Search results for: cluster synchronization

Authors: Santosh B. Phad, Priyanka V. Janbandhu, Dhananjay W. Bansod

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Population Ageing is a growing concern for the social scientists. There is a higher level of aged male participation compared to elderly females. Now, the critical question is whether participation in work improves the quality of life among the elderly and the impact of working status on the mental well-being of the elderly. While examining these research questions, the present paper focuses on the workforce participation of the elderly and the reasons behind it, additionally, determines the association between employment status and the mental well-being of the elderly. The present study has a base of two data sources. First one is Census of India data, 2001 and 2011, and another one is – the Study on Global Ageing and Adult Health (SAGE), a survey conducted in 2007. To capture the trend of workforce participation elderly Census data is significant and to obtain other information associated with this issue the SAGE data is studied. The research piece consists of univariate and bivariate analysis along with some statistical methods like principal component analysis (PCA) and regression modeling – to investigate the association between workforce participation of elderly and subjective well-being (SWB). The results show that the percentage of elderly participating in the labor market is gradually reducing, but the share of working elderly has increased within the group of overall workers. i.e., the ratio of aged workers to non-aged workers is rising. The findings from survey data specify that there is a considerable share of the elderly in the labor market; three-fourths of the employed elderly enrolled the workforce unwillingly. They are in need of some earnings mainly to afford the medical expenses on their health or the health of their spouse, also to support their family members who are economically inactive. Apart from need, duration of working is another vital aspect for the elderly, whereas more than 80 percent of the elderly are working for six hours or more, and most of them engaged in self-employment. However, more than one-third of the working elderly falls into a negative cluster of the subjective well-being (SWB) index, and it is consistent with the result of the discriminant analysis. Here, the SWB index calculated from the 12 items and the reliability score of these items is 0.89.

Keywords: ageing, workforce, census of India, SAGE

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Authors: César Coelho, Nikolai Wiegand

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The advancement of nanosatellite technology has opened new avenues for cost-effective and faster space missions. The NanoSat MO Framework (NMF) from the European Space Agency (ESA) provides a modular and simpler approach to the development of flight software and operations of small satellites. This paper presents a methodology using the NMF together with Docker for simulating constellations of satellites. By leveraging Docker containers, the software environment of individual satellites can be easily replicated within a simulated constellation. This containerized approach allows for rapid deployment, isolation, and management of satellite instances, facilitating comprehensive testing and development in a controlled setting. By integrating the NMF lightweight simulator in the container, a comprehensive simulation environment was achieved. A significant advantage of using Docker containers is their inherent scalability, enabling the simulation of hundreds or even thousands of satellites with minimal overhead. Docker's lightweight nature ensures efficient resource utilization, allowing for deployment on a single host or across a cluster of hosts. This capability is crucial for large-scale simulations, such as in the case of mega-constellations, where multiple traditional virtual machines would be impractical due to their higher resource demands. This ability for easy horizontal scaling based on the number of simulated satellites provides tremendous flexibility to different mission scenarios. Our results demonstrate that leveraging Docker containers with the NanoSat MO Framework provides a highly efficient and scalable solution for simulating satellite constellations, offering not only significant benefits in terms of resource utilization and operational flexibility but also enabling testing and validation of ground software for constellations. The findings underscore the importance of taking advantage of already existing technologies in computer science to create new solutions for future satellite constellations in space.

Keywords: containerization, docker containers, NanoSat MO framework, satellite constellation simulation, scalability, small satellites

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Authors: Rajesh Kumar Suman, Ipseeta Ray Mohanty, Manjusha K. Borde, Ujjawala maheswari, Y. A. Deshmukh

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Background: Metabolic syndrome encompasses cluster of risk factors for cardiovascular disease which includes abdominal obesity, dyslipidemia, hypertension, and hyperglycemia. The incidence of metabolic syndrome is on the rise globally. Objective: The present study was designed to develop a unique animal model that will mimic the pathological features seen in a large pool of individuals with diabetes and metabolic syndrome; suitable for pharmacological screening of drugs beneficial in this condition. Material and Methods: A combination of high fat diet (HFD) and low dose of streptozotocin (STZ) at 30, 35 and 40 mg/kg was used to induce metabolic syndrome co-existing with diabetes mellitus in Wistar rats. Results: The 40 mg/kg STZ produced sustained hyperglycemia and the dose was thus selected for our study to induce diabetes mellitus. Rat fed HFD (HF-DC) group showed significant (p < 0.001) increase in body weight on 4th and 7th week as compared with NC (Normal Control) group rats. However, the increase in body weight of HF-DC group rats was not sustained at the end of 10th weeks. Various components of metabolic syndrome such as dyslipidemia {(Increased Triglyceride, total Cholesterol, LDL Cholesterol and decreased HDL Cholesterol)}, diabetes mellitus (Blood Glucose, HbA1c, Serum Insulin, C-peptide), hypertension {Systolic Blood pressure (p < 0.001)} were mimicked in the developed model of metabolic syndrome co existing with diabetes mellitus. In addition significant cardiac injury as indicated by CPK-MB levels, artherogenic index, hs-CRP. The decline in hepatic function {(p < 0.01) increase in the level of SGPT (U/L)} and renal function {(increase in creatinine levels (p < 0.01)} when compared to NC group rats. The histopathological assessment confirmed presence of edema, necrosis and inflammation in Heart, Pancreas, Liver and Kidney of HFD-DC group as compared to NC. Conclusion: The present study has developed a unique rodent model of metabolic syndrome; with diabetes as an essential component.

Keywords: diabetes, metabolic syndrome, high fat diet, streptozotocin, rats

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Authors: Godwin Bassey Okon

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The need to streamline viewers’ disposition towards the predominant portrayal of rituals, in most Nigerian home videos, as a way of life in the southern part of Nigeria necessitated this study. The focus however was on ascertaining if such portrayals dovetail within the framework of construction of social reality or misconstruction of social reality. In other words, do the people of the southern part of Nigeria engage in rituals as a means of acquiring wealth or do they merely have proclivity for diabolism, as frequently portrayed in home videos subsumed in their socio-cultural settings? The method of study was survey with the questionnaire as the predominant instrument. The questionnaire was used to elicit responses from Portharcourt city residents on their views and reactions in the light of ritual themes in Nigerian home videos. The choice of Portharcourt was informed by the fact that it is a foremost cosmopolitan city in the south. A Sample size of 400 was drawn from a population of 1,382,392 using Taro Yamane’s formula. Actual respondents were reached using a multi-stage cluster sampling technique. The reliability of the instrument as ascertained through Pearson’s Product Moment Correlation stood at 0.89. Findings however revealed that ritual themes, as used in Nigerian home videos, did not significantly reflect the cultural heritage of the people of southern Nigeria. Findings further showed that their excessive use in Nigerian home videos served only to create frills and thrills in plots. A synthesis of the foregoing, however, revealed that viewers are not favourably disposed towards the excessive use of ritual themes since they inadvertently portray the cultural heritage of the people of the south in the negative. To this end, it was recommended that producers of Nigerian home videos should focus more on themes that serve to construct social reality while projecting favorably the rich cultural heritage of the people. In terms of contribution to knowledge, the findings of this study tend to reinforce the notion of film as a conveyor belt in cognitive constructs.

Keywords: disposition, home videos, ritual, social reality, themes

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Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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Authors: Amr A. El Hanafy, Yasser M. Saad, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

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Camels are substantial providers of transport, milk, sport, meat, shelter, fuel, security and capital in many countries, particularly Saudi Arabia. Identification of animal breeds has progressed rapidly during the last decade. Advanced molecular techniques are playing a significant role in breeding or strain protection laws. On the other hand, fingerprinting of some molecular markers related to some productive traits in farm animals represents most important studies to our knowledge, which aim to conserve these local genetic resources, and to the genetic improvement of such local breeds by selective programs depending on gene markers. Milk records were taken two days in each week from female camels of Majahem, Safara, Wathaha, and Hamara breeds, respectively from different private farms in northern Jeddah, Riyadh and Alwagh governorates and average weekly yields were calculated. DNA sequencing for CSN2 gene was used for evaluating the genetic variations and calculating the genetic distance values among four Saudi camel populations which are Hamra(R), Safra(Y), Wadha(W) and Majaheim(M). In addition, this marker was analyzed for reconstructing the Neighbor joining tree among evaluating camel breeds. In respect to milk yield during winter season, result indicated that average weekly milk yield of Safara camel breed (30.05 Kg/week) is significantly (p < 0.05) lower than the other 3 breeds which ranged from 39.68 for Hamara to 42.42 Kg/week for Majahem, while there are not significant differences between these three breeds. The Neighbor Joining analysis that re-constructed based on DNA variations showed that samples are clustered into two unique clades. The first clade includes Y (from Y4 to Y18) and M (from M1, to M9). On the other hand, the second cluster is including all R (from R1 to R6) and W (from W1 to W6). The genetic distance values were equal 0.0068 (between the groups M&Y and R&W) and equal 0 (within each group).

Keywords: milk yield, beta-casein precursor (CSN2), Saudi camel, molecular markers

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Authors: Sanjeev Prasher, T. Sai Vijay, Chandan Parsad, Abhishek Banerjee, Sahakari Nikhil Krishna, Subham Chatterjee

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With rapid rise in internet retailing, the industry is set for a major implosion. Due to the little difference among competitors, companies find it difficult to segment and target the right shoppers. The objective of the study is to segment Indian online shoppers on the basis of the factors – website characteristics and shopping values. Together, these cover extrinsic and intrinsic factors that affect shoppers as they visit web retailers. Data were collected using questionnaire from 319 Indian online shoppers, and factor analysis was used to confirm the factors influencing the shoppers in their selection of web portals. Thereafter, cluster analysis was applied, and different segments of shoppers were identified. The relationship between income groups and online shoppers’ segments was tracked using correspondence analysis. Significant findings from the study include that web entertainment and informativeness together contribute more than fifty percent of the total influence on the web shoppers. Contrary to general perception that shoppers seek utilitarian leverages, the present study highlights the preference for fun, excitement, and entertainment during browsing of the website. Four segments namely Information Seekers, Utility Seekers, Value Seekers and Core Shoppers were identified and profiled. Value seekers emerged to be the most dominant segment with two-fifth of the respondents falling for hedonic as well as utilitarian shopping values. With overlap among the segments, utilitarian shopping value garnered prominence with more than fifty-eight percent of the total respondents. Moreover, a strong relation has been established between the income levels and the segments of Indian online shoppers. Web shoppers show different motives from being utility seekers to information seekers, core shoppers and finally value seekers as income levels increase. Companies can strategically use this information for target marketing and align their web portals accordingly. This study can further be used to develop models revolving around satisfaction, trust and customer loyalty.

Keywords: online shopping, shopping values, effectiveness of information content, web informativeness, web entertainment, information seekers, utility seekers, value seekers, core shoppers

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Authors: Tim Giesen, Raphael Adamietz, Pablo Mayer, Philipp Stiefel, Patrick Alle, Dirk Schlenker

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The competitiveness and success of new electrical energy storages such as battery cells are significantly dependent on a short time-to-market. Producers who decide to supply new battery cells to the market need to be easily adaptable in manufacturing with respect to the early customers’ needs in terms of cell size, materials, delivery time and quantity. In the initial state, the required output rates do not yet allow the producers to have a fully automated manufacturing line nor to supply handmade battery cells. Yet there was no solution for manufacturing battery cells in low to medium volumes in a reproducible way. Thus, in terms of cell format and output quantity, a concept for the flexible assembly of battery cells was developed by the Fraunhofer-Institute for Manufacturing Engineering and Automation. Based on clustered processes, the modular system platform can be modified, enlarged or retrofitted in a short time frame according to the ordered product. The paper shows the analysis of the production steps from a conventional battery cell assembly line. Process solutions were found by using I/O-analysis, functional structures, and morphological boxes. The identified elementary functions were subsequently clustered by functional coherences for automation solutions and thus the single process cluster was generated. The result presented in this paper enables to manufacture different cell products on the same production system using seven process clusters. The paper shows the solution for a batch-wise flexible battery cell production using advanced process control. Further, the performed tests and benefits by using the process clusters as cyber-physical systems for an integrated production and value chain are discussed. The solution lowers the hurdles for SMEs to launch innovative cell products on the global market.

Keywords: automation, battery production, carrier, advanced process control, cyber-physical system

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Authors: Antonio Marques, Graça Guedes

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The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also analyses the strategy follow in the innovation process, as suggested by Freeman and Soete, and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. Can conclude that the Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.

Keywords: footwear, innovation, “low-tech” industry, Oslo manual

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Authors: Sa’adu Mafara Abubakar, Muhammad Nuraddeen Danjuma, Adewole Tomiwa Adetunji, Richard Mundembe, Salisu Mohammed, Francis Bayo Lewu, Joseph I. Kiok

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Pearl millet is the most drought tolerant of all domesticated cereals, is cultivated extensively to feed millions of people who mainly live in hash agroclimatic zones. It serves as a major source of food for more than 40 million smallholder farmers living in the marginal agricultural lands of Northern Nigeria. Pearl millet grain is more nutritious than other cereals like maize, is also a principal source of energy, protein, vitamins, and minerals for millions of poorest people in the regions where it is cultivated. Pearl millet has recorded relatively little research attention compared with other crops and no sufficient work has analyzed its genetic diversity in north-western Nigeria. Therefore, this study was undertaken with the objectives to analyze the genetic diversity of pearl millet accessions using SSR marker and to analyze the extent of evolutionary relationship among pearl millet accessions at the molecular level. The result of the present study confirmed diversity among accessions of pearl millet in the study area. Simple Sequence Repeats (SSR) markers were used for genetic analysis and evolutionary relationship of the accessions of pearl millet. To analyze the level of genetic diversity, 8 polymorphic SSR markers were used to screen 69 accessions collected based on three maturity periods. SSR markers result reveal relationships among the accessions in terms of genetic similarities, evolutionary and ancestral origin, it also reveals a total of 53 alleles recorded with 8 microsatellites and an average of 6.875 per microsatellite, the range was from 3 to 9 alleles in PSMP2248 and PSMP2080 respectively. Moreover, both the factorial analysis and the dendrogram of phylogeny tree grouping patterns and cluster analysis were almost in agreement with each other that diversity is not clustering according to geographical patterns but, according to similarity, the result showed maximum similarity among clusters with few numbers of accessions. It has been recommended that other molecular markers should be tested in the same study area.

Keywords: pearl millet, genetic diversity, simple sequence repeat (SSR)

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Authors: Mohammad Rahim Rahnama

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Market-transaction price for housing is the main criteria for determining municipality taxes and is determined and announced on an annual basis. Of course, there is a discrepancy between the actual value of transactions in the Bureau of Finance (P for short) or municipality (P´ for short) and the real price on the market (P˝). The present research aims to determine the real price of housing in the metropolis of Mashhad and to pinpoint the price gap with those of the aforementioned apparatuses and identify the factors affecting it. In order to reach this practical objective, Automatic Linear Modeling, which calls for an explanatory research, was utilized. The population of the research consisted of all the residential units in Mashhad, from which 317 residential units were randomly selected. Through cluster sampling, out of the 170 income blocks defined by the municipality, three blocks form high-income (Kosar), middle-income (Elahieh), and low-income (Seyyedi) strata were surveyed using questionnaires during February and March of 2015 and the information regarding the price and specifications of residential units were gathered. In order to estimate the effect of various factors on the price, the relationship between independent variables (8 variables) and the dependent variable of the housing price was calculated using Automatic Linear Modeling in SPSS. The results revealed that the average for housing price index is 788$ per square meter, compared to the Bureau of Finance’s prices which is 10$ and that of municipality’s which is 378$. Correlation coefficient among dependent and independent variables was calculated to be R²=0.81. Out of the eight initial variables, three were omitted. The most influential factor affecting the housing prices is the quality of Quality of construction (Ordinary, Full, Luxury). The least important factor influencing the housing prices is the variable of number of sides. The price gap between low-income (Seyyedi) and middle-income (Elahieh) districts was not confirmed via One-Way ANOVA but their gap with the high-income district (Kosar) was confirmed. It is suggested that city be divided into two low-income and high-income sections, as opposed three, in terms of housing prices.

Keywords: automatic linear modeling, housing prices, Mashhad, Iran

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Authors: Maryam Farzaneh, Seyyedeh Nafiseh Hassani, Hossein Baharvand

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Objective: Chicken gonadal tissue has a two population such primordial germ cells (PGCs) and stromal cells (somatic cells). PGCs and embryonic germ cells (EGCs) that is a pluripotent type of PGCs in long-term culture are suitable sources for the production of chicken pluripotent stem cell lines, transgenic birds, vaccine and recombinant protein production. In general, the effect of growth factors such bFGF and mouse LIF on derivation of PGCs in vitro are important and in this study we could see the unique effect of small molecules such PD032 and SB43 as a chemical, in comparison to growth factors. Materials and Methods: After incubation of fertilized chicken egg up to 6 days and isolation of primary gonadal tissues and culture of mixed cells like PGCs and stromal cells. PGCs proliferate in the present of fetal calf serum (FCS) and small molecules and in another group bFGF, that these factors are important for PGCs culture and derivation. Somatic cells produce a multilayer feeder under the PGCs in primary culture and PGCs make a small cluster under these cells. Results: In present of small molecules and high volume of FCS (15%), the present of EGCs as a pluripotent stem cells were clear four weeks, that they had a positive immune-staining and periodic acid-Schiff staining (PAS), but in present of growth factors like bFGF without any chemicals, the present of PGCs were clear but after 7 until 10 days, there were disappear. Conclusion: Until now we have seen many researches about derivation and maintenance of chicken PGCs, in the hope of understanding the mechanisms that occur during germline development and production of a therapeutic product by transgenic birds. There are still many unknowns in this area and this project will try to have efficient conditions for identification of suitable culture medium for long-term culture of PGCs in vitro without serum and feeder cells.

Keywords: chicken gonadal primordial germ cells, pluripotent stem cells, growth factors, small molecules, transgenic birds

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Authors: Aschenaki Zerihun Kea, Bernt Lindtjorn, Achamyelesh Gebretsadik, Sven Gudmund Hinderaker

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Introduction: Maternal mortality studies conducted at the national level do not provide the information needed for planning and monitoring health programs at lower administrative levels. The aim of this study was to measure maternal mortality, identify risk factors and district-level variations in Sidama National Regional State, southern Ethiopia. Methods: A cross sectional population-based survey was carried out in households where women reported pregnancy and birth outcomes in the past five years. The study was conducted in the Sidama National Regional State, southern Ethiopia, from July 2019 to May 2020. Multi-stage cluster sampling technique was employed. The outcome variable of the study was maternal mortality. Complex sample logistic regression analysis was applied to assess variables independently associated with maternal mortality. Results: We registered 10602 live births (LB) and 48 maternal deaths, yielding an overall maternal mortality ratio (MMR) of 419; 95% CI: 260-577 per 100,000 LB. Aroresa district had the highest MMR with 1142 (95% CI: 693-1591) per 100,000 LB. Leading causes of death were haemorrhage 21 (41%) and eclampsia 10 (27%). Thirty (59%) mothers died during labour, or within 24 hours after delivery, 25 (47%) died at home and 17 (38%) at a health facility. Mothers who did not have formal education had a higher risk of maternal death (AOR: 4.4; 95% CI: 1.7 – 11.0). The risk of maternal death was higher in districts with a low midwife-to-population ratio (AOR: 2.9; 95% CI: 1.0-8.9). Conclusion: The high maternal mortality with district-level variations in Sidama Region highlights the importance of improving obstetric care and employing targeted interventions in areas with high mortality rates. Due attention should be given to improving access to female education. Additional midwives have to be trained and deployed to improve maternal health services and consequently save the lives of mothers.

Keywords: maternal mortality variation, maternal death, Sidama, Ethiopia

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: Akram Sadat Jafari Roodbandi, Farzaneh Akbari, Vafa Feyzi, Zahra Zare, Zohreh Foroozanfar

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Introduction: Circadian rhythm or sleep-awake cycle in 24 hours is one of the important factors affecting the physiological and psychological characteristics in humans that contribute to biochemical, physiological and behavioral processes and helps people to set up brain and body for sleep or active awakening during certain hours. The purpose of this study was to investigate the relationship between the characteristics of circadian rhythms on the sleep quality and sleepiness according to their demographic characteristics such as age. Methods: This cross-sectional descriptive-analytic study was carried out among the general population of Kerman, aged 15-84 years. After dividing the age groups into 10-year demographic characteristics questionnaire, the type of circadian questionnaire, Pittsburgh sleep quality questionnaire and Euporth sleepiness questionnaire were completed in equal numbers between men and women of that age group. Using cluster sampling with effect design equal 2, 1300 questionnaires were distributed during the various hours of 24 hours in public places in Kerman city. Data analysis was done using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: In this study, 1147 subjects were included in the study, 584 (50.9%) were male and the rest were women. The mean age was 39.50 ± 15.38. 133 (11.60%) subjects from the study participants had sleepiness and 308 (26.90%) subjects had undesirable sleep quality. Using linear regression test, sleep quality was the significant correlation with sex, hours needed for sleep at 24 hours, chronic illness, sleepiness, and circadian rhythm amplitude. Sleepiness was the meaningful relationship with marital status, sleep-wake schedule of other family members and the stability of circadian rhythm. Both women and men, with age, decrease the quality of sleep and increase the rate of sleepiness. Conclusion: Age, sex, and type of circadian people, the need for sleep at 24 hours, marital status, sleep-wake schedule of other family members are significant factors related to the sleep quality and sleepiness and their adaptation to night shift work.

Keywords: circadian type, sleep quality, sleepiness, age, shift work

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Tingting Huang, Sha Li, Geoffrey Griffiths, Martin Lukac, Jianning Zhu

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Territorial landscapes have experienced a gradual loss of their typical characteristics during long-term human activities. In order to protect the integrity of regional landscapes, it is necessary to characterize, evaluate and protect them in a graded manner. The study takes Fujian, China, as an example and classifies the landscape characters of the site at the regional scale, middle scale, and detailed scale. A multi-scale approach combining parametric and holistic approaches is used to classify and partition the landscape character types (LCTs) and landscape character areas (LCAs) at different scales, and a multi-element landscape assessment approach is adopted to explore the conservation strategies of the landscape character. Firstly, multiple fields and multiple elements of geography, nature and humanities were selected as the basis of assessment according to the scales. Secondly, the study takes a parametric approach to the classification and partitioning of landscape character, Principal Component Analysis, and two-stage cluster analysis (K-means and GMM) in MATLAB software to obtain LCTs, combines with Canny Operator Edge Detection Algorithm to obtain landscape character contours and corrects LCTs and LCAs by field survey and manual identification methods. Finally, the study adopts the Landscape Sensitivity Assessment method to perform landscape character conservation analysis and formulates five strategies for different LCAs: conservation, enhancement, restoration, creation, and combination. This multi-scale identification approach can efficiently integrate multiple types of landscape character elements, reduce the difficulty of broad-scale operations in the process of landscape character conservation, and provide a basis for landscape character conservation strategies. Based on the natural background and the restoration of regional characteristics, the results of landscape character assessment are scientific and objective and can provide a strong reference in regional and national scale territorial spatial planning.

Keywords: parameterization, multi-scale, landscape character identify, landscape character assessment

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Authors: Sebastian Kehne, Alexander Epple, Werner Herfs

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A new method for optimal selection of components for multi-axes forward-feed drive systems is proposed in which the choice of motors, gear boxes and ball screw drives is optimized. Essential is here the synchronization of electrical and mechanical frequency behavior of all axes because even advanced controls (like H∞-controls) can only control a small part of the mechanical modes – namely only those of observable and controllable states whose value can be derived from the positions of extern linear length measurement systems and/or rotary encoders on the motor or gear box shafts. Further problems are the unknown processing forces like cutting forces in machine tools during normal operation which make the estimation and control via an observer even more difficult. To start with, the open source Modelica Feed Drive Library which was developed at the Laboratory for Machine Tools, and Production Engineering (WZL) is extended from one axis design to the multi axes design. It is capable to simulate the mechanical, electrical and thermal behavior of permanent magnet synchronous machines with inverters, different gear boxes and ball screw drives in a mechanical system. To keep the calculation time down analytical equations are used for field and torque producing equivalent circuit, heat dissipation and mechanical torque at the shaft. As a first step, a small machine tool with a working area of 635 x 315 x 420 mm is taken apart, and the mechanical transfer behavior is measured with an impulse hammer and acceleration sensors. With the frequency transfer functions, a mechanical finite element model is built up which is reduced with substructure coupling to a mass-damper system which models the most important modes of the axes. The model is modelled with Modelica Feed Drive Library and validated by further relative measurements between machine table and spindle holder with a piezo actor and acceleration sensors. In a next step, the choice of possible components in motor catalogues is limited by derived analytical formulas which are based on well-known metrics to gain effective power and torque of the components. The simulation in Modelica is run with different permanent magnet synchronous motors, gear boxes and ball screw drives from different suppliers. To speed up the optimization different black-box optimization methods (Surrogate-based, gradient-based and evolutionary) are tested on the case. The objective that was chosen is to minimize the integral of the deviations if a step is given on the position controls of the different axes. Small values are good measures for a high dynamic axes. In each iteration (evaluation of one set of components) the control variables are adjusted automatically to have an overshoot less than 1%. It is obtained that the order of the components in optimization problem has a deep impact on the speed of the black-box optimization. An approach to do efficient black-box optimization for multi-axes design is presented in the last part. The authors would like to thank the German Research Foundation DFG for financial support of the project “Optimierung des mechatronischen Entwurfs von mehrachsigen Antriebssystemen (HE 5386/14-1 | 6954/4-1)” (English: Optimization of the Mechatronic Design of Multi-Axes Drive Systems).

Keywords: ball screw drive design, discrete optimization, forward feed drives, gear box design, linear drives, machine tools, motor design, multi-axes design

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Authors: Tammeen Siraj, Wenxing Zhou, Terry Huang, Mohammad Al-Amin

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The high resolution inline inspection (ILI) tool is used extensively in the pipeline industry to identify, locate, and measure metal-loss corrosion anomalies on buried oil and gas steel pipelines. Corrosion anomalies may occur singly (i.e. individual anomalies) or as clusters (i.e. a colony of corrosion anomalies). Although the ILI technology has advanced immensely, there are measurement errors associated with the sizes of corrosion anomalies reported by ILI tools due limitations of the tools and associated sizing algorithms, and detection threshold of the tools (i.e. the minimum detectable feature dimension). Quantifying the measurement error in the ILI data is crucial for corrosion management and developing maintenance strategies that satisfy the safety and economic constraints. Studies on the measurement error associated with the length of the corrosion anomalies (in the longitudinal direction of the pipeline) has been scarcely reported in the literature and will be investigated in the present study. Limitations in the ILI tool and clustering process can sometimes cause clustering error, which is defined as the error introduced during the clustering process by including or excluding a single or group of anomalies in or from a cluster. Clustering error has been found to be one of the biggest contributory factors for relatively high uncertainties associated with ILI reported anomaly length. As such, this study focuses on developing a consistent and comprehensive framework to quantify the measurement errors in the ILI-reported anomaly length by comparing the ILI data and corresponding field measurements for individual and clustered corrosion anomalies. The analysis carried out in this study is based on the ILI and field measurement data for a set of anomalies collected from two segments of a buried natural gas pipeline currently in service in Alberta, Canada. Data analyses showed that the measurement error associated with the ILI-reported length of the anomalies without clustering error, denoted as Type I anomalies is markedly less than that for anomalies with clustering error, denoted as Type II anomalies. A methodology employing data mining techniques is further proposed to classify the Type I and Type II anomalies based on the ILI-reported corrosion anomaly information.

Keywords: clustered corrosion anomaly, corrosion anomaly assessment, corrosion anomaly length, individual corrosion anomaly, metal-loss corrosion, oil and gas steel pipeline

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Authors: Thevaranchany Sivaskaran

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Women entrepreneurs are the key players in the society and their contributions is highly highlighted to enhance economic stability in the country. In Sri Lanka, especially in North and East provinces people badly affected by war. Most of them are widows and women headed families. Due to this changing environment, Educational opportunities, and the support of NGO’s Most of the women have started their business and become entrepreneurs. Even though existing family setup and social setup entrepreneurial women are overburdened and difficult to balance their business and family roles. The research has been conducted on the experiences of women entrepreneurs with the family role support and work-life balance within the small and micro- enterprise sector in Jaffna, Srilanka. This study aims to identify that what extent the role of family support will be the tool to balancing work and life effectively and, secondly, the main challenges they face in achieving work-life balance. This is done by drawing on literatures including those on work-life balance, small-and micro enterprises, and entrepreneurship theories. To find out this objective, the data were collected from 50 entrepreneurs among the members of Jaffna women chamber in each GS division basis (cluster random sampling). A qualitative methodological technique and semi-structured interviews were used to collect the data for the case study on these entrepreneurs. The results indicate that the majority of entrepreneurs do not enjoy a sense of work-life balance because most of them are women headed family and they need to work hard to generate financial profit for the benefit of family. The motivation for them to work in this way is to provide basic needs. Results confirmed for others that support of husbands is very important. Mostly, emotional support (belief and empowerment) is exposed; however, getting financial contribution seems to be highly appreciated. More responsibilities which spouses were ready to take over regarding the home responsibilities (that is, childcare) should also not be neglected in the system of support to their entrepreneurial wives. Although, more important for all, women with children appreciated other members and spouses help and assistance to a higher extent. Results showed that majority of women who started their own business feel that in the first year of ope-ration the emotional support of family members was more important.

Keywords: family support, work life balance, women entrepreneurs, Jaffna District, Sri Lanka

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Authors: Humphrey Agevi, Harrison Tsingalia, Richard Onwonga, Shem Kuyah

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Most of the world ecosystems have been affected by the effects of climate change. Efforts have been made to mitigate against climate change effects. While most studies have been done in forest ecosystems and pure plant plantations, trees on farms including agroforestry have only received attention recently. Agroforestry systems and tree cover on agricultural lands make an important contribution to climate change mitigation but are not systematically accounted for in the global carbon budgets. This study sought to: (i) determine tree diversity in different agroforestry practices; (ii) determine tree biomass in different agroforestry practices. Study area was determined according to the Land degradation surveillance framework (LSDF). Two study sites were established. At each of the site, a 5km x 10km block was established on a map using Google maps and satellite images. Way points were then uploaded in a GPS helped locate the blocks on the ground. In each of the blocks, Nine (8) sentinel clusters measuring 1km x 1km were randomized. Randomization was done in a common spreadsheet program and later be downloaded to a Global Positioning System (GPS) so that during surveys the researchers were able to navigate to the sampling points. In each of the sentinel cluster, two farm boundaries were randomly identified for convenience and to avoid bias. This led to 16 farms in Kakamega South and 16 farms in Kakamega North totalling to 32 farms in Kakamega Site. Species diversity was determined using Shannon wiener index. Tree biomass was determined using allometric equation. Two agroforestry practices were found; homegarden and hedgerow. Species diversity ranged from 0.25-2.7 with a mean of 1.8 ± 0.10. Species diversity in homegarden ranged from 1-2.7 with a mean of 1.98± 0.14. Hedgerow species diversity ranged from 0.25-2.52 with a mean of 1.74± 0.11. Total Aboveground Biomass (AGB) determined was 13.96±0.37 Mgha-1. Homegarden with the highest abundance of trees had higher above ground biomass (AGB) compared to hedgerow agroforestry. This study is timely as carbon budgets in the agroforestry can be incorporated in the global carbon budgets and improve the accuracy of national reporting of greenhouse gases.

Keywords: agroforestry, allometric equations, biomass, climate change

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Authors: Tarek Elnimr, Reda Morsy, Assem El Fert, Aziza Ismail

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Hepatitis is an inflammation of the liver. The condition can be self-limiting or can progress to fibrosis, cirrhosis or liver cancer. Disease caused by the hepatitis virus, the virus can cause hepatitis infection, ranging in severity from a mild illness lasting a few weeks to a serious, lifelong illness. A growing body of evidence indicates that many trace elements play important roles in a number of carcinogenic processes that proceed with various mechanisms. To examine the status of trace elements during the development of hepatic carcinoma, we determined the iron, copper, zinc and selenium levels in some biological samples of patients at different stages of viral hepatic disease. We observed significant changes in the iron, copper, zinc and selenium levels in the biological samples of patients hepatocellular carcinoma, relative to those of healthy controls. The mean hair, nail, RBC, serum and whole blood copper levels in patients with hepatitis virus were significantly higher than that of the control group. In contrast the mean iron, zinc, and selenium levels in patients having hepatitis virus were significantly lower than those of the control group. On the basis of this study, we identified the impact of natural supplements to improve the treatment of viral liver damage, using the level of some trace elements such as, iron, copper, zinc and selenium, which might serve as biomarkers for increases survival and reduces disease progression. Most of the elements revealed diverse and random distribution in the samples of the donor groups. The correlation study pointed out significant disparities in the mutual relationships among the trace elements in the patients and controls. Principal component analysis and cluster analysis of the element data manifested diverse apportionment of the selected elements in the scalp hair, nail and blood components of the patients compared with the healthy counterparts.

Keywords: hepatitis, hair, nail, blood components, trace element, nutrition therapy, multivariate analysis, correlation, ICP-MS

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Authors: Aaron G. Laylo

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This paper mainly assumes that social entrepreneurship contributes significantly to youth empowerment i.e., work and community engagement. Two questions are thus raised in order to establish this hypothesis: 1) First, how does social entrepreneurship contribute to youth empowerment?; and 2) secondly, why is social entrpreneurship significantly incremental to youth empowerment? This research aims a) to investigate on the social aspect of entrepreneurship; b) to explore challenges in youth empowerment particularly in respect to work and community engagement; and c) to inquire into whether social enterprises have truly served as a catalyst for, thus an effective response to, youth empowerment. It must be emphasized that young people, which comprise 1.8 billion in a world of seven billion are an asset; Apparently, how to maximize that potential is crucial. By utilizing exploratory research design, the paper endeavors to generate new ideas in regards to both components, develop tentative theories on social entrepreneurship, and refine certain issues that are under observation and seek scholarly attention— a rather emerging phenomenon vis a vis the challenge to empower a significant cluster of the society. Case studies will be utilized as an approach in order to comparatively analyze youth-driven social enterprises in the Philippines that have been widely recognized as successful insofar as social impact is concerned. As most scholars attested, social entrepreneurship is still at its infancy stage. Youth empowerment, meanwhile, is yet a vast area to explore insofar as academic research is concerned. Programs and projects that advocate the pursuit of these components abound. However, academic research is yet to be undertaken to see and understand their social and economic relevance. This research is also an opportunity for scholars to explore, understand, and make sense of the promise that lies in social entrepreneurship research and how it can serve as a catalyst for youth empowerment. Youth-driven social enterprises can be an influential tool in sustaining development across the globe as they intend to provide opportunities for optimal economic productivity that recognizes social inclusion. Ultimately, this study should be able to contribute to both research and development-in-practice communities for the greater good of the society. By establishing the nexus between these two components, the research may contribute to fostering greater exploration of the benefits that both may yield to human progress as well as the gaps that have to be filled in by various policy stakeholders relevant to these units.

Keywords: social entpreneurship, youth, empowerment, social inclusion

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Authors: Pajaree Naramitpanich, Natchanok Jansawang, Panwilai Chomchid

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The aims of this are compared between the students’ logical thinking abilities of their learning for designing the 5-lesson instructional plans of the 2-instructional methods, namely; the STEM Education and the Creative Learning Process (CLP) for developing students’ logical thinking abilities that a sample consisted of 90 students from two chemistry classes of different learning outcomes in Wapi Phathum School with the cluster random sampling technique was used at the 11th grade level. To administer of their learning environments with the 45-experimenl student group by the STEM Education method and the 45-controlling student group by the Creative Learning Process. These learning different groups were obtained using the 5 instruments; the 5-lesson instructional plans of the STEM Education and the Creative Learning Process to enhance the logical thinking tests on Mineral issue were used. The efficiency of the Creative Learning Processes (CLP) Model and the STEM Education’s innovations of these each five instructional lesson plans based on criteria are higher than of 80/80 standard level with the IOC index from the expert educators. The averages mean scores of students’ learning achievement motives were assessed with the Pre and Post Techniques and Logical Thinking Ability Test (LTAT) and dependent t-test analysis were differentiated between the CLP and the STEM, significantly. Students’ perceptions of their chemistry classroom environment inventories with the MCI with the CLP and the STEM methods also were found, differently. Associations between students’ perceptions of their chemistry classroom learning environment inventories on the CLP Model and the STEM Education learning designs toward their logical thinking abilities toward chemistry, the predictive efficiency of R2 values indicate that 68% and 76% of the variances in students’ logical thinking abilities toward chemistry to their controlling and experimental chemistry classroom learning environmental groups with the MCI were correlated at .05 levels, significantly. Implementations of this result are showed the students’ learning by the CLP of the potential thinking life-changing roles in most their logical thinking abilities that it is revealed that the students perceive their abilities to be highly learning achievement in chemistry group are differentiated with the STEM education of students’ outcomes.

Keywords: design, the lesson instructional plans, the stem education, the creative learning process, logical thinking ability, different, learning outcome, student, chemistry class

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Authors: Hamza Javar Magnier, Leslie V. Woodcock

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We report extensive molecular dynamics (MD) computational investigations into the thermodynamic description of supercritical properties for a model fluid that is the simplest realistic representation of atoms or molecules. The pair potential is a hard-sphere repulsion of diameter σ with a very short attraction of length λσ. When λ = 1.005 the range is so short that the model atoms are referred to as “adhesive spheres”. Molecular dimers, trimers …etc. up to large clusters, or droplets, of many adhesive-sphere atoms are unambiguously defined. This then defines percolation transitions at the molecular level that bound the existence of gas and liquid phases at supercritical temperatures, and which define the existence of a supercritical mesophase. Both liquid and gas phases are seen to terminate at the loci of percolation transitions, and below a second characteristic temperature (Tc2) are separated by the supercritical mesophase. An analysis of the distribution of clusters in gas, meso- and liquid phases confirms the colloidal nature of this mesophase. The general phase behaviour is compared with both experimental properties of the water-steam supercritical region and also with formally exact cluster theory of Mayer and Mayer. Both are found to be consistent with the present findings that in this system the supercritical mesophase narrows in density with increasing T > Tc and terminates at a higher Tc2 at a confluence of the primary percolation loci. The expended plot of the MD data points in the mesophase of 7 critical and supercritical isotherms in highlight this narrowing in density of the linear-slope region of the mesophase as temperature is increased above the critical. This linearity in the mesophase implies the existence of a linear combination rule between gas and liquid which is an extension of the Lever rule in the subcritical region, and can be used to obtain critical parameters without resorting to experimental data in the two-phase region. Using this combination rule, the calculated critical parameters Tc = 0.2007 and Pc = 0.0278 are found be agree with the values found by of Largo and coworkers. The properties of this supercritical mesophase are shown to be consistent with an alternative description of the phenomenon of critical opalescence seen in the supercritical region of both molecular and colloidal-protein supercritical fluids.

Keywords: critical opalescence, supercritical, square-well, percolation transition, critical parameters.

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Authors: Soumita Mitra, Santosh Kumar Sarkar

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Hooghly river estuary (HRE), situated at the north eastern part of Bay of Bengal has global significance due to its holiness. It is of immense importance to the local population as it gives perpetual water supply for various activities such as transportation, fishing, boating, bathing etc. to the local people who settled on both the banks of this estuary. This study was done to assess the dissolved and particulate trace metal in the estuary covering a stretch of about 175 Km. The water samples were collected from the surface (0-5 cm) along the salinity gradient and metal concentration were studied both in dissolved and particulate phase using Graphite Furnace Atomic Absorption Spectrophotometer (GF-AAS) along some physical characteristics such as water temperature, salinity, pH, turbidity and total dissolved solids. Although much significant spatial variation was noticed but little enrichment was found along the downstream of the estuary. The mean concentration of the metals in the dissolved and particulate phase followed the same trend and as follows: Fe>Mn>Cr>Zn>Cu>Ni>Pb. The concentration of the metals in the particulate phase were much greater than that in dissolved phase which was also depicted from the values of the partition coefficient (Kd)(ml mg-1). The Kdvalues ranged from 1.5x105 (in case of Pb) to 4.29x106 (in case of Cr). The high value of Kd for Cr denoted that the metal Cr is mostly bounded with the suspended particulate matter while the least value for Pb signified it presence more in dissolved phase. Moreover, the concentrations of all the studied metals in the dissolved phase were many folds higher than their respective permissible limits assested by WHO 2008, 2009 and 2011. On the other hand, according to Sediment Quality Guidelines (SQGs), Zn, Cu and Ni in the particulate phase lied between ERL and ERM values but Cr exceeded ERM values at all the stations confirming that the estuary is mostly contaminated with the particulate Cr and it might cause frequent adverse effects on the aquatic life. Multivariate statistics Cluster analysis was also performed which separated the stations according to the level of contamination from several point and nonpoint sources. Thus, it is found that the estuarine system is much polluted by the toxic metals and further investigation, toxicological studies should be implemented for full risk assessment of this system, better management and restoration of the water quality of this globally significant aquatic system.

Keywords: dissolved and particulate phase, Hooghly river estuary, partition coefficient, surface water, toxic metals

Procedia PDF Downloads 280