Search results for: the health belief model

Authors: Jun Yang, Ching-Liang Hsieh, Yi-Wen Lin

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Chronic inflammatory pain results from peripheral tissue injury or local inflammation to increase the release of protons, histamines, adenosine triphosphate, and several proinflammatory cytokines. Transient receptor potential vanilloid 1 (TRPV1) is involved in fibromyalgia, neuropathic, and inflammatory pain; however, its exact mechanisms in chronic inflammatory pain are still unclear. We investigate the analgesic effect of EA by injecting complete Freund’s adjuvant (CFA) in the hind paw of mice to induce chronic inflammatory pain ( > 14 d). Our results showed that EA significantly reduced chronic mechanical and thermal hyperalgesia in the chronic inflammatory pain model. Chronic mechanical and thermal hyperalgesia was also abolished in TRPV1−/− mice. TRPV1 increased in the dorsal root ganglion (DRG) and spinal cord (SC) at 2 weeks after CFA injection. The expression levels of downstream molecules such as pPKA, pPI3K, and pPKC increased, as did those of pERK, pp38, and pJNK. Transcription factors (pCREB and pNFκB) and nociceptive ion channels (Nav1.7 and Nav1.8) were involved in this process. Inflammatory mediators such as GFAP (Glial fibrillary acidic protein), S100B, and RAGE (Receptor for advanced glycation endproducts) were also involved. The expression levels of these molecules were reduced in EA (electroacupuncture) and TRPV1−/−mice but not in the sham EA group. The present study demonstrated that EA or TRPV1 gene deletion reduced chronic inflammatory pain through TRPV1 and related molecules. In addition, our data provided evidence to support the clinical use of EA for treating chronic inflammatory pain.

Keywords: auricular electric-stimulation, epileptic seizures, anti-inflammation, electroacupuncture

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Authors: Syed Toqueer Akhter, Hussain Hamid

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Over the last few decades an upward trend has been observed in the case of labor migration from Pakistan. The emigrants are not just economically motivated and in search of a safe living environment towards more developed countries in Europe, North America and Middle East. The opportunity cost of migration comes in the form of brain drain that is the loss of qualified and skilled human capital. Throughout the history of Pakistan, situations of political instability have emerged ranging from violation of political rights, political disappearances to political assassinations. Providing security to the citizens is a major issue faced in Pakistan due to increase in crime and terrorist activities. The aim of the study is to test the impact of political instability, appearing in the form of political terror, violation of political rights and civil liberty on skilled migration of labor. Three proxies are used to measure the political instability; political terror scale (based on a scale of 1-5, the political terror and violence that a country encounters in a particular year), political rights (a rating of 1-7, that describes political rights as the ability for the people to participate without restraint in political process) and civil liberty (a rating of 1-7, civil liberty is defined as the freedom of expression and rights without government intervention). Using time series data from 1980-2011, the distributed lag models were used for estimation because migration is not a onetime process, previous events and migration can lead to more migration. Our research clearly shows that political instability appearing in the form of political terror, political rights and civil liberty all appeared significant in explaining the extent of skilled migration of Pakistan.

Keywords: skilled labor migration, political terror, political rights, civil liberty, distributed lag model

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Authors: Neha Singh, Anuj Ranjan, Tanu Jindal

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Over the last decade, the exponential growth of mobile communication has been accompanied by a parallel increase in density of electromagnetic fields (EMF). The continued expansion of mobile phone usage raises important questions as EMF, especially radio frequency (RF), have long been suspected of having biological effects. In the present experiments, we studied the effects of RF-EMF on cell death (apoptosis) and DNA damage of a well- tested biological model, Drosophila melanogaster exposed to 2400 MHz frequency for different time duration i.e. 2 hrs, 4 hrs, 6 hrs,8 hrs, 10 hrs, and 12 hrs each day for five continuous days in ambient temperature and humidity conditions inside an exposure chamber. The flies were grouped into control, sham-exposed, and exposed with 100 flies in each group. In this study, well-known techniques like Comet Assay and TUNEL (Terminal deoxynucleotide transferase dUTP Nick End Labeling) Assay were used to detect DNA damage and for apoptosis studies, respectively. Experiments results showed DNA damage in the brain cells of Drosophila which increases as the duration of exposure increases when observed under the observed when we compared results of control, sham-exposed, and exposed group which indicates that EMF radiation-induced stress in the organism that leads to DNA damage and cell death. The process of apoptosis and mutation follows similar pathway for all eukaryotic cells; therefore, studying apoptosis and genotoxicity in Drosophila makes similar relevance for human beings as well.

Keywords: cell death, apoptosis, Comet Assay, DNA damage, Drosophila, electromagnetic fields, EMF, radio frequency, RF, TUNEL assay

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Authors: Yohanes Buang, Suwari

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Increasing interest of society in use and creation of herbal medicines has encouraged scientists/researchers to establish an ideal method to produce the best quality and quantity of pharmaceutical extracts. To have highest the antioxidative extracts, the method used must be at optimum conditions. Hence, the best method is not only able to provide highest quantity and quality of the isolated pharmaceutical extracts but also it has to be easy to do, simple, fast, and cheap. The characterization of solvents in maceration technique, in present study, involved various variables influencing quantity and quality of the pharmaceutical extracts, such as solvent’s optimum acidity-alkalinity (pH), temperature, concentration, and contact time. The shifting polarity of the solvent by combinations of water with ethanol (70:30) and (50:50) were also performed to completely record the best solvent system in application of maceration technology. Among those three solvents threated within Myrmecodia pendens, as a model of natural product, the results showed that water solvent system with conditions of alkalinity pH, optimum temperature, concentration, and contact time, is the best system to perform the maceration in order to have the highest isolated antioxidative activated extracts. The optimum conditions of the water solvent are at the alkalinity pH 9 up, 30 mg/mL of concentration, 40 min of contact time, 100 °C of temperature, and no ethanol used to replace parts of the water solvent. The present study strongly recommended the best conditions of solvent system to isolate the pharmaceutical extracts of natural products in application of the maceration technology.

Keywords: extracts, herbal medicine, natural product, maceration technique

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Authors: Mariam Alsharifi, Hussein Znad, Ming Ang

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Considering the environmental issues and the shortage in the conventional fossil fuel sources, biodiesel has gained a promising solution to shift away from fossil based fuel as one of the sustainable and renewable energy. It is synthesized by transesterification of vegetable oils or animal fats with alcohol (methanol or ethanol) in the presence of a catalyst. This study focuses on synthesizing a high efficient Li/TiO2 heterogeneous catalyst for biodiesel production from canola oil. In this work, lithium immobilized onto TiO2 by the simple impregnation method. The catalyst was evaluated by transesterification reaction in a batch reactor under moderate reaction conditions. To study the effect of Li concentrations, a series of LiNO3 concentrations (20, 30, 40 wt. %) at different calcination temperatures (450, 600, 750 ºC) were evaluated. The Li/TiO2 catalysts are characterized by several spectroscopic and analytical techniques such as XRD, FT-IR, BET, TG-DSC and FESEM. The optimum values of impregnated Lithium nitrate on TiO2 and calcination temperature are 30 wt. % and 600 ºC, respectively, along with a high conversion to be 98 %. The XRD study revealed that the insertion of Li improved the catalyst efficiency without any alteration in structure of TiO2 The best performance of the catalyst was achieved when using a methanol to oil ratio of 24:1, 5 wt. % of catalyst loading, at 65◦C reaction temperature for 3 hours of reaction time. Moreover, the experimental kinetic data were compatible with the pseudo-first order model and the activation energy was (39.366) kJ/mol. The synthesized catalyst Li/TiO2 was applied to trans- esterify used cooking oil and exhibited a 91.73% conversion. The prepared catalyst has shown a high catalytic activity to produce biodiesel from fresh and used oil within mild reaction conditions.

Keywords: biodiesel, canola oil, environment, heterogeneous catalyst, impregnation method, renewable energy, transesterification

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Authors: Shweta Singh, Sudaman Katti

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The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.

Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity

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

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

Keywords: handwashing, hygyiene, sanitation, behaviour change

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Authors: C. Xavier Mendieta, J. J McArthur

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Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

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Authors: Syed Toqueer Akhter, Muhammad Muzaffar Abbas

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Conflicts in Pakistan are a result of a configuration of factors, which are directly related to the system of the state, the unstable regional setting, and the geo-strategic location of Pakistan at large. This paper examines the impact of regional conflict onto the socio-political sustainability of Pakistan. The magnitude of the spillover from a conflicted region is similar in size of the equivalent increase in domestic conflict. Pakistan has gone at war three times with India; the border with India is named as the tensest borderlines of the world. Disagreements with India and lack of dispute settlement mechanisms have negatively effected the peace in the region, influx of illegal weapons and refugees from Afghanistan as an outcome of 9/11 incidence, have exasperated the criticality of levels of internal conflict in Pakistan. Our empirical findings are based on the data collected on regional conflict levels, regional trade, global trade, comparative defence capabilities of the region in contrast to Pakistan and the government regime (Autocratic, Democratic) over 1972-2007. It has been proposed in this paper that the intent of domestic conflict is associated with the conflict in the region, regional trade, global trade and the government regime of Pakistan. The estimated model (OLS) implies that domestic conflict is effected positively and significantly with long term impact of conflict in the region. Also, if defence capabilities of the region are better than that of Pakistan it effects domestic conflict positively and significantly. Conflict in neighbouring countries are found as a source of domestic conflict in Pakistan, whereas the regional trade as well as type of government regimes in Pakistan lowered the intensity of domestic conflict significantly, while globalized trade imply risk of domestic conflict to be reduced but not significantly.

Keywords: conflict, regional trade, socio-politcal instability

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Authors: Krasimir Ivanov, Dimitar Dimitrov, Tatyana Tabakova, Stefka Kirkova, Anna Stoilova, Violina Angelova

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It has been suggested that nicotine, CO and tar in mainstream smoke are the most important substances and have been judged as the most harmful compounds, responsible for the health hazards of smoking. As nicotine is extremely important for smoking qualities of cigarettes and the tar yield in the tobacco smoke is significantly reduced due to the use of filters with various content and design, the main efforts of cigarettes researchers and manufacturers are related to the search of opportunities for CO content reduction. Highly active ceria supported gold catalyst was prepared by the deposition-precipitation method, and the possibilities for CO oxidation in the synthetic gaseous mixture were evaluated using continuous flow equipment with fixed bed glass reactor at atmospheric pressure. The efficiently of the catalyst in CO oxidation in the real cigarette smoke was examined by a single port, puf-by-puff smoking machine. Quality assessment of smoking using cigarette holder containing catalyst was carried out. It was established that the catalytic activity toward CO oxidation in cigarette smoke rapidly decreases from 70% for the first cigarette to nearly zero for the twentieth cigarette. The present study shows that there are two critical factors which do not permit the successful use of catalysts to reduce the CO content in the mainstream cigarette smoke: (i) significant influence of the processes of adsorption and oxidation on the main characteristics of tobacco products and (ii) rapid deactivation of the catalyst due to the covering of the catalyst’s grains with condensate.

Keywords: cigarette smoke, CO oxidation, gold catalyst, mainstream

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Authors: Shabana Mohammad, Muhammad Irfan

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The aim of this study was to bring out the facts regarding the effects of gender discrimination in fulfilling the basic needs of females at home. The purpose of the study was to observe whether gender discrimination affects the fulfillment of their basic needs in comparison to male siblings. Balochistan is the largest province of Pakistan geographically and has a tribal system. Due to having tribal systems, the women are not treated equally as men at home because males are considered the strength and privilege of tribes; males are more valuable because they support their families economically as well, and females are not allowed to work outside the home. That’s why females are deprived of their basic needs of life. The females (women) are neglected to have better nourishment, health facilities, easy access to get an education, safe house, and self-confidence. The type of research is quantitative, and data was collected from all government girls’ degree colleges of Quetta city (the capital of Balochistan province) under the age of 18. Two hundred (200) Students of all FA arts faculty (first year) were selected through simple random sampling (fishbowl draw). Data were analyzed by SPSS, and a coefficient test was applied to test the hypothesis. The regression of coefficient has a significant association between gender discrimination and basic needs (P-value =.000). The results showed that women are underprivileged from all basic needs (fundamental rights) of life, which are entitled to everyone by their birth because of male preference that creates gender disparity between men and women.

Keywords: basic needs, discrimination, value of women at home, hurdles of women

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Authors: Abid Kousay

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Appeared and developed essentially in large companies and multinationals, Talent Management (TM) in Small and Medium-Sized Enterprises (SMEs) has remained an under-explored subject till today. Although the literature on TM in the Anglo-Saxon context is developing, it remains monopolized in non-European contexts, especially in France. Therefore, this article aims to address these shortcomings through contributing to TM issues, by adopting a multilevel approach holding the goal of reaching a global holistic vision of interactions between various levels, while applying TM. A qualitative research study carried out within 12 SMEs in France, built on the methodological perspective of grounded theory, will be used in order to go beyond description, to generate or discover a theory or even a unified theoretical explanation. Our theoretical contributions are the results of the grounded theory, the fruit of context considerations and the dynamic of the multilevel approach. We aim firstly to determine the perception of talent and TM in SMEs. Secondly, we formalize TM in SME through the empowerment of all 3 levels in the organization (individual, collective, and organizational). And we generate a multilevel dynamic system model, highlighting the institutionalization dimension in SMEs and the managerial conviction characterized by the domination of the leader's role. Thirdly, this first study shed the light on the importance of rigorous implementation of TM in SMEs in France by directing CEO and HR and TM managers to focus on elements that upstream TM implementation and influence the system internally. Indeed, our systematic multilevel approach policy reminds them of the importance of the strategic alignment while translating TM policy into strategies and practices in SMEs.

Keywords: French context, institutionalization, talent, multilevel approach, talent management system

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Authors: Han Xiao, Zhang Lei, Huang Hai, Lv Shizeng

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Space environment simulator is a device for spacecraft test. KM8 large space environment simulator built in Tianjing Space City is the largest as well as the most advanced space environment simulator in China. Large deviation of spacecraft level will lead to abnormally work of the thermal control device in spacecraft during the thermal vacuum test. In order to avoid thermal vacuum test failure, level adjusting mechanism system is developed in the KM8 large space environment simulator as one of the most important subsystems. According to the level adjusting requirements of spacecraft’s thermal vacuum tests, the four fulcrums adjusting model is established. By means of collecting level instruments and displacement sensors data, stepping motors controlled by PLC drive four supporting legs simultaneous movement. In addition, a PID algorithm is used to control the temperature of supporting legs and level instruments which long time work under the vacuum cold and black environment in KM8 large space environment simulator during thermal vacuum tests. Based on the above methods, the data acquisition and processing, the analysis and calculation, real time adjustment and fault alarming of the level adjusting mechanism system are implemented. The level adjusting accuracy reaches 1mm/m, and carrying capacity is 20 tons. Debugging showed that the level adjusting mechanism system of KM8 large space environment simulator can meet the thermal vacuum test requirement of the new generation spacecraft. The performance and technical indicators of the level adjusting mechanism system which provides important support for the development of spacecraft in China have been ahead of similar equipment in the world.

Keywords: space environment simulator, thermal vacuum test, level adjusting, spacecraft, parallel mechanism

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Authors: Mohamed El-Khateeb

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Encompassing inventory, warehousing, and transportation management, logistics is a crucial predictor of firm performance. This has been extensively proven by extant literature in business and operations management. Logistics is also a fundamental determinant of a country's ability to access international markets. Available studies in international and transport economics have shown that limited transport infrastructure and underperforming transport services can severely affect international competitiveness. However, the evidence lacks the overall impact of logistics performance-encompassing all inventory, warehousing, and transport components- on global trade. In order to fill this knowledge gap, the paper uses a gravitational trade model with 155 countries from all geographical regions between 2007 and 2018. Data on logistics performance is obtained from the World Bank's Logistics Performance Index (LPI). First, the relationship between logistics performance and a country’s total trade is estimated, followed by a breakdown by the economic sector. Then, the analysis is disaggregated according to the level of technological intensity of traded goods. Finally, after evaluating the intensive margin of trade, the relevance of logistics infrastructure and services for the extensive trade margin is assessed. Results suggest that: (i) improvements in both logistics infrastructure and services are associated with export growth; (ii) manufactured goods can significantly benefit from these improvements, especially when both exporting and importing countries increase their logistics performance; (iii) the quality of logistics infrastructure and services becomes more important as traded goods are technology-intensive; and (iv) improving the exporting country's logistics performance is essential in the intensive margin of trade while enhancing the importing country's logistics performance is more relevant in the extensive margin.

Keywords: low-cost, recycling, reuse, solid waste, wastewater treatment

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Authors: Qurat-ul-Ain, Humaira Mehmood

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Background: HIV infection (a global pandemic) in pregnant women has turn out to be an emerging aspect of public health because of its role in the spread of HIV infection, predominantly among children. Aim: The aim was to analyze the trends of diagnosis with respect to gestational age and an overview of the mode of delivery over ten years. Methods: A retrospective data collection from clinical records of diagnosed HIV infected pregnant females attended at HIV antenatal clinic (special clinic), at Pakistan Institute of Medical Sciences, Islamabad, for various complaints during the period of 10 years from February 2007 to December 2016 was done. Results: A total of 113 pregnancies were reported with HIV infection in 10 years. Cases diagnosed at the 1st trimester (1-12 weeks) of pregnancy were (50.4%, 57/113), at the 2nd trimester (13-26 weeks) were (24.8%, 28/113), at the 3rd trimester (27-40+ weeks) were (24.7%, 28/113). Most deliveries were by caesarean section (53.1%, 60/113), elective caesarean sections were (58.3%, 35/60) and emergency caesarean sections were (41.6%,25/60). Vaginal deliveries were (26.5%, 30/113). Reported miscarriages were (17.7%, 20/113). Conclusion: At 1st trimester, 50% of the females were diagnosed with HIV infection, and 50% remained undiagnosed at their 1st trimester. Routine antenatal HIV testing throughout the country is vastly needed for timely diagnoses and prompt treatment(antiretroviral therapy), to suppress the virus, to reduce the risk of spread of HIV infection, to plan elective caesarean section delivery and to prevent mother-to-child transmission.

Keywords: gestational age, HIV infection, mode of delivery, pregnancy

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Authors: Christian Kapuku, Seung-Young Kho

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An accurate representation of the transportation system serving the region is one of the important aspects of transportation modeling. Such representation often requires developing an abstract model of the system elements, which also requires important amount of data, surveys and time. However, in some cases such as in developing countries, data deficiencies, time and budget constraints do not always allow such accurate representation, leaving opportunities to assumptions that may negatively affect the quality of the analysis. With the emergence of Internet open source data especially in the mapping technologies as well as the advances in Geography Information System, opportunities to tackle these issues have raised. Therefore, the objective of this paper is to demonstrate such application through a practical case of the development of the transportation network for the city of Kinshasa. The GIS geo-referencing was used to construct the digitized map of Transportation Analysis Zones using available scanned images. Centroids were then dynamically placed at the center of activities using an activities density map. Next, the road network with its characteristics was built using OpenStreet data and other official road inventory data by intersecting their layers and cleaning up unnecessary links such as residential streets. The accuracy of the final network was then checked, comparing it with satellite images from Google and Bing. For the validation, the final network was exported into Emme3 to check for potential network coding issues. Results show a high accuracy between the built network and satellite images, which can mostly be attributed to the use of open source data.

Keywords: geographic information system (GIS), network construction, transportation database, open source data

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Authors: Morsli Mourad, Tahiri Mohamed, Samdi Azzeddine

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Casablanca is the biggest city in Morocco. It concentrates more than 60% of the economic and industrial activity of the kingdom. Its building and public works (BTP) sector is the leading source of inert waste scattered in open areas. This inert waste is a major challenge for the city of Casablanca, as it is not properly managed, thus causing a significant nuisance for the environment and the health of the population. Hence the vision of our project is to recycle and valorize concrete waste. In this work, we present concrete results in the exploitation of this abundant and permanent deposit. Typical wastes are concrete, clay and concrete bricks, ceramic tiles, marble panels, gypsum, scrap metal, wood . The work performed included: geolocation with a combination of artificial intelligence and Google Earth, estimation of the amount of waste per site, sorting, crushing, grinding, and physicochemical characterization of the samples. Then, we proceeded to the exploitation of the types of substrates to be developed: light cement, coating, and glue for ceramics... The said products were tested and characterized by X-ray fluorescence, specific surface, resistance to bending and crushing, etc. We will present in detail the main results of our research work and also describe the specific properties of each material developed.

Keywords: déchets de démolition et des chantiers de construction, logiciels de combinaison SIG, valorisation de déchets inertes, enduits, ciment leger, casablanca

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Authors: K. Dhanalakshmi, N. Deepak, E. Manikandan, S. Kanagaraj, M. Sulthan Ariff Rahman, P. Chilambarasan C. Abhimanyu, C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

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In this paper using a validated double precision, density-based implicit standard k-ε model, the detailed 2D and 3D numerical studies have been carried out to examine the external flow choking at wing-in-ground (WIG) effect craft. The CFD code is calibrated using the exact solution based on the Sanal flow choking condition for adiabatic flows. We observed that at the identical WIG effect conditions the numerically predicted 2D boundary layer blockage is significantly higher than the 3D case and as a result, the airfoil exhibited an early external flow choking than the corresponding wing, which is corroborated with the exact solution. We concluded that, in lieu of the conventional 2D numerical simulation, it is invariably beneficial to go for a realistic 3D simulation of the wing in ground effect, which is analogous and would have the aspects of a real-time parametric flow. We inferred that under the identical flying conditions the chances of external flow choking at WIG effect is higher for conventional aircraft than an aircraft facilitating a divergent channel effect at the bottom surface of the fuselage as proposed herein. We concluded that the fuselage and wings integrated geometry optimization can improve the overall aerodynamic performance of WIG craft. This study is a pointer to the designers and/or pilots for perceiving the zone of danger a priori due to the anticipated external flow choking at WIG effect craft for safe flying at the close proximity of the terrain and the dynamic surface of the marine.

Keywords: boundary layer blockage, chord dominated ground effect, external flow choking, WIG effect

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Authors: Ghadeer A.Al-Jabaree, Husam Aldeen Al-Khadash, M. Nassar

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This study aimed at investigating the effect of well-designed corporate governance system on the financial stability of insurance companies listed in ASE. Further, this study provides a comprehensive model for evaluating and analyzing insurance companies' financial position and prospective for comparing the degree of corporate governance application provisions among Jordanian insurance companies. In order to achieve the goals of the study, a whole population that consist of (27) listed insurance companies was introduced through the variables of (board of director, audit committee, internal and external auditor, board and management ownership and block holder's identities). Statistical methods were used with alternative techniques by (SPSS); where descriptive statistical techniques such as means, standard deviations were used to describe the variables, while (F) test and ANOVA analysis of variance were used to test the hypotheses of the study. The study revealed the existence of significant effect of corporate governance variables except local companies that are not listed in ASE on financial stability within control variables especially debt ratio (leverage),where it's also showed that concentration in motor third party doesn't have significant effect on insurance companies' financial stability during study period. Moreover, the study concludes that Global financial crisis affect the investment side of insurance companies with insignificant effect on the technical side. Finally, some recommendations were presented such as enhancing the laws and regulation that help the appropriate application of corporate governance, and work on activating the transparency in the disclosures of the financial statements and focusing on supporting the technical provisions for the companies, rather than focusing only on profit side.

Keywords: corporate governance, financial stability and solvency margin, insurance companies, Jordan

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Authors: Onur Kaya, Halit Bayer

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Global grocery and supermarket sales are among the largest markets in the world and perishable products such as fresh produce, dairy and meat constitute the biggest section of these markets. Due to their deterioration over time, the demand for these products depends highly on their freshness. They become totally obsolete after a certain amount of time causing a high amount of wastage and decreases in grocery profits. In addition, customers are asking for higher product variety in perishable product categories, leading to less predictable demand per product and to more out-dating. Effective management of these perishable products is an important issue since it is observed that billions of dollars’ worth of food is expired and wasted every month. We consider coordinated inventory and pricing decisions for perishable products with a time and price dependent random demand function. We use stochastic dynamic programming to model this system for both periodically-reviewed and continuously-reviewed inventory systems and prove certain structural characteristics of the optimal solution. We prove that the optimal ordering decision scenario has a monotone structure and the optimal price value decreases by time. However, the optimal price changes in a non-monotonic structure with respect to inventory size. We also analyze the effect of 1 different parameters on the optimal solution through numerical experiments. In addition, we analyze simple-to-implement heuristics, investigate their effectiveness and extract managerial insights. This study gives valuable insights about the management of perishable products in order to decrease wastage and increase profits.

Keywords: age-dependent demand, dynamic programming, perishable inventory, pricing

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Authors: Andrey Kupriyanov

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In recent years, much attention has been paid to the problems of ionospheric disturbances and their influence on the signals of global navigation satellite systems (GNSS) around the world. This is due to the increase in solar activity, the expansion of the scope of GNSS, the emergence of new satellite systems, the introduction of new frequencies and many others. The influence of the Earth's ionosphere on the propagation of radio signals is an important factor in many applied fields of science and technology. The paper considers the application of the method of transionospheric sounding using measurements from signals from Global Navigation Satellite Systems to determine the TEC distribution and scintillations of the ionospheric layers. To calculate these parameters, the International Reference Ionosphere (IRI) model of the ionosphere, refined in the local area, is used. The organization of operational monitoring of ionospheric parameters is analyzed using several NovAtel GPStation6 base stations. It allows performing primary processing of GNSS measurement data, calculating TEC and fixing scintillation moments, modeling the ionosphere using the obtained data, storing data and performing ionospheric correction in measurements. As a result of the study, it was proved that the use of the transionospheric sounding method for reconstructing the altitude distribution of electron concentration in different altitude range and would provide operational information about the ionosphere, which is necessary for solving a number of practical problems in the field of many applications. Also, the use of multi-frequency multisystem GNSS equipment and special software will allow achieving the specified accuracy and volume of measurements.

Keywords: global navigation satellite systems (GNSS), GPstation6, international reference ionosphere (IRI), ionosphere, scintillations, total electron content (TEC)

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Authors: Njeim Pressila, Hajj-Boutros Guy, Antony D. Karelis

Abstract:

Background: Acute resistance exercise is associated with an elevated inflammation response, which could lead to delayed onset muscle soreness (DOMS). There is evidence that suggests that ingesting foods that have anti-inflammation properties may help reduce DOMS. A vegan diet has also been shown to be an anti-inflammatory diet which could, in turn, decrease DOMS. Objective and hypothesis: The purpose of the present study will be to compare markers of DOMS between vegans and omnivores after acute resistance exercise in young females. We hypothesize that vegans will have a better recovery of DOMS markers after a resistance exercise session compared to omnivores. Methods: Population: We will recruit30 vegans and 30 omnivores to participate in this study. Allvolunteers will follow either a vegan or an omnivore diet for at least 2 years. Anthropometric measurements, body composition, musclestrength (leg and chest press), markers of DOMS (swelling, pain, and stiffness), and dietary factors, as well as a wellness and anxiety questionnaire will be measured. All participants will also perform an acute resistance exercise session in order to induce DOMS. Pertinence: This project will give us a better understanding on the recovery process of vegans after a resistance training session and, as such, provide useful information to health professionals and athletes/coaches (kinesiologists and nutritionists)

Keywords: vgeans, omnivores, delayed onset muscle soreness, pain, stifness

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Authors: Alanoud Moraya Aldalan, Abdulaziz Almaleh

Abstract:

A crucial component of maintaining a customer-oriented business as in the telecom industry is understanding the reasons and factors that lead to customer churn. Competition between telecom companies has greatly increased in recent years. It has become more important to understand customers’ needs in this strong market of telecom industries, especially for those who are looking to turn over their service providers. So, predictive churn is now a mandatory requirement for retaining those customers. Machine learning can be utilized to accomplish this. Churn Prediction has become a very important topic in terms of machine learning classification in the telecommunications industry. Understanding the factors of customer churn and how they behave is very important to building an effective churn prediction model. This paper aims to predict churn and identify factors of customers’ churn based on their past service usage history. Aiming at this objective, the study makes use of feature selection, normalization, and feature engineering. Then, this study compared the performance of four different machine learning algorithms on the Orange dataset: Logistic Regression, Random Forest, Decision Tree, and Gradient Boosting. Evaluation of the performance was conducted by using the F1 score and ROC-AUC. Comparing the results of this study with existing models has proven to produce better results. The results showed the Gradients Boosting with feature selection technique outperformed in this study by achieving a 99% F1-score and 99% AUC, and all other experiments achieved good results as well.

Keywords: machine learning, gradient boosting, logistic regression, churn, random forest, decision tree, ROC, AUC, F1-score

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Authors: Giuseppe Timperio, Robert De Souza

Abstract:

The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

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Authors: Javeria Ahmad, Ayesha Maryam, Zahid Rizwan, Nadeem Nasir, Yasir Nawab, Hafiz Shehbaz Ahmad

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Mitigation of electromagnetic interference (EMI) through thin, lightweight, and cost-effective materials is critical for electronic appliances as well as human health. The present research work discusses the design of composites that are suitable to minimize EMI through various stacking sequences. The carbon fibers reinforced composite structures impregnated with dielectric (MWCNTs) and magnetic nanofillers (Fe₂O₃) were developed to investigate their microwave absorption properties. The composite structure comprising a single type of nanofillers, each of MWCNTs & Fe₂O₃, was developed, and then their layers were stacked over each other with various stacking sequences to investigate the best stacking sequence, which presents good microwave absorption characteristics. A vector network analyzer (VNA) was used to analyze the microwave absorption properties of these developed composite structures. The composite structures impregnated with the layers of a dielectric nanofiller and sandwiched between the layers of a magnetic nanofiller show the highest EMI shielding value of 59 dB and a dielectric conductivity of 35 S/cm in the frequency range of 0.1 to 13.6 GHz. The results also demonstrate that the microwave absorption properties of the developed composite structures were dominant over reflection properties. The absence of an external peak in X-ray diffraction (XRD), marked the purity of the added nanofillers.

Keywords: nanocomposites, microwave absorption, EMI shielding, skin depth, reflection loss

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Authors: Jalal Maqbool, Gyu Myoung Lee

Abstract:

Using smart devices for context aware mobile learning is becoming increasingly popular. This has led to mobile learning technology becoming an indispensable part of today’s learning environment and platforms. However, some fundamental issues remain - namely, mobile learning still lacks the ability to truly understand human reaction and user behaviour. This is due to the fact that current mobile learning systems are passive and not aware of learners’ changing contextual situations. They rely on static information about mobile learners. In addition, current mobile learning platforms lack the capability to incorporate dynamic contextual situations into learners’ preferences. Thus, this thesis aims to address these issues highlighted by designing a context aware framework which is able to sense learner’s contextual situations, handle data dynamically, and which can use contextual information to suggest bespoke learning content according to a learner’s preferences. This is to be underpinned by a robust recommendation system, which has the capability to perform these functions, thus providing learners with a truly context-aware mobile learning experience, delivering learning contents using smart devices and adapting to learning preferences as and when it is required. In addition, part of designing an algorithm for the recommendation engine has to be based on learner and application needs, personal characteristics and circumstances, as well as being able to comprehend human cognitive processes which would enable the technology to interact effectively and deliver mobile learning content which is relevant, according to the learner’s contextual situations. The concept of this proposed project is to provide a new method of smart learning, based on a capable recommendation engine for providing an intuitive mobile learning model based on learner actions.

Keywords: aware, context, learning, mobile

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Authors: Karthikeyan Kalirajan, Ashok Joshi

Abstract:

An optimization problem is to setup to maximize the terminal kinetic energy of a maneuverable reentry vehicle (MaRV). The target location, the impact angle is given as constraints. The MaRV uses an explicit guidance law called Vector guidance. This law has two gains which are taken as decision variables. The problem is to find the optimal value of these gains which will result in minimum miss distance and impact angle error. Using a simple 3DOF non-rotating flat earth model and Lockheed martin HP-MARV as the reentry vehicle, the nature of solutions of the optimization problem is studied. This is achieved by carrying out a parametric study for a range of closed loop gain values and the corresponding impact angle error and the miss distance values are generated. The results show that there are well defined lower and upper bounds on the gains that result in near optimal terminal guidance solution. It is found from this study, that there exist common permissible regions (values of gains) where all constraints are met. Moreover, the permissible region lies between flat regions and hence the optimization algorithm has to be chosen carefully. It is also found that, only one of the gain values is independent and that the other dependent gain value is related through a simple straight-line expression. Moreover, to reduce the computational burden of finding the optimal value of two gains, a guidance law called Diveline guidance is discussed, which uses single gain. The derivation of the Diveline guidance law from Vector guidance law is discussed in this paper.

Keywords: Marv guidance, reentry trajectory, trajectory optimization, guidance gain selection

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Authors: Yamina Boukari, Nashiru Billa, Andrew Morris, Stephen Doughty, Kevin Shakesheff

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Poly (lactic-co-glycolic) acid (PLGA) is a synthetic polymer that can be used in bone tissue engineering with the aim of creating a scaffold in order to support the growth of cells. The formation of microspheres from this polymer is an attractive strategy that would allow for the development of an injectable system, hence avoiding invasive surgical procedures. The aim of this study was to develop a microsphere delivery system for use as an injectable scaffold in bone tissue engineering and evaluate various formulation parameters on its properties. Porous and lysozyme-containing PLGA microspheres were prepared using the double emulsion solvent evaporation method from various molecular weights (MW). Scaffolds were formed by sintering to contain 1 -3mg of lysozyme per gram of scaffold. The mechanical and physical properties of the scaffolds were assessed along with the release of lysozyme, which was used as a model protein. The MW of PLGA was found to have an influence on microsphere size during fabrication, with increased MW leading to an increased microsphere diameter. An inversely proportional relationship was displayed between PLGA MW and mechanical strength of formed scaffolds across loadings for low, intermediate and high MW respectively. Lysozyme release from both microspheres and formed scaffolds showed an initial burst release phase, with both microspheres and scaffolds fabricated using high MW PLGA showing the lowest protein release. Following the initial burst phase, the profiles for each MW followed a similar slow release over 30 days. Overall, the results of this study demonstrate that lysozyme can be successfully incorporated into porous PLGA scaffolds and released over 30 days in vitro, and that varying the MW of the PLGA can be used as a method of altering the physical properties of the resulting scaffolds.

Keywords: bone, microspheres, PLGA, tissue engineering

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Authors: Bliss Singhal

Abstract:

Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: Rujijan Vichivanives

Abstract:

This research aims to create a knowledge-based system as a database for self-healthcare analysis, diagnosis of simple illnesses, and the use of Thai herbs instead of modern medicine by using principles of Thai traditional medication theory. These were disseminated by website network programs within Suan Sunandha Rajabhat University. The population used in this study was divided into two groups: the first group consisted of four experts of Thai traditional medication and the second group was 300 website users. The methods used for collecting data were paper questionnaires and poll questionnaires on the website. The statistics used for analyzing data was at an average level. The results were divided into three parts: the first part was the development of a knowledge-based system and the second part was applied programs on website. Both parts could be fulfilled and achieved according to the set goal. The third part was the evaluation of the study: The evaluation of the viewpoints of the experts towards website designs were evaluated at a good level of 4.20. The satisfaction evaluation of the users was found at a good level of average satisfactory level at 4.24. It was found that the young population of those under the age of 16 had less cares about their health than the population of other teenagers, working age adults and those of older age. The research findings should be extended in order to encourage the lifestyle modifications to people of all ages by using the self-healthcare principles.

Keywords: developing, herbs, knowledge-based system, medical treatment

Procedia PDF Downloads 331