Search results for: randomized response model

Authors: Husham Bayazed

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Purpose of presentation: Pregnancy represents the most important period for the conservation of the species. The immune system is one of the most important systems protecting the mother against the environment and preventing damage to the fetus. This presentation aims to review and discuss the role of the immune system during pregnancy, the evolutionary inflammatory process through pregnancy, infectious and environmental exposure influences on the mother and the fetus, and the impacts of sexual dimorphism of the placenta on offspring susceptibility to different disorders. Recent Findings: In 1960, Peter Medawar (Nobel Prize Winner) proposed that the fetus, a semi-allograft, is similar to a tissue graft that escapes rejection through a mechanism involving systemic immune suppression (Graft –Host response). However, recent researchers and studies have documented that implantation means inflammation, and the inflammatory process is considered a breach of tolerance in pregnancy with immune induction, which is necessary for the protection of the mother and the fetus against infections and environmental triggers. This inflammatory process should be maintained during different pregnancy phases till parturition, and any block at any phase will be associated with pregnancy complications, including pregnancy failure or loss, miscarriage, and preterm birth subsequently. Maternal immune activation following any trigger can have a positive effect on the fetus. The old concept of the placenta being asexual is inaccurate, and being with sexual dimorphism with clear differences in susceptibility to different factors that stimulate maternal immunity. Summary: The presence of different immune cells ((i.e., T cells, B cells, NK cells, etc.) at the implantation site is considered proof of a strong maternal immune response to the fetus. Therefore, human pregnancy is considered a unique immunological paradigm requiring maternal immune modulation rather than suppression. So Medawar's postulation of maternal systemic immunosuppression is wrong. Maternal immune system activation triggered by infections, stress, diet, and pollution can have a positive effect on the fetus, with the development of fetal-trained immunity necessary for survival. The sexual dimorphism of the placenta seems to have an impact on the differences in sex susceptible to the environment maternal risk stimuli. This link to why the incidence of autism is increasing more among boys than girls.

Keywords: pregnancy, maternal immunity, implantation and inflammation, placenta sexual dimorphism

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Authors: B. Chikh, L. Moussa, H. Bechtoula, Y. Mehani, A. Zerzour

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This study presents a new method, applicable to evaluation and design of structures has been developed and illustrated by comparison with the capacity spectrum method (CSM, ATC-40). This method uses inelastic spectra and gives peak responses consistent with those obtained when using the nonlinear time history analysis. Hereafter, the seismic demands assessment method is called in this paper DSM, Ductility Spectrum Method. It is used to estimate the seismic deformation of Single-Degree-Of-Freedom (SDOF) systems based on DDRS, Ductility Demand Response Spectrum, developed by the author.

Keywords: seismic demand, capacity, inelastic spectra, design and structure

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Authors: Jacques Lamarche, Juhani Dickinson

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This paper introduces a computational model of a Grammar as Logic of Labeling (GLL), where the lexical primitives of morphosyntax are phonological matrixes, the form of words, understood as labels that apply to realities (or targets) assumed to be outside of grammar altogether. The hypothesis is that even though a lexical label relates to its target arbitrarily, this label in a complex (constituent) label is part of a labeling pattern which, depending on its value (i.e., N, V, Adj, etc.), imposes language-specific restrictions on what it targets outside of grammar (in the world/semantics or in cognitive knowledge). Lexical forms categorized as nouns, verbs, adjectives, etc., are effectively targets of labeling patterns in use. The paper illustrates GLL through a computer model of basic patterns in English NPs. A constituent label is a binary object that encodes: i) alignment of input forms so that labels occurring at different points in time are understood as applying at once; ii) endocentric structuring - every grammatical constituent has a head label that determines the target of the constituent, and a limiter label (the non-head) that restricts this target. The N or A values are restricted to limiter label, the two differing in terms of alignment with a head. Consider the head initial DP ‘the dog’: the label ‘dog’ gets an N value because it is a limiter that is evenly aligned with the head ‘the’, restricting application of the DP. Adapting a traditional analysis of ‘the’ to GLL – apply label to something familiar – the DP targets and identifies one reality familiar to participants by applying to it the label ‘dog’ (singular). Consider next the DP ‘the large dog’: ‘large dog’ is nominal by even alignment with ‘the’, as before, and since ‘dog’ is the head of (head final) ‘large dog’, it is also nominal. The label ‘large’, however, is adjectival by narrow alignment with the head ‘dog’: it doesn’t target the head but targets a property of what dog applies to (a property or value of attribute). In other words, the internal composition of constituents determines that a form targets a property or a reality: ‘large’ and ‘dog’ happen to be valid targets to realize this constituent. In the presentation, the computer model of the analysis derives the 8 possible sequences of grammatical values with three labels after the determiner (the x y z): 1- D [ N [ N N ]]; 2- D [ A [ N N ] ]; 3- D [ N [ A N ] ]; 4- D [ A [ A N ] ]; 5- D [ [ N N ] N ]; 5- D [ [ A N ] N ]; 6- D [ [ N A ] N ] 7- [ [ N A ] N ] 8- D [ [ Adv A ] N ]. This approach that suggests that a computer model of these grammatical patterns could be used to construct ontologies/knowledge using speakers’ judgments about the validity of lexical meaning in grammatical patterns.

Keywords: syntactic theory, computational linguistics, logic and grammar, semantics, knowledge and grammar

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Authors: Salem Alghamdi

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Genotypes collected from farmers at a different region of Saudi Arabia as well as from Egyptian cultivar and a new line from Yamen. Seeds of these genotypes were grown in Dirab Agriculture Research Station, (Middle Region) and Al-Ahsa Palms and Dates Research Center (East region), during summer of 2015. Field experiments were laid out in randomized complete block design on the first week of June with three replications. Each experiment plot contained 6 rows 3m in length. Inter- and intra-row spacing was 60 and 25cm, respectively. Seed yield and its components were estimated in addition to qualitative characters on cowpea plants grown only in Dirab using cowpea descriptor from IPGRI, 1982. Seeds for chemical composite and antioxidant contents were analyzed. Highly significant differences were detected between genotypes in both locations and the combined of two locations for seed yield and its components. Mean data clearly show exceeded determine genotypes in seed yield while indeterminate genotypes had higher biological yield that divided cowpea genotypes to two main groups 1- forage genotypes (KSU-CO98, KSU-CO99, KSU-CO100, and KSU-CO104) that were taller and produce higher branches, biological yield and these are suitable to feed on haulm 2- food genotypes (KSU-CO101, KSU-CO102, and KSU-CO103) that produce higher seed yield with lower haulm and also these genotypes characters by high seed index and light seed color. Highly significant differences were recorded for locations in all studied characters except the number of branches, seed index, and biological yield, however, the interaction of genotype x location was significant only for plant height, the number of pods and seed yield per plant.

Keywords: Cowpea, genotypes, antioxidant contents, yield

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Ritsuko Kawasaki, Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Godwin Chigozie Okpara, William Chimee Nwaoha

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The paper set out to stress on how financial inclusion index could be calculated and also investigated the impact of inclusive finance on inclusive growth in an emerging economy. In the light of these objectives, chi-wins method was used to calculate indexes of financial inclusion while co-integration and error correction model were used for evaluation of the impact of financial inclusion on inclusive growth. The result of the analysis revealed that financial inclusion while having a long-run relationship with GDP growth is an insignificant function of the growth of the economy. The speed of adjustment is correctly signed and significant. On the basis of these results, the researchers called for tireless efforts of government and banking sector in promoting financial inclusion in developing countries.

Keywords: chi-wins index, co-integration, error correction model, financial inclusion

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Authors: Kyaw Zin Htut

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In this article, the synthesis of the efficiency of intelligent diagnostic system in the aircraft measuring devices is described. The technology developments of the diagnostic system are considered based on the model errors of the gyro instruments, which are used to measure the parameters of the aircraft. The synthesis of the diagnostic intelligent system is considered on the example of the problem of assessment and forecasting errors of the gyroscope devices on the onboard aircraft. The result of the system is to detect of faults of the aircraft measuring devices as well as the analysis of the measuring equipment to improve the efficiency of its work.

Keywords: diagnostic, dynamic system, errors of gyro instruments, model errors, assessment, prognosis

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Authors: Chiao-Chen Chang, Yang-Chieh Chin

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Social media has created a change in the way the network community is clustered, especially from the location of the community, from the original virtual space to the intertwined network, and thus the communication between people will change from face to face communication to social media-based communication model. However, social media users who have had a fixed engagement may have an intention to switch to another service provider because of the emergence of new forms of social media. For example, some of Facebook or Twitter users switched to Instagram in 2014 because of social media messages or image overloads, and users may seek simpler and instant social media to become their main social networking tool. This study explores the impact of system features overload, information overload, social monitoring concerns, problematic use and privacy concerns as the antecedents on social media fatigue, dissatisfaction, and alternative attractiveness; further influence social media switching. This study also uses the online questionnaire survey method to recover the sample data, and then confirm the factor analysis, path analysis, model fit analysis and mediating analysis with the structural equation model (SEM). Research findings demonstrated that there were significant effects on multiple paths. Based on the research findings, this study puts forward the implications of theory and practice.

Keywords: social media, switching, social media fatigue, alternative attractiveness

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Authors: Eyad Almaita

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In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

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Authors: Fatima Sohail, Faizan Iftikhar

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This paper studies the relationship between digital finance, renewable energy, and the economic development of Pakistan and least developed countries from 2000 to 2022. The paper used panel analysis and generalized method of moments Arellano-Bond approaches. The findings show that under the growth model, renewable energy (RE) has a strong and favorable link with fixed broadband and mobile subscribers. However, FB and MD have a strong but negative association with the uptake of renewable energy (RE) in the average and simple model. This paper provides valuable insights for policymakers, investors of the digital economy.

Keywords: digital finance, renewable energy, economic development, mobile subscription, fixed broadband

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Hamza Saeed, Khurram Iqbal Ahmad Khan

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Effective information management is crucial for any construction project and its success. Primary areas of information generation are either the construction site or the design office. There are different types of information required at different stages of construction involving various stakeholders creating complexity. There is a need for effective management of information flows to reduce uncertainty creating complexity. Nature provides a unique perspective in terms of dealing with complexity, in particular, information complexity. System dynamics methodology provides tools and techniques to address complexity. It involves modeling and simulation techniques that help address complexity. Nature has been dealing with complex systems since its creation 4.5 billion years ago. It has perfected its system by evolution, resilience towards sudden changes, and extinction of unadaptable and outdated species that are no longer fit for the environment. Nature has been accommodating the changing factors and handling complexity forever. Humans have started to look at their natural counterparts for inspiration and solutions for their problems. This brings forth the possibility of using a biomimetics approach to improve the management practices used in the construction sector. Ants inhabit different habitats. Cataglyphis and Pogonomyrmex live in deserts, Leafcutter ants reside in rainforests, and Pharaoh ants are native to urban developments of tropical areas. Detailed studies have been done on fifty species out of fourteen thousand discovered. They provide the opportunity to study the interactions in diverse environments to generate collective behavior. Animals evolve to better adapt to their environment. The collective behavior of ants emerges from feedback through interactions among individuals, based on a combination of three basic factors: The patchiness of resources in time and space, operating cost, environmental stability, and the threat of rupture. If resources appear in patches through time and space, the response is accelerating and non-linear, and if resources are scattered, the response follows a linear pattern. If the acquisition of energy through food is faster than energy spent to get it, the default is to continue with an activity unless it is halted for some reason. If the energy spent is rather higher than getting it, the default changes to stay put unless activated. Finally, if the environment is stable and the threat of rupture is low, the activation and amplification rate is slow but steady. Otherwise, it is fast and sporadic. To further study the effects and to eliminate the environmental bias, the behavior of four different ant species were studied, namely Red Harvester ants (Pogonomyrmex Barbatus), Argentine ants (Linepithema Humile), Turtle ants (Cephalotes Goniodontus), Leafcutter ants (Genus: Atta). This study aims to improve the information system in the construction sector by providing a guideline inspired by nature with a systems-thinking approach, using system dynamics as a tool. Identified factors and their interdependencies were analyzed in the form of a causal loop diagram (CLD), and construction industry professionals were interviewed based on the developed CLD, which was validated with significance response. These factors and interdependencies in the natural system corresponds with the man-made systems, providing a guideline for effective use and flow of information.

Keywords: biomimetics, complex systems, construction management, information management, system dynamics

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Authors: Shuo Liu

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In Chinese text classification tasks, redundant words and phrases can interfere with the formation of extracted and analyzed text information, leading to a decrease in the accuracy of the classification model. To reduce irrelevant elements, extract and utilize text content information more efficiently and improve the accuracy of text classification models. In this paper, the text in the corpus is first extracted using the TextRank algorithm for abstraction, the words in the abstract are used as nodes to construct a text graph, and then the graph attention network (GAT) is used to complete the task of classifying the text. Testing on a Chinese dataset from the network, the classification accuracy was improved over the direct method of generating graph structures using text.

Keywords: Chinese natural language processing, text classification, abstract extraction, graph attention network

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Authors: Veronica S. Moertini, Niko Ibrahim, Verliyantina

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As market intermediary firms, e-commerce transaction broker firms need to strongly collaborate with suppliers in order to develop brands seek by customers. Developing suitable electronic Supplier Relationship Management (e-SRM) system is the solution to the need. In this paper, we propose our concept of e-SRM for transaction brokers owned by small medium enterprises (SMEs), which includes the integrated e-SRM and e-CRM architecture, the e-SRM applications with their functions. We then discuss the customization and implementation of the proposed e-SRM model in a specific transaction broker selling hotel rooms, which owned by an SME, KlikHotel.com. The implementation of the e-SRM in KlikHotel.com has been successfully boosting the number of suppliers (hotel members) and hotel room sales.

Keywords: e-CRM, e-SRM, SME, transaction broker

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Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

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Authors: K. D. Rajatha, S. Rajendra Prasad, N. Nethra

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Aeroponics is one of the advanced techniques to cultivate plants without soil with minimal water and nutrient consumption. This is the technology which could bring the vertical growth in agriculture. It is an eco-friendly approach widely used for commercial cultivation of vegetables to obtain the supreme quality and yield. In this context, to harvest potentiality of the technology, an experiment was designed to evaluate the suitability of the aeroponics method over the conventional method for hybrid seed production of tomato. The experiment was carried out under Completely Randomized Design with Factorial (FCRD) concept with three replications during the year 2017-18 at UAS, GKVK Bengaluru. Nutrients and pH were standardized; among the six different nutrient solutions, the crop performance was better in Hoagland’s solution with pH between 5.5-7. The results of the present study revealed that between TAG1F and TAG2F parental lines, TAG1F performed better in both the methods of seed production. Among the methods, aeroponics showed better performance for the quality parameters except for plant spread, due to better availability of nutrients and aeration, huge root biomass in aeroponics. Aeroponics method showed significantly higher plant length (124.9 cm), plant growth rate (0.669), seedling survival rate (100%), early flowering (27.5 days), highest fruit weight (121.5 g), 100 seed weight (0.373 g) and total seed yield plant⁻¹ (11.68 g) compared to the conventional method. By providing the best environment for plant growth, the genetically best possible plant could be grown, thus complete potentiality of the plant could be harvested. Hence, aeroponics could be a promising tool for quality and healthy hybrid seed production throughout the year within protected cultivation.

Keywords: aeroponics, Hoagland’s solution, hybrid seed production, Lycopersicon esculentum

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Authors: Mardiati Zain, W. S. N. Rusmana, Erpomen, Malik Makmur, Ezi Masdia Putri

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Background and Aim: The leaves of the Leucaenaleucocephala tree have potential as a nitrogen source for ruminants. Leucaena leaf meal as protein supplement has been shown to improve the feed quality of ruminants. The effects of different levels of Leucaena leucocephala supplementation as substitute of concentrate on fiber digestibility and in vitro rumen fermentation characteristics were investigated. This research was conducted in vitro. The study used a randomized block design consisting of 3 treatments and 5 replications. The treatments were A. 40% rice straw ammoniated + 60% concentrate, B. 40% rice straw ammoniated + 50% concentrate + 10% Leucaena leuchephala, C. 40% rice straw ammoniated + 40% concentrate + 20% Leucaena leuchephala, Result: The results showed that the addition of Leucaena leucocephala increased the digestibility of Neutral detergent Fiber NDF and Acid Detergent Fiber (ADF) (p < 0.05). In this study, rumen NH3, propionate, amount of escape protein and total Volatyl Fatty Acid (VFA) were found increased significantly at treatment B. No significant difference was observed in acetate and butyrate production. The populations of total protozoa and methane production had significantly decreased (P < .05) in supplemented group. Conclusion: Supplementation of leuchaena leucochepala on completed feed based on ammoniated rice straw in vitro can increase fiber digestibility, VFA production and decreased protozoa pupulataion and methane production. Supplementation of 10% and 20% L. leucochepala were suitable to be used for further studies, therefore in vivo experiment is required to study the effects on animal production.

Keywords: digestibility, Leucaena leucocephala, complete feed, rice straw ammoniated

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Authors: Pannathorn Chachvarat, Smarnjit Piromrun

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Aging is the reality for the future world. An urgent priority for the development of the elderlies’ quality living is needed. The promotion of quality the elderly to live longer in their dignity and being independence are essential. The objective of this descriptive research was to study the self-care regarding to the valuable living in Thai elderly. The randomized sample was 100 elderly who live in Muang district of Phayao province. The tools included 2 parts; 1) Personal data (gender, age, income, occupation, marital status, living condition and disease), and 2) the self-care regarding to the valuable living questionnaire consisted of 3 domains, physical (21items), spiritual (13 items) and social domain (12 items). The content validity tool was tested the IOC ranged between 0.60 – 1.00 and the reliability test, Cronbach Alpha was 0.82. The research found that; The most participants were female (60 %), Farmer (37%), and underlying disease (65 %). The range of age was 68 years. Overall of the self-care regarding to the valuable living of physical, spiritual and social were at the high level.The highest level of physical activities was self-taking bath twice a day (morning and evening), and slept at least 5-6 hours at night time.The highest level of spirit activities was a good member of the family, contributions to persons in family, good emotion. Additionally were enjoyable, accepting changes in the body such as the dry skin and the blurred vision, accepting the roles and duties in taking care of house and grandchildren, selecting the applicable activities and practice according to religious Buddhateachingfor the happiness and meditated life.The highest of the social activities were the good relationship between other elderlies and family members, happy to help social activities as of their capacity, and being happy to help other people who have problems.

Keywords: self-care, valuable living, elderly, Thai

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Authors: Ben Main Piotr Ozieranski

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State government spending on pharmaceuticals stands at 1 trillion USD globally, promoting criticism of the pharmaceutical industry's monetization of drug efficacy, product cost overvaluation, and health injustice. This paper elucidates the mechanisms behind a state-institutional response to this problem through the sociological lens of the strategic relational approach to state power. To do so, 30 expert interviews, legal and policy documents are drawn on to explain how state elites in New Zealand have successfully contested a 30-year “pharmaceutical spending containment policy”. Proceeding from Jessop's notion of strategic “selectivity”, encompassing analyses of the enabling features of state actors' ability to harness state structures, a theoretical explanation is advanced. First, a strategic context is described that consists of dynamics around pharmaceutical dealmaking between the state bureaucracy, pharmaceutical pricing strategies (and their effects), and the industry. Centrally, the pricing strategy of "bundling" -deals for packages of drugs that combine older and newer patented products- reflect how state managers have instigated an “incentivization game” that is played by state and industry actors, including HTA professionals, over pharmaceutical products (both current and in development). Second, a protective context is described that is comprised of successive legislative-judicial responses to the strategic context and characterized by the regulation and the societalisation of commercial law. Third, within the policy, the achievement of increased pharmaceutical coverage (pharmaceutical “mix”) alongside contained spending is conceptualized as a state defence of a "social profit". As such, in contrast to scholarly expectations that political and economic cultures of neo-liberalism drive pharmaceutical policy-making processes, New Zealand's state elites' approach is shown to be antipathetic to neo-liberals within an overall capitalist economy. The paper contributes an analysis of state pricing strategies and how they are embedded in state regulatory structures. Additionally, through an analysis of the interconnections of state power and pharmaceutical value Abrahams's neo-liberal corporate bias model for pharmaceutical policy analysis is problematised.

Keywords: pharmaceutical governance, pharmaceutical bureaucracy, pricing strategies, state power, value theory

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Authors: Kanokwan Chancharoenchai

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Economic growth can be considered as an important element of countries’ development process. For developing countries, like Thailand, to ensure the continuous growth of the economy, the Thai government usually implements various policies to stimulate economic growth. They may take the form of fiscal, monetary, trade, and other policies. Because of these different aspects, understanding factors relating to economic growth could allow the government to introduce the proper plan for the future economic stimulating scheme. Consequently, this issue has caught interest of not only policymakers but also academics. This study, therefore, investigates explanatory variables for economic growth in Thailand from 2005 to 2017 with a total of 52 quarters. The findings would contribute to the field of economic growth and become helpful information to policymakers. The investigation is estimated throughout the production function with non-linear Cobb-Douglas equation. The rate of growth is indicated by the change of GDP in the natural logarithmic form. The relevant factors included in the estimation cover three traditional means of production and implicit effects, such as human capital, international activity and technological transfer from developed countries. Besides, this investigation takes the internal and external instabilities into account as proxied by the unobserved inflation estimation and the real effective exchange rate (REER) of the Thai baht, respectively. The unobserved inflation series are obtained from the AR(1)-ARCH(1) model, while the unobserved REER of Thai baht is gathered from naive OLS-GARCH(1,1) model. According to empirical results, the AR(|2|) equation which includes seven significant variables, namely capital stock, labor, the imports of capital goods, trade openness, the REER of Thai baht uncertainty, one previous GDP, and the world financial crisis in 2009 dummy, presents the most suitable model. The autoregressive model is assumed constant estimator that would somehow cause the unbias. However, this is not the case of the recursive coefficient model from the state space model that allows the transition of coefficients. With the powerful state space model, it provides the productivity or effect of each significant factor more in detail. The state coefficients are estimated based on the AR(|2|) with the exception of the one previous GDP and the 2009 world financial crisis dummy. The findings shed the light that those factors seem to be stable through time since the occurrence of the world financial crisis together with the political situation in Thailand. These two events could lower the confidence in the Thai economy. Moreover, state coefficients highlight the sluggish rate of machinery replacement and quite low technology of capital goods imported from abroad. The Thai government should apply proactive policies via taxation and specific credit policy to improve technological advancement, for instance. Another interesting evidence is the issue of trade openness which shows the negative transition effect along the sample period. This could be explained by the loss of price competitiveness to imported goods, especially under the widespread implementation of free trade agreement. The Thai government should carefully handle with regulations and the investment incentive policy by focusing on strengthening small and medium enterprises.

Keywords: autoregressive model, economic growth, state space model, Thailand

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Authors: Nizar Caraka Trihanasia, Suparwoko

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The purpose of this paper is to analyze the design model of city gates on arterial roads as Yogyakarta’s “Istimewa” (special) identity. City marketing has become a trend among cities in the past few years. It began to compete with each other in promoting their identity to the world. One of the easiest ways to recognize the identity is by knowing the image of the city which can be seen through architectural buildings or urban elements. The idea is to recognize how the image of the city can represent Yogyakarta’s identity, which is limited to the contribution of the city gates distinctiveness on Yogyakarta urban area. This study has concentrated on the aspect of city gates as built environment that provides a diversity, configuration and scale of development that promotes a sense of place and community. The visual analysis will be conducted to interpreted the existing Yogyakarta city gates (as built environment) focussing on some variables of 1) character and pattern, 2) circulation system establishment, and 3) open space utilisation. Literature review and site survey are also conducted to understand the relationship between the built environment and the sense of place in the community. This study suggests that visually the Yogyakarta city gate model has strong visual characters and pattern by using the concept of a sense of place of Yogyakarta community value.

Keywords: visual analysis, model, Yogyakarta “Istimewa”, citygates

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Authors: Panagiotis T. Kanellos, Vaios T. Karathanos, Andriana C. Kaliora

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Introduction: The role of ghrelin and obestatin in appetite regulation has been investigated. However, data on ghrelin and obestatin changes after food ingestion are negligible. Objective: We aimed at assessing the appetite-regulating hormones, ghrelin, and obestatin, and furthermore calculate ghrelin/obestatin ratio in healthy normal-weight subjects after consumption of raisins. This survey is a comparative study of a glucose control with raisins containing fructose and glucose in similar concentrations as well as fibers. Methodology: Ten apparently healthy subjects who reported no history of glucose intolerance, diabetes, gastrointestinal disorders, or recent use of any antibiotics were enrolled in the study. The raisins used (Vitis vinifera) originate in Greece and are distributed worldwide as Corinthian raisins. In a randomized crossover design, all subjects after an overnight fast consumed, either 50g of glucose diluted in 240 mL of water (control) or 74 g of raisins (sugar content 50 g) with a 5-day interval between individual trials. Vein blood samples were collected at baseline and at 60, 120 and 180 min postprandially. In blood samples ghrelin and obestatin were measured applying specific enzyme linked immuno absorbent assays. Results: The subjects were of mean age 26.3 years, with BMI of 21.6 kg/m2, waist circumference of 77.7 cm, normal serum lipidemic parameters and normal HbA1c levels. Ghrelin levels were significantly lower after raisin consumption compared to glucose at 120 and at 180 min post-ingestion (p= 0.011 and p= 0.035, respectively). However, obestatin did not reach statistical significance between the two interventions. The ghrelin/obestatin ratio was found significantly lower (p=0.020) at 120 min after raisin ingestion compared to control. Conclusion: Two isocaloric foods containing equal amounts of sugars, however with a different composition, have different effects on appetite hormones ghrelin and obestatin in normal-weight healthy subjects.

Keywords: appetite, ghrelin, obestatin, raisins

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Authors: Babak Daneshvar Rouyendegh

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The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.

Keywords: Decision-Makers (DMs), Multi-Criteria Decision-Making (MCDM), Intuitionistic Fuzzy Elimination Et Choix Traduisant La REalite (IFELECTRE), Intuitionistic Fuzzy Numbers (IFN)

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Authors: Ja’afar Umar, Adamu Aliyu Aliero

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Plant growth, biochemical parameters, zinc metal concentrations were determined for Capsicum frutescens L. in response to varied concentration of zinc metal. The plant exhibited a decline in the vegetative parameters measured. Free proline and glycine betaine content increases with increasing concentration of zinc metal and differ significantly (P<0.05). It can be concluded that the osmolyte (pro and GB) accumulations, and high length of stem and wide leaf expansion are possible indicator of tolerance to heavy metals (Zinc) in Capsicum frutescens.

Keywords: zinc metal, osmolyte, Capsicum frutescens, stress

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Authors: Abdelatif Gadoum, Djilali Benyoucef, Mouloudj Hadj, Alla Eddine Toubal Maamar, Mohamed Habib Allah Lahoual

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Hydrogen occurs naturally in the form of chemical compounds, most often in water and hydrocarbons. The main objective of this study is 2D modeling of hydrogen production in inductively coupled plasma in methane at low pressure. In the present model, we include the motions and the collisions of both neutral and charged particles by considering 19 species (i.e in total ; neutrals, radicals, ions, and electrons), and more than 120 reactions (electron impact with methane, neutral-neutral, neutral-ions and surface reactions). The results show that the rate conversion of methane reach 90% and the hydrogen production is about 30%.

Keywords: hydrogen production, inductively coupled plasma, fluid model, methane plasma

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Authors: Mardiati Zain, Yetti Marlida, Elihasridas Elihasridas, Erpomen Erpomen, Andri Andri

Abstract:

Background: Livestock productivity is greatly influenced by the energy and protein balance in diet. This study aimed to determine the energy and protein balance of male Simenthal cattle diet with protein and energy levels. The experimental design used was a randomized block design (RBD) 2x3x3 factorial design. There are two factors namely A level of energy diet that is 65% and 70% TDN. Factor B is a protein level of diet used were 10, 12 and 14% and each treatment is repeated three times. The weight of Simenthal cattle used ranged between 240 - 300 kg. Diet consisted of ammoniated rice straw and concentrated with ratio 40:60. Concentrate consisted of palm kernel cake, rice brain, cassava, mineral, and urea. The variables measured were digestibility of dry matter, organic matter and fiber, dry matter intake, daily gain, feed efficiency and blood characteristic. Results: There was no interaction between protein and energy level of diet on the nutrients intake (DM intake, OM intake, CP intake), weight gain and efficiency (P < 0.01). There was an interaction between protein and energy level of diet on digestibility (DM, OM, CP and allantoin urine (P > 0.01) Nutrients intake decreases with increasing levels of energy and protein diet, while nutrient digestibility, Avarage daily gain and feed efficiency increases with increasing levels of energy and protein diet. Conclusions: The result can be concluded that the best treatment was A2B1 which is energy level 70% TDN and protein 10%, where are dry matter intake 7.66 kg/d, daily gain 1.25 kg/d, feed efficiency 16.12%, and dry matter and organic matter digestibility 64.08 and 69.42% respectively.

Keywords: energy and protein ratio, simenthal cattle, rice straw ammoniated, digestibility

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Authors: J. R. Wang, Y. Chiang, W. S. Hsu, S. H. Chen, J. H. Yang, S. W. Chen, C. Shih, Y. F. Chang, Y. H. Huang, B. R. Shen

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In this research, the RASCAL code was used to simulate and analyze the postulated UF₆ fire accident which may occur in the Institute of Nuclear Energy Research (INER). There are four main steps in this research. In the first step, the UF₆ data of INER were collected. In the second step, the RASCAL analysis methodology and model was established by using these data. Third, this RASCAL model was used to perform the simulation and analysis of the postulated UF₆ fire accident. Three cases were simulated and analyzed in this step. Finally, the analysis results of RASCAL were compared with the hazardous levels of the chemicals. According to the compared results of three cases, Case 3 has the maximum danger in human health.

Keywords: RASCAL, UF₆, safety, hydrogen fluoride

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Authors: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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Authors: Sadiq J. Abou-Loukh

Abstract:

The present work deals with implementation of Petri nets, which own the perfect ability of modeling, are used to establish a fault diagnosis model. Fault diagnosis of a control system received considerable attention in the last decades. The formalism of representing neural networks based on Petri nets has been presented. Neural Petri Net (NPN) reasoning model is investigated and developed for the fault diagnosis process of electric control system. The proposed NPN has the characteristics of easy establishment and high efficiency, and fault status within the system can be described clearly when compared with traditional testing methods. The proposed system is tested and the simulation results are given. The implementation explains the advantages of using NPN method and can be used as a guide for different online applications.

Keywords: petri net, neural petri net, electric control system, fault diagnosis

Procedia PDF Downloads 455