Search results for: humanitarian data management

Authors: Manzoor Ahmad

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The rapid advancement of mobile technology has transformed the way businesses engage with consumers, making mobile marketing a crucial strategy for organizations worldwide. This paper presents a comprehensive study on the adoption of mobile marketing in Pakistan, aiming to provide valuable insights into the current landscape, challenges, and opportunities in this emerging market. To achieve this objective, a mixed-methods approach was employed, combining quantitative surveys and qualitative interviews with industry experts, marketers, and consumers. The study encompassed a diverse range of sectors, including retail, telecommunications, banking, and e-commerce, ensuring a comprehensive understanding of mobile marketing practices across different industries. The findings indicate that mobile marketing has gained significant traction in Pakistan, with a growing number of organizations recognizing its potential for reaching and engaging with consumers effectively. Factors such as increasing smartphone penetration, affordable data plans, and the rise of social media usage have contributed to the widespread adoption of mobile marketing strategies. However, several challenges and barriers to mobile marketing adoption were identified. These include issues related to data privacy and security, limited digital literacy among consumers, inadequate infrastructure, and cultural considerations. Additionally, the study highlights the need for tailored and localized mobile marketing strategies to address the diverse cultural and linguistic landscape of Pakistan. Based on the insights gained from the study, practical recommendations are provided to support organizations in optimizing their mobile marketing efforts in Pakistan. These recommendations encompass areas such as consumer targeting, content localization, mobile app development, personalized messaging, and measurement of mobile marketing effectiveness. This research contributes to the existing literature on mobile marketing adoption in developing countries and specifically sheds light on the unique dynamics of the Pakistani market. It serves as a valuable resource for marketers, practitioners, and policymakers seeking to leverage mobile marketing strategies in Pakistan, ultimately fostering the growth and success of businesses operating in this region.

Keywords: mobile marketing, digital marketing, mobile advertising, adoption of mobile marketing

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Authors: S. W. Chen, W. K. Lin, J. R. Wang, C. Shih, H. T. Lin, H. C. Chang, W. Y. Li

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Kuosheng nuclear power plant (NPP) is a BWR/6 type NPP and located on the northern coast of Taiwan. First, Kuosheng NPP TRACE model were developed in this research. In order to assess the system response of Kuosheng NPP TRACE model, startup tests data were used to evaluate Kuosheng NPP TRACE model. Second, the over pressurization transient analysis of Kuosheng NPP TRACE model was performed. Besides, in order to confirm the mechanical property and integrity of fuel rods, FRAPTRAN analysis was also performed in this study.

Keywords: TRACE, safety analysis, BWR/6, FRAPTRA

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Authors: Jayme R. Swanke

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This study examined the benefits of maintaining public blogs about substance use disorder recovery. The data analyzed for this study included statements about the benefits derived by individuals who blogged about their recovery. The researcher developed classifications of statements that expressed what these individuals gained from blogging into common themes and developed an emerging theory based on these patterns. The findings indicate that these individuals in recovery benefit from blogging by developing connections, processing emotions, remaining accountable, as well as enjoying.

Keywords: substance use disorder recovery, connection, blogging, accountability, processing emotions

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Authors: Daniela Piana

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This work casts light on what lies underneath the rule of law. In order to do so it unfolds the arguments in three main steps. The first one is a pars destruens: the mainstreaming scholarship on judicial independence and judicial accountability is questioned under the large amount of data we have at our disposal (this step is accomplished in the first two paragraphs). The second step is the reframe of the concept of the rule of law and the consequent rise of a hidden dimension, which has been so far largely underexplored: responsiveness. The third step consists into offering the readers empirical support and drawing thereby consequences in terms of policy design and citizens engagement into the rule of law implementation (these two steps are accomplished in the third paragraph).

Keywords: rule of law, accountability, trust, citizens

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Authors: Raja Kannusamy

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The research focuses on reducing food waste in the restaurant industry. A study has been conducted on the chain of retail restaurant outlets. It has been observed that the food wastages are due to the inefficient inventory management systems practiced in the restaurant outlets. The major food items which are wasted more in quantity are being selected across the retail chain outlets. A moving average forecasting method has been applied for the selected food items so that their future demand could be predicted accurately and food wastage could be avoided. It has been found that the moving average prediction method helps in predicting forecasts accurately. The demand values obtained from the moving average method have been compared to the actual demand values and are found to be similar with minimum variations. The inventory optimization technique helps in reducing food wastage in restaurant supply chain outlets.

Keywords: food wastage, restaurant supply chain, inventory optimisation, demand forecasting

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Authors: Sohrab Donyavi

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The global construction market is experiencing significant shifts, particularly for micro, small, and medium enterprises (MSMEs), driven by the dual imperatives of technological advancement and sustainability. MSMEs play a crucial role in the construction industry, often being the backbone of economic development and fostering entrepreneurial skills. However, their dominance has also led to industry fragmentation and challenges such as technological lag and declining profit margins, which threaten their global competitiveness. This paper explores the integration of technology and sustainability in reshaping the paradigms for MSMEs in the construction sector. The adoption of advanced technologies, such as building information modeling (BIM) and AI, are pivotal for promoting sustainable construction practices. These tools enable MSMEs to design and construct environmentally responsible buildings, thereby contributing to the industry's sustainability goals. The research highlights that achieving sustainability in construction involves significant efforts in conservation, recycling, and the development of new materials and technologies. This approach aligns with the broader goal of integrating economic, environmental, and social aims into firm objectives to create long-term value while ensuring the protection of natural resources for future generations. Critical factors for implementing sustainable oriented innovation (SOI) practices in MSMEs include top management support, government initiatives, and financial resources. These factors are essential for fostering an environment conducive to innovation and sustainability. Furthermore, the empowerment of MSMEs through improved governance, market-oriented programs, sustainable productivity growth, and access to financing is vital. In developing regions like Indonesia, these strategies are crucial for enabling MSMEs to thrive in the face of globalization. The tendency of large firms to grow larger with the help of technology and globalization has led to the emergence of a high-technology oligopoly, posing a significant challenge to traditional construction practices. This shift necessitates that MSMEs adapt by leveraging technology and embracing sustainable practices to remain competitive. The research underscores the importance of integrating technology and sustainability not only as a competitive strategy but also as a means to contribute to the global effort of environmental conservation and sustainable development. This paper concludes that the successful integration of technology and sustainability in MSMEs requires a multifaceted approach. It involves the adoption of advanced technological tools, strong support from top management, proactive government policies, and access to financial resources. By addressing these factors, MSMEs can overcome the challenges of industry fragmentation, technological lag, and declining profit margins. Ultimately, this integration will enable MSMEs to play a pivotal role in driving the construction industry towards a more sustainable and technologically advanced future. The findings and recommendations are based on a comprehensive case study utilizing semi-structured interviews, observations, questionnaires, and document reviews.

Keywords: MSMEs, construction, technology, sustainability, innovation

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Authors: Mirain Rhys, Kevin Smith

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In 2017, the Welsh Government introduced an ambitious, new strategy to increase the number of Welsh speakers in Wales to 1 million by 2050. The Welsh education system is a vitally important feature of this strategy. All children attending state schools in Wales learn Welsh as a second language until the age of 16 and are assessed at General Certificate of Secondary Education (GCSE) level. In 2013, a review of Welsh second language instruction in Key Stages 3 and 4 was completed. The report identified considerable gaps in teachers’ preparation and training for teaching Welsh; poor Welsh language ethos at many schools; and a general lack of resources to support the instruction of Welsh. Recommendations were made across a number of dimensions including curriculum content, pedagogical practice, and teacher assessment, training, and resources. With a new national curriculum currently in development, this study builds on this review and provides unprecedented detail into pupils’ and teachers’ perceptions of Welsh language instruction. The current research built on data taken from an existing capacity building research project on Welsh education, the Wales multi-cohort study (WMS). Quantitative data taken from WMS surveys with over 1200 pupils in schools in Wales indicated that Welsh language lessons were the least enjoyable subject among pupils. The current research aimed to unpick pupil experiences in order to add to the policy development context. To achieve this, forty-four pupils and four teachers in three schools from the larger WMS sample participated in focus groups. Participants from years 9, 11 and 13 who had indicated positive, negative and neutral attitudes towards the Welsh language in a previous WMS survey were selected. Questions were based on previous research exploring issues including, but not limited to pedagogy, policy, assessment, engagement and (teacher) training. A thematic analysis of the focus group recordings revealed that the majority of participants held positive views around keeping the language alive but did not want to take on responsibility for its maintenance. These views were almost entirely based on their experiences of learning Welsh at school, especially in relation to their perceived lack of choice and opinions around particular lesson strategies and assessment. Analysis of teacher interviews highlighted a distinct lack of resources (materials and staff alike) compared to modern foreign languages, which had a negative impact on student motivation and attitudes. Both staff and students indicated a need for more practical, oral language instruction which could lead to Welsh being used outside the classroom. The data corroborate many of the review’s previous findings, but what makes this research distinctive is the way in which pupils poignantly address generally misguided aims for Welsh language instruction, poor pedagogical practice and a general disconnect between Welsh instruction and its daily use in their lives. These findings emphasize the complexity of incorporating the educational sector in strategies for Welsh language maintenance and the complications arising from pedagogical training, support, and resources, as well as teacher and pupil perceptions of, and attitudes towards, teaching and learning Welsh.

Keywords: bilingual education, language maintenance, language revitalisation, minority languages, Wales

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Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Danijela Tuljak-Suban, Valter Suban

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Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing of its physical or chemical characteristics considerably influences the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure stability conditions that limit the deterioration, since the value of the deterioration rate could be easily influenced by the transportation mode. Fuzzy definition of variables allows taking into account these variations. Furthermore an appropriate choice of the defuzzification method permits to adapt results, as much as possible, to real conditions. In the article will be applied the those methods to the relationship between the deterioration rate of perishable goods and transportation by ship, with the aim: (a) to minimize the total costs function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) to improve supply chain sustainability by reducing the environmental impact and waste disposal costs.

Keywords: perishable goods, fuzzy reasoning, transport by ship, supply chain sustainability

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Authors: Paula Linna

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During the recent years interest in inclusive business has increased. Still, research on inclusive business development is at infancy. This study provides empirical evidence on inclusive business development of mini-grid solution for the rural African communities. This study tests how well the insights of creation theory can explain inclusive business development process which often occurs under uncertainty due to demands for developing new technology, new business model and establishing business in new market. These several uncertain elements of business development impact what kind of business strategies the entrepreneur can practice and what kind of decision making tools to use. In addition, community engagement is essential for the successful operative management of a mini-grid solution. This study advances the understanding of inclusive business development and can be used as the foundation for future work to facilitate the process of new business venture creation at the BOP particularly when developing community-operated entrepreneurship model.

Keywords: creation theory, base of the pyramid (BOP), community-operated entrepreneurship, rural African communities

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Authors: M. Derraz, M.Farhaoui

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In the water treatment processes, the determination of the optimal dose of the coagulant is an issue of particular concern. Coagulant dosing is correlated to raw water quality which depends on some parameters (turbidity, ph, temperature, conductivity…). The objective of this study is to provide water treatment operators with a tool that enables to predict and replace, sometimes, the manual method (jar testing) used in this plant to predict the optimum coagulant dose. The model is constructed using actual process data for a water treatment plant located in the middle of Morocco (Meknes).

Keywords: coagulation process, aluminum sulfate, model, coagulant dose

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Authors: Asma AlAmri, Ahmed Hassab Errasoul

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Background & Objectives: Psychiatric disorders are common, affecting approximately one of five adults (17.6%) of the population. While most patients can be successfully treated as outpatients, admission to psychiatric wards is required during relapses or as part of crisis intervention. The first 72h of admission could be particularly critical due to increased risk of physical violence, non-medical discharge and absconding. Many patients requiring interventions such as seclusion, physical restrain, PRN psychotropic medications. This study aims to investigate the relationship between demographical, clinical and pharmacological factors in one hand and certain outcomes (physical aggression, use of PRN medications, need for seclusions and non-medical discharges) within the first 72hours of admission to acute psychiatric wards in KKUH/Riyadh Methods: All admissions to psychiatric wards over a 20 month period, between (May 2015- January 2017) were included. Data was collected on demographics, diagnosis, psychotropic medications prescription, documented physical aggression, and seclusion, self-discharge and absconding. Results: 134 males and 171 females were admitted over the study period. Mean age was 34.2 years (SD 11.96).48.9% (n=149) were single and most patients (n=198) were either unemployed or in educations. Bipolar disorder was the most frequent diagnosis recorded on admission (39.3%, n=120); followed by Schizophrenia and related disorders (34.8%; n=106). Most patients (77.4%, n= 236) received regular psychotropic medications on admission. Vis a vis, 223 patients (73%) received PRN medications. Nominal regression model revealed positive relationship between “no psychotropics prescribed on admission” and self-discharge in women but not in men. No statistically significant relationship was found between age, gender, admission diagnosis and use of regular psychotropic medications on admission and need for seclusion, time spent in seclusion, documented physical aggression and use of PRN medications. Conclusion: Contrary to what is expected, our study does not show association between gender, physical aggression and need for seclusion. This could be due to poor documentation practices by nursing staff in male ward comparing with those in the female ward. Use of PRN psychotropics in the first 72 hours of admission was quite high possibly leading to a “ceiling effect”. A limitation of this study is the retrospective data collection.

Keywords: discharge against medical advice, physical aggression, psychotropics, seclusion

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Authors: A. Er-Raki, D. Hartmann, J. P. Belaud, S. Negny

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This paper has a double purpose: firstly, a literature review of the life cycle analysis (LCA) and secondly a comparison between conventional (static) LCA and multi-level dynamic LCA on the following items: (i) inventories evolution with time (ii) temporal evolution of the databases. The first part of the paper summarizes the state of the art of the static LCA approach. The different static LCA limits have been identified and especially the non-consideration of the spatial and temporal evolution in the inventory, for the characterization factors (FCs) and into the databases. Then a description of the different levels of integration of the notion of temporality in life cycle analysis studies was made. In the second part, the dynamic inventory has been evaluated firstly for a single nuclear plant and secondly for the entire French nuclear power fleet by taking into account the construction durations of all the plants. In addition, the databases have been adapted by integrating the temporal variability of the French energy mix. Several iterations were used to converge towards the real environmental impact of the energy mix. Another adaptation of the databases to take into account the temporal evolution of the market data of the raw material was made. An identification of the energy mix of the time studied was based on an extrapolation of the production reference values of each means of production. An application to the construction of the French nuclear power plants from 1971 to 2000 has been performed, in which a dynamic inventory of raw material has been evaluated. Then the impacts were characterized by the ILCD 2011 characterization method. In order to compare with a purely static approach, a static impact assessment was made with the V 3.4 Ecoinvent data sheets without adaptation and a static inventory considering that all the power stations would have been built at the same time. Finally, a comparison between static and dynamic LCA approaches was set up to determine the gap between them for each of the two levels of integration. The results were analyzed to identify the contribution of the evolving nuclear power fleet construction to the total environmental impacts of the French energy mix during the same period. An equivalent strategy using a dynamic approach will further be applied to identify the environmental impacts that different scenarios of the energy transition could bring, allowing to choose the best energy mix from an environmental viewpoint.

Keywords: LCA, static, dynamic, inventory, construction, nuclear energy, energy mix, energy transition

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Authors: Riana V. Ramanantsalama, Aristide Andrianarimisa, Achille P. Raselimanana, Steven M. Goodman

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Few details are available on the consumption of ectoparasites, specifically bat flies (Diptera: Nycteribiidae and Streblidae), by their chiropteran hosts while grooming. Such details could provide information on the dynamics of host-parasite interactions. This study presents data on ectoparasite ingestion rates for an endemic Malagasy fruit bat (Pteropodidae: Rousettus madagascariensis) occupying a cave day roost colony in northern Madagascar. Using quantified behavioral analyses, grooming and associated ingestion rates were measured from infrared videos taken in close proximity to day-roosting bats. The recorded individual bats could be visually identified to age (adult, juvenile) and sex (male, female), allowing analyses of the proportion of time these different classes allocated to consuming ectoparasites via auto-grooming (self) or allo-grooming (intraspecific) per 10 min video recording session. These figures could then be extrapolated to estimates of individual daily consumption rates. Based on video recordings, adults spent significantly more time auto-grooming and allo-grooming than juveniles. The latter group was not observed consuming ectoparasites. Grooming rates and the average number of ectoparasites consumed per day did not differ between adult males and females. The mean extrapolated number consumed on a daily basis for individual adults was 37 ectoparasites. When these figures are overlaid on the estimated number of adult Rousettus occurring at the roost site during the dry season, the projected daily consumption rate was 57,905 ectoparasites. To the best knowledge of the authors of this study, the details presented here represent the first quantified data on bat consumption rates of their ectoparasites, specifically dipterans. These results provide new insights into host-parasite predation dynamics. More research is needed to explore the mechanism zoonotic diseases isolated from bat flies might be transmitted to their bat hosts, specifically those pathogens that can be communicated via an oral route.

Keywords: diptera, host-parasite interactions, Madagascar, nycteribiidae, pteropodidae, Rousettus madagascariensis

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Authors: Lakhdari Wassima, Ouffroukh Ammar, Dahliz Abderrahmène, Soud Adila, Hammi Hamida, M’lik Randa

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Prospected palm groves of Oued Righ regions (Ouargla, Algeria) allowed us to observe sudden death of palm trees aged between 05 and 70 years. Field examinations revealed abnormal clinical signs with sometimes a quick death of affected trees. Entomologic investigations have confirmed the absence of phytophagous insects on dead trees. Further investigations by questioning farmers on the global management of palm groves visited (Irrigation, water quality used, soil type, etc.) did not establish any relationship between these aspects and the death of palm trees, which naturally pushed us to focus our investigations for research on fungal pathogens. Thus, laboratory studies were conducted to know the real causes of this phenomenon, 13 fungi were found on different parts of the dead palm trees. The flowing fungal types were identified: 1-Diplodia phoenicum, 2-Theilaviopsis paradoxa, 3-Phytophthora sp, 4-Helminthosporium sp, 5-Stemphylium botryosum, 6-Alternaria sp, 7-Aspergillus niger, 8-Aspergillus sp.

Keywords: palm tree, death, fungal pathogens, Oued Righ

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Authors: Eric A. Morris, Xia Liu, Yee Ka Wong, Greg J. Evans, Jeff R. Brook

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Air quality monitoring stations tend to be widely distributed and are often located far from major roadways, thus, determining where, when, and which traffic-related air pollutants (TRAPs) have the greatest impact on public health becomes a matter of extrapolation. Compact, multipollutant sensor systems are an effective solution as they enable several TRAPs to be monitored in a geospatially dense network, thus filling in the gaps between conventional monitoring stations. This work describes two applications of one such system named AirSENCE for gathering actionable air quality data relevant to smart city infrastructures. In the first application, four AirSENCE devices were co-located with traffic monitors around the perimeter of a city block in Oshawa, Ontario. This study, which coincided with the COVID-19 outbreak of 2020 and subsequent lockdown measures, demonstrated a direct relationship between decreased traffic volumes and TRAP concentrations. Conversely, road construction was observed to cause elevated TRAP levels while reducing traffic volumes, illustrating that conventional smart city sensors such as traffic counters provide inadequate data for inferring air quality conditions. The second application used two AirSENCE sensors on opposite sides of a major 2-way commuter road in Toronto. Clear correlations of TRAP concentrations with wind direction were observed, which shows that impacted areas are not necessarily static and may exhibit high day-to-day variability in air quality conditions despite consistent traffic volumes. Both of these applications provide compelling evidence favouring the inclusion of air quality sensors in current and future smart city infrastructure planning. Such sensors provide direct measurements that are useful for public health alerting as well as decision-making for projects involving traffic mitigation, heavy construction, and urban renewal efforts.

Keywords: distributed sensor network, continuous ambient air quality monitoring, Smart city sensors, Internet of Things, traffic-related air pollutants

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Authors: Haftay Abraha Tadesse, Dawit Gebreegziabiher Hagos, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli (E. coli) are important foodborne pathogens affecting humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. This study was aimed to determine the prevalence, antimicrobial susceptibility patterns and associated risk factors for Salmonella species and E. coli in raw meat from butchery houses of Mekelle, Northern Ethiopia. Method: A cross-sectional study was conducted from January to December 2019. Socio-demographic data and risk factors were collected using a predesigned questionnaire. Meat samples were collected aseptically from the butchery houses and transported using icebox to Mekelle University, College of Veterinary Sciences for the isolation and identification of Salmonella species and E. coli. Antimicrobial susceptibility patterns were determined using Kirby disc diffusion method. Data obtained were cleaned and entered into Statistical Package for the Social Sciences version 22 and logistic regression models with odds ratio were calculated. P-value < 0.05 was considered as statistically significant. Results: A total of 153 out of 384 (39.8%) of the meat specimens were found to be contaminated. The contamination of Salmonella species and E. coli were 15.6% (n=60) and 20.8%) (n=80), respectively. Mixed contamination (Salmonella species and E. coli) was observed in 13 (3.4 %) of the analyzed. Poor washing hands regularly (AOR = 8.37; 95% CI: 2.75-25.50) and not using gloves during meat handling (AOR=11. 28; 95% CI:(4.69 27.10) were associated with overall bacterial contamination. About 100% of the tested isolates were sensitive to ciprofloxacin, gentamicin, Co trimoxazole , sulphamethoxazole, ceftriaxone, and trimethoprim and ciprofloxacin, gentamicin, and norfloxacine of E. coli and Salmonella species, respectively, while the resistance of amoxyclav_amoxicillin and erythromycin were both isolated bacteria species. The overall multidrug resistance pattern for Salmonella and E. coli were 51.4% (n=19) and 31.8% (14), respectively. Conclusion: Of the 153 (153/384) contaminated raw meat, 60 (15.6%) and 80 (20.8%) were contaminated by Salmonella species and E. coli, respectively. Poor handwashing practice and not using glove during meat handling showed a significant association with bacterial contamination. Multidrug-resistant showed in Salmonella species, and E. coli were 19 (51.4%) and 14 (31.8%), respectively.

Keywords: antimicrobial susceptibility test, butchery houses, E. coli, raw meat, salmonella species

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Authors: M. Cabrera, W. Tizani, J. Ninic, F. Wang

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Open section beam to concrete-filled tubular column structures has been increasingly utilized in construction over the past few decades due to their enhanced structural performance, as well as economic and architectural advantages. However, the use of this configuration in construction is limited due to the difficulties in connecting the structural members as there is no access to the inner part of the tube to install standard bolts. Blind-bolted systems are a relatively new approach to overcome this limitation as they only require access to one side of the tubular section to tighten the bolt. The performance of these connections in concrete-filled steel tubular sections remains uncharacterized due to the complex interactions between concrete, bolt, and steel section. Over the last years, research in structural performance has moved to a more sophisticated and efficient approach consisting of machine learning algorithms to generate metamodels. This method reduces the need for developing complex, and computationally expensive finite element models, optimizing the search for desirable design variables. Metamodels generated by a data fusion approach use numerical and experimental results by combining multiple models to capture the dependency between the simulation design variables and connection performance, learning the relations between different design parameters and predicting a given output. Fully characterizing this connection will transform high-rise and multistorey construction by means of the introduction of design guidance for moment-resisting blind-bolted connections, which is currently unavailable. This paper presents a review of the steps taken to develop metamodels generated by means of artificial neural network algorithms which predict the connection stress and stiffness based on the design parameters when using Extended Hollo-Bolt blind bolts. It also provides consideration of the failure modes and mechanisms that contribute to the deformability as well as the feasibility of achieving blind-bolted rigid connections when using the blind fastener.

Keywords: blind-bolted connections, concrete-filled tubular structures, finite element analysis, metamodeling

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Authors: Agim Kukelii, Gevorg Sargsyan

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This study, focusing on the base regional area (county level), estimates the effect of natural disaster damages on aggregate personal income, aggregate wages, wages per worker, aggregate employment, and aggregate income transfer. The study further estimates the dynamics of personal income, employment, and wages under natural disaster shocks. Southeast Texas, located at the center of Golf Coast, is hit by meteorological and hydrological caused natural disasters yearly. On average, there are more than four natural disasters per year that cane an estimated damage average of 2.2% of real personal income. The study uses the panel data method to estimate the average effect of natural disasters on the area’s economy (personal income, wages, employment, and income transfer). It also uses Panel Vector Autoregressive (PVAR) model to study the dynamics of macroeconomic variables under natural disaster shocks. The study finds that the average effect of natural disasters is positive for personal income and income transfer and is negative for wages and employment. The PVAR and the impulse response function estimates reveal that natural disaster shocks cause a decrease in personal income, employment, and wages. However, the economy’s variables bounce back after three years. The novelty of this study rests on several aspects. First, this is the first study to investigate the effects of natural disasters on macroeconomic variables at a regional level. Second, the study uses direct measures of natural disaster damages. Third, the study estimates that the time that the local economy takes to absorb the natural disaster damages shocks is three years. This is a relatively good reaction to the local economy, therefore, adding to the “resiliency” hypothesis. The study has several implications for policymakers, businesses, and households. First, this study serves to increase the awareness of local stakeholders that natural disaster damages do worsen, macroeconomic variables, such as personal income, employment, and wages beyond the immediate damages to residential and commercial properties, physical infrastructure, and discomfort in daily lives. Second, the study estimates that these effects linger on the economy on average for three years, which would require policymakers to factor in the time area need to be on focus.

Keywords: natural disaster damages, macroeconomics effects, PVAR, panel data

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Authors: Hassan Younis

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Purpose: The objective of this study is to review influential papers in the sustainability and supply chain studies domain, leveraging insights from this review to develop a structured framework for academics and researchers. This framework aims to assist scholars in identifying the most impactful publications for their scholarly pursuits. Subsequently, the study will apply and trial the developed framework on selected scholarly articles within the sustainability and supply chain studies domain to evaluate its efficacy, practicality, and reliability. Design/Methodology/Approach: Utilizing the "Publish or Perish" tool, a search was conducted to locate papers incorporating "sustainability" and "supply chain" in their titles. After rigorous filtering steps, a panel of university professors identified five crucial criteria for evaluating research robustness: average yearly citation counts (25%), scholarly contribution (25%), alignment of findings with objectives (15%), methodological rigor (20%), and journal impact factor (15%). These five evaluation criteria are abbreviated as “ACMAJ" framework. Each paper then received a tiered score (1-3) for each criterion, normalized within its category, and summed using weighted averages to calculate a Final Normalized Score (FNS). This systematic approach allows for objective comparison and ranking of the research based on its impact, novelty, rigor, and publication venue. Findings: The study's findings highlight the lack of structured frameworks for assessing influential sustainability research in supply chain management, which often results in a dependence on citation counts. A complete model that incorporates five essential criteria has been suggested as a response. By conducting a methodical trial on specific academic articles in the field of sustainability and supply chain studies, the model demonstrated its effectiveness as a tool for identifying and selecting influential research papers that warrant additional attention. This work aims to fill a significant deficiency in existing techniques by providing a more comprehensive approach to identifying and ranking influential papers in the field. Practical Implications: The developed framework helps scholars identify the most influential sustainability and supply chain publications. Its validation serves the academic community by offering a credible tool and helping researchers, students, and practitioners find and choose influential papers. This approach aids field literature reviews and study suggestions. Analysis of major trends and topics deepens our grasp of this critical study area's changing terrain. Originality/Value: The framework stands as a unique contribution to academia, offering scholars an important and new tool to identify and validate influential publications. Its distinctive capacity to efficiently guide scholars, learners, and professionals in selecting noteworthy publications, coupled with the examination of key patterns and themes, adds depth to our understanding of the evolving landscape in this critical field of study.

Keywords: supply chain management, sustainability, framework, model

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Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

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Authors: Z. Gharaee

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Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

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Authors: Thalita Carvalho Martins de Castro, Núbia Bernardi

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Currently, studies evidence that our cities are portraits of social relations. In the midst of so many segregations, cultural buildings emerge as a place to assemble collective activities and expressions. Through theater, exhibitions, educational workshops, libraries, the architecture approaches human relations and seeks to propose meeting places. The purpose of this research is to deepen the discussions about the contributions of cultural buildings in the use of the spaces of the contemporary city, based on the data and measure collected in the master's research in progress. The graphic analysis of the insertion of contemporary cultural buildings seeks to highlight the social use of space. The urban insertions of contemporary cultural buildings in the city of São Paulo (Brazil) will be analyzed to understand the relations between the architectural form and its audience. The collected data describe a dynamic of flows and the permanence in the use of these spaces, indicating the contribution of the cultural buildings, associated with artistic production, in the dynamics of urban spaces and the social modifications of their milieu. Among the case studies, the research in development is based on the registration and graphic analysis of the Praça das Artes (2012) building located in the historical central region of the city, which after a long period of great degradation undergoes a current redevelopment. The choice of this building was based on four parameters, both on the architectural scale and on the urban scale: urban insertion, local impact, cultural production and a mix of uses. For the analysis will be applied two methodologies of graphic analysis, one with diagrams accompanied by texts and another with the active analysis for open space projects using complementary graphic methodologies, with maps, plants, info-graphics, perspectives, time-lapse videos and analytical tables. This research aims to reinforce the debates between the methodologies of form-use spaces and visual synthesis applied in cultural buildings, in order that new projects can structure public spaces as catalysts for social use, generating improvements in the daily life of its users and in the cities where they are inserted.

Keywords: cultural buildings, design methodologies, graphic analysis, public spaces

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Authors: Dongfang Qiu, Yilin Lu

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The measurement of enterprise-university-research cooperative efficiency has important meanings in improving the cooperative efficiency, strengthening the effective integration of regional resource, enhancing the ability of regional innovation and promoting the development of regional economy. The paper constructs the DEA method and DEA-Malmquist productivity index method to research the cooperation efficiency of Hubei by making comparisons with other provinces in China. The study found out the index of technology efficiency is 0.52 and the enterprise-university- research cooperative efficiency is Non-DEA efficient. To realize the DEA efficiency of Hubei province, the amount of 1652.596 R&D employees and 638.368 R&D employees’ full time equivalence should be reduced or 137.89 billion yuan of new products’ sales income be increased. Finally, it puts forward policy recommendations on existing problems to strengthen the standings of the cooperation, realize the effective application of the research results, and improve the level of management of enterprise-university-research cooperation efficiency.

Keywords: cooperation ability, DEA method, enterprise-university-research cooperation, Malmquist efficiency index

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Authors: Toufic Abd El-Latif Sadek

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The Asphalt object represents the asphalted areas, like roads. The best original data of thermal images occurred at a specific time during the days of the year, by preventing the gaps in times which give the close and same brightness from different objects, using seven sample objects, asphalt, concrete, metal, rock, dry soil, vegetation, and water. It has been found in this study a general timing equation for capturing satellite thermal images at different locations, depends on a fixed time the sunrise and sunset; Capture Time= Tcap =(TM*TSR) ±TS.

Keywords: asphalt, satellite, thermal images, timing equation

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Authors: Pakinee Pooprasert, Wanxin Wang, Tina Parmar, Dana Ahnood, Tafadzwa Young-Zvandasara, James Morgan

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Homelessness has been shown to be correlated to poor health outcomes, including increased visual health morbidity. Despite this, there are relatively few studies regarding visual health in the homeless population, especially in the UK. This research aims to investigate visual disability and access barriers prevalent in the homeless population in Cardiff, South Wales. Data was collected from 100 homeless participants in three different shelters. Visual outcomes included near and distance visual acuity as well as non-cycloplegic refraction. Qualitative data was collected via a questionnaire and included socio-demographic profile, ocular history, subjective visual acuity and level of access to healthcare facilities. Based on the participants’ presenting visual acuity, the total prevalence of myopia and hyperopia was 17.0% and 19.0% respectively based on spherical equivalent from the eye with the greatest absolute value. The prevalence of astigmatism was 8.0%. The mean absolute spherical equivalent was 0.841D and 0.853D for right and left eye respectively. The number of participants with sight loss (as defined by VA= 6/12-6/60 in the better-seeing eye) was 27.0% in comparison to 0.89% and 1.1% in the general Cardiff and Wales population respectively (p-value is < 0.05). Additionally, 1.0% of the homeless subjects were registered blind (VA less than 3/60), in comparison to 0.17% for the national consensus after age standardization. Most participants had good knowledge regarding access to prescription glasses and eye examination services. Despite this, 85.0% never had their eyes examined by a doctor and 73.0% had their last optometrist appointment in more than 5 years. These findings suggested that there was a significant disparity in ocular health, including visual acuity and refractive error amongst the homeless in comparison to the general population. Further, the homeless were less likely to receive the same level of support and continued care in the community due to access barriers. These included a number of socio-economic factors such as travel expenses and regional availability of services, as well as administrative shortcomings. In conclusion, this research demonstrated unmet visual health needs within the homeless, and that inclusive policy changes may need to be implemented for better healthcare outcomes within this marginalized community.

Keywords: homelessness, refractive error, visual disability, Wales

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Authors: Ashwini Gowda K. S, Archana M. R, Anjaneyappa V

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This paper presents pavement maintenance and management system (PMMS) to obtain optimum pavement maintenance and rehabilitation strategies and maintenance scheduling for a network using a multi-objective genetic algorithm (MOGA). Optimal pavement maintenance & rehabilitation strategy is to maximize the pavement condition index of the road section in a network with minimum maintenance and rehabilitation cost during the planning period. In this paper, NSGA-II is applied to perform maintenance optimization; this maintenance approach was expected to preserve and improve the existing condition of the highway network in a cost-effective way. The proposed PMMS is applied to a network that assessed pavement based on the pavement condition index (PCI). The minimum and maximum maintenance cost for a planning period of 20 years obtained from the non-dominated solution was found to be 5.190x10¹⁰ ₹ and 4.81x10¹⁰ ₹, respectively.

Keywords: genetic algorithm, maintenance and rehabilitation, optimization technique, pavement condition index

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Authors: Henda J Thomas, Cornelia PJ Harmse, Cecile Schultz

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Wearables are one of the technologies that will flourish within the fourth industrial revolution and digital transformation arenas, allowing employers to integrate collected data into organisational information systems. The study aimed to investigate whether wearable technology readiness can predict employees’ acceptance to wear wearables in the workplace. The factors of technology readiness predisposition that predict acceptance and positive attitudes towards wearable use in the workplace were examined. A quantitative research approach was used. The population consisted of 8 081 South African Department of Employment and Labour employees (DEL). Census sampling was used, and questionnaires to collect data were sent electronically to all 8 081 employees, 351 questionnaires were received back. The measuring instrument called the Technology Readiness and Acceptance Model (TRAM) was used in this study. Four hypotheses were formulated to investigate the relationship between readiness and acceptance of wearables in the workplace. The results found consistent predictions of technology acceptance (TA) by eagerness, optimism, and discomfort in the technology readiness (TR) scales. The TR scales of optimism and eagerness were consistent positive predictors of the TA scales, while discomfort proved to be a negative predictor for two of the three TA scales. Insecurity was found not to be a predictor of TA. It was recommended that the digital transformation policy of the DEL should be revised. Wearables in the workplace should be embraced from the viewpoint of convenience, automation, and seamless integration with the DEL information systems. The empirical contribution of this study can be seen in the fact that positive attitude emerged as a factor that extends the TRAM. In this study, positive attitude is identified as a new dimension to the TRAM not found in the original TA model and subsequent studies of the TRAM. Furthermore, this study found that Perceived Usefulness (PU) and Behavioural Intention to Use and (BIU) could not be separated but formed one factor. The methodological contribution of this study can lead to the development of a Wearable Readiness and Acceptance Model (WRAM). To the best of our knowledge, no author has yet introduced the WRAM into the body of knowledge.

Keywords: technology acceptance model, technology readiness index, technology readiness and acceptance model, wearable devices, wearable technology, fourth industrial revolution

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Authors: M. Gogniashvili, I. Maisaia, A. Kotorashvili, N. Kotaria, T. Beridze

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Three types of plasmon (A, B and G) is typical for genus Triticum. In polyploid species - Triticum turgidum L. and Triticum aestivum L. plasmon B is detected. In the forthcoming paper, complete nucleotide sequence of chloroplast DNA of 11 representatives of Georgian wheat polyploid species, carrying plasmon B was determined. Sequencing of chloroplast DNA was performed on an Illumina MiSeq platform. Chloroplast DNA molecules were assembled using the SOAPdenovo computer program. All contigs were aligned to the reference chloroplast genome sequence using BLASTN. For detection of SNPs and Indels and phylogeny tree construction computer programs Mafft and Blast were used. Using Triticum aestivum L. subsp. macha (Dekapr. & Menabde) Mackey var. paleocolchicum Dekapr. et Menabde as a reference, 5 SNPs can be identified in chloroplast DNA of Georgian endemic polyploid wheat. The number of noncoding substitutions is 2, coding substitutions - 3. In comparison with reference DNA two - 38 bp and 56 bp inversions were observed in paleocolchicum subspecies. There were six 1 bp indels detected in Georgian polyploid wheats, all of them at microsatellite stretches. The phylogeny tree shows that subspecies macha, carthlicum and paleocolchicum occupy different positions. According to the simplified scheme based on SNP and indel data, the ancestral, female parent of the all studied polyploid wheat is unknown X predecesor, from which four lines were formed. 1 SNP and two inversions (38 bp and 56 bp) caused the formation of subsp. paleocolchicum. Three other lines are macha, durum and carthlicum lines. Macha line is further divided into two sublines (M_1 and M_4). Carthlicum line includes subsp.carthlicum and T.aestivum - C_1 - C_2 - A_1. One of the central question of wheat domestication is which people(s) participated in wheat domestication? It is proposed that the predecessors of Georgian peoples (Proto-Kartvelians) must be placed, on the evidence of archaic lexical and toponymic data, in the mountainous regions of the western and central part of the Little Caucasus (the Transcaucasian foothills) at least 4,000 years ago. One of the possibility to explain the ‘wheat puzzle’ is that Kartvelian speakers brought domesticated wheat species and subspecis from Fertile Crescent further north to South Caucasus.

Keywords: chloroplast DNA, sequencing, SNP, triticum

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