, Dietary habits were assessed by a food frequency questionnaire (FFQ) through food habits and consumption pattern was assessed. The next section life style data, in which the person's level of physical activity, sleep and smoking habits were assessed. The next section was statistical analysis. All the data obtained from the study were statistically analyzed and assessed. Most of the asthma Patients were females, with weight more than normal or even obese. Body Mass Index (BMI) was higher in asthma Patients than those in non-Asthmatic ones. When the nutritional Values were assessed, we came to know that these patients were low on certain nutrients and their diet included more junk and oily food than healthy vegetables and fruits. Beverages intake was also included in the same assessment. It is evident from this study that nutritional status has a contributory effect on asthma. So, patients on the verge of developing asthma or those who have developed asthma should focus on their diet, maintain good eating habits and take healthy diets, including fruits and vegetables rather than oily foods. Proper sleep may also contribute to the control of asthma.

Keywords: BMI, nutrition, PAL, diet

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Authors: Thiago R. Pereira

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The philosophical hermeneutics is able to change the Brazilian Judiciary because of the understanding of the characteristics of the human being. It is impossible for humans, to be invested in the function of being a judge, making absolutely neutral decisions, but the philosophical hermeneutics can assist the judge making impartial decisions, based on the federal constitution. The normative legal positivism imagined a neutral judge, a judge able to try without any preconceived ideas, without allowing his/her background to influence him/her. When a judge arbitrates based on legal rules, the problem is smaller, but when there are no clear legal rules, and the judge must try based on principles, the risk of the decision is based on what they believe in. Solipsistically, this issue gains a huge dimension. Today, the Brazilian judiciary is independent, but there must be a greater knowledge of philosophy and the philosophy of law, partially because the bigger problem is the unpredictability of decisions made by the judiciary. Actually, when a lawsuit is filed, the result of this judgment is absolutely unpredictable. It is almost a gamble. There must be the slightest legal certainty and predictability of judicial decisions, so that people, with similar cases, may not receive opposite sentences. The relativism, since classical antiquity, believes in the possibility of multiple answers. Since the Greeks in in the sixth century before Christ, through the Germans in the eighteenth century, and even today, it has been established the constitution as the great law, the Groundnorm, and thus, the relativism of life can be greatly reduced when a hermeneut uses the Constitution as North interpretational, where all interpretation must act as the hermeneutic constitutional filter. For a current philosophy of law, that inside a legal system with a Federal Constitution, there is a single correct answer to a specific case. The challenge is how to find this right answer. The only answer to this question will be that we should use the constitutional principles. But in many cases, a collision between principles will take place, and to resolve this issue, the judge or the hermeneut will choose a solipsism way, using what they personally believe to be the right one. For obvious reasons, that conduct is not safe. Thus, a theory of decision is necessary to seek justice, and the hermeneutic philosophy and the linguistic turn will be necessary for one to find the right answer. In order to help this difficult mission, it will be necessary to use philosophical hermeneutics in order to find the right answer, which is the constitutionally most appropriate response. The constitutionally appropriate response will not always be the answer that individuals agree to, but we must put aside our preferences and defend the answer that the Constitution gives us. Therefore, the hermeneutics applied to Law, in search constitutionally appropriate response, should be the safest way to avoid judicial individual decisions. The aim of this paper is to present the science of law starting from the linguistic turn, the philosophical hermeneutics, moving away from legal positivism. The methodology used in this paper is qualitative, academic and theoretical, philosophical hermeneutics with the mission to conduct research proposing a new way of thinking about the science of law. The research sought to demonstrate the difficulty of the Brazilian courts to depart from the secular influence of legal positivism. Moreover, the research sought to demonstrate the need to think science of law within a contemporary perspective, where the linguistic turn, philosophical hermeneutics, will be the surest way to conduct the science of law in the present century.

Keywords: hermeneutic, right answer, solipsism, Brazilian judiciary

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Authors: Elena Filova, Ondrej Kaplan, Marie Markova, Helena Dragounova, Roman Matejka, Eduard Brynda, Lucie Bacakova

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Decellularized vessels have been evaluated as small-diameter vascular prostheses. Reseeding autologous cells onto decellularized tissue prior implantation should prolong prostheses function and make them living tissues. Suitable cell types for reseeding are both endothelial cells and bone marrow-derived stem cells, with a capacity for differentiation into smooth muscle cells upon mechanical loading. Endothelial cells assure antithrombogenicity of the vessels and MSCs produce growth factors and, after their differentiation into smooth muscle cells, they are contractile and produce extracellular matrix proteins as well. Fibrin is a natural scaffold, which allows direct cell adhesion based on integrin receptors. It can be prepared autologous. Fibrin can be modified with bound growth factors, such as basic fibroblast growth factor (FGF-2) and vascular endothelial growth factor (VEGF). These modifications in turn make the scaffold more attractive for cells ingrowth into the biological scaffold. The aim of the study was to prepare thin surface-attached fibrin assemblies with bound FGF-2 and VEGF, and to evaluate growth and differentiation of bone marrow-derived mesenchymal stem cells on the fibrin (Fb) assemblies. Following thin surface-attached fibrin assemblies were prepared: Fb, Fb+VEGF, Fb+FGF2, Fb+heparin, Fb+heparin+VEGF, Fb+heparin+FGF2, Fb+heparin+FGF2+VEGF. Cell culture poly-styrene and glass coverslips were used as controls. Human MSCs (passage 3) were seeded at the density of 8800 cells/1.5 mL alpha-MEM medium with 2.5% FS and 200 U/mL aprotinin per well of a 24-well cell culture. The cells have been cultured on the samples for 6 days. Cell densities on day 1, 3, and 6 were analyzed after staining with LIVE/DEAD cytotoxicity/viability assay kit. The differentiation of MSCs is being analyzed using qPCR. On day 1, the highest density of MSCs was observed on Fb+VEGF and Fb+FGF2. On days 3 and 6, there were similar densities on all samples. On day 1, cell morphology was polygonal and spread on all sample. On day 3 and 6, MSCs growing on Fb assemblies with FGF2 became apparently elongated. The evaluation of expression of genes for von Willebrand factor and CD31 (endothelial cells), for alpha-actin (smooth muscle cells), and for alkaline phosphatase (osteoblasts) is in progress. We prepared fibrin assemblies with bound VEGF and FGF-2 that supported attachment and growth of mesenchymal stem cells. The layers are promising for improving the ingrowth of MSCs into the biological scaffold. Supported by the Technology Agency of the Czech Republic TA04011345, and Ministry of Health NT11270-4/2010, and BIOCEV – Biotechnology and Biomedicine Centre of the Academy of Sciences and Charles University” project (CZ.1.05/1.1.00/02.0109), funded by the European Regional Development Fund for their financial supports.

Keywords: fibrin assemblies, FGF-2, mesenchymal stem cells, VEGF

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Authors: Delana Theiventhiran, Wally J. Bartfay

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Background and Significance: As the Internet is becoming the epitome of modern communications, there are many pragmatic reasons why the digital divide matters in terms of accessing and using E-health based technologies. With the rise of technology usage globally, those in the older adult generation may not be as familiar and comfortable with technology usage and are thus put at a disadvantage compared to other generations such as millennials when examining and using E-health based platforms and technology. Currently, little is known about how older adults and millennials access and use e-health based technologies. Methods: A systemic review of the literature was undertaken employing the following three databases: (i) PubMed, (ii) ERIC, and (iii) CINAHL; employing the search term 'digital divide and generations' to identify potential articles. To extract required data from the studies, a data abstraction tool was created to obtain the following information: (a) author, (b) year of publication, (c) sample size, (d) country of origin, (e) design/methods, (f) major findings/outcomes obtained. Inclusion criteria included publication dates between the years of Jan 2009 to Aug 2018, written in the English language, target populations of older adults aged 65 and above and millennials, and peer reviewed quantitative studies only. Major Findings: PubMed provided 505 potential articles, where 23 of those articles met the inclusion criteria. Specifically, ERIC provided 53 potential articles, where no articles met criteria following data extraction. CINAHL provided 14 potential articles, where eight articles met criteria following data extraction. Conclusion: Practically speaking, identifying how newer E-health based technologies can be integrated into society and identifying why there is a gap with digital technology will help reduce the impact on generations and individuals who are not as familiar with technology and Internet usage. The largest concern of all is how to prepare older adults for new and emerging E-health technologies. Currently, there is a dearth of literature in this area because it is a newer area of research and little is known about it. The benefits and consequences of technology being integrated into daily living are being investigated as a newer area of research. Several of the articles (N=11) indicated that age is one of the larger factors contributing to the digital divide. Similarly, many of the examined articles (N=5) identify that privacy concerns were one of the main deterrents of technology usage for elderly individuals aged 65 and above. The older adult generation feels that privacy is one of the major concerns, especially in regards to how data is collected, used and possibly sold to third party groups by various websites. Additionally, access to technology, the Internet, and infrastructure also plays a large part in the way that individuals are able to receive and use information. Lastly, a change in the way that healthcare is currently used, received and distributed would also help attribute to the change to ensure that no generation is left behind in a technologically advanced society.

Keywords: digital divide, e-health, millennials, older adults

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Afif J Arabi

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On April 15, 2024, Iran announced its unprecedented military attack by sending waves of more than 300 drones and ballistic missiles toward Israel. The Attack lasted approximately five hours and was a widely covered, distributed, and followed media event. Iran’s military action against Israel was a long-awaited action across the Middle East since the early days of the October 7th war on Gaza and after a long history of verbal threats. While people in many Arab countries stayed up past midnight in anticipation of watching the disastrous results of this unprecedented attack, voices on traditional and social media alike started to question the timed public announcement of the attack, which gave Israel at least a two-hour notice to prepare its defenses. When live news coverage started showing that nearly all the drones and missiles were intercepted by Israel – with help from the U.S. and other countries – and no deaths were reported, the social media response to this media event turned toward sarcasm, mockery, irony, and humor. Social media users posted sarcastic pictures, jokes, and comments mocking the Iranian offensive. This research examines this unique media event and the sarcastic response it generated on social media. The study aims to investigate the causes leading to media sarcasm in militarized political conflict, the social function of such generated sarcasm, and the role of social media as a platform for consuming frustration, dissatisfaction, and outrage passively through various media products. The study compares the serious traditional media coverage of the event with the humorous social media response among Arab countries. The research uses an eclectic theoretical approach using framing theory as a paradigm for understanding and investigating communication social functionalism theory in media studies to examine sarcasm. Social functionalism theory is a sociological perspective that views society as a complex system whose parts work together to promote solidarity and stability. In the context of media and sarcasm, this theory would suggest that sarcasm serves specific functions within society, such as reinforcing social norms, providing a means for social critique, or functioning as a safety valve for expressing social tension.; and a qualitative analysis of specific examples including responses of SM commentators to such manifestations of political criticism. The preliminary findings of this study point to a heightened dramatization of the televised event and a widespread belief that this attack was a staged show incongruent with Iran’s official enmity and death threats toward Israel. The social media sarcasm reinforces Arab’s view of Iran and Israel as mutual threats. This belief stems from the complex dynamics, historical context, and regional conflict surrounding these three nations: Iran, Israel, and Arabs.

Keywords: social functionalism, social media sarcasm, Television news framing, live militarized conflict coverage, iran, israel, communication theory

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Authors: Pawel Kiper, Alfonc Baba, Mahmoud Alhelou, Giorgia Pregnolato, Michela Agostini, Andrea Turolla

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Impairment of cervical spine mobility is often related to pain triggered by musculoskeletal disorders or direct traumatic injuries of the spine. To date, these disorders are assessed with goniometers and inclinometers, which are the most popular devices used in clinical settings. Nevertheless, these technologies usually allow measurement of no more than two-dimensional range of motion (ROM) quotes in static conditions. Conversely, the wide use of motion tracking systems able to measure 3 to 6 degrees of freedom dynamically, while performing standard ROM assessment, are limited due to technical complexities in preparing the setup and high costs. Thus, motion tracking systems are primarily used in research. These systems are an integral part of virtual reality (VR) technologies, which can be used for measuring spine mobility. To our knowledge, the accuracy of VR measure has not yet been studied within virtual environments. Thus, the aim of this study was to test the reliability of a protocol for the assessment of sensorimotor function of the cervical spine in a population of healthy subjects and to compare whether using immersive or non-immersive VR for visualization affects the performance. Both VR assessments consisted of the same five exercises and random sequence determined which of the environments (i.e. immersive or non-immersive) was used as first assessment. Subjects were asked to perform head rotation (right and left), flexion, extension and lateral flexion (right and left side bending). Each movement was executed five times. Moreover, the participants were invited to perform head reaching movements i.e. head movements toward 8 targets placed along a circular perimeter each 45°, visualized one-by-one in random order. Finally, head repositioning movement was obtained by head movement toward the same 8 targets as for reaching and following reposition to the start point. Thus, each participant performed 46 tasks during assessment. Main measures were: ROM of rotation, flexion, extension, lateral flexion and complete kinematics of the cervical spine (i.e. number of completed targets, time of execution (seconds), spatial length (cm), angle distance (°), jerk). Thirty-five healthy participants (i.e. 14 males and 21 females, mean age 28.4±6.47) were recruited for the cervical spine assessment with immersive and non-immersive VR environments. Comparison analysis demonstrated that: head right rotation (p=0.027), extension (p=0.047), flexion (p=0.000), time (p=0.001), spatial length (p=0.004), jerk target (p=0.032), trajectory repositioning (p=0.003), and jerk target repositioning (p=0.007) were significantly better in immersive than non-immersive VR. A regression model showed that assessment in immersive VR was influenced by height, trajectory repositioning (p<0.05), and handedness (p<0.05), whereas in non-immersive VR performance was influenced by height, jerk target (p=0.002), head extension, jerk target repositioning (p=0.002), and by age, head flex/ext, trajectory repositioning, and weight (p=0.040). The results of this study showed higher accuracy of cervical spine assessment when executed in immersive VR. The assessment of ROM and kinematics of the cervical spine can be affected by independent and dependent variables in both immersive and non-immersive VR settings.

Keywords: virtual reality, cervical spine, motion analysis, range of motion, measurement validity

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Authors: Elisa Santana-Monagas, Juan L. Núñez, Jaime León, Samuel Falcón, Celia Fernández, Rocío P. Solís

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Students’ emotional experiences have been a widely discussed theme among researchers, proving a central role on students’ outcomes. Yet, up to now, far too little attention has been paid to teaching practices that negatively relate with students’ negative emotions in the higher education. The present work aims to examine the relationship between teachers’ teaching practices (i.e., students’ evaluations of teaching and autonomy support), the students’ feelings of boredom and agentic engagement and motivation in the higher education context. To do so, the present study incorporates one of the most popular tools in natural processing language to address students’ evaluations of teaching: sentiment analysis. Whereas most research has focused on the creation of SA models and assessing students’ satisfaction regarding teachers and courses to the author’s best knowledge, no research before has included results from SA into an explanatory model. A total of 225 university students (Mean age = 26.16, SD = 7.4, 78.7 % women) participated in the study. Students were enrolled in degree and masters’ studies at the faculty of Education of a public university of Spain. Data was collected using an online questionnaire students could access through a QR code they completed during a teaching period where the assessed teacher was not present. To assess students’ sentiments towards their teachers’ teaching, we asked them the following open-ended question: “If you had to explain a peer who doesn't know your teacher how he or she communicates in class, what would you tell them?”. Sentiment analysis was performed with Microsoft's pre-trained model. For this study, we relied on the probability of the students answer belonging to the negative category. To assess the reliability of the measure, inter-rater agreement between this NLP tool and one of the researchers, who independently coded all answers, was examined. The average pairwise percent agreement and the Cohen’s kappa were calculated with ReCal2. The agreement reached was of 90.8% and Cohen’s kappa .68, both considered satisfactory. To test the hypothesis relations a structural equation model (SEM) was estimated. Results showed that the model fit indices displayed a good fit to the data; χ² (134) = 351.129, p < .001, RMSEA = .07, SRMR = .09, TLI = .91, CFI = .92. Specifically, results show that boredom was negatively predicted by autonomy support practices (β = -.47[-.61, -.33]), whereas for the negative sentiment extracted from SET, this relation was positive (β = .23[.16, .30]). In other words, when students’ opinion towards their instructors’ teaching practices was negative, it was more likely for them to feel bored. Regarding the relations among boredom and student outcomes, results showed a negative predictive value of boredom on students’ motivation to study (β = -.46[-.63, -.29]) and agentic engagement (β = -.24[-.33, -.15]). Altogether, results show a promising future for sentiment analysis techniques in the field of education as they proved the usefulness of this tool when evaluating relations among teaching practices and student outcomes.

Keywords: sentiment analysis, boredom, motivation, agentic engagement

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Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: Marita Pigłowska, Beata Kurc, Maciej Galiński

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The application of carbon materials in the branches of the electrochemical industry shows an increasing tendency each year due to the many interesting properties they possess. These are, among others, a well-developed specific surface, porosity, high sorption capacity, good adsorption properties, low bulk density, electrical conductivity and chemical resistance. All these properties allow for their effective use, among others in supercapacitors, which can store electric charges of the order of 100 F due to carbon electrodes constituting the capacitor plates. Coals (including expanded graphite, carbon black, graphite carbon fibers, activated carbon) are commonly used in electrochemical methods of removing oil derivatives from water after tanker disasters, e.g. phenols and their derivatives by their electrochemical anodic oxidation. Phenol can occupy practically the entire surface of carbon material and leave the water clean of hydrophobic impurities. Regeneration of such electrodes is also not complicated, it is carried out by electrochemical methods consisting in unblocking the pores and reducing resistances, and thus their reactivation for subsequent adsorption processes. Graphite is commonly used as an anode material in lithium-ion cells, while due to the limited capacity it offers (372 mAh g-1), new solutions are sought that meet both capacitive, efficiency and economic criteria. Increasingly, biodegradable materials, green materials, biomass, waste (including agricultural waste) are used in order to reuse them and reduce greenhouse effects and, above all, to meet the biodegradability criterion necessary for the production of lithium-ion cells as chemical power sources. The most common of these materials are cellulose, starch, wheat, rice, and corn waste, e.g. from agricultural, paper and pharmaceutical production. Such products are subjected to appropriate treatments depending on the desired application (including chemical, thermal, electrochemical). Starch is a biodegradable polysaccharide that consists of polymeric units such as amylose and amylopectin that build an ordered (linear) and amorphous (branched) structure of the polymer. Carbon is also used as a catalyst. Elemental carbon has become available in many nano-structured forms representing the hybridization combinations found in the primary carbon allotropes, and the materials can be enriched with a large number of surface functional groups. There are many examples of catalytic applications of coal in the literature, but the development of this field has been hampered by the lack of a conceptual approach combining structure and function and a lack of understanding of material synthesis. In the context of catalytic applications, the integrity of carbon environmental management properties and parameters such as metal conductivity range and bond sequence management should be characterized. Such data, along with surface and textured information, can form the basis for the provision of network support services.

Keywords: carbon materials, catalysis, BET, capacitors, lithium ion cell

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Authors: Ayodele James Akinola

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This study investigated the use of English in doctor-patient interaction in a university teaching hospital from a southwestern state in Nigeria with the aim of identifying the role of communication in an L2, patterns of communication, discourse strategies, pragmatic acts, and contexts that shape the interaction. Jacob Mey’s Pragmatic Acts notion complemented with Emanuel and Emanuel’s model of doctor-patient relationship provided the theoretical standpoint. Data comprising 7 audio-recorded doctors-patient interactions were collected from a University Hospital in Oyo state, Nigeria. Interactions involving the use of English language were purposefully selected. These were supplemented with patients’ case notes and interviews conducted with doctors. Transcription was patterned alongside modified Arminen’s notations of conversation analysis. In the study, interaction in English between doctor and patients has the preponderance of direct-translation, code-mixing and switching, Nigerianism and use of cultural worldviews to express medical experience. Irrespective of these, three patterns communication, namely the paternalistic, interpretive, and deliberative were identified. These were exhibited through varying discourse strategies. The paternalistic model reflected slightly casual conversational conventions and registers. These were achieved through the pragmemic activities of situated speech acts, psychological and physical acts, via patients’ quarrel-induced acts, controlled and managed through doctors’ shared situation knowledge. All these produced empathising, pacifying, promising and instructing practs. The patients’ practs were explaining, provoking, associating and greeting in the paternalistic model. The informative model reveals the use of adjacency pairs, formal turn-taking, precise detailing, institutional talks and dialogic strategies. Through the activities of the speech, prosody and physical acts, the practs of declaring, alerting and informing were utilised by doctors, while the patients exploited adapting, requesting and selecting practs. The negotiating conversational strategy of the deliberative model featured in the speech, prosody and physical acts. In this model, practs of suggesting, teaching, persuading and convincing were utilised by the doctors. The patients deployed the practs of questioning, demanding, considering and deciding. The contextual variables revealed that other patterns (such as phatic and informative) are also used and they coalesced in the hospital within the situational and psychological contexts. However, the paternalistic model was predominantly employed by doctors with over six years in practice, while the interpretive, informative and deliberative models were found among registrar and others below six years of medical practice. Doctors’ experience, patients’ peculiarities and shared cultural knowledge influenced doctor-patient communication in the study.

Keywords: pragmatics, communication pattern, doctor-patient interaction, Nigerian hospital situation

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Authors: Marcus Lee

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The energy sector is the largest contributor of greenhouse gas emissions in Malaysia, which induces climate change. The climate change problem is therefore an energy sector problem. Tackling climate change issues successfully is contingent on actions taken in the energy sector. The researcher propounds that ‘Climate Policy Integration’ (CPI) into energy policy is a viable and insufficiently developed strategy in Malaysia that promotes the synergies between climate change and energy objectives, in order to achieve the targets found in both climate change and energy policies. In exploring this hypothesis, this paper presentation will focus on two particular aspects. Firstly, the meaning of CPI as an approach and as a concept will be explored. As an approach, CPI into energy policy means the integration of climate change objectives into the energy policy area. Its subject matter focuses on establishing the functional interrelations between climate change and energy objectives, by promoting their synergies and minimising their contradictions. However, its conceptual underpinnings are less than straightforward. Drawing from the ‘principle of integration’ found in international treaties and declarations such as the Stockholm Declaration 1972, the Rio Declaration 1992 and the United Nations Framework on Climate Change 1992 (‘UNFCCC’), this paper presentation will explore the contradictions in international standards on how the sustainable development tenets of environmental sustainability, social development and economic development are to be balanced and its relevance to CPI. Further, the researcher will consider whether authority may be derived from international treaties and declarations in order to argue for the prioritisation of environmental sustainability over the other sustainable development tenets through CPI. Secondly, this paper presentation will also explore the degree to which CPI into energy policy has been achieved and pursued in Malaysia. In particular, the strength of the conceptual framework with regard to CPI in Malaysian governance will be considered by assessing Malaysia’s National Policy on Climate Change (2009) (‘NPCC 2009’). The development (or the lack of) of CPI as an approach since the publication of the NPCC 2009 will also be assessed based on official government documents and policies that may have a climate change and/or energy agenda. Malaysia’s National Renewable Energy Policy and Action Plan (2010), draft National Energy Efficiency Action Plan (2014), Intended Nationally Determined Contributions (2015) in relation to the Paris Agreement, 11th Malaysia Plan (2015) and Biennial Update Report to the UNFCCC (2015) will be discussed. These documents will be assessed for the presence of CPI based on the language/drafting of the documents as well as the degree of subject matter regarding CPI expressed in the documents. Based on the analysis, the researcher will propose solutions on how to improve Malaysia’s climate change and energy governance. The theory of reflexive governance will be applied to CPI. The concluding remarks will be about whether CPI reflects reflexive governance by demonstrating how the governance process can be the object of shaping outcomes.

Keywords: climate policy integration, mainstreaming, policy coherence, Malaysian energy governance

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Authors: Kayla Belanger, Pascale Vigneron, Guy Schlatter, Bernard Devauchelle, Christophe Egles

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A severe injury to a peripheral nerve leads to its degeneration and the loss of sensory and motor function. To this day, there still lacks a more effective alternative to the autograft which has long been considered the gold standard for nerve repair. In order to overcome the numerous drawbacks of the autograft, tissue engineered biomaterials may be effective alternatives. Silk fibroin is a favorable biomaterial due to its many advantageous properties such as its biocompatibility, its biodegradability, and its robust mechanical properties. In this study, bio-mimicking multi-channeled nerve guidance conduits made of aligned nanofibers achieved by electrospinning were functionalized with signaling biomolecules and were tested in vitro and in vivo for nerve regeneration support. Silk fibroin (SF) extracted directly from silkworm cocoons was put in solution at a concentration of 10wt%. Poly(ethylene oxide) (PEO) was added to the resulting SF solution to increase solution viscosity and the following three electrospinning solutions were made: (1) SF/PEO solution, (2) SF/PEO solution with nerve growth factor and ciliary neurotrophic factor, and (3) SF/PEO solution with nerve growth factor and neurotrophin-3. Each of these solutions was electrospun into a multi-layer architecture to obtain mechanically optimized aligned nanofibrous mats. For in vitro studies, aligned fibers were treated to induce β-sheet formation and thoroughly rinsed to eliminate presence of PEO. Each material was tested using rat embryo neuron cultures to evaluate neurite extension and the interaction with bio-functionalized or non-functionalized aligned fibers. For in vivo studies, the mats were rolled into 5mm long multi-, micro-channeled conduits then treated and thoroughly rinsed. The conduits were each subsequently implanted between a severed rat sciatic nerve. The effectiveness of nerve repair over a period of 8 months was extensively evaluated by cross-referencing electrophysiological, histological, and movement analysis results to comprehensively evaluate the progression of nerve repair. In vitro results show a more favorable interaction between growing neurons and bio-functionalized silk fibers compared to pure silk fibers. Neurites can also be seen having extended unidirectionally along the alignment of the nanofibers which confirms a guidance factor for the electrospun material. The in vivo study has produced positive results for the regeneration of the sciatic nerve over the length of the study, showing contrasts between the bio-functionalized material and the non-functionalized material along with comparisons to the experimental control. Nerve regeneration has been evaluated not only by histological analysis, but also by electrophysiological assessment and motion analysis of two separate natural movements. By studying these three components in parallel, the most comprehensive evaluation of nerve repair for the conduit designs can be made which can, therefore, more accurately depict their overall effectiveness. This work was supported by La Région Picardie and FEDER.

Keywords: electrospinning, nerve guidance conduit, peripheral nerve regeneration, silk fibroin

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Authors: María-Luisa Pinto-Salamanca, Wilson-Javier Pérez-Holguín

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Reconstruction of contact forces is a fundamental technique for analyzing the properties of a touched object and is essential for regulating the grip force in slip control loops. This is based on the processing of the distribution, intensity, and direction of the forces during the capture of the sensors. Currently, efficient hardware alternatives have been used more frequently in different fields of application, allowing the implementation of computationally complex algorithms, as is the case with tactile signal processing. The use of hardware for smart tactile sensing systems is a research area that promises to improve the processing time and portability requirements of applications such as artificial skin and robotics, among others. The literature review shows that hardware implementations are present today in almost all stages of smart tactile detection systems except in the force reconstruction process, a stage in which they have been less applied. This work presents a hardware implementation of a model-driven reported in the literature for the contact force reconstruction of flat and rigid tactile sensor arrays from normal stress data. From the analysis of a software implementation of such a model, this implementation proposes the parallelization of tasks that facilitate the execution of matrix operations and a two-dimensional optimization function to obtain a vector force by each taxel in the array. This work seeks to take advantage of the parallel hardware characteristics of Field Programmable Gate Arrays, FPGAs, and the possibility of applying appropriate techniques for algorithms parallelization using as a guide the rules of generalization, efficiency, and scalability in the tactile decoding process and considering the low latency, low power consumption, and real-time execution as the main parameters of design. The results show a maximum estimation error of 32% in the tangential forces and 22% in the normal forces with respect to the simulation by the Finite Element Modeling (FEM) technique of Hertzian and non-Hertzian contact events, over sensor arrays of 10×10 taxels of different sizes. The hardware implementation was carried out on an MPSoC XCZU9EG-2FFVB1156 platform of Xilinx® that allows the reconstruction of force vectors following a scalable approach, from the information captured by means of tactile sensor arrays composed of up to 48 × 48 taxels that use various transduction technologies. The proposed implementation demonstrates a reduction in estimation time of x / 180 compared to software implementations. Despite the relatively high values of the estimation errors, the information provided by this implementation on the tangential and normal tractions and the triaxial reconstruction of forces allows to adequately reconstruct the tactile properties of the touched object, which are similar to those obtained in the software implementation and in the two FEM simulations taken as reference. Although errors could be reduced, the proposed implementation is useful for decoding contact forces for portable tactile sensing systems, thus helping to expand electronic skin applications in robotic and biomedical contexts.

Keywords: contact forces reconstruction, forces estimation, tactile sensor array, hardware implementation

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Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier

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Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.

Keywords: eating disorders, risk factors, physical activity, machine learning

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: automotive Industry, industry 4.0, Internet of Things, IATF 16949:2016, measurement system analysis

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Authors: N. Uaphongsathorn, C. Worawong, S. Thaewpia

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Background and significance: The population is aging in Thai society, the elderly dependent is at great risk of various functional, psychological, and socio-economic problems as well as less access to health care. They may require long term care at home to maximize their functional abilities and activities of daily living and to improve their quality of life during their own age. Therefore, there is a need to develop a home-based long term care to meet the long term care needs of elders dependent. Methods: The research purpose was to develop long term care model among the elderly dependent in Chaiyaphum province in Northeast region of Thailand. Action Research which is composing of planning, action, observation, and reflection phases was used. Research was carried out for 12 months in all sub-districts of 6 districts in Chaiyaphum province. Participants (N = 1,010) participating in the processes of model development were comprised of 3 groups: a) a total of 110 health care professionals, b) a total of 600 health volunteers and family caregivers and c) a total of 300 the elderly dependent with chronically medical illnesses or disabilities. Descriptive statistics and content analysis were used to analyze data. Findings: Results have shown that the most common health problems among elders dependent with physical disabilities to function independently were cardiovascular disease, dementia, and traffic injuries. The development of home-based long term care model among elders dependent in Chaiyaphum province was composed of six key steps. They are: a) initiating policies supporting formal and informal caregivers for the elder dependent in all sub-districts, b) building network and multidisciplinary team, c) developing 3-day care manager training program and 3-day care provider training program d) training case managers and care providers for the elderly dependent through team and action learning, e) assessing, planning and providing care based on care individual’s needs of the elderly dependent, and f) sharing experiences for good practice and innovation for long term care at homes in district urban and rural areas. Among all care managers and care providers, the satisfaction level for training programs was high with a mean score of 3.98 out of 5. The elders dependent and family caregivers addressed that long term care at home could contribute to improving life’s daily activities, family relationship, health status, and quality of life. Family caregivers and volunteers have feeling a sense of personal satisfaction and experiencing providing meaningful care and support for elders dependent. Conclusion: In conclusion, a home-based long term care is important to Thai elders dependent. Care managers and care providers play a large role and responsibility to provide appropriate care to meet the elders’ needs in both urban and rural areas in Thai society. Further research could be rigorously studied with a larger group of populations in similar socio-economic and cultural contexts.

Keywords: elderly people, care manager, care provider, long term care

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Authors: Carla M. Machado, André A. Silva, Armando Bastos, Telmo G. Santos, J. Pamies Teixeira

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Advanced high-strength steels (AHSS) are increasingly being used in automotive components. The use of AHSS sheets plays an important role in reducing weight, as well as increasing the resistance to impact in vehicle components. However, the large-scale use of these sheets becomes more difficult due to the limitations during the forming process. Such limitations are due to the elastically driven change of shape of a metal sheet during unloading and following forming, known as the springback effect. As the magnitude of the springback tends to increase with the strength of the material, it is among the most worrisome problems in the use of AHSS steels. The prediction of strain hardening, especially under non-proportional loading conditions, is very limited due to the lack of constitutive models and mainly due to very limited experimental tests. It is very clear from the literature that in experimental terms there is not much work to evaluate deformation behavior under real conditions, which implies a very limited and scarce development of mathematical models for these conditions. The Bauschinger effect is also fundamental to the difference between kinematic and isotropic hardening models used to predict springback in sheet metal forming. It is of major importance to deepen the phenomenological knowledge of the mechanical and microstructural behavior of the materials, in order to be able to reproduce with high fidelity the behavior of extension of the materials by means of computational simulation. For this, a multi phenomenological analysis and characterization are necessary to understand the various aspects involved in plastic deformation, namely the stress-strain relations and also the variations of electrical conductivity and magnetic permeability associated with the metallurgical changes due to plastic deformation. Aiming a complete mechanical-microstructural characterization, uniaxial tensile tests involving successive cycles of loading and unloading were performed, as well as biaxial tests such as the Erichsen test. Also, nondestructive evaluation comprising eddy currents to verify microstructural changes due to plastic deformation and ultrasonic tests to evaluate the local variations of thickness were made. The material parameters for the stable yield function and the monotonic strain hardening were obtained using uniaxial tension tests in different material directions and balanced biaxial tests. Both the decrease of the modulus of elasticity and Bauschinger effect were determined through the load-unload tensile tests. By means of the eddy currents tests, it was possible to verify changes in the magnetic permeability of the material according to the different plastically deformed areas. The ultrasonic tests were an important aid to quantify the local plastic extension. With these data, it is possible to parameterize the different models of kinematic hardening to better approximate the results obtained by simulation with the experimental results, which are fundamental for the springback prediction of the stamped parts.

Keywords: advanced high strength steel, Bauschinger effect, sheet metal forming, springback

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Authors: Ebenezer Joseph

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Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

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Authors: Maria Luisa Barcena De Arellano, Sofya Pozdniakova, Pavelas Karkacas, Anja Kuhl, Istvan Baczko, Yury Ladilov, Vera Regitz-Zagrosek

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Introduction: Aging is associated with deterioration of the physiological function, leading to systemic inflammation and mitochondrial dysfunction that promote the development of cardiovascular diseases. Sex differences in aging-related cardiovascular diseases have been postulated. However, their precise mechanisms remain unclear. In the current study, we aimed to investigate the sex difference in the age-related alteration in Sirt1-AMPK signaling and its relation to the mitochondrial biogenesis and inflammation. Methods: Male and female human non-disease lateral left ventricular wall tissue (young (17–40 years; n= 7 male and 7 female) and old (50–68 years; n= 9 male and 8 female)) were used. qRT-PCR, western blot and immunohistochemistry assays were performed for expression analyses of Sirt1, AMPK, pAMPK, ac-Ku70, TFAM, PGC-1α, Sirt3, SOD2 and catalase. CD68 was used as a marker for macrophages and the ratio of IL-12:IL10 (pro-inflammatory phenotype (high IL-12/low IL-10) and anti-inflammatory phenotype (low IL-12/high IL-10) was used to examine the inflammatory stage in the heart. Results: Sirt1 expression was significantly higher in young females compared to young males, whereas in aged hearts Sirt1 expression was significantly downregulated in females, but not in males. In line with the Sirt1 downregulation in aged females, acetylation of nuclear Ku70, a direct target of Sirt1, in aged female hearts was significantly elevated. The activity of AMPK was significantly decreased in aged individuals, however no sex differences in the AMPK expression or activity were found in young or old individuals. The expression of mitochondrial proteins TOM40, SOD2 and Sirt3 was significantly higher in young females compared to young males, while in aged female hearts SOD2 and TOM40 were downregulated. In addition, the expression of catalase, a key cytosolic and mitochondrial anti-oxidative enzyme was significantly higher in young females and this female sex benefit was lost in aged hearts. In addition, the number of cardiac macrophages was significantly increased in old female, but not in male hearts. Consistently, the pro-inflammatory shift in old females was further confirmed by differences in the IL12/IL10 ratio in young female cardiac tissue in a favour of the anti-inflammatory mediator IL-10 (ratio 1:4) compared to young males (ratio 1:1). The anti-inflammatory environment in the heart was lost in aged females (ratio 1:1). Conclusion: Aging leads to the significant downregulation of Sirt1 expression and elevated acetylation of Ku70 in female, but not in male hearts. Furthermore, a beneficial upregulation of mitochondrial and anti-oxidative proteins in young females is lost with aging. Moreover, the malfunctions in the expression of Sirt1 and mitochondrial proteins in aged female hearts is accompanied by a significant pro-inflammatory shift. The study provides a molecular basis for the increased incidence of cardiovascular diseases in old women.

Keywords: inflammation, mitochondrial dysfunction, aging, Sirt1-AMPK axis

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Authors: Erika Mattio

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The aim of this project is to study the Chinese presence in Ethiopia, in the area between the Saba River and the Coptic areas of the Tigray, with detailed documentation of the Danakil region, from which the salt pickers caravans departed; the study was created to understand the relationships and consequences of the Chinese advance in these areas, inhabited by tribes linked to ancient, still practiced religious rituals, and home to unique landscapes and archaeological sites. Official estimates of the number of Chinese in Africa vary widely; on the continent, there are increasingly diverse groups of Chinese migrants in terms of language, dialect, class, education, and employment. Based on this and on a very general state of the art, it was decided to increase the studies on this phenomenon, focusing the attention on one of the most interesting countries for its diversity, cultural wealth, and for strong Chinese presence: Ethiopia. The study will be integrated with interdisciplinary investigation methods, such as landscape archeology, historiographic research, participatory anthropology, geopolitics, and cultural anthropology and ethnology. There are two main objectives of the research. The first is to predict what will happen to these populations and how the territory will be modified, trying to monitor the growth of infrastructure in the country and the effects it will have on the population. Risk analyzes will be carried out to understand what the foreign presence may entail, such as the absence of sustenance for local populations, the ghettoization of foreigners, unemployment of natives and the exodus of the population to the capital; the relationships between families and the local population will be analyzed, trying to understand the dynamics of socialization and interaction. Thanks to the use of GIS, the areas affected by the Chinese presence will be geo-referenced and mapped, delimiting the areas most affected and creating a risk analysis, both in desert areas and in archaeologically and historically relevant areas. The second point is to document the life and rituals of Ethiopian populations in order not to lose the aspects of uniqueness that risk being lost. Local interviews will collect impressions and criticisms from the local population to understand if the Chinese presence is perceived as a threat or as a solution. Furthermore, Afar leaders in the Logya area will be interviewed, in truly exclusive research, to understand their links with the foreign presence. From the north, along the Saba river, we will move to the northwest, in the Tigray region, to know the impressions in the Coptic area, currently less threatened by the Chinese presence but still affected by urbanization proposals. There will also be documented the Coptic rituals of Gennà and Timkat, unique expressions of a millennial tradition. This will allow the understanding of whether the Maoist presence could influence the religious rites and forms of belief present in the country, or the country will maintain its cultural independence.

Keywords: Ethiopia, GIS, risk perceptions, salt caravans

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Authors: Ismene Ithai Bras-Ruiz

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Learning Analytics (LA) is employed by universities not only as a tool but as a specialized ground to enhance students and professors. However, not all the academic programs apply LA with the same goal and use the same tools. In fact, LA is formed by five main fields of study (academic analytics, action research, educational data mining, recommender systems, and personalized systems). These fields can help not just to inform academic authorities about the situation of the program, but also can detect risk students, professors with needs, or general problems. The highest level applies Artificial Intelligence techniques to support learning practices. LA has adopted different techniques: statistics, ethnography, data visualization, machine learning, natural language process, and data mining. Is expected that any academic program decided what field wants to utilize on the basis of his academic interest but also his capacities related to professors, administrators, systems, logistics, data analyst, and the academic goals. The Open and Distance University System (SUAYED in Spanish) of the University National Autonomous of Mexico (UNAM), has been working for forty years as an alternative to traditional programs; one of their main supports has been the employ of new information and communications technologies (ICT). Today, UNAM has one of the largest network higher education programs, twenty-six academic programs in different faculties. This situation means that every faculty works with heterogeneous populations and academic problems. In this sense, every program has developed its own Learning Analytic techniques to improve academic issues. In this context, an investigation was carried out to know the situation of the application of LA in all the academic programs in the different faculties. The premise of the study it was that not all the faculties have utilized advanced LA techniques and it is probable that they do not know what field of study is closer to their program goals. In consequence, not all the programs know about LA but, this does not mean they do not work with LA in a veiled or, less clear sense. It is very important to know the grade of knowledge about LA for two reasons: 1) This allows to appreciate the work of the administration to improve the quality of the teaching and, 2) if it is possible to improve others LA techniques. For this purpose, it was designed three instruments to determinate the experience and knowledge in LA. These were applied to ten faculty coordinators and his personnel; thirty members were consulted (academic secretary, systems manager, or data analyst, and coordinator of the program). The final report allowed to understand that almost all the programs work with basic statistics tools and techniques, this helps the administration only to know what is happening inside de academic program, but they are not ready to move up to the next level, this means applying Artificial Intelligence or Recommender Systems to reach a personalized learning system. This situation is not related to the knowledge of LA, but the clarity of the long-term goals.

Keywords: academic improvements, analytical techniques, learning analytics, personnel expertise

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Authors: Mary Farrell, Maria Soubra, Sandra Vega, Dorothy Kakraba, Joanne Fontanilla, Moira Kendra, Danielle Tonzola, Stephanie Chiu

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Pneumonia is the most common infectious cause of hospitalizations in the United States, with more than one million admissions annually and costs of $10 billion every year, making it the 8th leading cause of death. Aspiration pneumonia is an aggressive type of pneumonia that results from inhalation of oropharyngeal secretions and/or gastric contents and is preventable. The authors hypothesized that an evidence-based aspiration pneumonia clinical care pathway could reduce 30-day hospital readmissions and mortality rates, while improving the overall care of patients. We conducted a retrospective chart review on 979 patients discharged with aspiration pneumonia from January 2021 to December 2022 at Overlook Medical Center. The authors identified patients who were coded with aspiration pneumonia and/or stable sepsis. Secondarily, we identified 30-day readmission rates for aspiration pneumonia from a SNF. The Aspiration Pneumonia Clinical Care Pathway starts in the emergency department (ED) with the initiation of antimicrobials within 4 hours of admission and early recognition of aspiration. Once this is identified, a swallow test is initiated by the bedside nurse, and if the patient demonstrates dysphagia, they are maintained on strict nothing by mouth (NPO) followed by a speech and language pathologist (SLP) referral for an appropriate modified diet recommendation. Aspiration prevention techniques included the avoidance of straws, 45-degree positioning, no talking during meals, taking small bites, placement of the aspiration wrist band, and consuming meals out of the bed in a chair. Nursing education was conducted with a newly created online learning module about aspiration pneumonia. The authors identified 979 patients, with an average age of 73.5 years old, who were diagnosed with aspiration pneumonia on the index hospitalization. These patients were reviewed for a 30-day readmission for aspiration pneumonia or stable sepsis, and mortality rates from January 2021 to December 2022 at Overlook Medical Center (OMC). The 30-day readmission rates were significantly lower in the cohort that received the clinical care pathway (35.0% vs. 27.5%, p = 0.011). When evaluating the mortality rates in the pre and post intervention cohort the authors discovered the mortality rates were lower in the post intervention cohort (23.7% vs 22.4%, p = 0.61) Mortality among non-white (self-reported as non-white) patients were lower in the post intervention cohort (34.4% vs. 21.0% , p = 0.05). Patients who reported as a current smoker/vaper in the pre and post cohorts had increased mortality rates (5.9% vs 22%). There was a decrease in mortality for the male population but an increase in mortality for women in the pre and post cohorts (19% vs. 25%). The authors attributed this increase in mortality in the post intervention cohort to more active smokers, more former smokers, and more being admitted from a SNF. This research identified that implementation of an Aspiration Pneumonia Clinical Care Pathway showed a statistically significant decrease in readmission rates and mortality rates in non-whites. The 30-day readmission rates were lower in the cohort that received the clinical care pathway (35.0% vs. 27.5%, p = 0.011).

Keywords: aspiration pneumonia, mortality, quality improvement, 30-day pneumonia readmissions

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