Search results for: mixed effects models

Authors: Paula A. Cruise, Carvell McLeary

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Employee turnover leads to lowered productivity, decreased morale and work quality, and psychological effects associated with employee separation and replacement. Yet, it remains unknown why talented employees willingly withdraw from organizations. This uncertainty is worsened as studies; a) priorities organizational over individual predictors resulting in restriction in range in turnover measurement; b) focus on actual rather than intended turnover thereby limiting conceptual understanding of the turnover construct and its relationship with other variables and; c) produce inconsistent findings across cultures, contexts and industries despite a clear need for a unified perspective. The current study addressed these gaps by adopting the theory of planned behavior (TPB) framework to examine socio-cognitive factors in organizational trust and individual turnover intentions among bankers and energy employees in Jamaica. In a comparative study of n=369 [n_bank= 264; male=57 (22.73%); n_energy =105; male =45 (42.86)], it was hypothesized that organizational trust was a predictor of employee turnover intention, and the effect of individual, group, cognitive and socio-affective variables varied across industry. Findings from structural equation modelling confirmed the hypothesis, with a model of both cognitive and socio-affective variables being a better fit [CMIN (χ²) = 800.067, df = 364, p ≤ .000; CFI = 0.950; RMSEA = 0.057 with 90% C.I. (0.052 - 0.062); PCLOSE = 0.016; PNFI = 0.818 in predicting turnover intention. The findings are discussed in relation to socio-cognitive components of trust models and predicting negative employee behaviors across cultures and industries.

Keywords: context-specific organizational trust, cross-cultural psychology, theory of planned behavior, employee turnover intention

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Authors: Mohammed Salahat, Steve Wade

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This paper presents and compares the SSDDD “Systematic Soft Domain Driven Design Framework” to DDD “Domain Driven Design Framework” as a soft system approach of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework has been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, a comparison between SSDDD and DDD is presented in this paper, to show how SSDDD improved DDD as an approach to modelling and implementing business domain perspectives for Information Systems Development. The comparison process, the results, and the improvements are presented in the following sections of this paper.

Keywords: domain-driven design, soft domain-driven design, naked objects, soft language

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Authors: Hossein Motaghedi, Kaveh Arkani, Siavash Salamatpoor

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Usually the piles are important tools for safety and economical design of high and heavy structures. For this aim the response of single pile under dynamic load is so effective. Also, the agents which have influence on single pile response are properties of pile geometrical, soil and subjected loads. In this study the finite difference numerical method and by using FLAC 3D software is used for evaluation of single pile behavior under peak ground acceleration (PGA) of El Centro earthquake record in California (1940). The results of this models compared by experimental results of other researchers and it will be seen that the results of this models are approximately coincide by experimental data's. For example the maximum moment and displacement in top of the pile is corresponding to the other experimental results of pervious researchers. Furthermore, in this paper is tried to evaluate the effective properties between soil and pile. The results is shown that by increasing the pile diagonal, the pile top displacement will be decreased. As well as, by increasing the length of pile, the top displacement will be increased. Also, by increasing the stiffness ratio of pile to soil, the produced moment in pile body will be increased and the taller piles have more interaction by soils and have high inertia. So, these results can help directly to optimization design of pile dimensions.

Keywords: pile seismic response, interaction between soil and pile, numerical analysis, FLAC 3D

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Authors: A. A. M. A. S. S. Perera, L. A. Ranasinghe, T. K. H. Nimeshika, D. M. Dhanushka Dissanayake, Namalie Walgampaya

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Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speed up the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensive computer vision and image processing scheme is used to process the image for the disease identification. This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more. This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.

Keywords: Circularity Index, Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix, Local Binary Pattern, Object detection, Ring Detection, Shape Identification

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Authors: Karthika Durairaj, Buvaneswari G., Gowdham M., Gilles M., Velmurugan G.

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Background: Hyperglycaemia is the primary cause of metabolic illness. Recently, researchers focused on the possibility that chemical exposure could promote metabolic disease. Hyperglycaemia causes a variety of metabolic diseases dependent on its etiologic conditions. According to animal and population-based research, individual chemical exposure causes health problems through alteration of endocrine function with the influence of microbial influence. We were intrigued by the function of gut microbiota variation in high fat and chemically induced hyperglycaemia. Methodology: C57/Bl6 mice were subjected to two different treatments to generate the etiologic-based diabetes model: I – a high-fat diet with a 45 kcal diet, and II - endocrine disrupting chemicals (EDCs) cocktail. The mice were monitored periodically for changes in body weight and fasting glucose. After 120 days of the experiment, blood anthropometry, faecal metagenomics and metabolomics were performed and analyzed through statistical analysis using one-way ANOVA and student’s t-test. Results: After 120 days of exposure, we found hyperglycaemic changes in both experimental models. The treatment groups also differed in terms of plasma lipid levels, creatinine, and hepatic markers. To determine the influence on glucose metabolism, microbial profiling and metabolite levels were significantly different between groups. The gene expression studies associated with glucose metabolism vary between hosts and their treatments. Conclusion: This research will result in the identification of biomarkers and molecular targets for better diabetes control and treatment.

Keywords: hyperglycaemia, endocrine-disrupting chemicals, gut microbiota, host metabolism

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Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

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The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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Authors: Renato André S. Silva, Nana L. F. Sampaio, Carlos J. G. Cruz, Bruno Vianna, Flávio O. Pires

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multiple stage bicycle races require high physiological loads from professional cyclists. Such demands can lead to immunosuppression and health problems. However, in this type of competition, little is known about its physiological effects on amateur athletes, who generally receive less medical support. Thus, this study analyzes the hematological effects of a multiple stage bicycle race on amateur cyclists. Seven Brazilian national amateur cyclists (34 ± 4.21 years) underwent a laboratory test to evaluate VO2Max (69.89 ± 7.43 ml⋅kg-1⋅min-1). Six days later, these volunteers raced in the Tour of Goiás, participating in five races in four days (435 km) of competition. Arterial blood samples were collected one day before and one day after the competition. The Kolmogorov-Smirnov tests were used to evaluate the data distribution and Wilcoxon to compare the two moments (p <0.05) of data collection. The results show: Red cells ↓ 7.8% (5.1 ± 0.28 vs 4.7 ± 0.37 106 / mm 3, p = 0.01); Hemoglobin ↓ 7.9% (15.1 ± 0.31 vs 13.9 ± 0.27 g / dL, p = 0.01); Leukocytes ↑ 9.5% (4946 ± 553 versus 5416 ± 1075 / mm 3, p = 0.17); Platelets ↓ 7.0% (200.2 ± 51.5 vs 186.1 ± 39.5 / mm 3, p = 0.01); LDH ↑ 11% (164.4 ± 28.5 vs 182.5 ± 20.5 U / L, p = 0.17); CK ↑ 13.5% (290.7 ± 206.1 vs 330.1 ± 90.5 U / L, p = 0.39); CK-MB ↑ 2% (15.7 ± 3.9 vs. 20.1 ± 2.9 U / L, p = 0.06); Cortizol ↓ 13.5% (12.1 ± 2.4 vs 9.9 ± 1.9 μg / dL, p = 0.01); Total testosterone ↓ 7% (453.6 ± 120.1 vs 421.7 ± 74.3 ng / dL, p = 0.12); IGF-1 ↓ 15.1% (213.8 ± 18.8 vs 181.5 ± 34.7 ng / mL, p = 0.04). This means that there was significant reductions in O2 allocation / transport capacities, vascular injury disruption, and a fortuitous reduction of muscle skeletal anabolism along with maintenance and / or slight elevation of immune function, glucose and lipid energy and myocardial damage. Therefore, the results suggest that no abnormal health effect was identified among the athletes after participating in the Tour de Goiás.

Keywords: cycling, health effects, cycling stages races, haematology

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Authors: Lali Kalanadzde

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We investigated magneto-optical Kerr effect in transparent region of implanted ferrite-garnet films for the (YBiCa)3(FeGe)5O12. The implantation process was carried out at room temperature by Ne+ ions with energy of 100 KeV and with various doses (0.5-2.5) 1014 ion/cm². We discovered that slight deviation of the plane of external alternating magnetic field from plane of sample leads to appearance intensive magneto-optical maximum in transparent region of garnet films ħω=0.5-2.0 eV. In the proceeding, we have also found that the deviation of polarization plane from P- component of incident light leads to the appearance of the similar magneto-optical effects in this region. The research of magnetization processes in transparent region of garnet films showed that the formation of magneto-optical effects in region ħω⁼0.5-2.3 eV has a rather complex character.

Keywords: ferrite-garnet films, ion implantation, magneto-optical, thin films

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

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Authors: Fang-Bo Yu, Li-Bo Guan, Sheng-Dao Shan

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Biogas slurry was mixed with six commercial fungicides and screening against 11 phytopathogens was carried out. Results showed that inhibition of biogas slurry was different for the test strains and no significant difference between treatments of Didymella bryoniae, Fusarium oxysporum f. sp. vasinfectum, Aspergillus niger, Rhizoctonia cerealis, F. graminearum and Septoria tritici was observed. However, significant differences were found among Penicillium sp., Botrytis cinerea, Alternaria sonali, F. oxysporum F. sp. melonis and Sclerotinia sclerotiorum. The approach described here presents a promising alternative to current manipulation although some issues still need further examination. This study could contribute to the development of sustainable agriculture and better utilization of biogas slurry.

Keywords: anaerobic digestion, biogas slurry, phytopathogen, sustainable agriculture

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Authors: Wallapa Boonrod

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Thai National Education Act 1999 required all educational institutions received external quality evaluation at least once every five years. The purpose of this study was to compare the awareness in the code of ethics for nurse educators among nurse educators, professional nurses, and nursing students under The Royal Thai Army Nurse College. The sample consisted of 51 of nurse educators 200 nursing students and 340 professional nurses from Army nursing college and hospital by stratified random sampling techniques. The descriptive statistics indicated that the nurse educators, nursing students and professional nurses had different levels of awareness in the 9 roles of nurse educators: Nurse, Reliable Sacrifice, Intelligence, Giver, Nursing Skills, Teaching Responsibility, Unbiased Care, Tie to Organization, and Role Model. The code of ethics for nurse educators (CENE) measurement models from the awareness of nurse educators, professional nurses, and nursing students were well fitted with the empirical data. The CENE models from them were invariant in forms, but variant in factor loadings. Thai Army nurse educators strive to create a learning environment that nurtures the highest nursing potential and standards in their nursing students.

Keywords: awareness of the code of ethics for nurse educators, nursing college and hospital under The Royal Thai Army, Thai Army nurse educators, professional nurses

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Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

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The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

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Authors: Sekkal Nawel, Mahammed Nadir

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The proliferation of online activities on Online Social Networks (OSNs) has captured significant user attention. However, this growth has been hindered by the emergence of fraudulent accounts that do not represent real individuals and violate privacy regulations within social network communities. Consequently, it is imperative to identify and remove these profiles to enhance the security of OSN users. In recent years, researchers have turned to machine learning (ML) to develop strategies and methods to tackle this issue. Numerous studies have been conducted in this field to compare various ML-based techniques. However, the existing literature still lacks a comprehensive examination, especially considering different OSN platforms. Additionally, the utilization of bio-inspired algorithms has been largely overlooked. Our study conducts an extensive comparison analysis of various fake profile detection techniques in online social networks. The results of our study indicate that supervised models, along with other machine learning techniques, as well as unsupervised models, are effective for detecting false profiles in social media. To achieve optimal results, we have incorporated six bio-inspired algorithms to enhance the performance of fake profile identification results.

Keywords: machine learning, bio-inspired algorithm, detection, fake profile, system, social network

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Authors: Tanakrit Doltanakarn

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Introduction: These days, cannabis is being accepted in many countries due to the fact that cannabis could be use in medical. The medical cannabis is used to treat and reduce the pain many diseases. For example, neuropathic pain, Parkinson, autism disorders, cancer pain reduce the adverse effect of chemotherapy, diabetes, and migraine. Active ingredients in cannabis that modulate patients' perceptions of their conditions include Δ9‐tetrahydrocannabinol (THC), cannabidiol (CBD), flavonoids, and terpenes. However, there is an adverse effect of cannabis, cardiovascular effects, psychosis, schizophrenia, mood disorder, and cognitive alternation. These effects are from the THC and CBD ingredients in the cannabis. The metabolize processes of delta-9 THC to 11-OH-delta 9 -THC (inactive form), THC were cause of adverse effects. Interestingly, the distributions of CYP2C9 gene (CYP2C9*2 and CYP2C9*3, poor metabolizer) that might affect incidences of adverse effects in patients who treated with medical cannabis. Objective: The aim of this study we want to investigate the association between genetic polymorphism of CYP2C9 frequency and Thai patients who treated with medical cannabis. Materials and Methods:We recruited sixty-five unrelated Thai patients from the College of Pharmacy, Rangsit University. DNA were extracted using Genomic DNA Mini Kit. Genotyping of CYP2C9*2 (430C>T, rs1799853) and CYP2C9*3 (1075A>C, rs1057910) were genotyped by the TaqMan Real-time PCR assay. Results: Among these 31 medicals cannabis-induced ADRs patients, they were diagnosed with 22 (33.85%) tachycardia and 3 (4.62%) arrhythmia. There were 34 (52.31%) medical cannabis-tolerant controls who were included in this study.40 (61.53%) Thai patients were female, and 25 (38.46%) were male, with median age of 57 (range 27 – 87) years. In this study, we found none of the medical cannabis-induced ADRs carried CYP2C9*2 variant along with medical cannabis-tolerant control group. CYP2C9*3 variant (intermediate metabolizer, IM) was found just only one of thirty-one (3.23%) in the medical cannabis-induced ADRs and two of thirty-fourth (5.88%) in the tolerant controls. Conclusions: Thus, the distribution of CYP2C9 alleles offer a comprehensive view of pharmacogenomics marker in Thai population that could be used as a reference for worldwide to investigate the pharmacogenomics application.

Keywords: medical cannabis, adverse effect, CYP2C9, thai patients

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Gayatri Ghosh

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In this work, a flavour theory of a neutrino mass model based on A_4 symmetry is considered to explain the phenomenology of neutrino mixing. The spontaneous symmetry breaking of A_4 symmetry in this model leads to tribimaximal mixing in the neutrino sector at a leading order. We consider the effect of Z_2 × Z_2 invariant perturbations in neutrino sector and find the allowed region of correction terms in the perturbation matrix that is consistent with 3σ ranges of the experimental values of the mixing angles. We study the entanglement of this formalism on the other phenomenological observables, such as δ_CP phase, the neutrino oscillation probability P(νµ → νe), the effective Majorana mass |mee| and |meff νe |. A Z_2 × Z_2 invariant perturbations in this model is introduced in the neutrino sector which leads to testable predictions of θ_13 and CP violation. By changing the magnitudes of perturbations in neutrino sector, one can generate viable values of δ_CP and neutrino oscillation parameters. Next we investigate the feasibility of charged lepton flavour violation in type-I seesaw models with leptonic flavour symmetries at high energy that leads to tribimaximal neutrino mixing. We consider an effective theory with an A_4 × Z_2 × Z_2 symmetry, which after spontaneous symmetry breaking at high scale which is much higher than the electroweak scale leads to charged lepton flavour violation processes once the heavy Majorana neutrino mass degeneracy is lifted either by renormalization group effects or by a soft breaking of the A_4 symmetry. In this context the implications for charged lepton flavour violation processes like µ → eγ, τ → eγ, τ → µγ are discussed.

Keywords: Z2 × Z2 invariant perturbations, CLFV, delta CP phase, tribimaximal neutrino mixing

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Authors: Stephan Treuke

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The paper analyses the neighbourhood effects on the economic mobility of the inhabitants of three segregated communities of Salvador (Brazil), in other words, the socio-economic advantages and disadvantages affecting the lives of poor people due to their embeddedness in specific socio-residential contexts. Recent studies performed in Brazilian metropolis have concentrated on the structural dimensions of negative externalities in order to explain neighbourhood-level variations in a field of different phenomena (delinquency, violence, access to the labour market and education) in spatial isolated and socially homogeneous slum areas (favelas). However, major disagreement remains whether the contiguity between residents of poor neighbourhoods and higher-class condominio-dwellers provides structures of opportunities or whether it fosters socio-spatial stigmatization. Based on a set of interviews, investigating the variability of interpersonal networks and their activation in the struggle for economic inclusion, the study confirms that the proximity of Nordeste de Amaralina to middle-/upper-class communities affects positively the access to labour opportunities. Nevertheless, residential stigmatization, as well as structures of social segmentation, annihilate these potentials. The lack of exposition to individuals and groups extrapolating from the favela’s social, educational and cultural context restricts the structures of opportunities to local level. Therefore, residents´ interpersonal networks reveal a high degree of redundancy and localism, based on bonding ties connecting family and neighbourhood members. The resilience of segregational structures in Plataforma contributes to the naturalization of social distance patters. It’s embeddedness in a socially homogeneous residential area (Subúrbio Ferroviário), growing informally and beyond official urban politics, encourages the construction of isotopic patterns of sociability, sharing the same values, social preferences, perspectives and behaviour models. Whereas it’s spatial isolation correlates with the scarcity of economic opportunities, the social heterogeneity of Fazenda Grande II interviewees and the socialising effects of public institutions mitigate the negative repercussions of segregation. The networks’ composition admits a higher degree of heterophilia and a greater proportion of bridging ties accounting for the access to broader information actives and facilitating economic mobility. The variability observed within the three different scenarios urges to reflect about the responsability of urban politics when it comes to the prevention or consolidation of the social segregation process in Salvador. Instead of promoting the local development of the favela Plataforma, public housing programs priorize technocratic habitational solutions without providing the residents’ socio-economic integration. The impact of negative externalities related to the homogeneously poor neighbourhood is potencialized in peripheral areas, turning its’ inhabitants socially invisible, thus being isolated from other social groups. The example of Nordeste de Amaralina portrays the failing interest of urban politics to bridge the social distances structuring the brazilian society’s rigid stratification model, founded on mecanisms of segmentation (unequal access to labour market and education system, public transport, social security and law protection) and generating permanent conflicts between the two socioeconomically distant groups living in geographic contiguity. Finally, in the case of Fazenda Grande II, the public investments in both housing projects and complementary infrastructure (e.g. schools, hospitals, community center, police stations, recreation areas) contributes to the residents’ socio-economic inclusion.

Keywords: economic mobility, neighborhood effects, Salvador, segregation

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Authors: Sevilay Konya, Sadife Güngör, Zeynep Karaçor

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Turkish economy is occurred depending on different factors from time to time and the banking crises of different magnitudes. Foremost among the factors which hinder the development of countries and societies- crises in the country's economy. Countries' economic growth rates affect inflation, unemployment and external trade. In this study, effect of November 2000, February 2001 and 2008 banking crisis on Turkey's economy and banking crisis will be examined and announced as conceptual. In this context, this study is investigates Turkey's GDP, inflation, unemployment and foreign trade figures. Turkey's economy affected have been identified from 2000 November 2001 February and 2008 banking crisis.

Keywords: banking crises, Turkey’s economy, economic effects, Turkey

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Authors: Misagh Faezipour

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This paper explores the effects of screen time on children from a systems engineering perspective. We reviewed literature from several related works on the effects of screen time on children to explore all factors and interrelationships that would impact children that are subjected to using long screen times. Factors such as kids' age, parent attitudes, parent screen time influence, amount of time kids spend with technology, psychosocial and physical health outcomes, reduced mental imagery, problem-solving and adaptive thinking skills, obesity, unhealthy diet, depressive symptoms, health problems, disruption in sleep behavior, decrease in physical activities, problematic relationship with mothers, language, social, emotional delays, are examples of some factors that could be either a cause or effect of screen time. A systems engineering perspective is used to explore all the factors and factor relationships that were discovered through literature. A causal model is used to illustrate a graphical representation of these factors and their relationships. Through the causal model, the factors with the highest impacts can be realized. Future work would be to develop a system dynamics model to view the dynamic behavior of the relationships and observe the impact of changes in different factors in the model. The different changes on the input of the model, such as a healthier diet or obesity rate, would depict the effect of the screen time in the model and portray the effect on the children’s health and other factors that are important, which also works as a decision support tool.

Keywords: children, causal model, screen time, systems engineering, system dynamics

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Authors: Amandeep Sharma, Digvaijay Verma, Ruplal Choudhary

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Food processing is an activity across the globe that help in better handling of agricultural produce, including dairy, meat, and fish. The operations carried out in the food industry includes raw material quality authenticity; sorting and grading; processing into various products using thermal treatments – heating, freezing, and chilling; packaging; and storage at the appropriate temperature to maximize the shelf life of the products. All this is done to safeguard the food products and to ensure the distribution up to the consumer. The approaches to develop predictive models based on mathematical or statistical tools or empirical models’ development has been reported for various milk processing activities, including plant maintenance and wastage. Recently AI is the key factor for the fourth industrial revolution. AI plays a vital role in the food industry, not only in quality and food security but also in different areas such as manufacturing, packaging, and cleaning. A new conceptual model was developed, which shows that smaller sample size as only spectra would be required to predict the other values hence leads to saving on raw materials and chemicals otherwise used for experimentation during the research and new product development activity. It would be a futuristic approach if these tools can be further clubbed with the mobile phones through some software development for their real time application in the field for quality check and traceability of the product.

Keywords: predictive modlleing, ann, ai, food

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Authors: Nikolaos Reppas, Yilin Gui, Ben Wetenhall, Colin Davie

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Injection of CO2 inside wellbore can induce different kind of loadings that can lead to thermal, hydraulic, and mechanical changes on the surrounding rock. A dual-porosity theoretical constitutive model will be presented for the stability analysis of the wellbore during CO2 injection. An elastoplastic damage response will be considered. A bounding yield surface will be presented considering damage effects on sandstone. The main target of the research paper is to present a theoretical constitutive model that can help industries to safely store CO2 in geological rock formations and forecast any changes on the surrounding rock of the wellbore. The fully coupled elasto-plastic damage Thermo-Hydraulic-Mechanical theoretical model will be validated from existing experimental data for sandstone after simulating some scenarios by using FEM on MATLAB software.

Keywords: carbon capture and storage, rock mechanics, THM effects on rock, constitutive model

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Authors: Carlo Bianchini, Lorenzo Catena

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The appearance of 3D scanners and then, more recently, of image-based systems that generate point clouds directly from common digital images have deeply affected the survey process in terms of both capturing and 2D/3D modelling. In this context, low cost and mobile systems are increasingly playing a key role and actually paving the way to the democratization of what in the past was the realm of few specialized technicians and expensive equipment. The application of Google Tango on the ancient church of Santa Maria delle Vigne in Pratica di Mare – Rome presented in this paper is one of these examples.

Keywords: the architectural survey, augmented/mixed/virtual reality, Google Tango project, image-based 3D capturing

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Authors: Chapman Eze Nnadozie

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Communication, the activity of conveying information, remains a vital resource for the growth and development of any given society. Mobile communication, popularly known as global system for mobile communication (GSM) is a globally accepted standard for digital cellular communication. GSM, which is a wireless technology, remains the fastest growing communication means worldwide. Indeed, mobile phones have become a critical business tool and part of everyday life in both developed and developing countries. This study examines the effects of mobile communication on the Nigerian populace. The methodology used in this study is the survey research method with the main data collection tool as questionnaires. The questionnaires were administered to a total of seventy respondents in five cities across the country, namely: Aba, Enugu, Bauchi, Makurdi, and Lagos. The result reveals that though there is some quality of service issues, mobile communication has very significant positive efforts on the economic and social development of the Nigerian populace.

Keywords: effect, mobile communication, populace, GSM, wireless technology, mobile phone

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Authors: Yuva Bellik, Selles Mohamed Amar

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The beneficial health effects including antioxidant properties of mint (Mentha spicata) and honey bees (Apis mellifera) have been extensively studied. However, there is no data about the effects of their associated use. In this study the total phenolic and flavonoid contents for individual extracts of mint and honey and their combination were determined. The antioxidant activity was investigated by using reducing power, 1,1-diphenyl-2-picrylhydrazyl (DPPH), 2,2´- azinobis-(3-ethylbenzothiazoline-6-sulphonic acid diamonium salt (ABTS), and chelating power methods. The results showed that individual extracts contained important quantity of phenolics and flavonoids and their combination was found to produce best antioxidant activity. A significant linear correlation between the phenolic/flavonoid contents and antioxidant activity, especially with reducing power and free radical scavenging abilities, was observed.

Keywords: honey, mint, synergy, antioxidant activity

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Authors: Vilma Zydziunaite, Simona Kersiene

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The concept of focused leadership means that the leader gathers the entire community in various ways to communicate and cooperate with each other, to share their knowledge and responsibility, to get involved in problem-solving, to create a safe and trusting environment and to satisfy the needs and interests of each community member. The study's aim is to analyze the teamwork of teachers working in kindergartens and schools and its CEOs by implementing confused leadership. A mixed research design was used for the research study. Quantitative research used the teamwork test "Team-Puls" (2003). Data is processed by the IBM SPSS version 29.0 software package. Semi-structured interviews were used for data collection, and qualitative content analysis was applied for data analysis. The results of quantitative research show that there is no statistically significant difference between the evaluation averages of kindergarten and school teachers. Likewise, the effectiveness and evaluation of teacher teamwork in educational institutions depend on different characteristics and processes, such as the number of participating teachers, the involvement of the institution's administration or the stages of team formation. In the qualitative research, the components of the focused leadership categories applied by the kindergarten and school CEOs emerged. The categories reflect the components of shared leadership. In the study, the sharing of responsibilities and cooperation among teachers and the sharing of knowledge among themselves is distinguished. This shows that the action takes place between the teachers when they participate in the processes voluntarily, according to their wishes or for certain reasons. Distributed leadership components occurs when leadership responsibility is extended beyond the school CEO. The components of servant leadership are expressed when the CEO achieves organizational goals in the service of others. Servant leadership is helping and striving for others, creating a safe environment. The level of the educational institution does not affect working teachers in the evaluation of working in a team. Giving freedom to teachers, the role of the CEO is dividing responsibilities and creating cooperation between teachers as well as ensuring teachers' interests, needs, emotional well-being and professional development.

Keywords: teamwork, school, teacher, school CEO, school environment, mixed research, Team-Puls test, semi-structured interview, questioning survey, qualitative content analysis, focused leadership, teacher leadership

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Authors: Andrey Khalov

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The rapid growth of unstructured data necessitates advanced methods for transforming raw information into structured knowledge, particularly in domain-specific contexts such as IT service management and outsourcing. This paper presents a methodology for automatically constructing domain ontologies using the DOLCE framework as the base ontology. The research focuses on expanding ITIL-based ontologies by integrating concepts from ITSMO, followed by the extraction of entities and relationships from domain-specific texts through transformers and statistical methods like formal concept analysis (FCA). In particular, this work introduces an R-GNN-based approach for ontology mapping, enabling more efficient entity extraction and ontology alignment with existing knowledge bases. Additionally, the research explores transfer learning techniques using pre-trained transformer models (e.g., DeBERTa-v3-large) fine-tuned on synthetic datasets generated via large language models such as LLaMA. The resulting ontology, termed IT Ontology (ITO), is evaluated against existing methodologies, highlighting significant improvements in precision and recall. This study advances the field of ontology engineering by automating the extraction, expansion, and refinement of ontologies tailored to the IT domain, thus bridging the gap between unstructured data and actionable knowledge.

Keywords: ontology mapping, knowledge graphs, R-GNN, ITIL, NER

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Authors: Darshini Mahadevia, Kanika Gounder, Saumya Lathia

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Cities, an outcome of natural growth and migration, are ever-expanding due to urban sprawl. In the Global South, urban areas are experiencing a switch from public transport to private vehicles, coupled with intensified urban agglomeration, leading to frequent longer commutes by automobiles. This increase in travel distance and motorized vehicle kilometres lead to unsustainable cities. To achieve the nationally pledged GHG emission mitigation goal, the government is prioritizing a modal shift to low-carbon transport modes like mass transit and paratransit. Mixed land-use and urban densification are crucial for the economic viability of these projects. Informed by desktop assessment of mobility plans and in-person primary surveys, the paper explores the challenges around urban densification and travel patterns in two Indian cities of contrasting nature- Surat, a metropolitan industrial city with a 5.9 million population and a very compact urban form, and Udaipur, a heritage city attracting large international tourists’ footfall, with limited scope for further densification. Dense, mixed-use urban areas often improve access to basic services and economic opportunities by reducing distances and enabling people who don't own personal vehicles to reach them on foot/ cycle. But residents travelling on different modes end up contributing to similar trip lengths, highlighting the non-uniform distribution of land-uses and lack of planned transport infrastructure in the city and the urban-peri urban networks. Additionally, it is imperative to manage these densities to reduce negative externalities like congestion, air/noise pollution, lack of public spaces, loss of livelihood, etc. The study presents a comparison of the relationship between transport systems with the built form in both cities. The paper concludes with recommendations for managing densities in urban areas along with promoting low-carbon transport choices like improved non-motorized transport and public transport infrastructure and minimizing personal vehicle usage in the Global South.

Keywords: India, low-carbon transport, travel behaviour, trip length, urban densification

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Authors: Albert Amagyei, Julia Carroll, Amanda R. Amorim Adegboye, Laura Strumidlo, Rosie Kneafsey

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Introduction: Classroom-based learning has persisted as the mainstream model of pre-registration nurse education. This model is often rigid, teacher-centered, and unable to support active learning and the practical learning needs of nursing students. Health Education England (HEE), a public body of the Department of Health and Social Care, hypothesises that blended learning (BL) programmes may address health system and nursing profession challenges, such as nursing shortages and lack of digital expertise, by exploring opportunities for providing predominantly online, remote-access study which may increase nursing student recruitment, offering alternate pathways to nursing other than the traditional classroom route. This study will provide evidence for blended learning strategies adopted in nursing education as well as examine nursing student learning experiences concerning the challenges and opportunities related to using blended learning within nursing education. Objective: This review will explore the challenges and opportunities of BL within pre-registration nurse education from the student's perspective. Methods: The search was completed within five databases. Eligible studies were appraised independently by four reviewers. The JBI-convergent segregated approach for mixed methods review was used to assess and synthesize the data. The study’s protocol has been registered with the International Register of Systematic Reviews with registration number// PROSPERO (CRD42023423532). Results: Twenty-seven (27) studies (21 quantitative and 6 qualitative) were included in the review. The study confirmed that BL positively impacts nursing students' learning outcomes, as demonstrated by the findings of the meta-analysis and meta-synthesis. Conclusion: The review compared BL to traditional learning, simulation, laboratory, and online learning on nursing students’ learning and programme outcomes as well as learning behaviour and experience. The results show that BL could effectively improve nursing students’ knowledge, academic achievement, critical skills, and clinical performance as well as enhance learner satisfaction and programme retention. The review findings outline that students’ background characteristics, BL design, and format significantly impact the success of the BL nursing programme.

Keywords: nursing student, blended learning, pre-registration nurse education, online learning

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Authors: Magdy Abouzeid

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Objectives: The aim of this study was to examine the influence of Monofin training, 36 weeks, 6 times per week, 90 min/unit on left ventricular performance in elite Egyptian Monofin athletes. Background: The elite athletes are one who has superior athletic talent. Monofin swimming already provide the most efficient way of swimming for human being, it is an aquatics sport practice on the surface or under water. Methods :To study these effects,14 elite Monofin children(3 girls and 11boys) aged(11.95± 1.09yr) HT (153.07± 4.2 cm) , WT(52.4 ± 3.7 kg ) , body surface area (BSA.m2 1.48 ± 5.6 m2 ) took part in long-term Monofin Training(LTMT).All subjects underwent two-dimension and M-mode Echordiography at rest before and after(LTMT). Results: There was significant difference (P < 0.01) and percentage improvement for all echocardiography parameter after (LTMT). Inter ventricular septal thickness in diastole and in systole increased by 27.9 % and 42.75 %. Left ventricular end systolic dimension and diastole increased by 16.81 % and 42.7 % respectively. Posterior wall thickness in systole was very highly increased by 283.3 % and in diastole increased by 51.78 %. Left ventricular mass in diastole and in systole increased by 44.8 % and 40.1 % respectively. Stroke volume and resting heart rate (HR) significant changed (sv) 25 %, (HR) 14.7 %. Conclusion: Monofin training is an effective sport to enhance ‘Heart athlete's’ for children, because the unique swim fin tool and create propulsion and overcome resistance. Further researches are needed to determine the effects of Monofin training on right ventricular in child athletes.

Keywords: prepubertal, monofin training, heart athlete's, elite child athlete, echocardiography

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