Search results for: multi-layer neural networks

Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Safee Chaudhary, Mahnoor Naseer Gondal, Hira Anees Awan, Abdul Rehman, Ammar Arif, Risham Hussain, Huma Khawar, Zainab Arshad, Muhammad Faizyab Ali Chaudhary, Waleed Ahmed, Muhammad Umer Sultan, Bibi Amina, Salaar Khan, Muhammad Moaz Ahmad, Osama Shiraz Shah, Hadia Hameed, Muhammad Farooq Ahmad Butt, Muhammad Ahmad, Sameer Ahmed, Fayyaz Ahmed, Omer Ishaq, Waqar Nabi, Wim Vanderbauwhede, Bilal Wajid, Huma Shehwana, Muhammad Tariq, Amir Faisal

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Cancer is a manifestation of multifactorial deregulations in biomolecular pathways. These deregulations arise from the complex multi-scale interplay between cellular and extracellular factors. Such multifactorial aberrations at gene, protein, and extracellular scales need to be investigated systematically towards decoding the underlying mechanisms and orchestrating therapeutic interventions for patient treatment. In this work, we propose ‘TISON’, a next-generation web-based multiscale modeling platform for clinical systems oncology. TISON’s unique modeling abstraction allows a seamless coupling of information from biomolecular networks, cell decision circuits, extra-cellular environments, and tissue geometries. The platform can undertake multiscale sensitivity analysis towards in silico biomarker identification and drug evaluation on cellular phenotypes in user-defined tissue geometries. Furthermore, integration of cancer expression databases such as The Cancer Genome Atlas (TCGA) and Human Proteome Atlas (HPA) facilitates in the development of personalized therapeutics. TISON is the next-evolution of multiscale cancer modeling and simulation platforms and provides a ‘zero-code’ model development, simulation, and analysis environment for application in clinical settings.

Keywords: systems oncology, cancer systems biology, cancer therapeutics, personalized therapeutics, cancer modelling

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Authors: Sevde Altuntas, Fatih Buyukserin

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Alzheimer’s disease is responsible for irreversible neural damage of brain parts. One of the disease markers is Amyloid-β 1-42 protein that accumulates in the brain in the form plaques. The basic problem for detection of the protein is the low amount of protein that cannot be detected properly in body liquids such as blood, saliva or urine. To solve this problem, tests like ELISA or PCR are proposed which are expensive, require specialized personnel and can contain complex protocols. Therefore, Surface-enhanced Raman Spectroscopy (SERS) a good candidate for detection of Amyloid-β 1-42 protein. Because the spectroscopic technique can potentially allow even single molecule detection from liquid and solid surfaces. Besides SERS signal can be improved by using nanopattern surface and also is specific to molecules. In this context, our study proposes to fabricate diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin - T to detect low concentrations of Amyloid-β 1-42 protein in water and artificial saliva medium by the enhancement of protein SERS signal. The nanopatterned PC surface that was used to enhance SERS signal was fabricated by using Anodic Alumina Membranes (AAM) as a template. It is possible to produce AAMs with different column structures and varying thicknesses depending on voltage and anodization time. After fabrication process, the pore diameter of AAMs can be arranged with dilute acid solution treatment. In this study, two different columns structures were prepared. After a surface modification to decrease their surface energy, AAMs were treated with PC solution. Following the solvent evaporation, nanopatterned PC films with tunable pillared structures were peeled off from the membrane surface. The PC film was then modified with Au and Thioflavin-T for the detection of Amyloid-β 1-42 protein. The protein detection studies were conducted first in water via this biosensor platform. Same measurements were conducted in artificial saliva to detect the presence of Amyloid Amyloid-β 1-42 protein. SEM, SERS and contact angle measurements were carried out for the characterization of different surfaces and further demonstration of the protein attachment. SERS enhancement factor calculations were also completed via experimental results. As a result, our research group fabricated diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin-T to detect low concentrations of Alzheimer’s Amiloid – β protein in water and artificial saliva medium. This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) Grant No: 214Z167.

Keywords: alzheimer, anodic aluminum oxide, nanotopography, surface enhanced Raman spectroscopy

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Authors: Teresa Isabel Lozano Pérez, Sandra Soca Lozano

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In Cuba, the childcare is one of the programs prioritized by the Ministry of Public Health and the birth of a child becomes a desired and rewarding event for the family, which is prepared for the reception of a healthy child. When this does not happen and after the first months of the child's birth begin to appear developmental deviations that indicate the presence of a disorder, the event becomes a live event potentially negative and generates disruptions in the family health. A quantitative, descriptive, and cross-sectional research methodology was conducted to describe the impact on family health of diagnosis of autism in a sample of 25 families of children diagnosed with infantile autism at the University Pediatric Hospital Juan Manuel Marquez Havana, Cuba; in the period between January 2014 and May 2015. The sample was non probabilistic and intentional from the inclusion criteria selected. As instruments, we used a survey to identify the structure of the family, life events inventory and an instrument to assess the relative impact, adaptive resources of family and social support perceived (IRFA) to identify the diagnosis of autism as life event. The main results indicated that the majority of families studied were nuclear, small and medium and in the formation stage. All households surveyed identified the diagnosis of autism in a child as an event of great importance and negative significance for the family, taking in most of the families studied a high impact on the four areas of family health and impact enhancer of involvement in family health. All the studied families do not have sufficient adaptive resources to face this situation, sensing that they received social support frequently, mainly in information and emotional areas. We conclude that the diagnosis of autism one of the members of the families studied is valued as a life event highly significant with unfavorably way causing an enhancer impact of involvement in family health especially in the areas ‘health’ and ‘socio-psychological’. Among the social support networks health institutions, partners and friends are highlighted. We recommend developing intervention strategies in families of these children to support them in the process of adapting the diagnosis.

Keywords: family, family health, infantile autism, life event

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Authors: Guillaume P. Fernandez

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Individual language use is a matter of choice in particular interactions. The paper proposes a conceptual and theoretical framework with methodological consideration to develop how language produced in dyadic relations is to be considered and situated in the larger social configuration the interaction is embedded within. An integrated and comprehensive view is taken: social interactions are expected to be ruled by a normative context, defined by the chain of interdependences that structures the personal network. In this approach, the determinants of discursive practices are not only constrained by the moment of production and isolated from broader influences. Instead, the position the individual and the dyad have in the personal network influences the discursive practices in a twofold manner: on the one hand, the network limits the access to linguistic resources available within it, and, on the other hand, the structure of the network influences the agency of the individual, by the social control inherent to particular network characteristics. Concretely, we investigate how and to what extent consistent ego is from one interaction to another in his or her use of adverbs. To do so, social network analysis (SNA) methods are mobilized. Participants (N=130) are college students recruited in the french speaking part of Switzerland. The personal network of significant ones of each individual is created using name generators and edge interpreters, with a focus on social support and conflict. For the linguistic parts, respondents were asked to record themselves with five of their close relations. From the recordings, we computed an average similarity score based on the adverb used across interactions. In terms of analyses, two are envisaged: First, OLS regressions including network-level measures, such as density and reciprocity, and individual-level measures, such as centralities, are performed to understand the tenets of linguistic similarity from one interaction to another. The second analysis considers each social tie as nested within ego networks. Multilevel models are performed to investigate how the different types of ties may influence the likelihood to use adverbs, by controlling structural properties of the personal network. Primary results suggest that the more cohesive the network, the less likely is the individual to change his or her manner of speaking, and social support increases the use of adverbs in interactions. While promising results emerge, further research should consider a longitudinal approach to able the claim of causality.

Keywords: personal network, adverbs, interactions, social influence

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Authors: Martin Mensinger, Marjolaine Pfaffinger, Matthias Haslbeck

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The maintenance and expansion of the railway network represents a central task for transport planning in the future. In addition to the ultimate limit states, the aspects of resource conservation and sustainability are increasingly more necessary to include in the basic engineering. Therefore, as part of the AiF research project, ‘Integrated assessment of steel and composite railway bridges in accordance with sustainability criteria’, the entire lifecycle of engineering structures is involved in planning and evaluation, offering a way to optimize the design of steel bridges. In order to reduce the life cycle costs and increase the profitability of steel structures, it is particularly necessary to consider the demands on hanger connections resulting from fatigue. In order for accurate analysis, a number simulations were conducted as part of the research project on a finite element model of a reference bridge, which gives an indication of the internal forces of the individual structural components of a tied arch bridge, depending on the stress incurred by various types of trains. The calculations were carried out on a detailed FE-model, which allows an extraordinarily accurate modeling of the stiffness of all parts of the constructions as it is made up surface elements. The results point to a large impact of the formation of details on fatigue-related changes in stress, on the one hand, and on the other, they could depict construction-specific specifics over the course of adding stress. Comparative calculations with varied axle-stress distribution also provide information about the sensitivity of the results compared to the imposition of stress and axel distribution on the stress-resultant development. The calculated diagrams help to achieve an optimized hanger connection design through improved durability, which helps to reduce the maintenance costs of rail networks and to give practical application notes for the formation of details.

Keywords: fatigue, influence line, life cycle, tied arch bridge

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Authors: Zeinu Ahmed Rabba, Derek D Stretch

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Remote sensing contributes valuable information to streamflow estimates. Usually, stream flow is directly measured through ground-based hydrological monitoring station. However, in many developing countries like Ethiopia, ground-based hydrological monitoring networks are either sparse or nonexistent, which limits the manage water resources and hampers early flood-warning systems. In such cases, satellite remote sensing is an alternative means to acquire such information. This paper discusses the application of remotely sensed rainfall data for streamflow modeling in Gilgel Ghibe basin in Ethiopia. Ten years (2001-2010) of two satellite-based precipitation products (SBPP), TRMM and WaterBase, were used. These products were combined with the PyTOPKAPI hydrological model to generate daily stream flows. The results were compared with streamflow observations at Gilgel Ghibe Nr, Assendabo gauging station using four statistical tools (Bias, R², NS and RMSE). The statistical analysis indicates that the bias-adjusted SBPPs agree well with gauged rainfall compared to bias-unadjusted ones. The SBPPs with no bias-adjustment tend to overestimate (high Bias and high RMSE) the extreme precipitation events and the corresponding simulated streamflow outputs, particularly during wet months (June-September) and underestimate the streamflow prediction over few dry months (January and February). This shows that bias-adjustment can be important for improving the performance of the SBPPs in streamflow forecasting. We further conclude that the general streamflow patterns were well captured at daily time scales when using SBPPs after bias adjustment. However, the overall results demonstrate that the simulated streamflow using the gauged rainfall is superior to those obtained from remotely sensed rainfall products including bias-adjusted ones.

Keywords: Ethiopia, PyTOPKAPI model, remote sensing, streamflow, Tropical Rainfall Measuring Mission (TRMM), waterBase

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Authors: Soumen Mitra, Aparna Saha

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The perceived link between the city and the countryside is evolving rapidly and is getting shifted away from the assumptions of mainstream paradigms to new conceptual networks where rural-urban links are being redefined. In this conceptual field, the fringe interface is still considered as a transitional zone between city and countryside, and is defined as a diffused area rather than a discrete territory. In developing countries fringe areas are said to have both rural and urban characteristics but are devoid of basic municipal facilities. Again, when the urban core areas envelopes the fringe areas along with it the character of fringe changes but services are not well facilitated which in turn results to uneven growth, rapid and haphazard development. One of the major services present in fringe areas is inter-linkages in terms of transit corridors. Planning for the appropriate and sustainable future of fringe areas requires a sheer focus on these corridors pertaining to transit facility, for better accessibility and mobility. Inducing a transit facility plan enhances the various facilities and also increases their proximity for user groups. The study focuses on the western fringe region of Kolkata metropolis which is a major source of industrial hub and housing sector, thus converting the agricultural lands into non-agricultural use. The study emphasizes on providing transit facilities both physical (stops, sheds, terminals, etc.) and operational (ticketing system, route prioritization, integration of transit modes, etc.), to facilitate the region as well as accelerate the growth pattern systematically. Hence, the scope of this work is on the basis of prevailing conditions in fringe areas and attempts for an effective transit facility plan. The strategies and recommendations are in terms of road widening, service coverage, feeder route prioritization, bus stops facilitation, pedestrian facilities, etc, which in turn enhances the region’s growth pattern. Thus, this context of transit facility planning acts as a catalytic agent to avoid the future unplanned growth and accelerates it towards an integrated development.

Keywords: feeder route, fringe, municipal planning, transit facility

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Authors: Chukwu Fidelis Ndubuisi, Madufor Michael Ozims, Asogwa Vivian Ndidiamaka, Egenamba Juliet Ngozi, Okonkwo Stephen C., Kamah Chukwudi David

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Deflection of the vertical is a quantity used in reducing geodetic measurements related to geoidal networks to the ellipsoidal plane; and it is essential in Geoid modeling processes. Computing the deflection of the vertical component of a point in a given area is necessary in evaluating the standard errors along north-south and east-west direction. Using combined approach for the determination of deflection of the vertical component provides improved result but labor intensive without appropriate method. Least square method is a method that makes use of redundant observation in modeling a given sets of problem that obeys certain geometric condition. This research work is aimed to computing the deflection of vertical component of Owerri West local government area of Imo State using geometric method as field technique. In this method combination of Global Positioning System on static mode and precise leveling observation were utilized in determination of geodetic coordinate of points established within the study area by GPS observation and the orthometric heights through precise leveling. By least square using Matlab programme; the estimated deflections of vertical component parameters for the common station were -0.0286 and -0.0001 arc seconds for the north-south and east-west components respectively. The associated standard errors of the processed vectors of the network were computed. The computed standard errors of the North-south and East-west components were 5.5911e-005 and 1.4965e-004 arc seconds, respectively. Therefore, including the derived component of deflection of the vertical to the ellipsoidal model will yield high observational accuracy since an ellipsoidal model is not tenable due to its far observational error in the determination of high quality job. It is important to include the determined deflection of the vertical component for Owerri West Local Government in Imo State, Nigeria.

Keywords: deflection of vertical, ellipsoidal height, least square, orthometric height

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Authors: Sonu Rana, Jyoti Verma, A. K. Gautam

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In most developing countries like India, the majority of the population heavily relies on agriculture for their livelihood. The yield of agriculture is heavily dependent on uncertain weather conditions like a monsoon, soil fertility, availability of irrigation facilities and fertilizers as well as support from the government. The agricultural yield is quite less compared to the effort put in due to inefficient agricultural facilities and obsolete farming practices on the one hand and lack of knowledge on the other hand, and ultimately agricultural community does not prosper. It is therefore essential for the farmers to improve their harvest yield by the acquisition of related data such as soil condition, temperature, humidity, availability of irrigation facilities, availability of, manure, etc., and adopt smart farming techniques using modern agricultural equipment. Nowadays, using IOT technology in agriculture is the best solution to improve the yield with fewer efforts and economic costs. The primary focus of this work-related is IoT technology in the agriculture field. By using IoT all the parameters would be monitored by mounting sensors in an agriculture field held at different places, will collect real-time data, and could be transmitted by a transmitting device like an antenna. To improve the system, IoT will interact with other useful systems like Wireless Sensor Networks. IoT is exploring every aspect, so the radio frequency spectrum is getting crowded due to the increasing demand for wireless applications. Therefore, Federal Communications Commission is reallocating the spectrum for various wireless applications. An antenna is also an integral part of the newly designed IoT devices. The main aim is to propose a new antenna structure used for IoT agricultural applications and compatible with this new unlicensed frequency band. The main focus of this paper is to present work related to these technologies in the agriculture field. This also presented their challenges & benefits. It can help in understanding the job of data by using IoT and correspondence advancements in the horticulture division. This will help to motivate and educate the unskilled farmers to comprehend the best bits of knowledge given by the huge information investigation utilizing smart technology.

Keywords: smart agriculture, IoT, agriculture technology, data analytics, smart technology

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Authors: Shayla He

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Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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Authors: Diana Gibson

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Aim: The first aim of the study was to ascertain the percentage of people who had been diagnosed with High Blood Pressure and/ or Type2 Diabetes Mellitus in Matzikama municipal district, Western Cape, South Africa. These two conditions are reportedly very high in this particular province, even though few statistics are available. A second aim was to gain insight into the understanding of these two conditions among sufferers. A third aim was to determine their allopathic use as well as indigenous medicinal plants to manage these conditions. A fourth aim was to understand how users of medicinal plants attend to their materiality and relationality as a continuum between humans and plants. The final aim was to ascertain the conservation status of medicinal plants utilised. Methods: One thousand one hundred and eighty-four (1184) respondents were interviewed. Semi-structured surveys were utilised to gather data on the percentage of people who had been medically diagnosed with High Blood Pressure and/or Type 2 Diabetes Mellitus. Local healers and knowledgeable old people were subsequently selected through a non-probability snowball sampling method. They were helped with plant collection. The plants were botanically identified. Results: The study found that people who have been diagnosed with High Blood Pressure or Type 2 Diabetes Mellitus drew on and continuously moved between biomedical and local understandings of these conditions. While they followed biomedical treatment regimens as far as possible they also drew on alternative ways of managing it through the use of medicinal plants. The most commonly used plant species overall were Lessertia frutescens, Tulbaghia violacea, Artemisia afra and Leonotus leonurus. For the users, medicinal plants were not mere material entities, they were actants in social networks where knowledge was produced through particular practices in specific places. None of the identified plants are currently threatened. Significance: Sufferers had a good understanding of the symptoms of and biomedical treatment regime for both conditions, but in everyday life they adhered to their local understandings and medicinal plants for treatment. The majority used reportedly used prescribed medication as well as plant alternatives.

Keywords: diabetes, high blood pressure, medicine, plants

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Authors: Julio Jesus Salazar, Max Jesus De Lama

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The challenges of water management are aggravated by global change, which implies high complexity and associated uncertainty; water management is difficult because water networks cross domains (natural, societal, and political), scales (space, time, jurisdictional, institutional, knowledge, etc.) and levels (area: patches to global; knowledge: a specific case to generalized principles). In this context, we need to apply natural and non-natural measures to manage water and soil. The Basin Management Methodology considers multifunctional measures of natural water retention and erosion control and soil formation to protect water resources and address the challenges related to the recovery or conservation of the ecosystem, as well as natural characteristics of water bodies, to improve the quantitative status of water bodies and reduce vulnerability to floods and droughts. This method of water management focuses on the positive impacts of the chemical and ecological status of water bodies, restoration of the functioning of the ecosystem and its natural services; thus, contributing to both adaptation and mitigation of climate change. This methodology was applied in 7 interventions in the sub-basin of the Shullcas River in Huancayo-Junín-Peru, obtaining great benefits in the framework of the participation of alliances of actors and integrated planning scenarios. To implement the methodology in the sub-basin of the Shullcas River, a process called Climate Smart Territories (CST) was used; with which the variables were characterized in a highly complex space. The diagnosis was then worked using risk management and adaptation to climate change. Finally, it was concluded with the selection of alternatives and projects of this type. Therefore, the CST approach and process face the challenges of climate change through integrated, systematic, interdisciplinary and collective responses at different scales that fit the needs of ecosystems and their services that are vital to human well-being. This methodology is now replicated at the level of the Mantaro river basin, improving with other initiatives that lead to the model of a resilient basin.

Keywords: climate-smart territories, climate change, ecosystem services, natural measures, Climate Smart Territories (CST) approach

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Authors: Şenay Güngör, Emre Elbaşi, Beyda Sadikoğlu, Utku Eren Bağci, Ömer Uzunel

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One of the first places that comes to mind when it comes to tourism in Turkey is the Cappadocia Region. Due to its rich geological and geomorphological heritage, Cappadocia is one of the most visited destinations in the world. In fact, in the first half of 2023, the number of international tourists visiting Cappadocia exceeded 2 million. Considering that the economy of the Cappadocia region is largely based on tourism, it is understood that the quality and technology integration levels of the touristic services offered in the region are of great importance. In this context; as a result of the observations made in Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys, where the important hiking routes of the Cappadocia Region are located, it has been observed that the digital level of the routes is insufficient. It has been observed that the telephone networks in the area are very low or have completely lost their signal strength. In addition, it was determined that the materials such as maps and brochures used by tourism agencies to introduce the valleys are simple and incomplete. It is thought that this situation negatively affects the tourists' orientation and touristic experience in the field. Eliminating these deficiencies identified in the field, improving the digital level of the above-mentioned hiking routes and increasing the added value in destinations are among the main objectives of our study. Within the scope of the study, a mobile application that can work both online and offline on hiking routes has been prepared. 3D modeling of Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys were made using Geographical Information Systems (GIS). In addition, a website has been created to enable tourists to easily access all the above-mentioned information, visuals and technological applications related to the routes. As it is known, the effective use of information and communication technologies in touristic regions not only increases the satisfaction levels of tourists, but also positively affects the attraction of qualified tourists to the region. When the tangible and intangible outputs of this study are evaluated, it is thought that it will serve the social and economic development of the region and set an example for the digital transformation of other routes in the region.

Keywords: nevşehir, cappadocia, cappadocia valleys, trekking route

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Authors: Pennapa Palapin

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This research sought to study the traditional local wisdom and study the promotion and dissemination of traditional local wisdom in order to find the forms of promotion and dissemination of traditional local wisdom to create occupations among the elderly at Nonmueng Community, Muang Sub-District, Baan Dung District, UdonThani Province. The criterion used to select the research sample group was, being a person having a role involved in the promotion and dissemination of traditional local wisdom to create occupations among the elderly at Nonmueng Community, Muang Sub-District, Baan Dung District, UdonThani Province; being an experienced person whom the residents of Nonmueng Community find trustworthy; and having lived in Nonmueng Community for a long time so as to be able to see the development and change that occurs. A total of 16 people were selected. Data was gathered as a qualitative study, through semi-structured in-depth interviews. The collected data was then summarised and discussed according to the research objectives. Finally, the data was presented in a narrative format. Results found that the identifying traditional local wisdom of the community (which grew from the residents’ experience and beneficial usage in daily life, passed down from generation to generation) was the weaving of cloth and basketry. As for the manner of promotion and dissemination of traditional local wisdom, the skills were passed down through teaching by example to family members, relatives and others in the community. This was done by the elders or elderly members of the community. For the promotion and dissemination of traditional local wisdom to create occupations among the elderly, the traditional local wisdom should be supported in every way through participation of the community members. For example, establish a museum of traditional local wisdom for the collection of traditional local wisdom in various fields, both in the past and at present. This would be a source of pride for the community, in order to make traditional local wisdom widely known and to create income for the community’s elderly. Additional ways include exhibitions of products made by traditional local wisdom, finding both domestic and international markets, as well as building both domestic and international networks aiming to find opportunities to market products made by traditional local wisdom.

Keywords: traditional local wisdom, occupation, elderly, community

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Authors: T. Yasmin, M. A. Farrelly, B. C. Rogers

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Urban water governance in developing countries faces numerous challenges arising from uncontrolled urban population expansion, water pollution, greater economic push and more recently, climate change impact while undergoing transitioning towards a sustainable system. Sustainability transition requires developing adaptive capacities of the socio-ecological and socio-technical system to be able to deal with complexity. Adaptive capacities deliver strategies to connect individuals, organizations, agencies and institutions at multiple levels for dealing with such complexity. Understanding the level of adaptive capacities for sustainability transformation thus has gained significant research attention within developed countries, much less so in developing countries. Filling this gap, this article develops a conceptual framework for analysing the level of adaptive capacities (if any) within a developing context. This framework then applied to the chronological development of urban water governance strategies in Bangladesh for almost two centuries. The chronological analysis of governance interventions has revealed that crisis (public health, food and natural hazards) became the opportunities and thus opened the windows for experimentation and learning to occur as a deviation from traditional practices. Self-organization and networks thus created the platform for development or disruptions to occur for creating change. Leadership (internal or external) is important for nurturing and upscaling theses development or disruptions towards guiding policy vision and targets as well as championing ground implementation. In the case of Bangladesh, the leadership from the international and national aid organizations and targets have always lead the development whereas more often social capital tools (trust, power relations, cultural norms) act as disruptions. Historically, this has been evident in the development pathways of urban water governance in Bangladesh. Overall this research has shown some level of adaptive capacities is growing for sustainable urban growth in big cities, nevertheless unclear regarding the growth in medium and small cities context.

Keywords: adaptive capacity, Bangladesh, sustainability transformation, water governance

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Authors: Haian Dukhan

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The death of Hafez al-Assad and the ascension of his son, Bashar, to rule brought an end to the state-society dynamics that his father worked on for decades. Hafez al-Assad built an authoritarian state that rests on patronage networks that connected his regime to the society. During Bashar’s reign, these patronage relationships have been affected by the policies of privatization and liberalization. Privatization and liberalisation of the economy have created new economic and social players that transformed the populist nature of the authoritarian regime into a regime that is connected mainly with bourgeoisie and the upper class neglecting the rural tribal constituency that was a vital part of Hafez al-Assad’s authoritarian state. Drawing on different data gathered through interviews as well as written literature, this paper will explore the policies that Bashar al-Assad carried out towards the Arab tribes in the period extended from 2000 until 2010. The paper starts by outlining how Bashar al-Assad narrowed the coalition of his rule to depend mainly on his family, the city merchants excluding the lower and middle strata in the periphery. It will then trace the disintegration of the social contract between the regime and the Arab tribe as a result of the latter’s failure to deliver adequate development services in their regions. Losing the support of the tribes undermined the stability of the regime resulting in different clashes between the tribes themselves, the tribes and the Kurds, the tribes and the druze (a sect of Islam situated in Southern Syria), which will be investigated in detail in this paper. In similar policies adopted by his father who used the tribes as leverage against the Islamists and the Kurds, Bashar al-Assad’s regime encouragement of Syrian tribal youth to join the Iraqi insurgency against the Americans will be explored in detail. The regime’s tolerance of Iran missionary activities in the tribal regions and its accommodation of Islamists group’s activities in those regions have erased the regime’s secular foundation. This paper will argue that Bashar al-Assad’s policies towards the Arab tribes have chipped away the regime’s ideological pillars and threatened the longer-term cohesion of its social base which paved the way for the uprising to start in the tribal regions.

Keywords: Syria, tribes, uprising, regime

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Authors: Şenay Güngör, Emre Elbaşi, Beyda Sadikğlu, Utku Eren Bağci, Ömer Uzunel

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One of the first places that comes to mind when it comes to tourism in Turkey is the Cappadocia Region. Due to its rich geological and geomorphological heritage, Cappadocia is one of the most visited destinations in the world. In fact, in the first half of 2023, the number of international tourists visiting Cappadocia exceeded 2 million. Considering that the economy of the Cappadocia region is largely based on tourism, it is understood that the quality and technology integration levels of the touristic services offered in the region are of great importance. In this context; as a result of the observations made in Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys, where the important hiking routes of the Cappadocia Region are located, it has been observed that the digital level of the routes is insufficient. It has been observed that the telephone networks in the area are very low or have completely lost their signal strength. In addition, it was determined that the materials such as maps and brochures used by tourism agencies to introduce the valleys are simple and incomplete. It is thought that this situation negatively affects the tourists' orientation and touristic experience in the field. Eliminating these deficiencies identified in the field, improving the digital level of the above-mentioned hiking routes and increasing the added value in destinations are among the main objectives of our study. Within the scope of the study, a mobile application that can work both online and offline on hiking routes has been prepared. 3D modeling of Kızılçukur, Meskendir, Güllüdere 1 and Güllüdere 2 valleys were made using Geographical Information Systems (GIS). In addition, a website has been created to enable tourists to easily access all the above-mentioned information, visuals and technological applications related to the routes. As it is known, the effective use of information and communication technologies in touristic regions not only increases the satisfaction levels of tourists, but also positively affects the attraction of qualified tourists to the region. When the tangible and intangible outputs of this study are evaluated, it is thought that it will serve the social and economic development of the region and set an example for the digital transformation of other routes in the region.

Keywords: nevşehir, cappadocia, cappadocia valleys, tourism route

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Authors: Poonam Sharma, Ankur Srivastav

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Cities are complex and dynamic systems that constitute a significant challenge to urban planning. The increasing size of the built-up area owing to growing population pressure and economic growth have lead to massive Landuse/Landcover change resulted in the loss of natural habitat and thus reducing the green covers in urban areas. Urban environmental quality is influenced by several aspects, including its geographical configuration, the scale, and nature of human activities occurring and environmental impacts generated. Cities have transformed into complex and dynamic systems that constitute a significant challenge to urban planning. Cities and their sustainability are often discussed together as the cities stand confronted with numerous environmental concerns as the world becoming increasingly urbanized, and the cities are situated in the mesh of global networks in multiple senses. A rapid transformed urban setting plays a crucial role to change the green area of natural habitats. To examine the pattern of urban growth and to measure the Landuse/Landcover change in Gurgoan in Haryana, India through the integration of Geospatial technique is attempted in the research paper. Satellite images are used to measure the spatiotemporal changes that have occurred in the land use and land cover resulting into a new cityscape. It has been observed from the analysis that drastically evident changes in land use has occurred with the massive rise in built up areas and the decrease in green cover and therefore causing the sustainability of the city an important area of concern. The massive increase in built-up area has influenced the localised temperatures and heat concentration. To enhance the decision-making process in urban planning, a detailed and real world depiction of these urban spaces is the need of the hour. Monitoring indicators of key processes in land use and economic development are essential for evaluating policy measures.

Keywords: cityscape, geospatial techniques, green cover index, urban environmental quality, urban planning

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Authors: Park Eri, Sklad Marcin, Tsirogianni Stavroula

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In a world where there is increasing exchange and movement of populations groups, and interconnectedness, there are plenty of opportunities for mutual cultural enrichment. However, in everyday life, relations among different cultural groups do not go that smoothly often resulting in discrimination, inequalities and violence. The increasing differentiation of roles, values and worldviews raise a lot of tensions and dilemmas for the state and people -especially in western liberal societies- about issues of acceptance, fairness, justice, autonomy, plurality, freedom, equality and cohesion. Cultural diversity requires a deeper understanding of the roots, meaning and consequences of group differences. We argue, that a psychology from the standpoint of the subject needs to be developed further according to new societal needs. This means within a globalised society, issues regarding the construction of the other as another have become of utmost importance. In constructing the other human beings construct their ideal and possible worlds and meanings about their lives and their significance by drawing on a set of cultural norms, beliefs and values embedded in the different contexts whereby they find themselves in. In this article, we are describing a series of exercises developed in collaboration with University students in the Netherlands that have been piloted with undergraduate 2nd year University Psychology students. These exercises aimed at making tangible and obvious how students apply different moral principles and norms to regulate relationships, which are linked to hegemonic ideological forces. The exercises were in the form of thought experiments that included 8 moral dilemmas, inspired by the moral foundations theory, that touched on different moral principles. The moral dilemmas were built onto each other in incremental steps: from a very tangible/hands-on level to more challenging and demanding ones which require to step into pre-existing networks on knowledge and discourses. After the execution of every dilemma, a discussion followed, which is focused on building links between the ‘theme of the exercise’ and participants’ own lives experiences. In this paper, we provide an evaluation of the methodology used through a discursive analysis of the discussion between the students and the teacher.

Keywords: citizenship, moral dilemmas, social justice, education

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Fiza Azam, Sahar Zia, Fatima Nazir Ali, Aysha Hanif

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Health is a fundamental human right, and a healthy population is essential for the prosperity and sustainable development of any country. This research is aligned with United Nations' Goal 3: Good Health and Well-being. It aims to assess and rank key health indicators across selected South Asian countries. The study focuses on urban areas in these nations, drawing on data from the World Bank’s primary collection of relevant indicators and specific health determinants outlined by the World Health Organization (WHO). These determinants include the physical environment, income and social status, education, social support networks, and personal behavior. To evaluate disparities in urban health across the region, the Urban Health Index (UHI) developed by Georgia State University, USA, is employed, followed by a mapping technique including visualization through a choropleth map to identify the pattern of spatial variations in our key variables, such as socioeconomic indicators across the region. This index serves as a comparative tool to rank health outcomes, where higher UHI values indicate better health conditions. The findings reveal notable disparities across South Asia. Afghanistan, with the lowest UHI score of 0.0423, ranks first, indicating the least favorable urban health conditions. Pakistan follows with a UHI score of 0.1190. Bangladesh and India rank third and fourth with UHI scores of 0.3099 and 0.3250, respectively. The Maldives and Sri Lanka rank fifth and sixth, with UHI scores of 0.3432 and 0.3495. Bhutan is ranked seventh with a score of 0.4750. Nepal, with a UHI score of 0.5012, ranks eighth, indicating the best urban health conditions among the countries studied. The findings of this research are crucial for addressing health disparities, improving living conditions, and enhancing social well-being in the region. These insights can inform policy measures aimed at reducing inequalities and promoting sustainable urban health in South Asia.

Keywords: urban health index, health disparities, sustainable development, South Asia, World Health Organization, United Nations, living conditions, public health

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Authors: Subham Ghosh, Banani Basu, Marami Das

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Background: The development of compact, low-power antenna sensors has resulted in hardware restructuring, allowing for wireless ubiquitous sensing. The antenna sensors can create wireless body-area networks (WBAN) by linking various wireless nodes across the human body. WBAN and IoT applications, such as remote health and fitness monitoring and rehabilitation, are becoming increasingly important. In particular, Parkinson’s disease (PD), a common neurodegenerative disorder, presents clinical features that can be easily misdiagnosed. As a mobility disease, it may greatly benefit from the antenna’s nearfield approach with a variety of activities that can use WBAN and IoT technologies to increase diagnosis accuracy and patient monitoring. Methodology: This study investigates the feasibility of leveraging a single patch antenna mounted (using cloth) on the wrist dorsal to differentiate actual Parkinson's disease (PD) from false PD using a small hardware platform. The semi-flexible antenna operates at the 2.4 GHz ISM band and collects reflection coefficient (Γ) data from patients performing five exercises designed for the classification of PD and other disorders such as essential tremor (ET) or those physiological disorders caused by anxiety or stress. The obtained data is normalized and converted into 2-D representations using the Gabor wavelet transform (GWT). Data augmentation is then used to expand the dataset size. A lightweight deep-learning (DL) model is developed to run on the GPU-enabled NVIDIA Jetson Nano platform. The DL model processes the 2-D images for feature extraction and classification. Findings: The DL model was trained and tested on both the original and augmented datasets, thus doubling the dataset size. To ensure robustness, a 5-fold stratified cross-validation (5-FSCV) method was used. The proposed framework, utilizing a DL model with 1.356 million parameters on the NVIDIA Jetson Nano, achieved optimal performance in terms of accuracy of 88.64%, F1-score of 88.54, and recall of 90.46%, with a latency of 33 seconds per epoch.

Keywords: antenna, deep-learning, GPU-hardware, Parkinson’s disease

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Authors: Hanna Kroczak

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In Poland, the system of social and professional reintegration of people at risk of social exclusion is, in fact, based on the activity of social economy enterprises. Playing this significant role these entities have to cope with various problems, related to the necessity of being successful on the open market, location on the peripheral (especially rural) areas or the “socialist heritage” in social and economic relations, which is certainly not favorable for implementing the idea of activation policy. One of the main objectives of the project entitled “Innovation among people. The analysis of the innovations creation and implementation in companies and social economy enterprises operating in Poland”, was to investigate the innovativeness of Polish social economy entities as a possible way for them to be prosperous (the project was funded by the Polish National Science Centre grant on the decision DEC-2013/11/B/HS4/00691). The ethnographic research in this matter was conducted in 2015 in two parts: six three-day studies using participant observation and individual in-depth interview (IDI) techniques (in three social cooperatives and three social integration centres) and two one-month shadowings (in one social cooperative and one social integration centre). Enterprises were selected from various provinces in Poland on the basis of data from previous computer-assisted telephone interviewing (CATI) research, where they declared that innovation management is a central element of their strategy. The ethnographic study revealed that they, indeed, create innovations and the main types of them are social and organisational innovations – but not always and not all the employees are aware of that. Moreover, it turned out that wherever the research was conducted, researchers found some similar opportunities of innovations creating process, like a “charismatic leader”, true passion and commitment not depended on the earned money or building local institutional networks, and similar threats, e.g. under-staffed offices or the great bureaucracy of some institutions. The primary conclusion for the studied entities is that being innovative is not only their challenge and opportunity for well-being at the same time, but even a necessity, something deeply rooted in their specific organisational structures. Explanations and illustrations for the statements above will be presented in the proposed paper.

Keywords: ethnographic research, innovation, Polish social economy, professional reintegration, social economy enterprises, social reintegration

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Authors: K. Anas, M. Selvakumar, Samson David, R. R. Babu, S. Chattopadhyay

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The dynamic deformation of a visco elastic material can cause heat generation. This heat generation is aspect energy dissipation. The present work investigates the contribution of various factors like; elastomer structure, cross link type and density, filler networking, reinforcement potential and temperature at energy dissipation mechanism. The influences of these elements are investigated using very high frequency analyzer (VHF ) and dynamical mechanical analysis(DMA).VHF follows transmissibility and vibration isolation principle whereas DMA works on dynamical mechanical deformation principle. VHF analysis of different types of elastomers reveals that elastomer can act as a transmitter or damper of energy depending on the applied frequency ratio (ω/ωn). Dynamic modulus (G') of low damping rubbers like natural rubber does not varies rapidly with frequency but vice-versa for high damping rubber like butyl rubber (IIR). VHF analysis also depicts that polysulfidic linkages has high damping ratio (ζ) than mono sulfidic linkages due to its dissipative nature. At comparable cross link density, mono sulfidic linkages shows higher glass transition temperature (Tg) than poly sulfidic linkages. The intensity and location of loss modulus (G'') peak of different types of carbon black filled natural rubber compounds suggests that segmental relaxation at glass transition temperature (Tg) is seldom affected by filler particles, but the filler networks can influence the cross link density by absorbing the curatives. The filler network breaking and reformation during a dynamic strain is a thermally activated process. Thus, stronger aggregates are highly dissipative in nature. Measurements indicate that at lower temperature regimes polymeric chain friction is highly dissipative in nature.

Keywords: damping ratio, natural frequency, crosslinking density, segmental motion, surface activity, dissipative, polymeric chain friction

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Authors: Constanza Monterrubio-Solis, Jose Tomas Ibarra

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The fertile interdependence of social-ecological systems reveals itself in the interactions between native forests and seeds, home gardens, kitchens, foraging activities, local knowledge, and food practices, creating particular flavors and food meanings as part of cultural identities within territories. Resilience in local-food systems, from a relational perspective, can be understood as the balance between persistence and adaptability to change. Food growing, preparation, and consumption are constantly changing and adapting as expressions of agency of female and male indigenous peoples and peasants. This paper explores local food systems’ expressions of resilience in the la Araucanía region of Chile, namely: diversity, redundancy, buffer capacity, modularity, self-organization, governance, learning, equity, and decision-making. Applying ethnographic research methods (participant observation, focus groups, and semi-structured interviews), this work reflects on the experience developed through work with Mapuche women cultivating home gardens in the region since 2012; it looks to material and symbolic elements of resilience in the local indigenous food systems. Local food systems show indeed indicators of social-ecological resilience. The biocultural memory is expressed in affection to particular flavors and recipes, the cultural importance of seeds and reciprocity networks, as well as an accurate knowledge about the indicators of the seasons and weather, which have allowed local food systems to thrive with a strong cultural foundation. Furthermore, these elements turn into biocultural resistance in the face of the current institutional pressures for rural specialization, processes of cultural assimilation such as agroecosystems and diet homogenization, as well as structural threats towards the diversity and freedom of native seeds. Thus, the resilience-resistance dynamic shown by the social-ecological systems of the southern Andes is daily expressed in the local food systems and flavors and is key for diverse and culturally sound social-ecological health.

Keywords: biocultural heritage, indigenous food systems, social-ecological resilience, southern Andes

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Authors: Imad Khan, Imran Shafi, Sarmad Farooq

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Large diameter pipes, barrels, tubes, and ducts are used in a variety of applications covering civil and defense-related technologies. This may include heating/cooling networks, sign poles, bracing, casing, and artillery and tank gun barrels. These large diameter assemblies require regular inspection and cleaning to increase their life and reduce replacement costs. This paper describes the design, development, and testing results of an efficient yet simplified, low maintenance mechanical design controlled with minimal essential electronics using an electric motor for a non-technical staff. The proposed solution provides a simplified user interface and an automated cleaning mechanism that requires a single user to optimally clean pipes and barrels in the range of 105 mm to 203 mm caliber. The proposed system employs linear motion of specially designed brush along the barrel using a chain of specific strength and a pulley anchor attached to both ends of the barrel. A specially designed and manufactured gearbox is coupled with an AC motor to allow movement of contact brush with high torque to allow efficient cleaning. A suitably powered AC motor is fixed to the front adapter mounted on the muzzle side whereas the rear adapter has a pulley-based anchor mounted towards the breach block in case of a gun barrel. A mix of soft nylon and hard copper bristles-based large surface brush is connected through a strong steel chain to motor and anchor pulley. The system is equipped with limit switches to auto switch the direction when one end is reached on its operation. The testing results based on carefully established performance indicators indicate the superiority of the proposed user-friendly cleaning mechanism vis-à-vis its life cycle cost.

Keywords: pipe cleaning mechanism, limiting switch, pipe cleaning robot, large pipes

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Authors: Emanuela Zilli, Antonio Madia, Milvia Marchiori, Paola Anello, Chiara Cabbia, Emanuela Velo, Delia Campagnolo, Michele Scomazzon, Emanuela Salvatico, S. Tikvina, Antonio Miotti

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Hepatitis C is an inflammation of the liver caused by the hepatitis C virus (HCV). Antiviral medicines can cure more than 95% of cases of hepatitis C infection, but access to diagnosis and treatment remains low. The ULSS 6 Euganea – Health Trust has implemented a campaign to eradicate hepatitis C in the province of Padua (North-East of Italy), which can be subdivided into three areas: North (300.000 inhabitants), Centre (400.000) and South (300.000). In September 2021, the project was launched in the Northern area; a set of brochures was distributed in outpatient services, general practitioners’ clinics and offices, community pharmacy services, social health districts, and through social networks. The Hepatology Service contacted 460 patients selected by the Clinical Laboratory (positivity for HCV antibodies): 83 patients (18.0%) had been already cured of HCV infection, missing or deceased; 377 patients (82.0%) met the criteria to be eligible for HCV eradication therapy and were therefore included in a Day Service specific agenda and followed by a multidisciplinary team of healthcare professionals, with a dedicated telephone line. Haemato-chemical tests, general medical check-ups and ultrasound tests with fibroscan were performed. Patients were tested for Sars-CoV-2 positivity; those not yet vaccinated against Covid-19 were encouraged to complete the vaccination scheme. All 377 patients (100%) received HCV eradication therapy at the community pharmacy service; a detailed explanation of how to take their medication was provided. At the end of the first phase, Covid-19 vaccination rate was 100% (377/377), including patients already vaccinated and new-vaccinated. Check-up appointments were arranged after 2 or 3 months, according to the treatment plan. The awareness campaign and the organization of HCV eradication therapy service by ULSS 6 Euganea are proving to be effective; the project is now going to be applied to Central and Southern areas of the province (1.132 patients).

Keywords: public health, HCV-eradication, Covid-19 emergency, health communication strategies

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Authors: M. Achemo, O. Saito

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Jefoure land use system is one of the traditional landscape human settlement patterns, and it is a cultural design and peculiar art of the people of Gurage in Ethiopia via which houses and trees flank roads left and right. Assessment of the multiple benefits of the traditional road that benefit society and development could enhance the understanding of the land use planners and decision makers to pay attention while planning and managing the land use system. Recent trend shows that the Jefoure land use is on the threshold of change as a result of flourishing road networks, overgrazing, and agricultural expansion. This study aimed to evaluate the multiple ecosystem services provided by the Jefoure land use system after characterization of the socio-ecological landscape. Information was compiled from existing data sources such as ordnance survey maps, aerial photographs, recent high resolution satellite imageries, designated questionnaires and interviews, and local authority contacts. The result generated scientific data on the characteristics, ecosystem services provision, and drivers of changes. The cultural landscape has novel characteristics and providing multiple ecosystem services to the community for long period of time. It is serving as road for humans, livestock and vehicles, habitat for plant species, regulating local temperature, climate, runoff and infiltration, and place for meeting, conducting religious and spiritual activities, holding social events such as marriage and mourning, playing station for children and court for football and other traditional games. As a result of its aesthetic quality and scenic beauty, it is considered as recreational place for improving mental and physical health. The study draws relevant land use planning and management solution in the improvement of socio-ecological resilience in the Jefoure land use system. The study suggests the landscape needs to be registrar as heritage site for recognizing the wisdom of the community and enhancing the conservation mechanisms.

Keywords: cultural landscape, ecosystem services, Gurage, Jefoure

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