Search results for: global sustainable index

Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Adela Diepoltova, Klara Konecna, Ondrej Jandourek, Petr Nachtigal

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A loss of control over antibiotic-resistant pathogens has become a global issue due to severe and often untreatable infections. This state is reflected in complicated treatment, health costs, and higher mortality. All these factors emphasize the urgent need for the discovery and development of new anti-infectives. One of the most common pathogens mentioned in the phenomenon of antibiotic resistance are bacteria of the genus Staphylococcus. These bacterial agents have developed several mechanisms against the effect of antibiotics. One of them is biofilm formation. In staphylococci, biofilms are associated with infections such as endocarditis, osteomyelitis, catheter-related bloodstream infections, etc. To author's best knowledge, no validated and standardized methodology evaluating candidate compound activity against staphylococcal biofilms exists. However, a variety of protocols for in vitro drug activity testing has been suggested, yet there are often fundamental differences. Based on our experience, a key methodological step that leads to credible results is to form a robust biofilm with appropriate attributes such as firm adherence to the substrate, a complex arrangement in layers, and the presence of extracellular polysaccharide matrix. At first, for the purpose of drug antibiofilm activity evaluation, the focus was put on various conditions (supplementation of cultivation media by human plasma/fetal bovine serum, shaking mode, the density of initial inoculum) that should lead to reproducible and robust in vitro staphylococcal biofilm formation in microtiter plate model. Three model staphylococcal reference strains were included in the study: Staphylococcus aureus (ATCC 29213), methicillin-resistant Staphylococcus aureus (ATCC 43300), and Staphylococcus epidermidis (ATCC 35983). The total biofilm biomass was quantified using the Christensen method with crystal violet, and results obtained from at least three independent experiments were statistically processed. Attention was also paid to the viability of the biofilm-forming staphylococcal cells and the presence of extracellular polysaccharide matrix. The conditions that led to robust biofilm biomass formation with attributes for biofilms mentioned above were then applied by introducing an alternative method analogous to the commercially available test system, the Calgary Biofilm Device. In this test system, biofilms are formed on pegs that are incorporated into the lid of the microtiter plate. This system provides several advantages (in situ detection and quantification of biofilm microbial cells that have retained their viability after drug exposure). Based on our preliminary studies, it was found that the attention to the peg surface and substrate on which the bacterial biofilms are formed should also be paid to. Therefore, further steps leading to the optimization were introduced. The surface of pegs was coated by human plasma, fetal bovine serum, and L-polylysine. Subsequently, the willingness of bacteria to adhere and form biofilm was monitored. In conclusion, suitable conditions were revealed, leading to the formation of reproducible, robust staphylococcal biofilms in vitro for the microtiter model and the system analogous to the Calgary biofilm device, as well. The robustness and typical slime texture could be detected visually. Likewise, an analysis by confocal laser scanning microscopy revealed a complex three-dimensional arrangement of biofilm forming organisms surrounded by an extracellular polysaccharide matrix.

Keywords: anti-biofilm drug activity screening, in vitro biofilm formation, microtiter plate model, the Calgary biofilm device, staphylococcal infections, substrate modification, surface coating

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Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

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Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

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Authors: Hilary Modir, Kyle Dutton, Michelle Swab, Shabnam Asghari

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Since its emergence, the cutaneous manifestations of COVID-19 have been documented in the literature. However, the majority are case reports with significant limitations in appraisal quality, thus leaving the role of dermatological manifestations of COVID-19 erroneously underexplored. The primary aim of this review was to systematically examine clinical patterns of dermatological manifestations as reported in the literature. This study was designed as a systematic review of case reports. The inclusion criteria consisted of all published reports and articles regarding COVID-19 in English, from September 1st, 2019, until June 22nd, 2020. The population consisted of confirmed cases of COVID-19 with associated cutaneous signs and symptoms. Exclusion criteria included research in planning stages, protocols, book reviews, news articles, review studies, and policy analyses. With the collaboration of a librarian, a search strategy was created consisting of a mixture of keyword terms and controlled vocabulary. Electronic databases searched were MEDLINE via PubMed, EMBASE, CINAHL, Web of Science, LILACS, PsycINFO, WHO Global Literature on Coronavirus Disease, Cochrane Library, Campbell Collaboration, Prospero, WHO International Clinical Trials Registry Platform, Australian and New Zealand Clinical Trials Registry, U.S. Institutes of Health Ongoing Trials Register, AAD Registry, OSF preprints, SSRN, MedRxiV and BioRxiV. The study selection featured an initial pre-screening of titles and abstracts by one independent reviewer. Results were verified by re-examining a random sample of 1% of excluded articles. Eligible studies progressed for full-text review by two calibrated independent reviewers. Covidence was used to store and extract data, such as citation information and findings pertaining to COVID-19 and cutaneous signs and symptoms. Data analysis and summarization methodology reflect the framework proposed by PRISMA and recommendations set out by Cochrane and Joanna Brigg’s Institute for conducting systematic reviews. The Oxford Centre for Evidence-Based Medicine’s level of evidence was used to appraise the quality of individual studies. The literature search revealed a total of 1221 articles. After the abstract and full-text screening, only 95 studies met the eligibility criteria, proceeding to data extraction. Studies were divided into 58% case reports and 42% series. A total of 833 manifestations were reported in 723 confirmed COVID-19 cases. The most frequent lesions were 23% maculopapular, 15% urticarial and 13% pseudo-chilblains, with 46% of lesions reporting pruritus, 16% erythema, 14% pain, 12% burning sensation, and 4% edema. The most common lesion locations were 20% trunk, 19.5% lower limbs, and 17.7% upper limbs. The time to resolution of lesions was between one and twenty-one days. In conclusion, over half of the reported cutaneous presentations in COVID-19 positive patients were maculopapular, urticarial and pseudo-chilblains, with the majority of lesions distributed to the extremities and trunk. As this review’s sample size only contained COVID-19 confirmed cases with skin presentations, it becomes difficult to deduce the direct relationship between skin findings and COVID-19. However, it can be correlated that acute onset of skin lesions, such as chilblains-like, may be associated with or may warrant consideration of COVID-19 as part of the differential diagnosis.

Keywords: COVID-19, cutaneous manifestations, cutaneous signs, general dermatology, medical dermatology, Sars-Cov-2, skin and infectious disease, skin findings, skin manifestations

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Authors: Giuliana Murfet, Heidi Behrens

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Chronic disease is Australia’s biggest health concern and obesity the leading risk factor for many. Obesity and chronic disease have a higher representation in rural Tasmania, where levels of socio-disadvantage are also higher. People living outside major cities have less access to health services and poorer health outcomes. To help primary healthcare professionals manage obesity, the Australian NHMRC evidence-based clinical practice guidelines for management of overweight and obesity in adults were developed. They include recommendations for practice and models for obesity management. To our knowledge there has been no research conducted that investigates translation of these guidelines into practice in rural-regional areas; where implementation can be complicated by limited financial and staffing resources. Also, the systematic review that informed the guidelines revealed a lack of evidence for chronic disease models of obesity care. The aim was to establish and evaluate a multidisciplinary model for obesity management in a group of adult people with type 2 diabetes in a dispersed rural population in Australia. Extensive stakeholder engagement was undertaken to both garner support for an obesity clinic and develop a sustainable model of care. A comprehensive nurse practitioner-led outpatient model for obesity care was designed. Multidisciplinary obesity clinics for adults with type 2 diabetes including a dietitian, psychologist, physiotherapist and nurse practitioner were set up in the north-west of Tasmania at two geographically-rural towns. Implementation was underpinned by the NHMRC guidelines and recommendations focused on: assessment approaches; promotion of health benefits of weight loss; identification of relevant programs for individualising care; medication and bariatric surgery options for obesity management; and, the importance of long-term weight management. A clinical pathway for adult weight management is delivered by the multidisciplinary team with recognition of the impact of and adjustments needed for other comorbidities. The model allowed for intensification of intervention such as bariatric surgery according to recommendations, patient desires and suitability. A randomised controlled trial is ongoing, with the aim to evaluate standard care (diabetes-focused management) compared with an obesity-related approach with additional dietetic, physiotherapy, psychology and lifestyle advice. Key barriers and enablers to guideline implementation were identified that fall under the following themes: 1) health care delivery changes and the project framework development; 2) capacity and team-building; 3) stakeholder engagement; and, 4) the research project and partnerships. Engagement of not only local hospital but also state-wide health executives and surgical services committee were paramount to the success of the project. Staff training and collective development of the framework allowed for shared understanding. Staff capacity was increased with most taking on other activities (e.g., surgery coordination). Barriers were often related to differences of opinions in focus of the project; a desire to remain evidenced based (e.g., exercise prescription) without adjusting the model to allow for consideration of comorbidities. While barriers did exist and challenges overcome; the development of critical partnerships did enable the capacity for a potential model of obesity care for rural regional areas. Importantly, the findings contribute to the evidence base for models of diabetes and obesity care that coordinate limited resources.

Keywords: diabetes, interdisciplinary, model of care, obesity, rural regional

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Authors: Kalaumari Mayoral-Peña, Ana I. Montejano-Montelongo, Josué Reyes-Muñoz, Gonzalo A. Ortiz-Mancilla, Mayrin Rodríguez-Cruz, Víctor Hernández-Villalobos, Jesús A. Guzmán-López, Santiago García-Jacobo, Iván Licona-Vázquez, Grisel Fierros-Romero, Rosario Flores-Vallejo

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The group B-lactamic antibiotics include some of the most frequently used small drug molecules against bacterial infections. Nevertheless, an alarming decrease in their efficacy has been reported due to the emergence of antibiotic-resistant bacteria. Infections caused by bacteria expressing extended Spectrum B-lactamases (ESBLs) are difficult to treat and account for higher morbidity and mortality rates, delayed recovery, and high economic burden. According to the Global Report on Antimicrobial Resistance Surveillance, it is estimated that mortality due to resistant bacteria will ascend to 10 million cases per year worldwide. These facts highlight the importance of developing low-cost and readily accessible detection methods of drug-resistant ESBLs bacteria to prevent their spread and promote accurate and fast diagnosis. Bacterial detection is commonly done using molecular diagnostic techniques, where PCR stands out for its high performance. However, this technique requires specialized equipment not available everywhere, is time-consuming, and has a high cost. Loop-Mediated Isothermal Amplification (LAMP) is an alternative technique that works at a constant temperature, significantly decreasing the equipment cost. It yields double-stranded DNA of several lengths with repetitions of the target DNA sequence as a product. Although positive and negative results from LAMP can be discriminated by colorimetry, fluorescence, and turbidity, there is still a large room for improvement in the point-of-care implementation. DNA origami is a technique that allows the formation of 3D nanometric structures by folding a large single-stranded DNA (scaffold) into a determined shape with the help of short DNA sequences (staples), which hybridize with the scaffold. This research aimed to generate DNA origami structures using LAMP products as scaffolds to improve the sensitivity to detect ESBLs in point-of-care diagnosis. For this study, the coding sequence of the CTM-X-15 ESBL of E. coli was used to generate the LAMP products. The set of LAMP primers were designed using PrimerExplorerV5. As a result, a target sequence of 200 nucleotides from CTM-X-15 ESBL was obtained. Afterward, eight different DNA origami structures were designed using the target sequence in the SDCadnano and analyzed with CanDo to evaluate the stability of the 3D structures. The designs were constructed minimizing the total number of staples to reduce costs and complexity for point-of-care applications. After analyzing the DNA origami designs, two structures were selected. The first one was a zig-zag flat structure, while the second one was a wall-like shape. Given the sequence repetitions in the scaffold sequence, both were able to be assembled with only 6 different staples each one, ranging between 18 to 80 nucleotides. Simulations of both structures were performed using scaffolds of different sizes yielding stable structures in all the cases. The generation of the LAMP products were tested by colorimetry and electrophoresis. The formation of the DNA structures was analyzed using electrophoresis and colorimetry. The modeling of novel detection methods through bioinformatics tools allows reliable control and prediction of results. To our knowledge, this is the first study that uses LAMP products and DNA-origami in combination to delect ESBL-producing bacterial strains, which represent a promising methodology for diagnosis in the point-of-care.

Keywords: beta-lactamases, antibiotic resistance, DNA origami, isothermal amplification, LAMP technique, molecular diagnosis

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Authors: Olga Kononova, Sergey Lyapin

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Global information society requirements are transparency and reliability of data, as well as ability to manage information resources independently; particularly to search, to analyze, to evaluate information, thereby obtaining new expertise. Moreover, it is satisfying the society information needs that increases the efficiency of the enterprise management and public administration. The study of structurally organized thematic and semantic contexts of different types, automatically extracted from unstructured data, is one of the important tasks for the application of information technologies in education, science, culture, governance and business. The objectives of this study are the contextual knowledge typologization, selection or creation of effective tools for extracting and analyzing contextual knowledge. Explication of various kinds and forms of the contextual knowledge involves the development and use full-text search information systems. For the implementation purposes, the authors use an e-library 'Humanitariana' services such as the contextual search, different types of queries (paragraph-oriented query, frequency-ranked query), automatic extraction of knowledge from the scientific texts. The multifunctional e-library «Humanitariana» is realized in the Internet-architecture in WWS-configuration (Web-browser / Web-server / SQL-server). Advantage of use 'Humanitariana' is in the possibility of combining the resources of several organizations. Scholars and research groups may work in a local network mode and in distributed IT environments with ability to appeal to resources of any participating organizations servers. Paper discusses some specific cases of the contextual knowledge explication with the use of the e-library services and focuses on possibilities of new types of the contextual knowledge. Experimental research base are science texts about 'e-government' and 'computer games'. An analysis of the subject-themed texts trends allowed to propose the content analysis methodology, that combines a full-text search with automatic construction of 'terminogramma' and expert analysis of the selected contexts. 'Terminogramma' is made out as a table that contains a column with a frequency-ranked list of words (nouns), as well as columns with an indication of the absolute frequency (number) and the relative frequency of occurrence of the word (in %% ppm). The analysis of 'e-government' materials showed, that the state takes a dominant position in the processes of the electronic interaction between the authorities and society in modern Russia. The media credited the main role in these processes to the government, which provided public services through specialized portals. Factor analysis revealed two factors statistically describing the used terms: human interaction (the user) and the state (government, processes organizer); interaction management (public officer, processes performer) and technology (infrastructure). Isolation of these factors will lead to changes in the model of electronic interaction between government and society. In this study, the dominant social problems and the prevalence of different categories of subjects of computer gaming in science papers from 2005 to 2015 were identified. Therefore, there is an evident identification of several types of contextual knowledge: micro context; macro context; dynamic context; thematic collection of queries (interactive contextual knowledge expanding a composition of e-library information resources); multimodal context (functional integration of iconographic and full-text resources through hybrid quasi-semantic algorithm of search). Further studies can be pursued both in terms of expanding the resource base on which they are held, and in terms of the development of appropriate tools.

Keywords: contextual knowledge, contextual search, e-library services, frequency-ranked query, paragraph-oriented query, technologies of the contextual knowledge extraction

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Authors: Kaori Nakamura, Shun Su, Yusak Sulio, Daisuke Fukuda

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Active modes of transportation, such as walking and cycling, are crucial in promoting healthy and sustainable urban environments. Encouraging the use of these modes requires a well-designed road environment that ensures safety and comfort. Understanding what constitutes a safe environment for these users is essential. While previous research mainly focuses on subjective safety or the likelihood of collisions, there needs to be more analysis of the real-time experiences of travelers and dynamic transitions of their discomfort perceptions. Post-ride surveys or pre-ride impressions, the typical evaluation methods in past studies, may not accurately capture the immediate reactions and discomforts experienced during their rides. Though past experimental studies may also use physiological and behavioral data to evaluate road designs, they evaluated road design by comparing time-average physiological and behavioral data across different designs. This study aims to investigate the effects of the dynamic riding environmental changes experienced by cyclists during their rides on their dynamic physiological and behavioral responses and then explore how these conditions contribute to cyclists' overall subjective safety and comfort. We conducted an experiment with 24 participants who cycled approximately 500 meters in a virtual reality (VR) environment designed to mimic a typical road environment of Japanese local towns where lanes for cyclists and regular cars are adjacent in limited road spaces. Participants experienced six road designs varying in width, separation type, and bike lane color. We measured their physiological data, such as heart rate and skin conductance, and behavioral data, including steering, acceleration, and coordination of bicycles. Questionnaires for eliciting subjective impressions were conducted before and after each ride. The data analysis results indicate that wider paths (i.e., 1.5m and 2m width) are preferred, enhancing perceived safety and reducing stress, as supported by lower heart rates and skin conductance levels over narrower ones (1m width). Designs with clear divisions from car lanes may enhance perceived safety and reduce stress. The analysis of the physiological data also supports these arguments, showing that lower heart rates and skin conductance levels are found in wider, clearly marked paths. Further, the drift-diffusion decision model was performed to reveal whether different road environment designs may impact dynamic decision-making processes and physiological attributes. Designing a 1.5m wide bike lane with clear divisions from car lanes showed the highest level of clarity and safety in decision-making parameters. In contrast, designs without clear separations from car lanes resulted in less favorable decision-making outcomes. These results coincide with previous primary research indicating a preference for bike lane widths more significant than 1.5m. In conclusion, the analysis using the drift-diffusion decision model showed that decision-making ease slightly differs from subjective safety perceptions, providing a comprehensive understanding of how different road designs impact users. This study offers a solid foundation for assessing the perceptions of active mode users and highlights the importance of considering both real-time physiological and subjective data in designing road environments that encourage active transportation modes.

Keywords: active transport modes, cognitive and decision-making modeling, road environment designs, virtual reality experiment

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Authors: Cory B. Portner, Julie A. Grauert, Lisa M. Stromme, Shelby D. Anderson, Franji H. Mayes

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Introduction: WASHINGTON state in the Pacific Northwest of the United States is internationally known for its technology industry, fisheries, agriculture, and vistas. On January 21, 2020, Washington state also became known as the first state with a confirmed COVID-19 case in the United States, thrusting the state into the international spotlight as the world came to grips with the global threat of this disease presented. Tourism is Washington state’s fourth-largest industry. Tourism to the state generates over 1.8 billion dollars (USD) in local and state tax revenue and employs over 180,000 people. Communicating with residents, stakeholders, and visitors on the status of disease activity, prevention measures, and response updates was vital to stopping the pandemic and increasing compliance and awareness. Significance: In order to communicate vital public health updates, guidance implementation, and safety measures to the public, the Washington State Department of Health established routine live virtual media briefings to reach audiences via social media, internet television, and broadcast television. Through close partnership with regional broadcast news stations and the state public affairs news network, the Washington State Department of Health hosted 95 media briefings from January 2020 through September 2022 and continues to regularly host live virtual media briefings to accommodate the needs of the public and media. Methods: Our methods quickly evolved from hosting briefings in the cement closet of a military base to being able to produce and stream the briefings live from any home-office location. The content was tailored to the hot topic of the day and to the reporter's questions and needs. Virtual media briefings hosted through inexpensive or free platforms online are extremely cost-effective: the only mandatory components are WiFi, a laptop, and a monitor. There is no longer a need for a fancy studio or expensive production software to achieve the goal of communicating credible, reliable information promptly. With minimal investment and a small learning curve, facilitators and panelists are able to host highly produced and engaging media availabilities from their living rooms. Results: The briefings quickly developed a reputation as the best source for local and national journalists to get the latest and most factually accurate information about the pandemic. In the height of the COVID-19 response, 135 unique media outlets logged on to participate in the briefing. The briefings typically featured 4-5 panelists, with as many as 9 experts in attendance to provide information and respond to media questions. Preparation was always a priority: Public Affairs staff for the Washington State Department of Health produced over 170 presenter remarks, including guidance on talking points for 63 expert guest panelists. Implication For Practice: Information is today’s most valuable currency. The ability to disseminate correct information urgently and on a wide scale is the most effective tool in crisis communication. Due to our role as the first state with a confirmed COVID-19 case, we were forced to develop the most accurate and effective way to get life-saving information to the public. The cost-effective, web-based methods we developed can be applied in any crisis to educate and protect communities under threat, ultimately saving lives from a laptop.

Keywords: crisis communications, public relations, media management, news media

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Authors: Gospel Iyioku, Jana Mazancova, Jiri Hejkrlik

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The “Agricultural Promotion Policy (2016–2020)” represents a strategic initiative by the Nigerian government to address domestic food shortages and the challenges in exporting products at the required quality standards. Hindered by an inefficient system for setting and enforcing food quality standards, coupled with a lack of market knowledge, the Federal Ministry of Agriculture and Rural Development (FMARD) aims to enhance support for the production and activities of key crops like cashew. By collaborating with farmers, processors, investors, and stakeholders in the cashew sector, the policy seeks to define and uphold high-quality standards across the cashew value chain. Given the challenges and opportunities faced by Nigerian cashew farmers, active participation in cashew marketing groups becomes imperative. These groups serve as essential platforms for farmers to collectively navigate market intricacies, access resources, share knowledge, improve output quality, and bolster their overall bargaining power. Through engagement in these cooperative initiatives, farmers not only boost their economic prospects but can also contribute significantly to the sustainable growth of the cashew industry, fostering resilience and community development. This study explores the perceptions and intentions of farmers regarding their involvement in cashew marketing cooperatives, utilizing an expanded version of the Theory of Planned Behaviour. Drawing insights from a diverse sample of 321 cashew farmers in Southwest Nigeria, the research sheds light on the factors influencing decision-making in cooperative participation. The demographic analysis reveals a diverse landscape, with a substantial presence of middle-aged individuals contributing significantly to the agricultural sector and cashew-related activities emerging as a primary income source for a substantial proportion (23.99%). Employing Structural Equation Modelling (SEM) with Maximum Likelihood Robust (MLR) estimation in R, the research elucidates the associations among latent variables. Despite the model’s complexity, the goodness-of-fit indices attest to the validity of the structural model, explaining approximately 40% of the variance in the intention to join cooperatives. Moral norms emerge as a pivotal construct, highlighting the profound influence of ethical considerations in decision-making processes, while perceived behavioural control presents potential challenges in active participation. Attitudes toward joining cooperatives reveal nuanced perspectives, with strong beliefs in enhanced connections with other farmers but varying perceptions on improved access to essential information. The SEM analysis establishes positive and significant effects of moral norms, perceived behavioural control, subjective norms, and attitudes on farmers’ intention to join cooperatives. The knowledge construct positively affects key factors influencing intention, emphasizing the importance of informed decision-making. A supplementary analysis using partial least squares (PLS) SEM corroborates the robustness of our findings, aligning with covariance-based SEM results. This research unveils the determinants of cooperative participation and provides valuable insights for policymakers and practitioners aiming to empower and support this vital demographic in the cashew industry.

Keywords: marketing cooperatives, theory of planned behaviour, structural equation modelling, cashew farmers

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Authors: Lina Wu

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The excessive discharge of nitrogen in sewage greatly intensifies the eutrophication of water bodies and threatens water quality. Nitrogen pollution control has become a global concern. The concentration of nitrogen in water is reduced by converting ammonia nitrogen, nitrate nitrogen and nitrite nitrogen into nitrogen-containing gas through biological treatment, physicochemical treatment and oxidation technology. However, some wastewater containing high ammonia nitrogen including landfill leachate, is difficult to be treated by traditional nitrification and denitrification because of its high COD content. The core process of denitrification is that denitrifying bacteria convert nitrous acid produced by nitrification into nitrite under anaerobic conditions. Still, its low-carbon nitrogen does not meet the conditions for denitrification. Many studies have shown that the natural autotrophic anammox bacteria can combine nitrous and ammonia nitrogen without a carbon source through functional genes to achieve total nitrogen removal, which is very suitable for removing nitrogen from leachate. In addition, the process also saves a lot of aeration energy consumption than the traditional nitrogen removal process. Therefore, anammox plays an important role in nitrogen conversion and energy saving. The short-range nitrification and denitrification coupled with anaerobic ammoX ensures total nitrogen removal. It improves the removal efficiency, meeting the needs of society for an ecologically friendly and cost-effective nutrient removal treatment technology. In recent years, research has found that the symbiotic system has more water treatment advantages because this process not only helps to improve the efficiency of wastewater treatment but also allows carbon dioxide reduction and resource recovery. Microalgae use carbon dioxide dissolved in water or released through bacterial respiration to produce oxygen for bacteria through photosynthesis under light, and bacteria, in turn, provide metabolites and inorganic carbon sources for the growth of microalgae, which may lead the algal bacteria symbiotic system save most or all of the aeration energy consumption. It has become a trend to make microalgae and light-avoiding anammox bacteria play synergistic roles by adjusting the light-to-dark ratio. Microalgae in the outer layer of light particles block most of the light and provide cofactors and amino acids to promote nitrogen removal. In particular, myxoccota MYX1 can degrade extracellular proteins produced by microalgae, providing amino acids for the entire bacterial community, which helps anammox bacteria save metabolic energy and adapt to light. As a result, initiating and maintaining the process of combining dominant algae and anaerobic denitrifying bacterial communities has great potential in treating landfill leachate. Chlorella has a brilliant removal effect and can withstand extreme environments in terms of high ammonia nitrogen, high salt and low temperature. It is urgent to study whether the algal mud mixture rich in denitrifying bacteria and chlorella can greatly improve the efficiency of landfill leachate treatment under an anaerobic environment where photosynthesis is stopped. The optimal dilution concentration of simulated landfill leachate can be found by determining the treatment effect of the same batch of bacteria and algae mixtures under different initial ammonia nitrogen concentrations and making a comparison. High-throughput sequencing technology was used to analyze the changes in microbial diversity, related functional genera and functional genes under optimal conditions, providing a theoretical and practical basis for the engineering application of novel bacteria-algae symbiosis system in biogas slurry treatment and resource utilization.

Keywords: nutrient removal and recovery, leachate, anammox, Partial nitrification, Algae-bacteria interaction

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Authors: Roven Tumaneng, Angelica Kristina Monzon, Ralph Sedricke Lapuz, Jose Don De Alban, Jennica Paula Masigan, Joanne Rae Pales, Laila Monera Pornel, Dennis Tablazon, Rizza Karen Veridiano, Jackie Lou Wenceslao, Edmund Leo Rico, Neil Aldrin Mallari

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Most protected area management plans in the Philippines, particularly the smaller and more remote islands suffer from insufficient baseline data, which should provide the bases for formulating measureable conservation targets and appropriate management interventions for these protected areas. Attempts to synthesize available data particularly on cultural and socio-economic characteristic of local peoples within and outside protected areas also suffer from the lack of comprehensive and detailed inventories, which should be considered in designing adaptive management interventions to be used for those protected areas. Mt Guiting-guiting Natural Park (MGGNP) located in Sibuyan Island is one of the poorly studied protected areas in the Philippines. In this study, we determined the highly biologically important areas of the protected area using Maximum Entropy approach (MaxEnt) from environmental predictors (i.e., topographic, bioclimatic,land cover, and soil image layers) derived from global remotely sensed data and point occurrence data of species of birds and trees recorded during field surveys on the island. A total of 23 trigger species of birds and trees was modeled and stacked to generate species richness maps for biological high conservation value areas (HCVAs). Forest habitat change was delineated using dual-polarised L-band ALOS-PALSAR mosaic data at 25 meter spatial resolution, taken at two acquisition years 2007 and 2009 to provide information on forest cover ad habitat change in the island between year 2007 and 2009. Determining the livelihood guilds were also conducted using the data gathered from171 household interviews, from which demographic and livelihood variables were extracted (i.e., age, gender, number of household members, educational attainment, years of residency, distance from forest edge, main occupation, alternative sources of food and resources during scarcity months, and sources of these alternative resources).Using Principal Component Analysis (PCA) and Kruskal-Wallis test, the diversity and patterns of forest resource use by people in the island were determined with particular focus on the economic activities that directly and indirectly affect the population of key species as well as to identify levels of forest resource use by people in different areas of the park.Results showed that there are gaps in the area occupied by the natural park, as evidenced by the mismatch of the proposed HCVAs and the existing perimeters of the park. We found out that subsistence forest gathering was the possible main driver for forest degradation out of the eight livelihood guilds that were identified in the park. Determining the high conservation areas and identifyingthe anthropogenic factors that influence the species richness and abundance of key species in the different management zone of MGGNP would provide guidance for the design of a protected area management plan and future monitoring programs. However, through intensive communication and consultation with government stakeholders and local communities our results led to setting conservation targets in local development plans and serve as a basis for the reposition of the boundaries and reconfiguration of the management zones of MGGNP.

Keywords: conservation gaps, livelihood guilds, MaxEnt, protected area

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Authors: Alexandria Carey, Angela Starkweather, Ann Horgas, Hwayoung Cho, Jason Beneciuk

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Background/Significance: Over 3.4 million acute axial low back pain (aLBP) cases are treated annually in the United States (US) emergency departments (ED). ED patients with aLBP receive varying verbal and written discharge routine care (RC), leading to ineffective patient self-management. Ineffective self-management increase chronic low back pain (cLPB) transition risks, a chief cause of worldwide disability, with associated costs >$60 million annually. This research addresses this significant problem by evaluating an ED digital pain self-management intervention (EDPSI) focused on improving self-management through improved knowledge retainment, skills, and self-efficacy (confidence) (KSC) thus reducing aLBP to cLBP transition in ED patients discharged with aLBP. The research has significant potential to increase self-efficacy, one of the most potent mechanisms of behavior change and improve health outcomes. Focusing on accessibility and usability, the intervention may reduce discharge disparities in aLBP self-management, especially with low health literacy. Study Questions: This research will answer the following questions: 1) Will an EDPSI focused on improving KSC progress patient self-management behaviors and health status?; 2) Is the EDPSI sustainable to improve pain severity, interference, and pain recurrence?; 3) Will an EDPSI reduce aLBP to cLBP transition in patients discharged with aLBP? Aims: The pilot randomized-controlled trial (RCT) study’s objectives assess the effects of a 12-week digital self-management discharge tool in patients with aLBP. We aim to 1) Primarily assess the feasibility [recruitment, enrollment, and retention], and [intervention] acceptability, and sustainability of EDPSI on participant’s pain self-management; 2) Determine the effectiveness and sustainability of EDPSI on pain severity/interference among participants. 3) Explore patient preferences, health literacy, and changes among participants experiencing the transition to cLBP. We anticipate that EDPSI intervention will increase likelihood of achieving self-management milestones and significantly improve pain-related symptoms in aLBP. Methods: The study uses a two-group pilot RCT to enroll 30 individuals who have been seen in the ED with aLBP. Participants are randomized into RC (n=15) or RC + EDPSI (n=15) and receive follow-up surveys for 12-weeks post-intervention. EDPSI innovative content focuses on 1) highlighting discharge education; 2) provides self-management treatment options; 3) actor demonstration of ergonomics, range of motion movements, safety, and sleep; 4) complementary alternative medicine (CAM) options including acupuncture, yoga, and Pilates; 5) combination therapies including thermal application, spinal manipulation, and PT treatments. The intervention group receives Booster sessions via Zoom to assess and reinforce their knowledge retention of techniques and provide return demonstration reinforcing ergonomics, in weeks two and eight. Outcome Measures: All participants are followed for 12-weeks, assessing pain severity/ interference using the Brief Pain Inventory short-form (BPI-sf) survey, self-management (measuring KSC) using the short 13-item Patient Activation Measure (PAM), and self-efficacy using the Pain Self-Efficacy Questionnaire (PSEQ) weeks 1, 6, and 12. Feasibility is measured by recruitment, enrollment, and retention percentages. Acceptability and education satisfaction are measured using the Education-Preference and Satisfaction Questionnaire (EPSQ) post-intervention. Self-management sustainment is measured including PSEQ, PAM, and patient satisfaction and healthcare utilization (PSHU) requesting patient overall satisfaction, additional healthcare utilization, and pain management related to continued back pain or complications post-injury.

Keywords: digital, pain self-management, education, tool

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Authors: Pejman Salimi, Sebastiano Tieuli, Somayeh Taghavi, Michela Signoretto, Remo Proietti Zaccaria

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Increasing the growth of industrial waste due to the large quantities of production leads to numerous environmental and economic challenges, such as climate change, soil and water contamination, human disease, etc. Energy recovery of waste can be applied to produce heat or electricity. This strategy allows for the reduction of energy produced using coal or other fuels and directly reduces greenhouse gas emissions. Among different factories, leather manufacturing plays a very important role in the whole world from the socio-economic point of view. The leather industry plays a very important role in our society from a socio-economic point of view. Even though the leather industry uses a by-product from the meat industry as raw material, it is considered as an activity demanding integrated prevention and control of pollution. Along the entire process from raw skins/hides to finished leather, a huge amount of solid and water waste is generated. Solid wastes include fleshings, raw trimmings, shavings, buffing dust, etc. One of the most abundant solid wastes generated throughout leather tanning is shaving waste. Leather shaving is a mechanical process that aims at reducing the tanned skin to a specific thickness before tanning and finishing. This product consists mainly of collagen and tanning agent. At present, most of the world's leather processing is chrome-tanned based. Consequently, large amounts of chromium-containing shaving wastes need to be treated. The major concern about the management of this kind of solid waste is ascribed to chrome content, which makes the conventional disposal methods, such as landfilling and incineration, not practicable. Therefore, many efforts have been developed in recent decades to promote eco-friendly/alternative leather production and more effective waste management. Herein, shaving waste resulting from metal-free tanning technology is proposed as low-cost precursors for the preparation of carbon material as anodes for lithium-ion batteries (LIBs). In line with the philosophy of a reduced environmental impact, for preparing fully sustainable and environmentally friendly LIBs anodes, deionized water and carboxymethyl cellulose (CMC) have been used as alternatives to toxic/teratogen N-methyl-2- pyrrolidone (NMP) and to biologically hazardous Polyvinylidene fluoride (PVdF), respectively. Furthermore, going towards the reduced cost, we employed water solvent and fluoride-free bio-derived CMC binder (as an alternative to NMP and PVdF, respectively) together with LiFePO₄ (LFP) when a full cell was considered. These actions make closer to the 2030 goal of having green LIBs at 100 $ kW h⁻¹. Besides, the preparation of the water-based electrodes does not need a controlled environment and due to the higher vapour pressure of water in comparison with NMP, the water-based electrode drying is much faster. This aspect determines an important consequence, namely a reduced energy consumption for the electrode preparation. The electrode derived from leather waste demonstrated a discharge capacity of 735 mAh g⁻¹ after 1000 charge and discharge cycles at 0.5 A g⁻¹. This promising performance is ascribed to the synergistic effect of defects, interlayer spacing, heteroatoms-doped (N, O, and S), high specific surface area, and hierarchical micro/mesopore structure of the biochar. Interestingly, these features of activated biochars derived from the leather industry open the way for possible applications in other EESDs as well.

Keywords: biowaste, lithium-ion batteries, physical activation, waste management, leather industry

Procedia PDF Downloads 148

Authors: G. Senoga, D. Nakimuli, B. Ndagire, B. Lukwago, D. Kyamagwa

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Background: The COVID-19 epidemic affected the education sector, with some private schools closing while other children missed schooling for fear contracting COVID-19. Post COVID-19, PSIU in collaborated with Kampala City Council Authority Directorate of Education and Social Science, Water and Sanitation department, and Directorate of Public Health and Environment to improve sanitation and hygiene among pupils and staff in 50 public and private school system in Kampala city. The “Be Clean, Stay Healthy Campaign” used a behavioral change approach in educating, reinforcing and engaging learners on proper hand washing behaviors, proper toilet usage and garbage disposal. In April 2022, 40 Washa lots were constructed, to reduce the pupil - hand wash station ratio; distributed KCCA approved printed materials; oriented 50 teachers, WASH committees to execute and implement hygiene promotion. To ensure sustainability, WASH messages were memorized and practiced through hand washing songs, Pledge, prayer, Poems, Skits, Music, dance and drama, coupled with participatory, practical demonstrations using peer to peer approach, guest speakers at assemblies and in classes. This improved hygiene and sanitation practices. Premised on this, PSI conducted an end line assessment to explore the impact of a hand washing campaign in regards to improvements in hand washing practices and hand hygiene among pupils, accessibility, functionality and usage of the constructed hygiene and sanitation facilities. Method: A cross-sectional post intervention assessment using a mixed methods approach, targeting headteachers, wash committee members and pupils less <17 years was used. Quantitative approaches with a mix of open-ended questions were used in purposively selected respondents in 50 schools. Primary three to primary seven pupils were randomly selected, data was analyzed using the Statistical Package for Social Scientists (SPSS) Outcomes and Findings: 46,989 pupils (51% female), 1,127 and 524 teaching and non-teaching staff were reached by the intervention, respectively. 96% of schools trained on sanitation, sustainable water usage and hygiene constituted 17-man school WASH committees with teacher, parents and pupils representatives. (31%) of the WASH committees developed workplans, (78%) held WASH meetings monthly. This resulted into improved sanitation, water usage, waste management, proper use of toilets, and improved pupils’ health with reduced occurrences of stomach upsets, diarrhoea initially attributed to improper use of latrines and general waste management. Teachers reported reduced number of school absenteeism due to improved hygiene and general waste management at school, especially proper management of sanitary pads. School administrations response rate in purchase of hygiene equipment’s and detergents like soap improved. Regular WASH meetings in classes, teachers and community supervision ensured WASH facilities are used appropriately. Conclusion and Recommendations: Practical behaviour change innovations improves pupil’s knowledge and understanding of hygiene messages and usage. Over 70% of pupils had clear recall of key WASH Messages. There is need for continuous water flow in the Washa lots, harvesting rain water would reduce water bills while complementing National water supply coupled with increasing on Washa lots in densely populated schools.

Keywords: handwashing, hygyiene, sanitation, behaviour change

Procedia PDF Downloads 64

Authors: Angshuman Raha, Abesh Kumar Sanyal, Uttaran Bandyopadhyay, Kaushik Mallick, Kamalika Bhattacharyya, Subrata Gayen, Gaurab Nandi Das, Mohd. Ali, Kailash Chandra

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Indian Himalayan Region (IHR), due to its sheer latitudinal and altitudinal expanse, acts as a mixing ground for different zoogeographic faunal elements. The innumerable unique and distributional restricted rare species of IHR are constantly being threatened with extinction by the ongoing climate change scenario. Many of which might have faced extinction without even being noticed or discovered. Monitoring the community dynamics of a suitable taxon is indispensable to assess the effect of this global perturbation at micro-habitat level. Lepidoptera, particularly moths are suitable for this purpose due to their huge diversity and strict herbivorous nature. The present study aimed to collate scattered historical records of moths from IHR and spatially disseminate the same in Geographic Information System (GIS) domain. The study also intended to identify moth species with significant altitudinal shifts which could be prioritised for monitoring programme to assess the effect of climate change on biodiversity. A robust database on moths recorded from IHR was prepared from voluminous secondary literature and museum collections. Historical sampling points were transformed into richness grids which were spatially overlaid on altitude, annual precipitation and vegetation layers separately to show moth richness patterns along major environmental gradients. Primary samplings were done by setting standard light traps at 11 Protected Areas representing five Indian Himalayan biogeographic provinces. To identify significant altitudinal shifts, past and present altitudinal records of the identified species from primary samplings were compared. A consolidated list of 4107 species belonging to 1726 genera of 62 families of moths was prepared from a total of 10,685 historical records from IHR. Family-wise assemblage revealed Erebidae to be the most speciose family with 913 species under 348 genera, followed by Geometridae with 879 species under 309 genera and Noctuidae with 525 species under 207 genera. Among biogeographic provinces, Central Himalaya represented maximum records with 2248 species, followed by Western and North-western Himalaya with 1799 and 877 species, respectively. Spatial analysis revealed species richness was more or less uniform (up to 150 species record per cell) across IHR. Throughout IHR, the middle elevation zones between 1000-2000m encompassed high species richness. Temperate coniferous forest associated with 1500-2000mm rainfall zone showed maximum species richness. Total 752 species of moths were identified representing 23 families from the present sampling. 13 genera were identified which were restricted to specialized habitats of alpine meadows over 3500m. Five historical localities with high richness of >150 species were selected which could be considered for repeat sampling to assess climate change influence on moth assemblage. Of the 7 species exhibiting significant altitudinal ascend of >2000m, Trachea auriplena, Diphtherocome fasciata (Noctuidae) and Actias winbrechlini (Saturniidae) showed maximum range shift of >2500m, indicating intensive monitoring of these species. Great Himalayan National Park harbours most diverse assemblage of high-altitude restricted species and should be a priority site for habitat conservation. Among the 13 range restricted genera, Arichanna, Opisthograptis, Photoscotosia (Geometridae), Phlogophora, Anaplectoides and Paraxestia (Noctuidae) were dominant and require rigorous monitoring, as they are most susceptible to climatic perturbations.

Keywords: altitudinal shifts, climate change, historical records, Indian Himalayan region, Lepidoptera

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Authors: Delia Gabriela Moisa, Demos Parapanos, Tim Heap

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The tourism sector is mainly comprised of small and medium-sized tourism enterprises (SMEs), representing approximately 80% of global businesses in this field. These entities require focused attention and support to address challenges, ensuring their competitiveness and relevance in a dynamic industry characterized by continuously changing customer preferences. To address these challenges, it becomes imperative to consider not only socio-demographic factors but also delve into the intricate interplay of psychological elements influencing consumer behavior. This study investigates the impact of personality traits and travel motivations on visitor activities in Cumbria, United Kingdom, an iconic region marked by UNESCO World Heritage Sites, including The Lake District National Park and Hadrian's Wall. With a £4.1 billion tourism industry primarily driven by SMEs, Cumbria serves as an ideal setting for examining the relationship between tourist psychology and activities. Employing the Big Five personality model and the Travel Career Pattern motivation theory, this study aims to explain the relationship between psychological factors and tourist activities. The study further explores SME perspectives on personality-based market segmentation, providing strategic insights into addressing evolving tourist preferences.This pioneering mixed-methods study integrates quantitative data from 330 visitor surveys, subsequently complemented by qualitative insights from tourism SME representatives. The findings unveil that socio-demographic factors do not exhibit statistically significant variations in the activities pursued by visitors in Cumbria. However, significant correlations emerge between personality traits and motivations with preferred visitor activities. Open-minded tourists gravitate towards events and cultural activities, while Conscientious individuals favor cultural pursuits. Extraverted tourists lean towards adventurous, recreational, and wellness activities, while Agreeable personalities opt for lake cruises. Interestingly, a contrasting trend emerges as Extraversion increases, leading to a decrease in interest in cultural activities. Similarly, heightened Agreeableness corresponds to a decrease in interest in adventurous activities. Furthermore, travel motivations, including nostalgia and building relationships, drive event participation, while self-improvement and novelty-seeking lead to adventurous activities. Additionally, qualitative insights from tourism SME representatives underscore the value of targeted messaging aligned with visitor personalities for enhancing loyalty and experiences. This study contributes significantly to scholarship through its novel framework, integrating tourist psychology with activities and industry perspectives. The proposed conceptual model holds substantial practical implications for SMEs to formulate personalized offerings, optimize marketing, and strategically allocate resources tailored to tourist personalities. While the focus is on Cumbria, the methodology's universal applicability offers valuable insights for destinations globally seeking a competitive advantage. Future research addressing scale reliability and geographic specificity limitations can further advance knowledge on this critical relationship between visitor psychology, individual preferences, and industry imperatives. Moreover, by extending the investigation to other districts, future studies could draw comparisons and contrasts in the results, providing a more nuanced understanding of the factors influencing visitor psychology and preferences.

Keywords: personality trait, SME, tourist behaviour, tourist motivation, visitor activity

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Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: H. M. El-Askary, S. A. Abd El-Mawla, M. Allali, M. M. El-Hattab, M. El-Raey, A. M. Farahat, M. Kafatos, S. Nickovic, S. K. Park, A. K. Prasad, C. Rakovski, W. Sprigg, D. Struppa, A. Vukovic

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A clear distinction between weather and climate is a necessity because while they are closely related, there are still important differences. Climate change is identified when we compute the statistics of the observed changes in weather over space and time. In this work we will show how the changing climate contribute to the frequency, magnitude and extent of different extreme events using a multi sensor approach with some synergistic modeling activities. We are exploring satellite observations of dust over North Africa, Gulf Region and the Indo Gangetic basin as well as dust versus anthropogenic pollution events over the Delta region in Egypt and Seoul through remote sensing and utilize the behavior of the dust and haze on the aerosol optical properties. Dust impact on the retreat of the glaciers in the Himalayas is also presented. In this study we also focus on the identification and monitoring of a massive dust plume that blew off the western coast of Africa towards the Atlantic on October 8th, 2012 right before the development of Hurricane Sandy. There is evidence that dust aerosols played a non-trivial role in the cyclogenesis process of Sandy. Moreover, a special dust event "An American Haboob" in Arizona is discussed as it was predicted hours in advance because of the great improvement we have in numerical, land–atmosphere modeling, computing power and remote sensing of dust events. Therefore we performed a full numerical simulation to that event using the coupled atmospheric-dust model NMME–DREAM after generating a mask of the potentially dust productive regions using land cover and vegetation data obtained from satellites. Climate change also contributes to the deterioration of different marine habitats. In that regard we are also presenting some work dealing with change detection analysis of Marine Habitats over the city of Hurghada, Red Sea, Egypt. The motivation for this work came from the fact that coral reefs at Hurghada have undergone significant decline. They are damaged, displaced, polluted, stepped on, and blasted off, in addition to the effects of climate change on the reefs. One of the most pressing issues affecting reef health is mass coral bleaching that result from an interaction between human activities and climatic changes. Over another location, namely California, we have observed that it exhibits highly-variable amounts of precipitation across many timescales, from the hourly to the climate timescale. Frequently, heavy precipitation occurs, causing damage to property and life (floods, landslides, etc.). These extreme events, variability, and the lack of good, medium to long-range predictability of precipitation are already a challenge to those who manage wetlands, coastal infrastructure, agriculture and fresh water supply. Adding on to the current challenges for long-range planning is climate change issue. It is known that La Niña and El Niño affect precipitation patterns, which in turn are entwined with global climate patterns. We have studied ENSO impact on precipitation variability over different climate divisions in California. On the other hand the Nile Delta has experienced lately an increase in the underground water table as well as water logging, bogging and soil salinization. Those impacts would pose a major threat to the Delta region inheritance and existing communities. There has been an undergoing effort to address those vulnerabilities by looking into many adaptation strategies.

Keywords: remote sensing, modeling, long range transport, dust storms, North Africa, Gulf Region, India, California, climate extremes, sea level rise, coral reefs

Procedia PDF Downloads 463

Authors: Anjula Negi, Sanjay Gupta

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Paradigms studied inform inadequacies of financial resources, be it to finance metro rails for construction or to meet operational revenues or to derive profits in the long term. Funding sustainability is far and wide for much-needed public transport modes, like urban rail or metro rails, to be successfully operated. India embarks upon a sustainable transport journey and has proposed metro rail systems countrywide. As an emerging economic leader, its fiscal constraints are paramount, and the land value capture (LVC) mechanism provides necessary support and innovation toward development. India’s metro rail policy promotes multiple methods of financing, including private-sector investments and public-private-partnership. The critical question that remains to be addressed is what factors can make such mechanisms work. Globally, urban rail is a revolution noted by many researchers as future mobility. Researchers in this study deep dive by way of literature review and empirical assessments into factors that can lead to the adoption of LVC mechanisms. It is understood that the adoption of LVC methods is in the nascent stages in India. Research posits numerous challenges being faced by metro rail agencies in raising funding and for incremental value capture. A few issues pertaining to land-based financing, inter alia: are long-term financing, inter-institutional coordination, economic/ market suitability, dedicated metro funds, land ownership issues, piecemeal approach to real estate development, property development legal frameworks, etc. The question under probe is what are the parameters that can lead to success in the adoption of land value capture (LVC) as a financing mechanism. This research provides insights into key parameters crucial to the adoption of LVC in the context of Indian metro rails. Researchers have studied current forms of LVC mechanisms at various metro rails of the country. This study is significant as little research is available on the adoption of LVC, which is applicable to the Indian context. Transit agencies, State Government, Urban Local Bodies, Policy makers and think tanks, Academia, Developers, Funders, Researchers and Multi-lateral agencies may benefit from this research to take ahead LVC mechanisms in practice. The study deems it imperative to explore and understand key parameters that impact the adoption of LVC. Extensive literature review and ratification by experts working in the metro rails arena were undertaken to arrive at parameters for the study. Stakeholder consultations in the exploratory factor analysis (EFA) process were undertaken for principal component extraction. 43 seasoned and specialized experts participated in a semi-structured questionnaire to scale the maximum likelihood on each parameter, represented by various types of stakeholders. Empirical data was collected on chosen eighteen parameters, and significant correlation was extracted for output descriptives and inferential statistics. Study findings reveal these principal components as institutional governance framework, spatial planning features, legal frameworks, funding sustainability features and fiscal policy measures. In particular, funding sustainability features highlight sub-variables of beneficiaries to pay and use of multiple revenue options towards success in LVC adoption. Researchers recommend incorporation of these variables during early stage in design and project structuring for success in adoption of LVC. In turn leading to improvements in revenue sustainability of a public transport asset and help in undertaking informed transport policy decisions.

Keywords: Exploratory factor analysis, land value capture mechanism, financing metro rails, revenue sustainability, transport policy

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Authors: Fatima Saeed, Abdullah Mudassar

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Introduction: Patient safety remains a global priority in the ever-evolving healthcare landscape. At the forefront of this endeavor are the International Patient Safety Goals (IPSGs), a standardized framework designed to mitigate risks and elevate the quality of care. Doctors, positioned as primary caregivers, wield a pivotal role in upholding and adhering to IPSGs, underscoring the critical significance of their knowledge and understanding of these goals. This research embarks on a comprehensive exploration into the depth of Doctors ' comprehension of IPSGs, aiming to unearth potential gaps and provide insights for targeted educational interventions. Established by influential healthcare bodies, including the World Health Organization (WHO), IPSGs represent a universally applicable set of objectives spanning crucial domains such as medication safety, infection control, surgical site safety, and patient identification. Adherence to these goals has exhibited substantial reductions in adverse events, fostering an overall enhancement in the quality of care. This study operates on the fundamental premise that an informed Doctors workforce is indispensable for effectively implementing IPSGs. A nuanced understanding of these goals empowers Doctors to identify potential risks, advocate for necessary changes, and actively contribute to a safety-centric culture within healthcare institutions. Despite the acknowledged importance of IPSGs, there is a growing concern that nurses may need more knowledge to integrate these goals into their practice seamlessly. Methodology: A Comprehensive research methodology covering study design, setting, duration, sample size determination, sampling technique, and data analysis. It introduces the philosophical framework guiding the research and details material, methods, and the analysis framework. The descriptive quantitative cross-sectional study in teaching care hospitals utilized convenient sampling over six months. Data collection involved written informed consent and questionnaires, analyzed with SPSS version 23, presenting results graphically and descriptively. The chapter ensures a clear understanding of the study's design, execution, and analytical processes. Result: The survey results reveal a substantial distribution across hospitals, with 34.52% in MTIKTH and 65.48% in HMC MTI. There is a notable prevalence of patient safety incidents, emphasizing the significance of adherence to IPSGs. Positive trends are observed, including 77.0% affirming the "time-out" procedure, 81.6% acknowledging effective healthcare provider communication, and high recognition (82.7%) of the purpose of IPSGs to improve patient safety. While the survey reflects a good understanding of IPSGs, areas for improvement are identified, suggesting opportunities for targeted interventions. Discussion: The study underscores the need for tailored care approaches and highlights the bio-socio-cultural context of 'contagion,' suggesting areas for further research amid antimicrobial resistance. Shifting the focus to patient safety practices, the survey chapter provides a detailed overview of results, emphasizing workplace distribution, patient safety incidents, and positive reflections on IPSGs. The findings indicate a positive trend in patient safety practices with areas for improvement, emphasizing the ongoing need for reinforcing safety protocols and cultivating a safety-centric culture in healthcare. Conclusion: In summary, the survey indicates a positive trend in patient safety practices with a good understanding of IPSGs among participants. However, identifying areas for potential improvement suggests opportunities for targeted interventions to enhance patient safety further. Ongoing efforts to reinforce adherence to safety protocols, address identified gaps, and foster a safety culture will contribute to continuous improvements in patient care and outcomes.

Keywords: infection control, international patient safety, patient safety practices, proper medication

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Authors: Charaia Vakhtang

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Global oil prices are seeing new bottoms every day. The prices have already collapsed beneath the psychological verge of 30 USD. This tendency would be fully acceptable for the Georgian consumers, but there is one detail: two our neighboring countries (one friendly and one hostile) largely depend on resources of these hydrocarbons. Namely, the ratio of Azerbaijan in Georgia’s total FDI inflows in 2014 marked 20%. The ratio reached 40% in the January to September 2015. Azerbaijan is Georgia’s leading exports market. Namely, in 2014 Georgia’s exports to Azerbaijan constituted 544 million USD, i.e. 19% in Georgia’s total experts. In the January to November period of 2015, the ratio exceeded 11%. Moreover, Azerbaijan is Georgia’s strategic partner country as part of many regional projects that are designated for long-term perspectives. For example, the Baku-Tbilisi-Karsi railroad, the Black Sea terminal, preferential gas tariffs for Georgia and so on. The Russian economic contribution to the Georgian economy is also considerable, despite the losses the Russian hostile policy has inflicted to our country. Namely, Georgian emigrants are mainly employed in the Russian Federation and this category of Georgian citizens transfers considerable funds to Georgia every year. These transfers account for about 1 billion USD and consequently, these funds previously equalized to total FDI inflows. Moreover, despite the difficulties in the Russian market, Russia still remains a leader in terms of money transfers to Georgia. According to the last reports, money transfers from Russia to Georgia slipped by 276 million USD in 2015 compared to 2014 (-39%). At the same time, the total money transfers to Georgia in 2015 marked 1.08 billion USD, down 25% from 1.44 billion USD in 2014. This signifies the contraction in money transfers is by ¾ dependent on the Russian factor (in this case, contraction in oil prices and the Russian Ruble devaluation directly make negative impact on money transfers to Georgia). As to other countries, it is interesting that money transfers have also slipped from Italy (to 109 million USD from 121 million USD). Nevertheless, the country’s ratio in total money transfers to Georgia has increased to 10% from 8%. Money transfers to Georgia have increased by 22% (+18 million USD) from the USA. Money transfers have halved from Greece to 117 million USD from 205 million USD. As to Turkey, money transfers to Georgia from Turkey have increased by 1% to 69 million USD. Moreover, the problems with the national currencies of Russia and Azerbaijan, along with the above-mentioned developments, outline unfavorable perspectives for the Georgian economy. The depreciation of the national currencies of Azerbaijan and Russia is expected to bring unfavorable results for the Georgian economy. Even more so, the statement released by the Russian Finance Ministry on expected default is in direct relation to the welfare of the whole region and these tendencies will make direct and indirect negative impacts on Georgia’s economic indicators. Amid the economic slowdown in Armenia, Turkey and Ukraine, Georgia should try to enhance economic ties with comparatively stronger and flexible economies such as EU and USA. In other case, the Georgian economy will enter serious turbulent zone. We should make maximum benefit from the EU association agreement. It should be noted that the Russian economy slowdown that causes both regretful and happy moods in Georgia, will make negative impact on the Georgian economy. The same forecasts are made in relation to Azerbaijan. However, Georgia has many partner countries. Enhancement and development of the economic relations with these countries may maximally alleviate negative impacts from the declining economies. First of all, the EU association agreement should be mentioned as a main source for Georgia’s economic stabilization. It is the Georgian government‘s responsibility to successfully fulfill the EU association agreement requirements. In any case the imports must be replaced by domestic products and the exports should be stimulated through government support programs. The Authorities should ensure drawing more foreign investments and money resources, accumulating more tourism revenues and reducing external debts, budget expenditures should be balanced and the National Bank should carry out strict monetary policy. Moreover, the Government should develop a long-term state economic policy and carry out this policy at various Ministries. It is also of crucial importance to carry out constitutive policy and promote perspective directions on the domestic level.

Keywords: oil prices, economic growth, foreign direct investments, international trade

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Authors: Maria João Ferreira, Natalia Sierra-Garcia, Javier Cremades, Carla António, Ana M. Rodrigues, Helena Silva, Ângela Cunha

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Salicornia ramosissima, a halophyte that grows naturally in coastal areas of the northern hemisphere, is often considered the most promising halophyte candidate for extensive crop cultivation and saline agriculture practices. The expanding interest in this plant surpasses its use as gourmet food and includes their potential application as a source of bioactive compounds for the pharmaceutical industry. Despite growing well in saline soils, sustainable and ecologically friendly techniques to enhance crop production and the nutritional value of this plant are still needed. The root microbiome of S. ramosissima proved to be a source of taxonomically diverse plant growth-promoting bacteria (PGPB). Halotolerant strains of Bacillus, Salinicola, Pseudomonas, and Brevibacterium, among other genera, exhibit a broad spectrum of plant-growth promotion traits [e.g., 3-indole acetic acid (IAA), 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase, siderophores, phosphate solubilization, Nitrogen fixation] and express a wide range of extracellular enzyme activities. In this work, three plant growth-promoting bacteria strains (Brevibacterium casei EB3, Pseudomonas oryzihabitans RL18, and Bacillus aryabhattai SP20) isolated from the rhizosphere and the endosphere of S. ramosissima roots from different saltmarshes along the Portuguese coast were inoculated in S. ramosissima seeds. Plants germinated from inoculated seeds were grown for three months in pots filled with a mixture of perlite and estuarine sediment (1:1) in greenhouse conditions and later transferred to a growth chamber, where they were maintained two months with controlled photoperiod, temperature, and humidity. Pots were placed on trays containing the irrigation solution (Hoagland’s solution 20% added with 10‰ marine salt). Before reaching the flowering stage, plants were collected, and the fresh and dry weight of aerial parts was determined. Non-inoculated seeds were used as a negative control. Selected dried stems from the most promising treatments were later analyzed by GC-TOF-MS for primary metabolite composition. The efficiency of inoculation and persistence of the inoculum was assessed by Next Generation Sequencing. Inoculations with single strain EB3 and co-inoculations with EB3+RL18 and EB3+RL18+SP20 (All treatment) resulted in significantly higher biomass production (fresh and dry weight) compared to non-inoculated plants. Considering fresh weight alone, inoculation with isolates SP20 and RL18 also caused a significant positive effect. Combined inoculation with the consortia SP20+EB3 or SP20+RL18 did not significantly improve biomass production. The analysis of the profile of primary metabolites will provide clues on the mechanisms by which the growth-enhancement effect of the inoculants operates in the plants. These results sustain promising prospects for the use of rhizospheric and endophytic PGPB as biofertilizers, reducing environmental impacts and operational costs of agrochemicals and contributing to the sustainability and cost-effectiveness of saline agriculture. Acknowledgments: This work was supported by project Rhizomis PTDC/BIA-MIC/29736/2017 financed by Fundação para a Ciência e Tecnologia (FCT) through the Regional Operational Program of the Center (02/SAICT/2017) with FEDER funds (European Regional Development Fund, FNR, and OE) and by FCT through CESAM (UIDP/50017/2020 + UIDB/50017/2020), LAQV-REQUIMTE (UIDB/50006/2020). We also acknowledge FCT/FSE for the financial support to Maria João Ferreira through a PhD grant (PD/BD/150363/2019). We are grateful to Horta dos Peixinhos for their help and support during sampling and seed collection. We also thank Glória Pinto for her collaboration providing us the use of the growth chambers during the final months of the experiment and Enrique Mateos-Naranjo and Jennifer Mesa-Marín of the Departamento de Biología Vegetal y Ecología, the University of Sevilla for their advice regarding the growth of salicornia plants in greenhouse conditions.

Keywords: halophytes, PGPB, rhizosphere engineering, biofertilizers, primary metabolite profiling, plant inoculation, Salicornia ramosissima

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