Search results for: random number

Authors: Watchawin Ekphinitphithaya, Patompong Satapornpong

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Introduction: Carbamazepine (CBZ) is one of the most prescribed antiepileptic drugs (AEDs) by neurologists and non-neurologist worldwide. CBZ is usually prescribed along with other drugs, leading to the possibility of severe cutaneous adverse drug reactions (SCARs). The HLA-B*15:02 is strongly associated with CBZ-induced Stevens-Johnson syndrome and toxic epidermal necrolysis (SJS–TEN) in the Han Chinese and other Asian populations but not in European populations, while HLA-A*31:01 allele has been reported to be associated with CBZ-induced SCARs in European population and Japanese. Objective: The aim of this study is to investigate the distribution of pharmacogenetics HLA-A*31:01 marker in a healthy Thai population associated with Carbamazepine-induced SCARs. Materials and Methods: Prospective study, 350 unrelated healthy Thais were recruited in this study. Human leukocyte antigen-A alleles were genotyped using PCR-sequence specific oligonucleotides (PCR-SSOs). Results: The frequency of HLA-A alleles were HLA-A*11:01 (190 alleles, 27.14%), HLA-A*24:02 (82 alleles, 11.71%), HLA-A*02:03 (80 alleles, 11.43%), HLA-A*33:03 (76 alleles, 10.86%), HLA-A*02:07 (58 alleles, 8.29%), HLA-A*02:01 (35 alleles, 5.00%), HLA-A*24:07 (29 alleles, 4.14%), HLA-A*02:06 – HLA-A*30:01 (15 alleles, 2.14%), and HLA-A*01:01 (14 alleles, 2.00%). Particularly, the number of HLA-A*31:01 alleles was 6 of 700 (0.86%) in the healthy Thai population. Many research presented varying distributions of HLA-A*31:01 in Asians, including 2% of Han Chinese, 9% of Japanese and 5% of Koreans. In addition, this allele was found approximately 2-5% in the Caucasian population. Conclusions: Thus, the pharmacogenetics database is vital to support in many populations, especially in Thais, for screening HLA-A*31:01 allele to avoid CBZ-induced SCARs before initiating treatments in each population.

Keywords: Carbamazepine, HLA-A*31:01, Thai population, pharmacogenetics

Procedia PDF Downloads 175

Authors: Rania Khadim, Mohammed Erritali, Abdelhakim Maaden

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Nowadays Wireless Sensor Networks have attracted worldwide research and industrial interest, because they can be applied in various areas. Geographic routing protocols are very suitable to those networks because they use location information when they need to route packets. Obviously, location information is maintained by Location-Based Services provided by network nodes in a distributed way. In this paper we choose to evaluate the performance of two hierarchical rendezvous location based-services, GLS (Grid Location Service) and HLS (Hierarchical Location Service) coupled to the GPSR routing protocol (Greedy Perimeter Stateless Routing) for Wireless Sensor Network. The simulations were performed using NS2 simulator to evaluate the performance and power of the two services in term of location overhead, the request travel time (RTT) and the query Success ratio (QSR). This work presents also a new scalability performance study of both GLS and HLS, specifically, what happens if the number of nodes N increases. The study will focus on three qualitative metrics: The location maintenance cost, the location query cost and the storage cost.

Keywords: location based-services, routing protocols, scalability, wireless sensor networks

Procedia PDF Downloads 378

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Rhadinia Tayag-Relanes, Felina C. Young

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This study was conducted to analyze the noodle production process at Yan Hu Food Manufacturing for the basis of production improvement. The study utilized the PDCA approach and record review in the gathering of data for the calendar year 2019 from August to October data of the noodle products miki, canton, and misua. Causal-comparative research was used in this study; it attempts to establish cause-effect relationships among the variables such as descriptive statistics and correlation, both were used to compute the data gathered. The study found that miki, canton, and misua production has different cycle time sets for each production and has different production outputs in every set of its production process and a different number of wastages. The company has not yet established its allowable rejection rate/ wastage; instead, this paper used a 1% wastage limit. The researcher recommended the following: machines used for each process of the noodle product must be consistently maintained and monitored; an assessment of all the production operators by checking their performance statistically based on the output and the machine performance; a root cause analysis for finding the solution must be conducted; and an improvement on the recording system of the input and output of the production process of noodle product should be established to eliminate the poor recording of data.

Keywords: continuous improvement, process, operations, PDCA

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Authors: Rajan Vohra, Ravinder Singh Sawhney, Kunwar Partap Singh

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Electrical charge transport through two basic strands thymine and adenine of DNA have been investigated and analyzed using the jellium model approach. The FFT-2D computations have been performed for semi-empirical Extended Huckel Theory using atomistic tool kit to contemplate the charge transport metrics like current and conductance. The envisaged data is further evaluated in terms of transmission spectrum, HOMO-LUMO Gap and number of electrons. We have scrutinized the behavior of the devices in the range of -2V to 2V for a step size of 0.2V. We observe that both thymine and adenine can act as molecular devices when sandwiched between two gold probes. A prominent observation is a drop in HLGs of adenine and thymine when working as a device as compared to their intrinsic values and this is comparative more visible in case of adenine. The current in the thymine based device exhibit linear increase with voltage in spite of having low conductance. Further, the broader transmission peaks represent the strong coupling of electrodes to the scattering molecule (thymine). Moreover, the observed current in case of thymine is almost 3-4 times than that of observed for adenine. The NDR effect has been perceived in case of adenine based device for higher bias voltages and can be utilized in various future electronics applications.

Keywords: adenine, DNA, extended Huckel, thymine, transmission spectra

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Authors: Yin-Yann Chen, Jia-Ying Li

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Assembly line balancing problems can be categorized into one-sided, two-sided, and multi-manned ones by using the number of operators deployed at workstations. This study explores the balancing problem of a resource-constrained assembly line with multi-manned workstations. Resources include machines or tools in assembly lines such as jigs, fixtures, and hand tools. A mathematical programming model was developed to carry out decision-making and planning in order to minimize the numbers of workstations, resources, and operators for achieving optimal production efficiency. To improve the solution-finding efficiency, a genetic algorithm (GA) and a simulated annealing algorithm (SA) were designed and developed in this study to be combined with a practical case in car making. Results of the GA/SA and mathematics programming were compared to verify their validity. Finally, analysis and comparison were conducted in terms of the target values, production efficiency, and deployment combinations provided by the algorithms in order for the results of this study to provide references for decision-making on production deployment.

Keywords: heuristic algorithms, line balancing, multi-manned workstation, resource-constrained

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Authors: Deepak Chaudhary

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The main objective of the study is to explore the genesis and achievements of the Madhesh movement. Madhesh Movement is a social movement that brought massive political changes and contributed a lot to the nation-building process in the modern history of Nepal. This movement erupted in January 2007 in the Tarai/Madhesh region following the promulgation of the Interim Constitution that left the incorporation of federalism and proportional representation in the Constitution. The most excluded community in Nepal- Madheshi community, seemed to have angered against state-sponsored discrimination and exclusion that have been occurred for centuries. Since Madheshis were treated as non-Nepali, though the history of Nepal’s Tarai/Madhesh has been ancient. In the beginning, this movement was against Maoist, but later, it went against the state's prejudices and discriminations. It extended across the Tarai/Madhesh region of Nepal for a month. The movement was spontaneous to a large extent. A researcher himself is a witness to the movement. Key Informant Interviews with participants, including politicians, journalists, and activists, have mainly carried out for the study. This movement ensured Madheshi identity first. Secondly, the number of electoral constituencies was increased as it reached 120 in Tarai/Madhesh while it was 80 only. As a result, Madheshi representation in the Constitution Assembly reached 35 %, while it was 20% only. The main thing that this movement played a major role in ensuring the federalism as a political system in Nepal.

Keywords: dignity, exclusion, federalism, inclusion, Madhesh movement, nation-building

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Authors: S. Taghvamanesh

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Modern landfills are highly engineered containment systems that are designed to reduce the environmental and human health impacts of solid waste (trash). In modern landfills, waste is contained by a liner system. The primary goal of the liner system is to isolate the landfill contents from the environment, thereby protecting the soil and groundwater from pollution caused by the leachate of a landfill. Landfill leachate is the most serious threat to groundwater. Therefore, it is necessary to design a system that prevents the penetration of this dangerous substance into the environment. These layers are made up of two basic elements: clay and geosynthetics. Hydraulic conductivity and flexibility are two desirable properties of these materials. There are three different types of liner systems that will be discussed in this paper. According to available data, the current article analyzed materials and methods for constructing liner layers made of distinct leachates, including various harmful components and heavy metals from all around the world. Also, this study attempted to gather data on leachates for each of the sites discussed. In conclusion, every landfill requires a specific type of liner, which depends on the type of leachate that it produces daily. It should also be emphasized that, based on available data, this article focused on the number of landfills that each country or continent possesses.

Keywords: landfill, liner layer, impervious layer, barrier layer

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Authors: Dima Basma

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The unprecedented expansion in the use of Non-Fungible Tokens (NFTS) has prompted luxury brand owners to file their trademark applications for the use of their marks in the metaverse world. While NFTs provide a favorable tool for product traceability and anti-counterfeiting endeavors, the legal ramifications of such abrupt shift are complex, diverse, and yet to be understood. Practically, a sizable number of NFT creators are minting digital tokens associated with existing trademarks, selling them at strikingly high rates, thus disadvantaging trademark owners who joined and are yet to join the meta-verse world. As a result, multiple luxury brands are filing confusion and dilution lawsuits against alleged artists offering for sale NFTs depicting reputable marks labeling their use as “parody” and “social commentary.” Given the already muddled state of trademark law in relation to both traditional and modern infringement criteria, this paper aims to explore the feasibility of the current system in dealing with the emerging NFT trends. The paper firstly delves into the intersection between trademarks and NFTs. Furthermore, in light of the striking increase in NFT use, the paper sheds critical light on the shortcoming of the current system. Finally, the paper provides recommendations for overcoming current and prospective challenges in this area.

Keywords: trademarks, NFTs, dilution, social commentary

Procedia PDF Downloads 121

Authors: Pallabi Kalita, Hui Tag, Loxmi Jamoh, H. N. Sarma, A. K. Das

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Wild edible food plants contain a number of organic phytochemical that have been linked to the promotion of good health. These plants used by the local people of Arunachal Pradesh (Northeast India) are found to have high nutritional potential to maintain general balance diet. A study was conducted to evaluate the nutritional potential of five commonly found, unexplored wild food plants namely, Piper pedicellatum C. DC (leaves), Gonostegia hirta (Blume ex Hassk.) Miq. (leaves), Mussaenda roxburghii Hook. f. (leaves), Solanum spirale Roxb. (leaves and fruits) and Cyathea spinulosa Wall. ex Hook. (pith portion and tender rachis) from East Siang District of Arunachal Pradesh Northeast (India) for ascertaining their suitability for utilization as supplementary food. Results of study revealed that P. pedicellatum, C. spinulosa, and S. spirale (leaves) are the most promising species which have high nutritional content out of the five wild food plants investigated which is required for the normal growth and development of human.

Keywords: wild edible plants, gross energy, Gonostegia hirta, Cyathea spinulosa

Procedia PDF Downloads 337

Authors: Mochammad Indra Permana, Andhiani Sharfina Arnellya, Dika Pramita Destiani, Budhi Prihartanto

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Cardiovascular disease is the cause of the highest mortality rates in the world. The number of cardiovascular disease patients is increasing every year. Data obtained from World Health Organization (WHO) that 17,5 million people died from this disease. The condition of cardiovascular diseases such as atrial fibrillation, myocardial infarction, venous thromboembolism, and several other conditions need anticoagulant therapy. Results of the anticoagulant therapy are measured not only by the effectiveness of International Normalized Ratio (INR) value but also by the quality of life of the patients. The purpose of this study was to determine the quality of life of patients on oral anticoagulant therapy in outpatient cardiac department Dr. Hasan Sadikin central general hospital, Bandung, Indonesia. This is a cross-sectional study with collecting data from the quality of life questionnaire and medical record of the patients. The results of this study showed that 28 patients (46,7%) had a good quality of life, 30 patients (50%) had a moderate quality of life, and 2 patients (3,3%) had a poor quality of life with no significant differences in quality of life based on age, gender, diagnosis, and duration of drug use.

Keywords: anticoagulant, cardiovascular diseases, INR, quality of life

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Authors: Daniela Istrati, Alina Morosan, Maria Stanca, Bogdan Purcareanu, Adrian Fudulu, Laura Olariu, Alice Buteica, Ion Mindrila, Rodica Cristescu, Dan Eduard Mihaiescu

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Our present work is related to the synthesis, characterization and applications of new nanocomposite materials based on silica mesoporous nanocompozites systems. The nanocomposite support was obtained by using a specific step–by–step multilayer structure buildup synthetic route, characterized by XRD (X-Ray Difraction), TEM (Transmission Electron Microscopy), FT-IR (Fourier Transform-Infra Red Spectrometry), BET (Brunauer–Emmett–Teller method) and loaded with Salvia officinalis plant extract obtained by a hydro-alcoholic extraction route. The sustained release of the target compounds was studied by a modified LC method, proving low release profiles, as expected for the high specific surface area support. The obtained results were further correlated with the in vitro / in vivo behavior of the nanocomposite material and recommending the silica mesoporous nanocomposites as good candidates for biomedical applications. Acknowledgements: This study has been funded by the Research Project PN-III-P2-2.1-PTE-2016-0160, 49-PTE / 2016 (PROZECHIMED) and Project Number PN-III-P4-ID-PCE-2016-0884 / 2017.

Keywords: biomedical, mesoporous, nanocomposites, natural products, sustained release

Procedia PDF Downloads 222

Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag

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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.

Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling

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Authors: Mustafa Tufekci, Caner Guven

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In Automotive Industry, sliding door systems that are also used as body closures, are safety members. Extreme product tests are realized to prevent failures in a design process, but these tests realized experimentally result in high costs. Finite element analysis is an effective tool used for the design process. These analyses are used before production of a prototype for validation of design according to customer requirement. In result of this, the substantial amount of time and cost is saved. Finite element model is created for geometries that are designed in 3D CAD programs. Different element types as bar, shell and solid, can be used for creating mesh model. The cheaper model can be created by the selection of element type, but combination of element type that was used in model, number and geometry of element and degrees of freedom affects the analysis result. Sliding door system is a good example which used these methods for this study. Structural analysis was realized for sliding door mechanism by using FE models. As well, physical tests that have same boundary conditions with FE models were realized. Comparison study for these element types, were done regarding test and analyses results then the optimum combination was achieved.

Keywords: finite element analysis, sliding door mechanism, element type, structural analysis

Procedia PDF Downloads 332

Authors: Khairy M. A. Zoheir

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One of the most severe complications of Rheumatoid arthritis is delayed recovery. lipoic acid possesses antioxidant, hypoglycemic, and anti-inflammatory activity. In the present study, the effects of lipoic acid was investigated on the key mediators of Rheumatoid arthritis, namely, CD4+CD25+ T cell subsets, GITR expressing cells, CD4+CD25+Foxp3+ regulatory T (Treg) cells, T-helper-17 (Th17) cells, and pro-inflammatory cytokines Interleukin-1β (IL-1β), Interleukin-6 (IL-6) and Tumor Necrosis Factor- α (TNF-α)] through flow-cytometry and qPCR analyses. Lipoic acid treated mice showed a significant decrease in the Rheumatoid arthritis, the frequency of GITR-expressing cells, and Th1 cytokines (IL-17A, TNF-αand Interferon- γ (IFN-γ) compared with positive and negative controlled mice. Lipoic acid treatment also down regulated the mRNA expression of the inflammatory mediators compared with the Rheumatoid arthritis mouse model and untreated mice. The number of Tregs also found to be significantly upregulated in lipoic acid treated mice. Our results were confirmed by the histopathological examination. This study showed the beneficial role of lipoic acid in promoting a well-balanced tool for therapy Rheumatoid arthritis.

Keywords: lipoic acid, chemokines, inflammatory, rheumatoid arthritis

Procedia PDF Downloads 178

Authors: Melese Tadesse Morebo

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Pastoral and agro-pastoral communities in East Africa, particularly in Ethiopia, are vulnerable to climate-related risks. The aim of this study is to characterize the annual, seasonal, and monthly rainfall and temperature of the middle and lower awash areas of Ethiopia. Start of season (SOS), end of season (EOS), length of growing season (LGS), number of rainy days, and probability of dry spell occurrences were analyzed using INSTAT Plus (v3.7) software. Daily rainfall and temperature data for 33 years (1990–2022) from six stations were analyzed. The result of the study revealed that the annual rainfall in the study area as a whole showed an increasing trend, but its trend was statistically non-significant. During the study period, the Kiremt rainfall at Amibara station showed statistically significant increasing trends. The trend analysis of SOS, EOS, and LGS shows up and down trends at all stations. The mean lengths of growing seasons in the study area ranged from 20 to 61 days during the study period. In the study area, the annual mean maximum temperature ranged between 34.1°C and 38.3°C over the last three decades. All stations within the research area during the study period, the annual minimum temperature exhibited a substantial impact.

Keywords: annual rainfall, LGS, minimum temperature, Mann-Kendall test

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Authors: Stefan Wagenpfeil, Felix Engel, Paul McKevitt, Matthias Hemmje

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Multimedia Indexing and Retrieval is generally designed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, especially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelization. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information.

Keywords: indexing, retrieval, multimedia, graph algorithm, graph code

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Authors: N. Khater, S. A. Menina, H. Benbouza

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Juniperus thurefera is an endemic cupressacée constitutes a forest cover in the mountains of Aures (Algeria). It is a heritage and important ecological richness but continues to decline, highly endangered species in danger of extinction, these populations show significant originality due to climatic conditions of the environment, because of its strength and extraordinary vitality, made a powerful but fragile and unique ecosystem in which natural regeneration by seed is almost absent in Algeria. Because of the quality of seeds that are either dormant or affected at the tree and the ground level by a large number of pests and parasites, which will lead to the total disappearance of this species and consequently leading to the biodiversity. View the ecological and socio- economic interest presented by this case, it deserves to be preserved and produced in large quantities in this respect. The present work aims to try to regenerate the Juniperus thurefera via vegetative propagation. We studied the potential of cuttings to form adventitious roots and buds. Cuttings were taken from young subjects from 5 to 20 years treated with indole butyric acid (AIB) and planted out-inside perlite under atomizer whose temperature and light are controlled. Results indicated that the percentage of developing buds on cuttings is better than the rooting ones.

Keywords: Juniperus thurefera, indole butyric acid, cutting, buds, rooting

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Authors: Amir Zand-Moghadam, Mahnaz Alizadeh

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The aim of the present study was to investigate the effect of teacher-scaffolding versus peer-scaffolding on EFL learners’ metapragmatic awareness in the paradigm of task-based language teaching (TBLT). To this end, a number of dialogic information-gap tasks requiring two-way interactant relationship were designed for the five speech acts of request, refusal, apology, suggestion, and compliment following Ellis’s (2003) model. Then, 48 intermediate EFL learners were randomly selected, homogenized, and assigned to two groups: 26 participants in the teacher-scaffolding group (Group One) and 22 in the peer-scaffolding group (Group Two). While going through the three phases of pre-task, while-task, and post-task, the participants in the first group completed the designed tasks by the teacher’s interaction, scaffolding, and feedback. On the other hand, the participants in the second group were required to complete the tasks in expert-novice pairs through peer scaffolding in all the three phases of a task-based syllabus. The findings revealed that the participants in the teacher-scaffolding group developed their L2 metapragmatic awareness more than the peer-scaffolding group. Thus, it can be concluded that teacher-scaffolding is more effective than peer scaffolding in developing metapragmatic awareness among EFL learners. It can also be claimed that the use of tasks can be more influential when they are accompanied by teacher-scaffolding. The findings of the present study have implications for language teachers and researchers.

Keywords: ILP, metapragmatic awareness, scaffolding, task-based instruction

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Authors: Pinzhe Zhao

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This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

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Authors: Shweda Mohan, J. L. Nandagopal, S. Amritha

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This paper focuses on the dynamic modelling of unicycle robot. Two main concepts used for balancing unicycle robot are: reaction wheel pendulum and inverted pendulum. The pitch axis is modelled as inverted pendulum and roll axis is modelled as reaction wheel pendulum. The unicycle yaw dynamics is not considered which makes the derivation of dynamics relatively simple. For the roll controller, sliding-mode controller has been adopted and optimal methods are used to minimize switching-function chattering. For pitch controller, an LQR controller has been implemented to drive the unicycle robot to follow the desired velocity trajectory. The pitching and rolling balance could be achieved by two DC motors. Unicycle robot is a non-holonomic, non-linear, static unbalance system that has the minimal number of point contact to the ground, therefore, it is a perfect platform for researchers to study motion and balance control. These real-time solutions will be a viable solution for advanced robotic systems and controls.

Keywords: decoupled dynamics, linear quadratic regulator (LQR) control, Lyapunov function sliding mode control, unicycle robot, velocity and trajectory control

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Authors: Selena Gutiérrez, Araceli Martínez

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One of the most important challenges worldwide, scientific and technological, is to have a sustainable energy source; friendly to the environment and widely available. Currently, the 85% of the energy used comes from the fossil sources. Another important environmental problem is that several rubber products (tires, gloves, hoses, among others) are discarded practically without any treatment. In nature, the degradation of such products will take at least 500 years. In 2009, the worldwide rubber production was about 23.6 million tons. In order to solve this problems, our research focus in an alternative synthesis of biofuels in a two-step approach: The metathesis degradation of industrial rubber (models of rubber waste), and the oligomers transesterification. Thus, cis-1,4-polybutadiene (Mn= 9.1x105, Mw/Mn= 2.2) and styrene-butadiene block copolymers with 30% (Mn= 1.61x105; Mw/Mn= 1.3) and 21% wt styrene (Mn= 1.92x105; Mw/Mn= 1.4) were degraded via metathesis with soybean oil as chain transfer agent (CTA) and green solvent; using [(PCy3)2Cl2Ru=CHPh] and [(1,3-diphenyl-4,5-dihydroimidazol-2-ylidene)(PCy3)Ru=CHPh] catalysts. Afterwards, the products were transesterified by basic homogeneous catalysis. Before transesterification, the polystyrene microblocks (Mn= 16,761; Mw/Mn= 1.2) were isolated. Finally, the biofuels obtained (BO) were purified, characterized and showed similar properties to standards biodiesel (SB) (Norms: EN 14214-03 and ASTM D6751-02), i.e. (SB / BO): molecular weight [Daltons] (570 / 543-596), density [g/cm3] (0.86-0.90 / 0.88), kinematic viscosity [mm2/s] (1.90-6.0 / 3.5-4.5), iodine (97 / 97-98) and cetane number (Min.47 / 56-58).

Keywords: biofuels, industrial rubber, metathesis, vegetable oils

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: N. Coskun

Abstract:

Australia has received over 840,000 refugees since its establishment as a federation. Despite the long history of refugee intake, Australia appears to have prolonged problems in refugee education such as academic and social isolations of refugee background students (RBS), the discriminations towards RBS and the high number of RBS drop-outs. This paper examines the place of RBS in educational policies, which can help to identify the problems and set a foundation for solutions. This paper investigates the educational provisions for RBS in three stages. First, the paper identifies the needs of RBS through a comprehensive literature review, using the framework of Bronfenbrenner’s bio-ecological model. Second, the study explores the place of these needs in Australian national and state educational policies which are informed by multiculturalism. The findings conclude that social, academic and psychological needs of RBS hardly find a place in multicultural educational policies. The students and their specific needs are mostly invisible and are placed under a general category of newly arrived immigrants who learn English as a second language. Third, the study explores the possible reasons for the overlook on RBS and their needs with examining the general socio-political context surrounding refugees in Australia. The overall findings suggest that Australian multiculturalism policy in education are inadequate to address RBS' social, academic and psychological needs due to the disadvantaging socio-political context where refugees are placed.

Keywords: Australia, bio-ecological model, multiculturalism, refugee education

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Authors: Dalia Suša Vugec, Ana-Marija Stjepić, Darija Ivandić Vidović

Abstract:

Digital transformation is one of the latest trends on the global market. In order to maintain the competitive advantage and sustainability, increasing number of organizations are conducting digital transformation processes. Those organizations are changing their business processes and creating new business models with the help of digital technologies. In that sense, one should also observe the role of business process management (BPM) and its maturity in driving digital transformation. Therefore, the goal of this paper is to investigate the role of BPM in digital transformation process within one organization. Since experiences from practice show that organizations from financial sector could be observed as leaders in digital transformation, an insurance company has been selected to participate in the study. That company has been selected due to the high level of its BPM maturity and the fact that it has previously been through a digital transformation process. In order to fulfill the goals of the paper, several interviews, as well as questionnaires, have been conducted within the selected company. The results are presented in a form of a case study. Results indicate that digital transformation process within the observed company has been successful, with special focus on the development of digital strategy, BPM and change management. The role of BPM in the digital transformation of the observed company is further discussed in the paper.

Keywords: business process management, case study, Croatia, digital transformation, insurance company

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Authors: Shi-Yu Xu

Abstract:

The top three risk factors that have contributed to building collapses during past earthquake events in Taiwan are: "irregular floor plans or elevations," "insufficient columns in single-bay buildings," and the "weak-story problem." Fortunately, these unsound structural characteristics can be directly identified from the floor plans. However, due to the vast number of old buildings, conducting manual inspections to identify these compromised structural features in all existing structures would be time-consuming and prone to human errors. This study aims to develop an algorithm that utilizes artificial intelligence techniques to automatically pinpoint the structural components within a building's floor plans. The obtained spatial information will be utilized to construct a digital structural model of the building. This information, particularly regarding the distribution of columns in the floor plan, can then be used to conduct preliminary seismic assessments of the building. The study employs various image processing and pattern recognition techniques to enhance detection efficiency and accuracy. The study enables a large-scale evaluation of structural vulnerability for numerous old buildings, providing ample time to arrange for structural retrofitting in those buildings that are at risk of significant damage or collapse during earthquakes.

Keywords: structural vulnerability detection, object recognition, seismic capacity assessment, old buildings, artificial intelligence

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

Abstract:

By improving efficiency and production, information technology (IT) has transformed working environments, but it has also created new threats to occupational safety and health (OSH). This study evaluates the literature that has already been written on the subject of IT and OSH, identifies major findings and discussion points, and highlights gaps in the material that call for additional research. The study's findings, which look at how IT affects OSH in a sizable multinational organization, are also presented in the report. According to the report, IT poses a number of OSH problems, such as ergonomic dangers, eye strain, dangers related to cybersecurity, and psychological hazards. The report suggests using tactics like providing comfortable workstations, encouraging a healthy balance between work and life, and putting strong cybersecurity safeguards in place to reduce these dangers. The implications of these findings for OSH and IT are discussed in the paper's conclusion, and it emphasizes the need for more study and action to address these dangers and promote healthy and secure working environments in the age of digitization.

Keywords: information technology, occupational safety and health (OSH), ergonomic, hazards, workplace.

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Authors: Ashraf Aly

Abstract:

The aim of this study is to examine the impact of 5G communication technology radiation on human health and airport safety. The term 5G refers to the fifth generation of wireless mobile technology. The 5G wireless technology will increase the number of high-frequency-powered base stations and other devices and browsing and download speeds, as well as improve the network connectivity and play a big part in improving the performance of integrated applications, such as self-driving cars, medical devices, and robotics. 4G was the latest embedded version of mobile networking technology called 4G, and 5G is the new version of wireless technology. 5G networks have more features than 4G networks, such as lower latency, higher capacity, and increased bandwidth compared to 4G. 5G network improvements over 4G will have big impacts on how people live, business, and work all over the world. But neither 4G nor 5G have been tested for safety and show harmful effects from this wireless radiation. This paper presents biological factors on the effects of 5G radiation on human health. 5G services use C-band radio frequencies; these frequencies are close to those used by radio altimeters, which represent important equipment for airport and aircraft safety. The aviation industry, telecommunications companies, and their regulators have been discussing and weighing these interference concerns for years.

Keywords: wireless communication, radiofrequency, Electromagnetic field, environmental issues

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Authors: Audu Aly Fada, Adejoh Apeh Matthew

Abstract:

This research assesses the effects of social conflicts on tourism products in Plateau State. It was specifically set out to find out the major causes of social conflicts in Jos, evaluate the effects of social conflicts on the influx of tourists to Hill station hotel Jos, and the impact on revenue generation of the hotel. To achieve these objectives research questions were formulated and a sample of 30 hotel staff was selected as the respondents. Data collected were organized and analyzed using tables, percentages and mean statistics. It was found that the hospitality and tourism industry was adversely affected. The crisis brought about a decline in the number of tourist arrivals, increase in cancelled bookings, a decrease in the average length of stay of tourists and the average room occupancy. Peace is the best friend of travel and tourism, while war and insecurity are among its worst enemies. It is recommended that all stakeholders involved in tourism administration should device safer environment that supports continued patronage by providing modern security apparatus. In the same spirit, government as the main stake-holder in security provision should do more than paying lip service to guarantee security and safety of lives and properties.

Keywords: social conflict, crisis, security, tourism development

Procedia PDF Downloads 404

Authors: Youru Zhou

Abstract:

This paper seeks to unveil the quality assurance practices in the Chinese translation industry. Since China’s reform and opening up, the Chinese language service industry has enjoyed impressively rapid growth. However, while still in its early stage of professionalization, the Chinese translation industry is also facing many challenges, such as the lack of clear admission requirements, a powerful regulation authority and a great number of qualified professionals. ‘How quality is assured’ means a great deal to translation in China at this stage. In order to examine the mechanisms in which quality is assured, this paper studied four international and national standards that have gained widespread adoption by Chinese translation companies and examined the content that is relevant to translation quality assurance. Case studies with six selected Chinese translation companies of different sizes were conducted to confirm and exemplify the descriptions on the standards. It has been found that quality in the industry is a relative concept which is mainly determined by the demand of clients. Furthermore, the procedures of translation can vary from task to task dependent on the agreement made between the service provider and clients. Finally, there are companies relying on expert-oriented mechanisms to assure the quality of translation, while other companies and standards insist on process-oriented ones.

Keywords: case study, Chinese translation industry, professional practice, translation quality assurance, translation standards

Procedia PDF Downloads 151