Search results for: important feature points

Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

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The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

Procedia PDF Downloads 113

Authors: Muhammad Afiq Anaqi Bin Baharudin, Muhammad Izamuddin Bin Mohd Nasir, Syarifuddin Bin Sujuanda, Muhammad Syahmi Rusyaidi Bin Sham Suddin, Danish Hakimi Bin kamaruzaman, Muhammad Haqimi Nazim Bin Hasmanizam, Mohammad Akmal Zakwan Bin Amran, Muhammad Alparizi Bin Latif

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In particular, for small and medium enterprises (SMBs) in Malaysia, process safety management (PSM) is a crucial component of industrial safety. Limited resources, a lack of technical know-how, and linguistic and cultural obstacles are just a few of the difficulties SMBs in Malaysia encounter while putting PSM programmes into practice. A number of studies have emphasised the significance of leadership commitment, hazard identification and assessment, and employee involvement in the execution of effective PSM programmes, which are crucial for preventing accidents and incidents. In the literature, there has been a lot of discussion on the creation of specialised PSM frameworks for SMBs in Malaysia. Several studies have proposed implementation frameworks for PSM programmes that are based on recognised worldwide standards. Despite the significance of PSM in ensuring industrial safety, there are still a number of gaps in the literature on PSM in Malaysian SMBs. These gaps include the need for additional research on the efficiency of PSM programmes in reducing accidents and incidents in SMBs as well as the development of more specialised approaches to implementing PSM programmes in SMBs with limited resources and technical expertise. The goal of this review is to give a thorough overview of the body of research on PSM in Malaysian SMBs while highlighting important findings, points of contention, and knowledge gaps that need to be filled in.

Keywords: process safety management, occupational safety and health (OSH), small businesses, medium businesses, malaysia

Procedia PDF Downloads 100

Authors: Meshandren Naidoo

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Personhood is an important philosophical and ethical device that belies many major ethical and legal issues. The concept of African personhood is often overlooked, however, given the decolonization projects occurring in Africa, it is important to consider this view. African personhood, as opposed to Western personhood, is not individualistic in nature. The latter is predominantly Kantian and based on the notion that all persons have equal moral due to their capacity for a reason, whereas communitarianism is central to an African conception of personhood.

Keywords: African philosophy, bioethics, ethics, personhood

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Authors: Ozlem Temiz Arpaci, Meryem Tasci, Hakan Goker

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Benzimidazole, a structural isostere of indol and purine nuclei that can interact with biopolymers, can be identified as master key. So that benzimidazole compounds are important fragments in medicinal chemistry because of their wide range of biological activities including antimicrobial activity. We planned to synthesize some benzimidazole compounds for developing new antimicrobial drug candidates. In this study, we put some heterocyclic rings on second position and an amidine group on the fifth position of benzimidazole ring and synthesized them using a multiple step procedure. For the synthesis of the compounds, as the first step, 4-chloro-3-nitrobenzonitrile was reacted with cyclohexylamine in dimethyl formamide. Imidate esters (compound 2) were then prepared with absolute ethanol saturated with dry HCl gas. These imidate esters which were not too stable were converted to compound 3 by passing ammonia gas through ethanol. At the Pd / C catalyst, the nitro group is reduced to the amine group (compound 4). Finally, various aldehyde derivatives were reacted with sodium metabisulfite addition products to give compound 5-20. Melting points were determined on a Buchi B-540 melting point apparatus in open capillary tubes and are uncorrected. Elemental analyses were done a Leco CHNS 932 elemental analyzer. 1H-NMR and 13C-NMR spectra were recorded on a Varian Mercury 400 MHz spectrometer using DMSO-d6. Mass spectra were acquired on a Waters Micromass ZQ using the ESI(+) method. The structures of them were supported by spectral data. The 1H-NMR, 13C NMR and mass spectra and elemental analysis results agree with those of the proposed structures. Antimicrobial activity studies of the synthesized compounds are under the investigation.

Keywords: benzimidazoles, synthesis, structure elucidation, antimicrobial

Procedia PDF Downloads 139

Authors: Kien Xuan Ngo

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Cassiicolin (Cas), a toxin produced by Corynespora cassiicola, is responsible for corynespora leaf fall (CLF) disease in rubber trees. Currently, the molecular mechanism of the cytotoxicity of Cas isoforms (i.e., Cas1, Cas2) on rubber leaves and its host selectivity have not been fully elucidated. This study analyzed the binding of Cas1 and Cas2 to membranes consisting of different plant lipids and their membrane-disruption activities. Using high-speed atomic force microscopy and confocal microscopy, this study reveals that the binding and disruption activities of Cas1 and Cas2 on lipid membranes are strongly dependent on the specific plant lipids. The negative phospholipids, glycerolipids, and sterols are more susceptible to membrane damage caused by Cas1 and Cas2 than neutral phospholipids and betaine lipids. In summary, This study unveils that (i) Cas1 and Cas2 directly damage and cause necrosis in the leaves of specific rubber clones; (ii) Cas1 and Cas2 can form biofilm-like structures on specific lipid membranes (negative phospholipids, glycerolipids, and sterols). The biofilm-like formation of Cas toxin plays an important role in selective disruption on lipid membranes; (iii) Vulnerability of the specific cytoplasmic membranes to the selective Cas toxin is the most remarkable feature of cytotoxicity of Cas toxin on plant cells. Finally, researcher’s exploration is crucial to understand the basic molecular mechanism underlying the host-selective toxic interaction of Cas toxin with cytoplasmic membranes in plant cells.

Keywords: cassiicolin, corynespora leaf fall disease, high-speed AFM, giant liposome vesicles

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Authors: Jihuai Wu, Zeyu Song, Zhang Lan, Liuxue Sun

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Solar energy is clean, open, and infinite, but solar radiation on the earth is fluctuating, intermittent, and unstable. So, the sustainable utilization of solar energy requires a combination of high-efficient energy conversion and low-loss energy storage technologies. Hence, a photo capacitor integrated with photo-electrical conversion and electric-chemical storage functions in single device is a cost-effective, volume-effective and functional-effective optimal choice. However, owing to the multiple components, multi-dimensional structure and multiple functions in one device, especially the mismatch of the functional modules, the overall conversion and storage efficiency of the photocapacitors is less than 13%, which seriously limits the development of the integrated system of solar conversion and energy storage. To this end, two typical photocapacitors were studied. A three-terminal photocapacitor was integrated by using perovskite solar cell as solar conversion module and symmetrical supercapacitor as energy storage module. A function portfolio management concept was proposed the relationship among various efficiencies during photovoltaic conversion and energy storage process were clarified. By harmonizing the energy matching between conversion and storage modules and seeking the maximum power points coincide and the maximum efficiency points synchronize, the overall efficiency of the photocapacitor surpassed 18 %, and Joule efficiency was closed to 90%. A voltage adjustable hybrid supercapacitor (VAHSC) was designed as energy storage module, and two Si wafers in series as solar conversion module, a three-terminal photocapacitor was fabricated. The VAHSC effectively harmonizes the energy harvest and storage modules, resulting in the current, voltage, power, and energy match between both modules. The optimal photocapacitor achieved an overall efficiency of 15.49% and Joule efficiency of 86.01%, along with excellent charge/discharge cycle stability. In addition, the Joule efficiency (ηJoule) was defined as the energy ratio of discharge/charge of the devices for the first time.

Keywords: joule efficiency, perovskite solar cell, photocapacitor, silicon solar cell, supercapacitor

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Authors: Maria Gonzalez Alriols, Itziar Egues, Maria A. Andres, Mirari Antxustegi

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Peer to peer learning is an educational tool very useful to enhance teamwork and reinforce cooperation between mates. It is particularly successful to work with students of different level of previous knowledge, as it often happens among pupils of subjects in the first course of science and engineering studies. Depending on the performed pre-university academic itinerary, the acquired knowledge in disciplines as mathematics, physics, or chemistry may be quite different. This fact is an added difficulty to the tuition of first-course basic science subjects of engineering degrees, with inexperienced students that do not know each other. In this context, peer to peer learning applied in small groups facilitates the communication between mates and makes it easier for the students with low level to be helped by the ones with better prior knowledge. In this work, several collaborative learning strategies were designed to be applied in the tuition of the subject 'chemistry', which is imparted in the first course of an engineering degree. Students were organized in groups combining mates with different level of prior knowledge. The teaching role was offered to the more experienced students who were responsible for designing learning pills to help the other mates in their group. This workload was rewarded with an extra mark, and more extra points were offered to all the group mates if every student in the group reached a determined level at the end of the semester. It was very important to start these activities from the beginning of the semester in order to avoid absenteeism. The obtained results were positive as a higher percentage of mates signed up and passed the final exam, the obtained final marks were higher, and a much better atmosphere was observed in the class.

Keywords: peer to peer tuition, collaborative learning, engineering instruction, chemistry

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Authors: Jacquelyn Burkell, Jane Bailey

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Artificial intelligence (AI) solutions deployed within the justice system face the critical task of providing acceptable explanations for decisions or actions. These explanations must satisfy the joint criteria of public and professional accountability, taking into account the perspectives and requirements of multiple stakeholders, including judges, lawyers, parties, witnesses, and the general public. This research project analyzes and integrates two existing literature on explanations in order to propose guidelines for explainable AI in the justice system. Specifically, we review three bodies of literature: (i) explanations of the purpose and function of 'explainable AI'; (ii) the relevant case law, judicial commentary and legal literature focused on the form and function of reasons for judicial decisions; and (iii) the literature focused on the psychological and sociological functions of these reasons for judicial decisions from the perspective of the public. Our research suggests that while judicial ‘reasons’ (arguably accurate descriptions of the decision-making process and factors) do serve similar explanatory functions as those identified in the literature on 'explainable AI', they also serve an important ‘justification’ function (post hoc constructions that justify the decision that was reached). Further, members of the public are also looking for both justification and explanation in reasons for judicial decisions, and that the absence of either feature is likely to contribute to diminished public confidence in the legal system. Therefore, artificially automated judicial decision-making systems that simply attempt to document the process of decision-making are unlikely in many cases to be useful to and accepted within the justice system. Instead, these systems should focus on the post-hoc articulation of principles and precedents that support the decision or action, especially in cases where legal subjects’ fundamental rights and liberties are at stake.

Keywords: explainable AI, judicial reasons, public accountability, explanation, justification

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Authors: Lucélia Alcântara

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Reading has been seen as a passive skill by many people for a long time. However, when one comes to study it deeply and in a such a way that the act of reading equals acquiring knowledge through living an experience that belongs to him/her, passive definitely becomes active. Material development with a focus on reading has to consider much more than reading strategies. The following questions are asked: Is the material appropriate to the students’ reality? Does it make students think and state their points of view? With that in mind a lesson has been developed to illustrate theory becoming practice. Knowledge, criticality, intercultural experience and social interaction. That is what reading is for.

Keywords: reading, culture, material development, learning

Procedia PDF Downloads 519

Authors: Pamita Awasthi, Kirna, Shilpa Dogra, Manu Vatsal, Ritu Barthwal

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Doxorubicin, also known as adriamycin, is an anthracycline class of drug used in cancer chemotherapy. It is used in the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute leukemias, breast cancer, lung cancer, endometrium cancer and ovary cancers. It functions via intercalating DNA and ultimately killing cancer cells. The major side effects of doxorubicin are hair loss, myelosuppression, nausea & vomiting, oesophagitis, diarrhoea, heart damage and liver dysfunction. The minor modifications in the structure of compound exhibit large variation in the biological activity, has prompted us to carry out the synthesis of sulfonamide derivatives. Sulfonamide is an important feature with broad spectrum of biological activity such as antiviral, antifungal, diuretics, anti-inflammatory, antibacterial and anticancer activities. Structure of the synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilino-ethyl)benzene sulfonamide confirmed by proton nuclear magnetic resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools to assure the position of all protons and hence stereochemistry of the molecule. Further we have reported the binding potential of synthesized sulfonamide analogues in comparison to doxorubicin drug using Auto Dock 4.2 software. Computational binding energy (B.E.) and inhibitory constant (Ki) has been evaluated for the synthesized compound in comparison of doxorubicin against Poly (dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences. The in vitro cytotoxic study against human breast cancer cell lines confirms the better anticancer activity of the synthesized compound over currently in use anticancer drug doxorubicin. The IC50 value of the synthesized compound is 7.12 µM where as for doxorubicin is 7.2 µ.

Keywords: Doxorubicin, auto dock, in silco, in vitro

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Yu-Hong Lin

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Background: An adverse drug reaction (ADR) reported is an injury which caused by taking medicines. Sometimes the severity of ADR reported may be minor, but sometimes it could be a life-threatening situation. In order to provide healthcare professionals as a better reference in clinical practice, we do data collection and analysis from our hospital. Methods: This was a retrospective study of ADRs reported performed from 2014 to 2015 in our hospital in Taiwan. We collected assessment items of ADRs reported, which contain gender and age, occurring sources, Anatomical Therapeutic Chemical (ATC) classification of suspected drugs, types of adverse reactions, Naranjo score calculating by Naranjo Adverse Drug Reaction Probability Scale and so on. Results: The investigation included two hundred and seven ADRs reported. Most of ADRs reported were occurring in outpatient department (92%). The average age of ADRs reported was 65.3 years. Less than 65 years of age were in the majority in this study (54%). Majority of all ADRs reported were males (51%). According to ATC classification system, the major classification of suspected drugs was cardiovascular system (19%) and antiinfectives for systemic use (18%) respectively. Among the adverse reactions, Dermatologic Effects (35%) were the major type of ADRs. Also, the major Naranjo scores of all ADRs reported ranged from 1 to 4 points (91%), which represents a possible correlation between ADRs reported and suspected drugs. Conclusions: Definitely, ADRs reported is still an extremely important information for healthcare professionals. For that reason, we put all information of ADRs reported into our hospital's computer system, and it will improve the safety of medication use. By hospital's computer system, it can remind prescribers to think of information about patient's ADRs reported. No drugs are administered without risk. Therefore, all healthcare professionals should have a responsibility to their patients, who themselves are becoming more aware of problems associated with drug therapy.

Keywords: adverse drug reaction, Taiwan, healthcare professionals, safe use of medicines

Procedia PDF Downloads 212

Authors: Seyfollah Fazlollahi, Ahmad Bayan Memar

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Background: A review of manpower planning includes a training analysis based on job descriptions and job specifications which looks carefully at training from the points of view of the company, its various departments and personnel. This may show weaknesses in some departments and as a result, training is needed for the staff. Purpose: The aim of this research is to investigate the effects of training on employee’s efficiency in different aspects of work. Methodology: This is a descriptive-survey study. Statistical population was 85 official employees of University of Qom, Iran. 70 of these individuals were selected on a statistical random sampling method using Morgan&Gorki table. The instrument used in this study was a questionnaire including 22 questions. Result: Findings in this study according to data analysis indicate that majority of respondents had positive attitude towards training programs, in the job or off the job. They believed that training programs promoted and enhanced their behavior positively which leads to high efficiency in their job. In fact, data support the main hypothesis that training has positive effects on job performance and efficiency. Conclusion: It is concluded from this study and other related researches that training (on the job and off the job) has positive and effective role in human development and labor as employee’s efficiency. Employees get acquainted with different tasks of a job. Group co-operation, creativity and innovation will be enforced. Training leads to job skills, increasing knowledge and information about a job. It also increases technical and conceptual human skills, which are important in an organization. We can also mention workers' increasing positive motivation toward their job, enforcement of coordinating moral, their good human relations and good contact with clients.

Keywords: training, work efficiency, employee, human relation, job satisfaction

Procedia PDF Downloads 184

Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

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Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

Procedia PDF Downloads 51

Authors: Wang Yang

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Shenzhen is a modern city of China's reform and opening-up policy, the development of urban morphology has been established on the administration of the Chinese government. This city`s planning paradigm is primarily affected by the spatial structure and human behavior. The subjective urban agglomeration center is divided into several groups and centers. In comparisons of this effect, the city development law has better to be neglected. With the continuous development of the internet, extensive data technology has been introduced in China. Data mining and data analysis has become important tools in municipal research. Data mining has been utilized to improve data cleaning such as receiving business data, traffic data and population data. Prior to data mining, government data were collected by traditional means, then were analyzed using city-relationship research, delaying the timeliness of urban development, especially for the contemporary city. Data update speed is very fast and based on the Internet. The city's point of interest (POI) in the excavation serves as data source affecting the city design, while satellite remote sensing is used as a reference object, city analysis is conducted in both directions, the administrative paradigm of government is broken and urban research is restored. Therefore, the use of data mining in urban analysis is very important. The satellite remote sensing data of the Shenzhen city in July 2018 were measured by the satellite Modis sensor and can be utilized to perform land surface temperature inversion, and analyze city heat island distribution of Shenzhen. This article acquired and classified the data from Shenzhen by using Data crawler technology. Data of Shenzhen heat island and interest points were simulated and analyzed in the GIS platform to discover the main features of functional equivalent distribution influence. Shenzhen is located in the east-west area of China. The city’s main streets are also determined according to the direction of city development. Therefore, it is determined that the functional area of the city is also distributed in the east-west direction. The urban heat island can express the heat map according to the functional urban area. Regional POI has correspondence. The research result clearly explains that the distribution of the urban heat island and the distribution of urban POIs are one-to-one correspondence. Urban heat island is primarily influenced by the properties of the underlying surface, avoiding the impact of urban climate. Using urban POIs as analysis object, the distribution of municipal POIs and population aggregation are closely connected, so that the distribution of the population corresponded with the distribution of the urban heat island.

Keywords: POI, satellite remote sensing, the population distribution, urban heat island thermal map

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Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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Authors: Shamila Ahmed

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The paper examines how the fluidity between the local level and the global level is an intrinsic feature of new terrorism. Through using cosmopolitanism, the narratives of the two opposing sides of ISIS and the ‘war on terrorism’ response are explored. It is demonstrated how the fluidity between these levels facilitates the radicalisation process through exploring how groups such as ISIS highlight the perceived injustices against Muslims locally and globally and therefore exploit the globalisation process which has reduced the space between these levels. Similarly, it is argued that the ‘war on terror’ involves the intersection of fear, security, threat, risk and social control as features of both the international ‘war on terror’ and intra state policies.

Keywords: terrorism, war on terror, cosmopolitanism, global level terrorism

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Authors: Kevin Montanez, Patricia Garcia

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The confinement and restrictions adopted to avoid an exponential spread of the COVID-19 have negatively impacted the Peruvian economy. In this context, Industries offering essential products could continue operating, but they have to follow safety protocols and implement strategies to ensure employee health. In view of the increasing internet access and mobile phone ownership, “Alerta Temprana”, a mobile app, was developed to self-report COVID-19 symptoms in the work context. In this study, the usability of the mobile app “Alerta Temprana” was evaluated from the perspective of health monitors and workers. In addition to reporting the metrics related to the usability of the application, the utility of the system is also evaluated from the monitors' perspective. In this descriptive study, the participants used the mobile app for two months. Afterwards, System Usability Scale (SUS) questionnaire was answered by the workers and monitors. A Usefulness questionnaire with open questions was also used for the monitors. The data related to the use of the application was collected during one month. Furthermore, descriptive statistics and bivariate analysis were used. The workers rated the application as good (70.39). In the case of the monitors, usability was excellent (83.0). The most important feature for the monitors were the emails generated by the application. The average interaction per user was 30 seconds and a total of 6172 self-reports were sent. Finally, a statistically significant association was found between the acceptability scale and the work area. The results of this study suggest that Alerta Temprana has the potential to be used for surveillance and health monitoring in any context of face-to-face modality. Participants reported a high degree of ease of use. However, from the perspective of workers, SUS cannot diagnose usability issues and we suggest we use another standard usability questionnaire to improve "Alerta Temprana" for future use.

Keywords: public health in informatics, mobile app, usability, self-report

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Authors: Enrico Gugliandolo, Salvatore Cuzzocrea, Rosalia Crupi

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Osteoarthritis (OA) is one of the most common chronic pain conditions in dogs and cats. OA pain is currently viewed as a mixed phenomenon involving both inflammatory and neuropathic mechanisms at the peripheral (joint) and central (spinal and supraspinal) levels. Oxidative stress has been implicated in OA pain. Although nonsteroidal anti-inflammatory drugs are commonly prescribed for OA pain, they should be used with caution in pets because of adverse effects in the long term and controversial efficacy on neuropathic pain. An unmet need remains for safe and effective long-term treatments for OA pain. Palmitoyl-glucosamine (PGA) is an analogue of the ALIAamide palmitoylethanolamide, i.e., a body’s own endocannabinoid-like compound playing a sentinel role in nociception. PGA, especially in the micronized formulation, was shown safe and effective in OA pain. The aim of this study was to investigate the effect of a co-micronized formulation of PGA with the natural antioxidant curcumin (PGA-cur) on OA pain. Ten Sprague-Dawley male rats were used for each treatment group. The University of Messina Review Board for the care and use of animals authorized the study. On day 0, rats were anesthetized (5.0% isoflurane in 100% O2) and received intra-articular injection of MIA (3 mg in 25 μl saline) in the right knee joint, with the left being injected an equal volume of saline. Starting the third day after MIA injection, treatments were administered orally three times per week for 21 days, at the following doses: PGA 20 mg/kg, curcumin 10 mg/kg, PGA-cur (2:1 ratio) 30 mg/kg. On day 0 and 3, 7, 14 and 21 days post-injection, mechanical allodynia was measured using a dynamic plantar Von Frey hair aesthesiometer and expressed as paw withdrawal threshold (PWT) and latency (PWL). Motor functional recovery of the rear limb was evaluated on the same time points by walking track analysis using the sciatic functional index. On day 21 post-MIA injection, the concentration of the following inflammatory and nociceptive mediators was measured in serum using commercial ELISA kits: tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1β), nerve growth factor (NGF) and matrix metalloproteinase-1-3-9 (MMP-1, MMP-3, MMP-9). The results were analyzed by ANOVA followed by Bonferroni post-hoc test for multiple comparisons. Micronized PGA reduced neuropathic pain, as shown by the significant higher PWT and PWL values compared to vehicle group (p < 0.0001 for all the evaluated time points). The effect of PGA-cur was superior at all time points (p < 0.005). PGA-cur restored motor function already on day 14 (p < 0.005), while micronized PGA was effective a week later (D21). MIA-induced increase in the serum levels of all the investigated mediators was inhibited by PGA-cur (p < 0.01). PGA was also effective, except on IL-1 and MMP-3. Curcumin alone was inactive in all the experiments at any time point. The encouraging results suggest that PGA-cur may represent a valuable option in OA pain management and warrant further confirmation in well-powered clinical trials.

Keywords: ALIAmides, curcumin, osteoarthritis, palmitoyl-glucosamine

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Authors: Suliman Mohammed Alghanem

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Ecological and botanical surveys were conducted on Rawdhat Salasil, Al-Qassim region, Saudi Arabia. The survey also includes the study of the plant communities in the study area by sampling the associated species in each community using the List Count Quadrant method to study the density, frequency, and plant cover. The present study has shown an account of the under-mentioned five different communities: Haloxylonpersicum community is a dominant perennial shrub with an important value of 47.88%. This community is represented by 20 associated species. The chemical analysis of the soil of this habitat exhibits more alkalinity with low salinity. Tamarixnilotica communityis a perennial shrub with an important value of 60.48%. This community is represented by 14 associated species. The chemical analysis of the soil of this habitat demonstrates richness in alkalis with high salinity.Salsolaimbricata communityis a perennial herb with an important value of 60.18%. This community is represented by 17 associated species. The chemical analysis of the soil of this habitat exhibits richness in alkalis with low salinity.Panicumturgidum is a perennial herb with an important value of 65.1%. This community is represented by 11 associated species. The chemical analysis of the soil of this habitat exhibits richness in alkalis and the absence of salinity. Pulicariaundulata community is predominantly an annual shrub with an important value of 91.79%. This community is represented by 16 species. The chemical analysis of the soil of this habitat exhibits richness in alkalis, and the absence of salinity.

Keywords: rangelands, plant communities, Rawdhat Salasil, edaphic factors

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Authors: Ahmed Machmoum, Malika El Kyal

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We consider iterative parallel multi-splitting method for differential algebraic equations. The main feature of the proposed idea is to use the asynchronous form. We prove that the multi-splitting technique can effectively accelerate the convergent performance of the iterative process. The main characteristic of an asynchronous mode is that the local algorithm not have to wait at predetermined messages to become available. We allow some processors to communicate more frequently than others, and we allow the communication delays tobe substantial and unpredictable. Note that synchronous algorithms in the computer science sense are particular cases of our formulation of asynchronous one.

Keywords: computer, multi-splitting methods, asynchronous mode, differential algebraic systems

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Authors: M. Zezou

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This paper focuses on the design of a Massive Open Online Course (MOOC) about Content Language Integrated Learning (CLIL) and more specifically about how teachers can use CLIL as an educational approach incorporating technology in their teaching as well. All the four weeks of the MOOC will be presented and a step-by-step analysis of each lesson will be offered. Additionally, the paper includes detailed lesson plans about CLIL lessons with proposed CLIL activities and games in which technology plays a central part. The MOOC is structured based on certain criteria, in order to ensure success, as well as a positive experience that the learners need to have after completing this MOOC. It addresses to all language teachers who would like to implement CLIL into their teaching. In other words, it presents the methodology that needs to be followed so as to successfully carry out a CLIL lesson and achieve the learning objectives set at the beginning of the course. Firstly, in this paper, it is very important to give the definitions of MOOCs and LMOOCs, as well as to explore the difference between a structure-based MOOC (xMOOC) and a connectivist MOOC (cMOOC) and present the criteria of a successful MOOC. Moreover, the notion of CLIL will be explored, as it is necessary to fully understand this concept before moving on to the design of the MOOC. Onwards, the four weeks of the MOOC will be introduced as well as lesson plans will be presented: The type of the activities, the aims of each activity and the methodology that teachers have to follow. Emphasis will be placed on the role of technology in foreign language learning and on the ways in which we can involve technology in teaching a foreign language. Final remarks will be made and a summary of the main points will be offered at the end.

Keywords: CLIL, cMOOC, lesson plan, LMOOC, MOOC criteria, MOOC, technology, xMOOC

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Authors: Palaniraj Rama Raj, Himeesh Kumar, Paul Adler

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Purpose: To investigate the effect of ultrasound energy, expressed as cumulative dissipated energy (CDE), on short and long-term outcomes after uncomplicated cataract surgery by phacoemulsification. Methods: In this single-surgeon, two-center retrospective study, non-glaucomatous participants who underwent uncomplicated cataract surgery were investigated. Best-corrected visual acuity (BCVA) and intraocular pressure (IOP) were measured at 3 separate time points: pre-operative, Day 1 and ≥1 month. Anterior chamber (AC) inflammation and corneal odema (CO) were assessed at 2 separate time points: Pre-operative and Day 1. Short-term changes (Day 1) in BCVA, IOP, AC and CO and long-term changes (≥1 month) in BCVA and IOP were evaluated as a function of CDE using a multivariate multiple linear regression model, adjusting for age, gender, cataract type and grade, preoperative IOP, preoperative BCVA and duration of long-term follow-up. Results: 110 eyes from 97 non-glaucomatous participants were analysed. 60 (54.55%) were female and 50 (45.45%) were male. The mean (±SD) age was 73.40 (±10.96) years. Higher CDE counts were strongly associated with higher grades of sclerotic nuclear cataracts (p <0.001) and posterior subcapsular cataracts (p <0.036). There was no significant association between CDE counts and cortical cataracts. CDE counts also had a positive correlation with Day 1 CO (p <0.001). There was no correlation between CDE counts and Day 1 AC inflammation. Short-term and long-term changes in post-operative IOP did not demonstrate significant associations with CDE counts (all p >0.05). Though there was no significant correlation between CDE counts and short-term changes in BCVA, higher CDE counts were strongly associated with greater improvements in long-term BCVA (p = 0.011). Conclusion: Though higher CDE counts were strongly associated with higher grades of Day 1 postoperative CO, there appeared to be no detriment to long-term BCVA. Correspondingly, the strong positive correlation between CDE counts and long-term BCVA was likely reflective of the greater severity of underlying cataract type and grade. CDE counts were not associated with short-term or long-term postoperative changes in IOP.

Keywords: cataract surgery, phacoemulsification, cumulative dissipated energy, CDE, surgical outcomes

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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Authors: Ankur Chaudhuri, Sibani Sen Chakraborty

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In human, glutaminyl cyclase activity is highly abundant in neuronal and secretory tissues and is preferentially restricted to hypothalamus and pituitary. The N-terminal modification of β-amyloids (Aβs) peptides by the generation of a pyro-glutamyl (pGlu) modified Aβs (pE-Aβs) is an important process in the initiation of the formation of neurotoxic plaques in Alzheimer’s disease (AD). This process is catalyzed by glutaminyl cyclase (QC). The expression of QC is characteristically up-regulated in the early stage of AD, and the hallmark of the inhibition of QC is the prevention of the formation of pE-Aβs and plaques. A computer-aided drug design (CADD) process was employed to give an idea for the designing of potentially active compounds to understand the inhibitory potency against human glutaminyl cyclase (QC). This work elaborates the ligand-based and structure-based pharmacophore exploration of glutaminyl cyclase (QC) by using the known inhibitors. Three dimensional (3D) quantitative structure-activity relationship (QSAR) methods were applied to 154 compounds with known IC50 values. All the inhibitors were divided into two sets, training-set, and test-sets. Generally, training-set was used to build the quantitative pharmacophore model based on the principle of structural diversity, whereas the test-set was employed to evaluate the predictive ability of the pharmacophore hypotheses. A chemical feature-based pharmacophore model was generated from the known 92 training-set compounds by HypoGen module implemented in Discovery Studio 2017 R2 software package. The best hypothesis was selected (Hypo1) based upon the highest correlation coefficient (0.8906), lowest total cost (463.72), and the lowest root mean square deviation (2.24Å) values. The highest correlation coefficient value indicates greater predictive activity of the hypothesis, whereas the lower root mean square deviation signifies a small deviation of experimental activity from the predicted one. The best pharmacophore model (Hypo1) of the candidate inhibitors predicted comprised four features: two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature. The Hypo1 was validated by several parameters such as test set activity prediction, cost analysis, Fischer's randomization test, leave-one-out method, and heat map of ligand profiler. The predicted features were then used for virtual screening of potential compounds from NCI, ASINEX, Maybridge and Chembridge databases. More than seven million compounds were used for this purpose. The hit compounds were filtered by drug-likeness and pharmacokinetics properties. The selective hits were docked to the high-resolution three-dimensional structure of the target protein glutaminyl cyclase (PDB ID: 2AFU/2AFW) to filter these hits further. To validate the molecular docking results, the most active compound from the dataset was selected as a reference molecule. From the density functional theory (DFT) study, ten molecules were selected based on their highest HOMO (highest occupied molecular orbitals) energy and the lowest bandgap values. Molecular dynamics simulations with explicit solvation systems of the final ten hit compounds revealed that a large number of non-covalent interactions were formed with the binding site of the human glutaminyl cyclase. It was suggested that the hit compounds reported in this study could help in future designing of potent inhibitors as leads against human glutaminyl cyclase.

Keywords: glutaminyl cyclase, hit lead, pharmacophore model, simulation

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Authors: Michael Safwat Kotit Istemalek

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In this study, a project on a small project called Zeytinseli, which plays an important role from the beginning to the end of olive oil and olive oil production, is presented with the help of tourism companies that play an important role in the tourism sector. In the study, first of all, a framework of ideas about travel agency, tourism, specific tourism agency and rural tourism was created and tourism knowledge in the modern world was emphasized. After this, the "olive", which had an important place in both mythology and the religion of God, disappeared in the field of rural tourism. Since Didim Zeytinseli is the Aydın district, accommodation prices were calculated within the scope of the project and a 15-day factory tour was given at the end of the project. It can be said that the study is an original study as it covers not only environmental and agricultural tourism but also cultural tourism and non-traditional tourism98.

Keywords: financial problems, the problems of tourism businesses, tourism businesses, internet, marketing, tourism, tourism management economic competitiveness, enhancing competitiveness

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Authors: Qinghui Li, Lei Zhang

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In China, sport will play a more important role in the future development of the national economy, are facing greater challenges. Sports industry development in this background,innovative technology and cultural forces which will play an important role. Therefore, as a guide of sports culture, the development of science and technology, display the sports scientific and technological achievements, culture showed important - Sports Academic Journals sports technology platform of talent, but also innovation and value-added will through its value function,play an important role in the development of China's sports development and sports industry. At the same time, in the Chinese academic journals of social environment has undergone great changes,one aspect is the national news publishing system reform, change, development group of scientific publishing market has become the mainstream trend of development; on the other hand, digitalization, internationalization development speed of academic journal soon, in such a social background, how sports academic journal of development? How to serve for the development of sports? This research will be based on the sports academic journals in the past, the development status and characteristics and now plays in the history and context of modern academic value and social value, to explore the new era background, especially the development of the reform of the cultural system, marketization and the digital innovation situation of sports academic periodical show in sports, sports industry development and play a more important role in study.

Keywords: sports academin journals, strong sporting nation, innovation, China

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Authors: Yulia A. Kononova, Znang X. Ning

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Nowadays, architectural development is getting faster and faster. Nevertheless, modern architecture often does not meet all the points, which could help our planet to get better. As we know, people are spending an enormous amount of energy every day of their lives. Because of the uncontrolled energy usage, people have to increase energy production. As energy production process demands a lot of fuel sources, it courses a lot of problems such as climate changes, environment pollution, animals’ distinction, and lack of energy sources also. Nevertheless, nowadays humanity has all the opportunities to change this situation. Architecture is one of the most popular fields where it is possible to apply new methods of saving energy or even creating it. Nowadays we have kinds of buildings, which can meet new willing. One of them is energy effective buildings, which can save or even produce energy, combining several energy-saving principles. The main aim of this research is to provide information that helps to apply energy-saving methods while designing an environment-friendly building. The research methodology requires gathering relevant information from literature, building guidelines documents and previous research works in order to analyze it and sum up into a material that can be applied to energy-efficient building design. To mark results it should be noted that the usage of all the energy-saving methods applied to a design project of building results in ultra-low energy buildings that require little energy for space heating or cooling. As a conclusion it can be stated that developing methods of passive house design can decrease the need of energy production, which is an important issue that has to be solved in order to save planet sources and decrease environment pollution.

Keywords: accumulation, energy-efficient building, storage, superinsulation, passive house

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Authors: Yibo Shao, Jiajie Liu

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This article uncovers the practice of pragmatism of Singaporean foreign policy by analyzing its foreign diplomatic behavior. It also points out the Singapore’s hedging strategy on the relations between China and American and how to balance these two greater powers in Southeast Asian. This paper used qualitative approach by reviewing literature and policy documents intensively to find out the responses to our research questions.

Keywords: hedging, pragmatism, Sino-Singapore relations, South China Sea

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Authors: Jacqueline A. G. Sachett, Cláudia S. Nogueira, Diana C. P. Lima, Jessica T. S. Oliveira, Guilherme K. M. Salazar, Lílian K. Aguiar

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The Polo Amazon Telehealth offers several tools for professionals working in Primary Health Care as a second formative opinion, teleconsulting and training between the different areas, whether medicine, dentistry, nursing, physiotherapy, among others. These activities have a monthly schedule of free access to the municipalities of Amazonas registered. With this premise, and in partnership with the University of the State of Amazonas (UEA), is promoting the practice of the triad; teaching-research-extension in order to collaborate with the enrichment and acquisition of knowledge through educational practices carried out through teleconferences. Therefore, nursing is to join efforts and inserts as a collaborator of this project running, contributing to the education and training of these professionals who are part of the health system in full Amazon. The aim of this study is to report the experience of academic of Amazonas State University nursing course, about the experience in the extension project underway in Polo Telemedicine Amazon. This was a descriptive study, the experience report type, about the experience of nursing academic UEA, by extension 'Telenursing: teleconsulting and second formative opinion for FHS professionals in the state of Amazonas' project, held in Polo Telemedicine Amazon, through an agreement with the UEA and funded by the Foundation of Amazonas Research from July / 2012 to July / 2016. Initially developed active search of members of the Family Health Strategy professionals, in order to provide training and training teams to use the virtual clinic, as well as the virtual environment is the focus of this tool design. The election period was an aggravating factor for the implementation of teleconsulting proposal, due to change of managers in each municipality, requiring the stoppage until they assume their positions. From this definition, we established the need for new training. The first video conference took place on 03.14.2013 for learning and training in the use of Virtual Learning Environment and Virtual Clinic, with the participation of municipalities of Novo Aripuanã, São Paulo de Olivença and Manacapuru. During the whole project was carried out literature about what is being done and produced at the national level about the subject. By the time the telenursing project has received twenty-five (25) consultancy requests. The consultants sent by nursing professionals, all have been answered to date. Faced with the lived experience, particularly in video conferencing, face to cause difficulties issues, such as the fluctuation in the number of participants in activities, difficulty of participants to reconcile the opening hours of the units with the schedule of video conferencing, transmission difficulties and changes schedule. It was concluded that the establishment of connection between the Telehealth points is one of the main factors for the implementation of Telenursing and that this feature is still new for nursing. However, effective training and updating, may provide to these professional category subsidies to quality health care in the Amazon.

Keywords: Amazon, teleconsulting, telehealth, telenursing

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