Search results for: evidence based nursing

Authors: Franziska Moser, Martin Trautz, Anna-Lena Beger, Manuel Löwer, Jörg Feldhusen, Jürgen Prell, Alexandra Wormit, Björn Usadel, Christoph Kämpfer, Thomas-Benjamin Seiler, Henner Hollert

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The demand for bio-based materials and components in architecture has increased in recent years due to society’s heightened environmental awareness. Nowadays, most components are being developed via a substitution approach, which aims at replacing conventional components with natural alternatives who are then being processed, shaped and manufactured to fit the desired application. This contribution introduces a novel approach to the development of bio-based products that decreases resource consumption and increases recyclability. In this approach, natural organisms like plants or trees are not being used in a processed form, but grow into a near net shape before then being harvested and utilized as building components. By minimizing the conventional production steps, the amount of resources used in manufacturing decreases whereas the recyclability increases. This paper presents the approach of technical product harvesting, explains the theoretical basis as well as the matching process of product requirements and biological properties, and shows first results of the growth manipulation studies.

Keywords: design with nature, eco manufacturing, sustainable construction materials, technical product harvesting

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Authors: Shadan Dwairi

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Defining proper requirements is one of the key factors for a successful construction projects. Although there have been many attempts put forward in assist in identifying requirements, but still this area is under developed. In Buildings Information Modelling (BIM) projects. The Employer Information Requirements (EIR) is the fundamental requirements document and a necessary ingredient in achieving a successful BIM project. The provision on full and clear EIR is essential to achieving BIM Level-2. As Defined by PAS 1192-2, EIR is a “pre-tender document that sets out the information to be delivered and the standards and processes to be adopted by the supplier as part of the project delivery process”. It also notes that “EIR should be incorporated into tender documentation to enable suppliers to produce an initial BIM Execution Plan (BEP)”. The importance of effective definition of EIR lies in its contribution to a better productivity during the construction process in terms of cost and time, in addition to improving the quality of the built asset. Proper and clear information is a key aspect of the EIR, in terms of the information it contains and more importantly the information the client receives at the end of the project that will enable the effective management and operation of the asset, where typically about 60%-80% of the cost is spent. This paper reports on the research done in developing the Ontology-based tool for Employer Information Requirements (OntEIR). OntEIR has proven the ability to produce a full and complete set of EIRs, which ensures that the clients’ information needs for the final model delivered by BIM is clearly defined from the beginning of the process. It also reports on the work being done into transforming OntEIR into a smart tool for Defining Employer Information Requirements (smartEIR). smartEIR transforms the OntEIR tool into enabling it to develop custom EIR- tailored for the: Project Type, Project Requirements, and the Client Capabilities. The initial idea behind smartEIR is moving away from the notion “One EIR fits All”. smartEIR utilizes the links made in OntEIR and creating a 3D matrix that transforms it into a smart tool. The OntEIR tool is based on the OntEIR framework that utilizes both Ontology and the Decomposition of Goals to elicit and extract the complete set of requirements needed for a full and comprehensive EIR. A new ctaegorisation system for requirements is also introduced in the framework and tool, which facilitates the understanding and enhances the clarification of the requirements especially for novice clients. Findings of the evaluation of the tool that was done with experts in the industry, showed that the OntEIR tool contributes towards effective and efficient development of EIRs that provide a better understanding of the information requirements as requested by BIM, and support the production of a complete BIM Execution Plan (BEP) and a Master Information Delivery Plan (MIDP).

Keywords: building information modelling, employer information requirements, ontology, web-based, tool

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Authors: Tamseela Habib, Muhammad Amjad, Muhammad Edokali, Masome Moeni, Olivia Pickup, Ali Hassanpour

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Nanofluid-assisted steam generation is rapidly attracting attention amongst the scientific community since it can be applied in a wide range of industrial processes. Because of its high absorption rate of solar energy, nanoparticle-based solar steam generation could be a major contributor to many applications, including water desalination, sterilization and power generation. Lithium bromide-based iron oxide nanofluids have been previously studied in steam generation, which showed promising results. However, the efficiency of the system could be improved if a more heat-conductive nanofluid system could be utilised. In the current paper, we report on an experimental investigation of the photothermal conversion properties of functionalised Copper oxide (CuO) nanoparticles used in Lithium Bromide salt solutions. CuO binary nanofluid was prepared by chemical functionalization with polyethyleneimine (PEI). Long-term stability evaluation of prepared binary nanofluid was done by a high-speed centrifuge analyser which showed a 0.06 Instability index suggesting low agglomeration and sedimentation tendencies. This stability is also supported by the measurements from dynamic light scattering (DLS), transmission electron microscope (TEM), and ultraviolet-visible (UV-Vis) spectrophotometer. The fluid rheology is also characterised, which suggests the system exhibits a Newtonian fluid behavior. The photothermal conversion efficiency of different concentrations of CuO was experimentally investigated under a solar simulator. Experimental results reveal that the binary nanofluid in this study can remarkably increase the solar energy trapping efficiency and evaporation rate as compared to conventional fluids due to localized solar energy harvesting by the surface of the nanofluid. It was found that 0.1wt% CuO NP is the optimum nanofluid concentration for enhanced sensible and latent heat efficiencies.

Keywords: nanofluids, vapor absorption refrigeration system, steam generation, high salinity

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Authors: Maria Amaia Iza Padilla, Ibai Ostolozaga

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The objective of this paper is to analyze how transportation costs between regions within a country can affect not only domestic trade but also the allocation of resources in a given region, aggregate productivity, and relative domestic prices (tradable versus non-tradable). On the one hand, there is a vast literature that analyzes the transportation costs faced by countries when trading with the rest of the world. However, this paper focuses on the effect of transportation costs on domestic trade. Countries differ in their domestic road infrastructure and transport quality. There is also some literature that focuses on the effect of road infrastructure on the price difference between regions but not on relative prices at the aggregate level. On the other hand, this work is also related to the literature on resource misallocation. Finally, the paper is also related to the literature analyzing the effect of trade on the development of the manufacturing sector. Using the World Bank Enterprise Survey database, it is observed cross-country differences in the proportion of firms that consider transportation as an obstacle. From the International Comparison Program, we obtain a significant negative correlation between GDP per worker and relative prices (manufacturing sector prices relative to the service sector). Furthermore, there is a significant negative correlation between a country’s transportation quality and the relative price of manufactured goods with respect to the price of services in that country. This is consistent with the empirical evidence of a negative correlation between transportation quality and GDP per worker, on the one hand, and the negative correlation between GDP per worker and domestic relative prices, on the other. It is also shown that in a country, the share of manufacturing firms whose main market is at the local (regional) level is negatively related to the quality of the transportation infrastructure within the country. Similarly, this index is positively related to the share of manufacturing firms whose main market is national or international. The data also shows that those countries with a higher proportion of manufacturing firms operating locally have higher relative prices. With this information in hand, the paper attempts to quantify the effects of the allocation of resources between and within sectors. The higher the trade barriers caused by transportation costs, the less efficient allocation, which causes lower aggregate productivity. Second, it is built a two-sector model where regions within a country trade with each other. On the one hand, it is found that with respect to the manufacturing sector, those countries with less trade between their regions will be characterized by a smaller variety of goods, less productive manufacturing firms on average, and higher relative prices for manufactured goods relative to service sector prices. Thus, the decline in the relative price of manufactured goods in more advanced countries could also be explained by the degree of trade between regions. This trade allows for efficient intra-industry allocation (traders are more productive, and resources are allocated more efficiently)).

Keywords: misallocation, relative prices, TFP, transportation cost

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Nahid Tavakoli, Asghar Ehteshami, Akbar Hassanzadeh, Fatemeh Amini

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Introduction: The Information security incident management guidelines was been developed to help hospitals to meet their information security event and incident management requirements. The purpose of this Study was to investigate on Information Security Incident Management in Isfahan’s educational hospitals in accordance to ISO/IEC 27002 standards. Methods: This was a cross-sectional study to investigate on Information Security Incident Management of educational hospitals in 2014. Based on ISO/IEC 27002 standards, two checklists were applied to check the compliance with standards on Reporting Information Security Events and Weakness and Management of Information Security Incidents and Improvements. One inspector was trained to carry out the assessments in the hospitals. The data was analyzed by SPSS. Findings: In general the score of compliance Information Security Incident Management requirements in two steps; Reporting Information Security Events and Weakness and Management of Information Security Incidents and Improvements was %60. There was the significant difference in various compliance levels among the hospitals (p-valueKeywords: information security incident management, information security management, standards, hospitals

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Authors: V. Diaz, B. Pardo , D. Villegas

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In premature births most babies have complications at birth, these complications can be reduced, if an atmosphere of relaxation is provided and is also similar to intrauterine life, for this, there are programs where their mothers lull and sway them; however, the conditions in which they do so and the way in they do it may not be the indicated. Here we describe an investigation based on the biomimics of the kinematics of human fetal movement, which consists of determining the movements that the fetus experiences and the deformations of the components that surround the fetus during a gentle walk at week 32 of the gestation stage. This research is based on a 3D model that has the anatomical structure of the pelvis, fetus, muscles, uterus and its most important supporting elements (ligaments). Normal load conditions are applied to this model according to the stage of gestation and the kinematics of a gentle walk of a pregnant mother, which focuses on the pelvic bone, this allows to receive a response from the other elements of the model. To accomplish this modeling and subsequent simulation Solidworks software was used. From this analysis, the curves that describe the movement of the fetus at three different points were obtained. Additionally, we could found the deformation of the uterus and the ligaments that support it, showing the characteristics that these tissues can have in the face of the support of the fetus. These data can be used for the construction of artifacts that help the normal development of premature infants.

Keywords: simulation, biomimic, uterine model, fetal movement study

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Kayvan Khoramipour, Abbas Ali Gaeini, Elham Shirzad, Øyvind Sandbakk

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Basketball has different positions with individual movement profiles, which may influence metabolic demands. Accordingly, the present study aimed to compare the movement and metabolic load between different positions during elite male basketball games. Five main players of 14 teams (n = 70), who participated in the 2017-18 Iranian national basketball leagues, were selected as participants. The players were defined as backcourt (Posts 1-3) and frontcourt (Posts 4-5). Video based time motion analysis (VBTMA) was performed based on players’ individual running and shuffling speed using Dartfish software. Movements were classified into high and low intensity running with and without having the ball, as well as high and low-intensity shuffling and static movements. Mean frequency, duration, and distance were calculated for each class, except for static movements where only frequency was calculated. Saliva samples were collected from each player before and after 40-minute basketball games and analyzed using metabolomics. Principal component analysis (PCA) and Partial least square discriminant analysis (PLSDA) (for metabolomics data) and independent T-tests (for VBTMA) were used as statistical tests. Movement frequency, duration, and distance were higher in backcourt players (all p ≤ 0.05), while static movement frequency did not differ. Saliva samples showed that the levels of Taurine, Succinic acid, Citric acid, Pyruvate, Glycerol, Acetoacetic acid, Acetone, and Hypoxanthine were all higher in backcourt players, whereas Lactate, Alanine, 3-Metyl Histidine, and Methionine were higher in frontcourt players Based on metabolomics, we demonstrate that backcourt and frontcourt players have different metabolic profiles during games, where backcourt players move clearly more during games and therefore rely more on aerobic energy, whereas frontcourt players rely more on anaerobic energy systems in line with less dynamic but more static movement patterns.

Keywords: basketball, metabolomics, saliva, sport loadomics

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Authors: Rakesh Mishra, Rajni Singh, Mukunda Upadhyay

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Since the last few decades, the prima facie of development has shifted towards the working population in India. There has been a paradigm shift in the development approach with the realization that the present demographic dividend has to be harnessed for sustainable development. Rapid urbanization and improved socioeconomic characteristics experienced within its territory has catalyzed various forms of migration into it, resulting in massive transference of workforce between its states. Workforce in any country plays a very crucial role in deciding development of both the places, from where they have out-migrated and the place they are residing currently. In India, people are found to be migrating from relatively less developed states to a well urbanized and developed state for satisfying their neediness. Linking migration to HDI at place of destination, the regression coefficient (β ̂) shows affirmative association between them, because higher the HDI of the place would be, higher would be chance of earning and hence likeliness of the migrants would be more to choose that place as a new destination and vice versa. So the push factor is compromised by the cost of rearing and provides negative impulse on the in migrants letting down their numbers to metro cities or megacities of the states but increasing their mobility to the suburban areas and vice versa. The main objective of the study is to check the role of migration in deciding the dividend of the place of destination as well as people at the place of their usual residence with special focus to highly urban states in India. Idealized scenario of Indian migrants refers to some new theories in making. On analyzing the demographic dividend of the places we got to know that Uttar Pradesh provides maximum dividend to Maharashtra, West Bengal and Delhi, and the demographic divided of migrants are quite comparable to the native’s shares in the demographic dividend in these places. On analyzing the data from National Sample Survey 64th round and Census of India-2001, we have observed that for males in rural areas, the share of unemployed person declined by 9 percentage points (from 45% before migration to 36 % after migration) and for females in rural areas the decline was nearly 12 percentage points (from 79% before migration to 67% after migration. It has been observed that the shares of unemployed males in both rural and urban areas, which were significant before migration, got reduced after migration while the share of unemployed females in the rural as well as in the urban areas remained almost negligible both for before and after migration. So increase in the number of employed after migration provides an indication of changes in the associated cofactors like health and education of the place of destination and arithmetically to the place from where they have migrated out. This paper presents the evidence on the patterns of prevailing migration dynamics and corresponding demographic benefits in India and its states, examines trends and effects, and discusses plausible explanations.

Keywords: migration, demographic shift, human development index, multilevel analysis

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Authors: S. Masud, J. Merson, D. F. Robinson

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The management of environmental resources requires engagement of a range of stakeholders including public/private agencies and different community groups to implement sustainable conservation practices. The challenge which is often ignored is the analysis of agencies involved and their power relations. One of the barriers identified is the difference in risk perceptions among the agencies involved that leads to disjointed efforts of assessing and managing risks. Wood et al 2012, explains that it is important to have an integrated approach to risk management where decision makers address stakeholder perspectives. This is critical for an effective risk management policy. This abstract is part of a PhD research that looks into barriers to flood management under a changing climate and intends to identify bottlenecks that create maladaptation. Experiences are drawn from international practices in the UK and examined in the context of Australia through exploring the flood governance in a highly flood-prone region in Australia: the Hawkesbury Ne-pean catchment as a case study. In this research study several aspects of governance and management are explored: (i) the complexities created by the way different agencies are involved in assessing flood risks (ii) different perceptions on acceptable flood risk level; (iii) perceptions on community engagement in defining acceptable flood risk level; (iv) Views on a holistic flood risk management approach; and, (v) challenges of centralised information system. The study concludes that the complexity of managing a large catchment is exacerbated by the difference in the way professionals perceive the problem. This has led to: (a) different standards for acceptable risks; (b) inconsistent attempt to set-up a regional scale flood management plan beyond the jurisdictional boundaries: (c) absence of a regional scale agency with license to share and update information (d) Lack of forums for dialogue with insurance companies to ensure an integrated approach to flood management. The research takes the Hawkesbury-Nepean catchment as case example and draws from literary evidence from around the world. In addition, conclusions were extrapolated from eighteen semi-structured interviews from agencies involved in flood risk management in the Hawkesbury-Nepean catchment of NSW, Australia. The outcome of this research is to provide a better understanding of complexity in assessing risks against a rapidly changing climate and contribute towards developing effective risk communication strategies thus enabling better management of floods and achieving increased level of support from insurance companies, real-estate agencies, state and regional risk managers and the affected communities.

Keywords: adaptive governance, flood management, flood risk communication, stakeholder risk perceptions

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Authors: Xueying Zhao, Ke Ma, Hui Li, Yu Cao, Fan Yang, Qingwen Xu, Wenbin Liu

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Massively parallel sequencing (MPS) technologies allow high-throughput sequencing analyses with a relatively affordable price and have gradually been applied to forensic casework. MPS technology identifies short tandem repeat (STR) loci based on sequence so that repeat motif variation within STRs can be detected, which may help one to infer the origin of the mutation in some cases. Here, we report on one case with one three-step mismatch (D18S51) in family trios based on both capillary electrophoresis (CE) and MPS typing. The alleles of the alleged father (AF) are [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₁₅. The mother’s alleles are [AGAA]₁₉ and [AGAA]₉AGGA[AGAA]₃. The questioned child’s (QC) alleles are [AGAA]₁₉ and [AGAA]₁₂. Given that the sequence variants in repeat regions of AF and mother are not observed in QC’s alleles, the QC’s allele [AGAA]₁₂ was likely inherited from the AF’s allele [AGAA]₁₅ by loss of three repeat [AGAA]. Besides, two new alleles of D18S51 in this study, [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₉AGGA[AGAA]₃, have not been reported before. All the results in this study were verified using Sanger-type sequencing. In summary, the MPS typing method can offer valuable information for forensic genetics research and play a promising role in paternity testing.

Keywords: family trios analysis, forensic casework, ion torrent personal genome machine (PGM), massively parallel sequencing (MPS)

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Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Yang Yung, Tracy Lin Huan

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Glaucoma is a group of visual maladies represented by the scheduled optic nerve neuropathy; means to the increasing dwindling in vision ground, resulting in loss of sight. In this paper, a novel support vector machine based retinal therapeutic for glaucoma using machine learning algorithm is conservative. The algorithm has fitting pragmatism; subsequently sustained on correlation clustering mode, it visualizes perfect computations in the multi-dimensional space. Support vector clustering turns out to be comparable to the scale-space advance that investigates the cluster organization by means of a kernel density estimation of the likelihood distribution, where cluster midpoints are idiosyncratic by the neighborhood maxima of the concreteness. The predicted planning has 91% attainment rate on data set deterrent on a consolidation of 500 realistic images of resolute and glaucoma retina; therefore, the computational benefit of depending on the cluster overlapping system pedestal on machine learning algorithm has complete performance in glaucoma therapeutic.

Keywords: machine learning algorithm, correlation clustering mode, cluster overlapping system, glaucoma, kernel density estimation, retinal therapeutic

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Authors: Ejoh Nonso Francis

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: Irrigation scheduling is a critical aspect of sustainable agriculture as it ensures optimal use of water resources, reduces water waste, and enhances crop yields. This paper presents a case study of a farm in Onitsha, Anambra State, Nigeria, where irrigation scheduling was optimized using a combination of soil moisture sensors and weather data. The study aimed to evaluate the effectiveness of this approach in improving water use efficiency and crop productivity. The results showed that the optimized irrigation scheduling approach led to a 30% reduction in water use while increasing crop yield by 20%. The study demonstrates the potential of technology-based irrigation scheduling to enhance sustainable agriculture in Nigeria and beyond.

Keywords: irrigation scheduling, sustainable agriculture, soil moisture sensors, weather data, water use efficiency, crop productivity, nigeria, onitsha, anambra state, technology-based irrigation scheduling, water resources, environmental degradation, crop water requirements, overwatering, water waste, farming systems, scalability

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Authors: Medani Prasad Rijal

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The study outlines the impacts of decentralized forest policy on natural Sal (shorea robusta) forests in the Terai region of Nepal. The government has implemented community forestry program to manage the forest resources and improve the livelihood of local people collectively. The forest management authorities such as conserve, manage, develop and use of forest resources were shifted to the local communities, however, the ownership right of the forestland retained by the government. Local communities took the decision on harvesting, distribution, and sell of forest products by fixing the prices independently. The local communities were putting the low value of forest products and distributed among the user households on the name of collective decision. The decision of low valuation is devaluating the worth of forest products. Therefore, the study hypothesized that decision-making capacities are equally prominent next to the decentralized policy and program formulation. To accomplish the study, individual to group level discussions and questionnaire survey methods were applied with executive committee members and user households. The study revealed that the local intuition called Community Forest User Group (CFUG) committee normally took the decisions on consensus basis. Considering to the access and affording capacity of user households having poor economic backgrounds, low pricing mechanism of forest products has been practiced, even though the Sal timber is far expensive in the local market. The local communities thought that low pricing mechanism is accessible to all user households from poor to better off households. However, the analysis of forest products distribution opposed the assumption as most of the Sal timber, which is the most valuable forest product of community forest only purchased by the limited households of better economic conditions. Since the Terai region is heterogeneous by socio-economic conditions, better off households always have higher affording capacity and possibility of taking higher timber benefits because of low price mechanism. On the other hand, the minimum price rate of forest products has poor contribution in community fund collection. Consequently, it has poor support to carry out poverty alleviation activities to poor people. The local communities have been fixed Sal timber price rate around three times cheaper than normal market price, which is a strong evidence of forest product devaluation itself. Finally, the study concluded that the capacity building of local executives as the decision-makers of natural Sal forests is equally indispensable next to the policy and program formulation for effective decentralized forest management. Unilateral decentralized forest policy may devaluate the forest products rather than devolve of power to the local communities and empower to them.

Keywords: community forestry program, decentralized forest policy, Nepal, Sal forests, Terai

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Authors: Faris Algarni

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The Kingdom of Saudi Arabia adopted a new law of e-commerce on July 10, 2019, which is the first Saudi law regarding e-commerce. The practice of e-commerce has been started in Saudi Arabia a few years ago with no specific rules to govern e-commerce in the Kingdom. The adoption of the law raises the concern of the ability of the law to provide real protection to both the investors and the customers. Based on that, this article seeks to respond to some questions related to the protection of investors of e-commerce in Saudi Arabia, using a quantitative method through questionnaires to gather primary data. The study tried to find the impact of adopting a new Saudi law of e-commerce on the protection of the investors from the point of view of those investors. By answering this main question, this article provides an answer to the question of whether there is a need to reform the Saudi law of e-commerce to convince existing and potential foreign investors to invest in the Kingdom through e-commerce. Questions were put to the respondents to determine their level of satisfaction with the Saudi law of e-commerce and what reforms to that system would enhance the attractiveness of the Kingdom as an investment environment for e-commerce investors, based on the information gathered and the analysis of them. A key finding is that the law of e-commerce is a core factor in the decision of investors to continue investing in the e-commerce market in Saudi Arabia. A subsequent finding is that some of the respondents are not fully satisfied with the new law and think that the law provides more protection to the customers than the investors. So, they are suggesting some legal reforms to be implemented in the bylaw of e-commerce, which is not adopted yet in order to attract them to continue investing in the Kingdom.

Keywords: e-commerce, law, investors, protection, Saudi Arabia

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

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Authors: Tatsuya Iizuka, Takushi Kawamorita, Tomoya Handa, Hitoshi Ishikawa

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We report normative cone contrast sensitivity values and sensitivity and specificity values for a computer-based color vision test, the cone contrast test-HD (CCT-HD). The participants included 50 phakic eyes with normal color vision (NCV) and 20 dichromatic eyes (ten with protanopia and ten with deuteranopia). The CCT-HD was used to measure L, M, and S-CCT-HD scores (color vision deficiency, L-, M-cone logCS≦1.65, S-cone logCS≦0.425) to investigate the sensitivity and specificity of CCT-HD based on anomalous-type diagnosis with animalscope. The mean ± standard error L-, M-, S-cone logCS for protanopia were 0.90±0.04, 1.65±0.03, and 0.63±0.02, respectively; for deuteranopia 1.74±0.03, 1.31±0.03, and 0.61±0.06, respectively; and for age-matched NCV were 1.89±0.04, 1.84±0.04, and 0.60±0.03, respectively, with significant differences for each group except for S-CCT-HD (Bonferroni corrected α = 0.0167, p < 0.0167). The sensitivity and specificity of CCT-HD were 100% for protan and deutan in diagnosing abnormal types from 20 to 64 years of age, but the specificity decreased to 65% for protan and 55% for deutan in older persons > 65. CCT-HD is comparable to the diagnostic performance of the anomalous type in the anomaloscope for the 20-64-year-old age group. However, the results should be interpreted cautiously in those ≥ 65 years. They are more susceptible to acquired color vision deficiencies due to the yellowing of the crystalline lens and other factors.

Keywords: cone contrast test HD, color vision test, congenital color vision deficiency, red-green dichromacy, cone contrast sensitivity

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Authors: Fanny Desbiolles, Laure Malleret, Isabelle Laffont-Schwob, Christophe Tiliacos, Anne Piram, Mohamed Sarakha, Pascal Wong-Wah-Chung

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Pharmaceuticals in the environment have become a very hot topic in the recent years. This interest is related to the large amounts dispensed and to their release in urine or faeces from treated patients, resulting in their ubiquitous presence in water resources and wastewater treatment plants (WWTP) effluents. Thereby, many studies focused on the prediction of pharmaceuticals’ behaviour, to assess their fate and impacts in the environment. Carbamazepine is a widely consumed psychotropic pharmaceutical, thus being one of the most commonly detected drugs in the environment. This organic pollutant was proved to be persistent, especially with respect to its non-biodegradability, rendering it recalcitrant to usual biological treatment processes. Consequently, carbamazepine is very little removed in WWTP with a maximum abatement rate of 5 % and is then often released in natural surface waters. To better assess the environmental fate of carbamazepine in aqueous media, its photochemical transformation was undertaken in four natural waters (two French rivers, the Berre salt lagoon, Mediterranean Sea water) representative of coastal and inland water types. Kinetic experiments were performed in the presence of light using simulated solar irradiation (Xe lamp 300W). Formation of short-lifetime species was highlighted using chemical trap and laser flash photolysis (nanosecond). Identification of transformation by-products was assessed by LC-QToF-MS analyses. Carbamazepine degradation was observed after a four-day exposure and an abatement of 20% maximum was measured yielding to the formation of many by-products. Moreover, the formation of hydroxyl radicals (•OH) was evidenced in waters using terephthalic acid as a probe, considering the photochemical instability of its specific hydroxylated derivative. Correlations were implemented using carbamazepine degradation rate, estimated hydroxyl radical formation and chemical contents of waters. In addition, laser flash photolysis studies confirmed •OH formation and allowed to evidence other reactive species, such as chloride (Cl2•-)/bromine (Br2•-) and carbonate (CO3•-) radicals in natural waters. Radicals mainly originate from dissolved phase and their occurrence and abundance depend on the type of water. Rate constants between reactive species and carbamazepine were determined by laser flash photolysis and competitive reactions experiments. Moreover, LC-QToF-MS analyses of by-products help us to propose mechanistic pathways. The results will bring insights to the fate of carbamazepine in various water types and could help to evaluate more precisely potential ecotoxicological effects.

Keywords: carbamazepine, kinetic and mechanistic approaches, natural waters, photodegradation

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Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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Authors: Rihab Hamdi, Amel Hadri Hamida, Ouafae Bennis, Fatima Babaa, Sakina Zerouali

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This paper features a sliding mode controller (SMC) for closed-loop voltage control of DC-DC three-cells buck converter connected in parallel, operating in continuous conduction mode (CCM), based on pulse-width modulation (PWM). To maintain the switching frequency, the approach is to incorporate a pulse-width modulation that utilizes an equivalent control, inferred by applying the SM control method, to produce a control sign to be contrasted and the fixed-frequency within the modulator. Detailed stability and transient performance analysis have been conducted using Lyapunov stability criteria to restrict the switching frequency variation facing wide variations in output load, input changes, and set-point changes. The results obtained confirm the effectiveness of the proposed control scheme in achieving an enhanced output transient performance while faithfully realizing its control objective in the event of abrupt and uncertain parameter variations. Simulations studies in MATLAB/Simulink environment are performed to confirm the idea.

Keywords: DC-DC converter, pulse width modulation, power electronics, sliding mode control

Procedia PDF Downloads 138

Authors: M. J. Norashirene, Y. Zakiah, S. Nurdiana, I. Nur Hilwani, M. H. Siti Khairiyah, M. J. Muhamad Arif

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In this study, six bacterial isolates of a slightly thermophilic organism from the Sg. Klah hot spring, Malaysia were successfully isolated and designated as M7T55D1, M7T55D2, M7T55D3, M7T53D1, M7T53D2 and M7T53D3 respectively. The bacterial isolates were screened for their cellulose hydrolytic ability on Carboxymethlycellulose agar medium. The isolated bacterial strains were identified morphologically, biochemically and molecularly with the aid of 16S rDNA sequencing. All of the bacteria showed their optimum growth at a slightly alkaline pH of 7.5 with a temperature of 55°C. All strains were Gram-negative, non-spore forming type, strictly aerobic, catalase-positive and oxidase-positive with the ability to produce thermostable cellulase. Based on BLASTn results, bacterial isolates of M7T55D2 and M7T53D1 gave the highest homology (97%) with similarity to Tepidimonas ignava while isolates M7T55D1, M7T55D3, M7T53D2 and M7T53D3 showed their closest homology (97%-98%) with Tepidimonas thermarum. These cellulolytic thermophiles might have a commercial potential to produce valuable thermostable cellulase.

Keywords: cellulase, cellulolytic, thermophiles, 16S rDNA gene

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Authors: Ilma Robo, Saimir Heta, Emela Dalloshi, Nevila Alliu, Vera Ostreni

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The dental whitening process, beyond the fact that it is a mini-invasive dental treatment, has effects on the dental structure, or on the pulp of the tooth, where it is applied. The electronic search was performed using keywords to find articles published within the last 10 years about side effects, assessed as such, of minimally invasive dental bleaching treatment. Methodology: In selected articles, the other aim of the study was to evaluate the side effects of bleaching based on the percentage and type of solution used, where the latter was evaluated on the basic solution used for bleaching. Results: The side effects of bleaching are evaluated in selected articles depending on the method of bleaching application, which means it is carried out with recommended solutions, or with mixtures of alternative solutions or substances based on Internet information. Short conclusion: The dental bleaching process has side effects which have not yet been definitively evaluated, experimentally in large samples of individuals or animals (mice or cattle) to arrive at accurate numerical conclusions. The trend of publications about this topic is increasing in recent years, as long as the trend for aesthetic facial treatments, including dental ones, is increasing.

Keywords: teeth whitening, side effects, permanent teeth, formed dental apex

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Authors: Kailas L. Wasewar

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Biobutanol has been considered as a potential and alternative biofuel relative to the most popular biodiesel and bioethanol. End product toxicity is the major problems in commercialization of fermentation based process which can be reduce to some possible extent by removing biobutanol simultaneously. Several techniques have been investigated for removing butanol from fermentation broth such as stripping, adsorption, liquid–liquid extraction, pervaporation, and membrane solvent extraction. Liquid–liquid extraction can be performed with high selectivity and is possible to carry out inside the fermenter. Conventional solvents have few drawbacks including toxicity, loss of solvent, high cost etc. Hence alternative solvents must be explored for the same. Room temperature ionic liquids (RTILs) composed entirely of ions are liquid at room temperature having negligible vapor pressure, non-flammability, and tunable physiochemical properties for a particular application which term them as “designer solvents”. Ionic liquids (ILs) have recently gained much attention as alternatives for organic solvents in many processes. In particular, ILs have been used as alternative solvents for liquid–liquid extraction. Their negligible vapor pressure allows the extracted products to be separated from ILs by conventional low pressure distillation with the potential for saving energy. Morpholinium, imidazolium, ammonium, phosphonium etc. based ionic liquids have been employed for the separation biobutanol. In present chapter, basic concepts of ionic liquids and application in separation have been presented. Further, type of ionic liquids including, conventional, functionalized, polymeric, supported membrane, and other ionic liquids have been explored. Also the effect of various performance parameters on separation of biobutanol by ionic liquids have been discussed and compared for different cation and anion based ionic liquids. The typical methodology for investigation have been adopted such as contacting the equal amount of biobutanol and ionic liquids for a specific time say, 30 minutes to confirm the equilibrium. Further, biobutanol phase were analyzed using GC to know the concentration of biobutanol and material balance were used to find the concentration in ionic liquid.

Keywords: biobutanol, separation, ionic liquids, sustainability, biorefinery, waste biomass

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Authors: N. Borjalilu, P. Rabiei, A. Enjoo

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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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Authors: Bhrugesh Radadiya, Jaydeep Shah

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In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

Procedia PDF Downloads 724

Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

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There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

Procedia PDF Downloads 237

Authors: Budoor Al Abid

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Educational systems are increasingly provided as open online services, providing guidance and support for individual learners. To adapt the learning systems, a proper evaluation must be made. This paper builds the evaluation model Fuzzy C Means Adaptive System (FCMAS) based on data mining techniques to assess the difficulty of the questions. The following steps are implemented; first using a dataset from an online international learning system called (slepemapy.cz) the dataset contains over 1300000 records with 9 features for students, questions and answers information with feedback evaluation. Next, a normalization process as preprocessing step was applied. Then FCM clustering algorithms are used to adaptive the difficulty of the questions. The result is three cluster labeled data depending on the higher Wight (easy, Intermediate, difficult). The FCM algorithm gives a label to all the questions one by one. Then Random Forest (RF) Classifier model is constructed on the clustered dataset uses 70% of the dataset for training and 30% for testing; the result of the model is a 99.9% accuracy rate. This approach improves the Adaptive E-learning system because it depends on the student behavior and gives accurate results in the evaluation process more than the evaluation system that depends on feedback only.

Keywords: machine learning, adaptive, fuzzy logic, data mining

Procedia PDF Downloads 191

Authors: Ana-María Gómez-Carvajal, Hernando Santamaría-García, Mateo Bernal, Mario Valderrama, Daniela Lizarazo, Juliana Restrepo, María Fernanda Barreto, Angélica Parra, Paula Torres, Diana Matallana, Jaime Silva, José Santamaría-García, Sandra Baez

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Higher levels of oxytocin are associated with better performance on social cognition tasks. However, higher levels of oxytocin have also been associated with increased levels of envy and schadenfreude. Considering these antecedents, this study aims to explore social emotions (i.e., envy and schadenfreude) and other components of social cognition (i.e. ToM and empathy), in women in the puerperal period and their respective partners, compared to a control group of men and women without children or partners. Control women should be in the luteal phase of the menstrual cycle or taking oral contraceptives as they allow oxytocin levels to remain stable. We selected this population since increased levels of oxytocin are present in both mothers and fathers of newborn babies. Both groups were matched by age, sex, and education level. Twenty-two parents of newborns (11 women, 11 men) and 15 controls (8 women, 7 men) performed an experimental task designed to trigger schadenfreude and envy. In this task, each participant was shown a real-life photograph and a description of two target characters matched in age and gender with the participant. The task comprised two experimental blocks. In the first block, participants read 15 sentences describing fortunate events involving either character. After reading each sentence, participants rated the event in terms of how much envy they felt for the character (1=no envy, 9=extreme envy). In the second block, participants read and reported the intensity of their pleasure (schadenfreude, 1=no pleasure, 9=extreme pleasure) in response to 15 unfortunate events happening to the characters. Five neutral events were included in each block. Moreover, participants were assessed with ToM and empathy tests. Potential confounding variables such as general cognitive functioning, stress levels, hours of sleep and depression symptoms were also measured. Results showed that parents of newborns showed increased levels of envy and schadenfreude. These effects are not explained by any confounding factor. Moreover, no significant differences were found in ToM or empathy tests. Our results offer unprecedented evidence of specific differences in envy and schadenfreude levels in parents of newborns. Our findings support previous studies showing a negative relationship between oxytocin levels and negative social emotions. Further studies should assess the direct relationship between oxytocin levels in parents of newborns and the performance in social emotions tasks.

Keywords: envy, empathy, oxytocin, schadenfreude, social emotions, theory of mind

Procedia PDF Downloads 313