Search results for: generalized autoregressive score model

Authors: Xiao Wang, Qinge Zhang

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Background: This randomized, open-label study examined the therapeutic effects of computerized cognitive training (CCT) combined with selective serotonin reuptake inhibitors (SSRIs) on cognitive impairment among patients with late-life depression (LLD). Method: Study data were collected from May 5, 2021, to April 21, 2023. Outpatients who met diagnostic criteria for major depressive disorder according to the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria (i.e., a total score on the 17-item Hamilton Depression Rating Scale (HAMD-17) ≥ 18 and a total score on the Montreal Cognitive Assessment scale (MOCA) <26) were randomly assigned to receive up to 12 weeks of CCT and SSRIs treatment (n=57) or SSRIs and Control treatment (n=61). The primary outcome was the change in Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) scores from baseline to week 12 between the two groups. The secondary outcomes included changes in the HAMD-17 score, Hamilton Anxiety Scale (HAMA) score and Neuropsychiatric Inventory (NPI) score. Mixed model repeated measures (MMRM) analysis was performed on modified intention-to-treat (mITT) and completer populations. Results: The full analysis set (FAS) included 118 patients (CCT and SSRIs group, n=57; SSRIs and Control group, n =61). Over the 12-week study period, the reduction in the ADAS-cog total score was significant (P < 0.001) in both groups, while MMRM analysis revealed a significantly greater reduction in cognitive function (ADAS-cog total scores) from baseline to posttreatment in the CCT and SSRIs group than in the SSRI and Control group [(F (1,115) =13.65, least-squares mean difference [95% CI]: −2.77 [−3.73, −1.81], p<0.001)]. There were significantly greater improvements in depression symptoms (measured by the HAMD-17) in the CCT and SSRIs group than in the control group [MMRM, estimated mean difference (SE) between groups −3.59 [−5.02, −2.15], p < 0.001]. The least-squares mean changes in the HAMA scores and NPI scores between baseline and week 8 were greater in the CCT and SSRIs group than in the control group (all P < 0.05). There was no significant difference between groups on response rates and remission rates by using the last-observation-carried-forward (LOCF) method (all P > 0.05). The most frequent adverse events (AEs) in both groups were dry mouth, somnolence, and constipation. There was no significant difference in the incidence of adverse events between the two groups. Conclusions: CCT combined with SSRIs was efficacious and well tolerated in LLD patients with cognitive impairment.

Keywords: late-life depression, cognitive function, computerized cognitive training, SSRIs

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Authors: Phitsanu Phunphetchphan

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The purposes of this research was to investigate opinions of Rajabhat University staff towards performance of the university council committee by focusing on (1) personal characteristics of the committees; (2) duties designated by the university council; and (3) relationship between university council and staff. The population of this study included all high level of management from Suan Sunandha Rajabhat University which made a total of 200 respondents. Data analysis included frequency, percentage, mean and standard deviation. The findings revealed that the majority of staff rated the performance of university council at a high level. The 'overall appropriate qualification of the university council' was rated as the highest score while 'good governance' was rated as the lowest mean score. Moreover, the findings also revealed that the relationship between university council’s members and the staff was rated at a high level while 'the integrity of policy implementation' was rated as the lowest score.

Keywords: investigation, performance, university council, management

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Sergey A. Lurie, Yury O. Solyaev, Dmitry B. Volkov-Bogorodsky, Alexander V. Volkov

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The media with voids is considered and the method of the analytical estimation of the effective mechanical properties in the theory of elastic materials with voids is proposed. The variational model of the porous media is discussed, which is based on the model of the media with fields of conserved dislocations. It is shown that this model is fully consistent with the known model of the linear elastic materials with voids. In the present work, the generalized model of the porous media is proposed in which the specific surface properties are associated with the field of defects-pores in the volume of the deformed body. Unlike typical surface elasticity model, the strain energy density of the considered model includes the special part of the surface energy with the quadratic form of the free distortion tensor. In the result, the non-classical boundary conditions take modified form of the balance equations of volume and surface stresses. The analytical approach is proposed in the present work which allows to receive the simple enough engineering estimations for effective characteristics of the media with free dilatation. In particular, the effective flexural modulus and Poisson's ratio are determined for the problem of a beam pure bending. Here, the known voids elasticity solution was expanded on the generalized model with the surface effects. Received results allow us to compare the deformed state of the porous beam with the equivalent classic beam to introduce effective bending rigidity. Obtained analytical expressions for the effective properties depend on the thickness of the beam as a parameter. It is shown that the flexural modulus of the porous beam is decreased with an increasing of its thickness and the effective Poisson's ratio of the porous beams can take negative values for the certain values of the model parameters. On the other hand, the effective shear modulus is constant under variation of all values of the non-classical model parameters. Solutions received for a beam pure bending and the hydrostatic loading of the porous media are compared. It is shown that an analytical estimation for the bulk modulus of the porous material under hydrostatic compression gives an asymptotic value for the effective bulk modulus of the porous beam in the case of beam thickness increasing. Additionally, it is shown that the scale effects appear due to the surface properties of the porous media. Obtained results allow us to offer the procedure of an experimental identification of the non-classical parameters in the theory of the linear elastic materials with voids based on the bending tests for samples with different thickness. Finally, the problem of implementation of the Saint-Venant hypothesis for the transverse stresses in the porous beam are discussed. These stresses are different from zero in the solution of the voids elasticity theory, but satisfy the integral equilibrium equations. In this work, the exact value of the introduced surface parameter was found, which provides the vanishing of the transverse stresses on the free surfaces of a beam.

Keywords: effective properties, scale effects, surface defects, voids elasticity

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Authors: Harish Rajak, Preeti Patel

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The application of histone deacetylase inhibitors is a well-known strategy in prevention of cancer which shows acceptable preclinical antitumor activity due to its ability of growth inhibition and apoptosis induction of cancer cell. Molecular docking were performed using Histone Deacetylase protein (PDB ID:1t69) and prepared series of hydroxamic acid based HDACIs. On the basis of docking study, it was predicted that compound 1 has significant binding interaction with HDAC protein and three hydrogen bond interactions takes place, which are essential for antitumor activity. On docking, most of the compounds exhibited better glide score values between -8 to -10 which is close to the glide score value of suberoylanilide hydroxamic acid. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. The 3D-QSAR models provided a good correlation between predicted and actual anticancer activity. Best QSAR model showed Q2 (0.7974), R2 (0.9200) and standard deviation (0.2308). QSAR visualization maps suggest that hydrogen bond acceptor groups at carbonyl group of cap region and hydrophobic groups at ortho, meta, para position of R9 were favorable for HDAC inhibitory activity. We established structure activity correlation using docking, pharmacophore modeling and atom based 3D QSAR model for hydroxamic acid based HDACIs.

Keywords: HDACIs, QSAR, e-pharmacophore, docking, suberoylanilide hydroxamic acid

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Authors: Zhi-Wei Zheng, Zhong-Qi Liu, Jia-Ling Qiu, Shan-Qing Guo, Zhong-Wei Jia, Chun Hao

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Objectives: The purpose of this study was to understand and examine the association between diurnal mood variation and sexual/health-related status among men who have sex with men (MSM) using data from MSM Chinese Twitter messages. The study consists of 843,745 postings of 377,610 MSM users located in Guangdong that were culled from the MSM Chinese Twitter App. Positive affect, negative affect, sexual related behaviors, and health-related status were measured using the Simplified Chinese Linguistic Inquiry and Word Count. Emotions, including joy, sadness, anger, fear, and disgust were measured using the Weibo Basic Mood Lexicon. A positive sentiment score and a positive emotions score were also calculated. Linear regression models based on a permutation test were used to assess associations between affective states and sexual/health-related status. In the results, 5,871 active MSM users and their 477,374 postings were finally selected. MSM expressed positive affect and joy at 8 a.m. and expressed negative affect and negative emotions between 2 a.m. and 4 a.m. In addition, 25.1% of negative postings were directly related to health and 13.4% reported seeking social support during that sensitive period. MSM who were senior, educated, overweight or obese, self-identified as performing a versatile sex role, and with less followers, more followers, and less chat groups mainly expressed more negative affect and negative emotions. MSM who talked more about sexual-related behaviors had a higher positive sentiment score (β=0.29, p < 0.001) and a higher positive emotions score (β = 0.16, p < 0.001). MSM who reported more on their health status had a lower positive sentiment score (β = -0.83, p < 0.001) and a lower positive emotions score (β = -0.37, p < 0.001). The study concluded that psychological intervention based on an app for MSM should be conducted, as it may improve mental health.

Keywords: affect, men who have sex with men, sexual related behavior, health-related status, social media

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Authors: Bela Siska Afrida, Wisnu Barlianto, Desy Wulandari, Ery Olivianto

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Background: Allergic asthma, caused by IgE-mediated allergic reactions, remains a global health issue with high morbidity and mortality rates. Immunotherapy is the only etiology-based approach to treating asthma, but no standard biomarkers have been established to evaluate the therapy’s effectiveness. This study aims to determine the correlation between the ratios of serum levels of HDM-specific IgE/total IgE and Asthma Control Test (ACT) score as a biomarker of the response to immunotherapy in pediatric allergic asthma patients. Patient and Methods: This retrospective cohort study involved 26 pediatric allergic asthma patients who underwent HDM-specific subcutaneous immunotherapy for 14 weeks at the Pediatric Allergy Immunology Outpatient Clinic at Saiful Anwar General Hospital, Malang. Serum levels of HDM-Specific IgE and Total IgE were measured before and after immunotherapy using Chemiluminescence Immunoassay and Enzyme-linked Immunosorbent Assay (ELISA) method. Changes in asthma control were assessed using the ACT score. The Wilcoxon Signed Ranked Test and Spearman correlation test were used for data analysis. Results: There were 14 boys and 12 girls with a mean age of 6.48 ± 2.54 years. The study showed a significant decrease in serum HMD-specific levels before immunotherapy [9.88 ± 5.74 kuA/L] compared to those of 14 weeks after immunotherapy [4.51 ± 3.98 kuA/L], p = 0.000. Serum Total IgE levels significant decrease before immunotherapy [207.6 ± 120.8IU/ml] compared to those of 14 weeks after immunotherapy [109.83 ± 189.39 IU/mL], p = 0.000. The ratios of serum HDM-specific IgE/total IgE levels significant decrease before immunotherapy [0.063 ± 0.05] compared to those of 14 weeks after immunotherapy [0.041 ± 0.039], p = 0.012. There was also a significant increase in ACT scores before and after immunotherapy (each 15.5 ± 1.79 and 20.96 ± 2.049, p = 0.000). The correlation test showed a weak negative correlation between the ratios of HDM-specific IgE/total IgE levels and ACT score (p = 0.034 and r = -0.29). Conclusion: In conclusion, this study showed that a decrease in HDM-specific IgE levels, total IgE levels, and HDM-specific IgE/total IgE ratios, and an increase in ACT score, was observed after 14 weeks of HDM-specific subcutaneous immunotherapy. The weak negative correlation between the HDM-specific IgE/total IgE ratio and the ACT score suggests that this ratio can serve as a potential biomarker of the effectiveness of immunotherapy in treating pediatric allergic asthma patients.

Keywords: HDM-specific IgE/total IgE ratio, ACT score, immunotherapy, allergic asthma

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Authors: Snezana Mugosa, Zoran Todorovic, Zoran Bukumiric, Ivan Radosavljevic, Natasa Djordjevic

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Introduction: Various studies have shown that the frequency of clopidogrel resistance ranges from 4-40%. The aim of this study was to provide in depth analysis of genetic and non-genetic factors that influence clopidogrel resistance in cardiology patients. Methods: We have conducted a prospective study in 200 hospitalized patients hospitalized at Cardiology Centre of the Clinical Centre of Montenegro. CYP2C19 genetic testing was conducted, and the PREDICT score was calculated in 102 out of 200 patients treated with clopidogrel in order to determine the influence of genetic and non-genetic factors on outcomes of interest. Adverse cardiovascular events and adverse reactions to clopidogrel were assessed during 12 months follow up period. Results: PREDICT score and CYP2C19 enzymatic activity were found to be statistically significant predictors of expressing lack of therapeutic efficacy of clopidogrel by multivariate logistic regression, without multicollinearity or interaction between the predictors (p = 0.002 and 0.009, respectively). Conclusions: Pharmacogenetics analyses that were done in the Montenegrin population of patients for the first time suggest that these analyses can predict patient response to the certain therapy. Stepwise approach could be used in assessing the clopidogrel resistance in cardiology patients, combining the PREDICT score, platelet aggregation test, and genetic testing for CYP2C19 polymorphism.

Keywords: clopidogrel, pharmacogenetics, pharmacotherapy, PREDICT score

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Authors: Jason West

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Low profitability in agriculture production along with increasing scrutiny over environmental effects is limiting food production at scale. In contrast, the mining sector offers access to resources including energy, water, transport and chemicals for food production at low marginal cost. Scalable agricultural production can benefit from the nexus of resources (water, energy, transport) offered by mining activity in remote locations. A decision support bioeconomic model for controlled environment vertical farms was used. Four submodels were used: crop structure, nutrient requirements, resource-crop integration, and economic. They escalate to a macro mathematical model. A demonstrable dynamic systems framework is needed to prove productive outcomes are feasible. We demonstrate a generalized bioeconomic macro model for controlled environment production systems in minesites using systems dynamics modeling methodology. Despite the complexity of bioeconomic modelling of resource-agricultural dynamic processes and interactions, the economic potential greater than general economic models would assume. Scalability of production as an input becomes a key success feature.

Keywords: crop production systems, mathematical model, mining, agriculture, dynamic systems

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Authors: Mohamed Mohamed, Philip Bonello, Peter Russhard

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Blade Tip Timing (BTT) is a technology concerned with the estimation of both frequency and amplitude of rotating blades. A BTT system comprises two main parts: (a) the arrival time measurement system, and (b) the analysis algorithms. Simulators play an important role in the development of the analysis algorithms since they generate blade tip displacement data from the simulated blade vibration under controlled conditions. This enables an assessment of the performance of the different algorithms with respect to their ability to accurately reproduce the original simulated vibration. Such an assessment is usually not possible with real engine data since there is no practical alternative to BTT for blade vibration measurement. Most simulators used in the literature are based on a simple spring-mass-damper model to determine the vibration. In this work, a more realistic experimentally validated simulator based on the Finite Element (FE) model of a bladed disc (blisk) is first presented. It is then used to generate the necessary data for the assessment of different BTT algorithms. The FE modelling is validated using both a hammer test and two firewire cameras for the mode shapes. A number of autoregressive methods, fitting methods and state-of-the-art inverse methods (i.e. Russhard) are compared. All methods are compared with respect to both synchronous and asynchronous excitations with both single and simultaneous frequencies. The study assesses the applicability of each method for different conditions of vibration, amount of sampling data, and testing facilities, according to its performance and efficiency under these conditions.

Keywords: blade tip timing, blisk, finite element, vibration measurement

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Authors: Katsumi Mera

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The purpose of this study was to clarify the relationship between strengths/weaknesses on studying and subjective well-being among Japanese working adults. We conducted an online questionnaire survey of Japanese working adults (aged 20-69) and obtained 1,063 valid responses. Subjective well-being was evaluated using the Cantril Self-Anchoring Striving Scale, the method used in the World Happiness Survey, in which the highest possible life is set at 10, and the lowest possible life is set at 0. The mean subjective well-being of all 1,063 respondents was 5.87, which is a very similar value that was obtained in the Japanese World Happiness Survey in 2023. First, we investigated the respondents' strengths/weaknesses in studying and their subjective well-being. The results showed that the subjective well-being of the group who answered that they were good at studying (6.62) was significantly higher than that of the group who answered that they were poor at studying (5.15). Next, we investigated the subjective well-being of students who answered that they were good at Japanese, Math, English, Social studies, and Science, the major subjects in Japan, and found that the subjective well-being of the group that answered that they were good at these subjects was higher than that of the group that answered that they were poor at these subjects. When the correlation between the score of "strengths/weaknesses on studying" and the score of "subjective well-being" was examined, those who answered that they were good at studying had higher subjective well-being (correlation coefficient r = 0.26, p < 0.001). The correlation between the subjective well-being score and the score of "strengths/weaknesses on studying each subject” was examined. Among the subjects, the subjective well-being score was the highest for those who answered that they were good at English (correlation coefficient r = 0.17, p < 0.001). These results indicate a relationship between strengths/weaknesses on studying and subjective well-being among workers in Japan. These findings may provide an important basis for considering what kind of education should be focused on in order to nurture working adults with high levels of well-being.

Keywords: subject well-being, strengths/weaknesses, studying, Japanese working adults

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Authors: Dzhavidan Zeinalov, Bugra Sen, Firangiz Aslanova

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Most text-to-speech models cannot operate well in low-resource languages and require a great amount of high-quality training data to be considered good enough. Yet, with the improvements made in ASR systems, it is now much easier than ever to collect data for the design of custom text-to-speech models. In this work, our work on using the ASR model to collect data to build a viable text-to-speech system for one of the leading financial institutions of Azerbaijan will be outlined. NVIDIA’s implementation of the Tacotron 2 model was utilized along with the HiFiGAN vocoder. As for the training, the model was first trained with high-quality audio data collected from the Internet, then fine-tuned on the bank’s single speaker call center data. The results were then evaluated by 50 different listeners and got a mean opinion score of 4.17, displaying that our method is indeed viable. With this, we have successfully designed the first text-to-speech model in Azerbaijani and publicly shared 12 hours of audiobook data for everyone to use.

Keywords: Azerbaijani language, HiFiGAN, Tacotron 2, text-to-speech, transfer learning, whisper

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Authors: Inaam Nasrallah, Pascale Salameh, Abbas El-Outa, Assem Alkak, Rihab Nasr, Wafa Toufic Bawab

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Background: Hazardous Waste Management(HWM). is critical to human health outcomes and environmental protection. This study evaluated the knowledge regarding safety measures to be applied when collecting and storing waste in scientific laboratories of two universities in Lebanon.Method: A survey-based observational study was conducted in scientific laboratories of the public university and that of a private university, where a total of 309 participants were recruited.Result: The mean total knowledge score on safety measures of HWM was 9.02±4.34 (maximum attainable score, 13). Significant association (p<0.05) was found between knowledge score and job function, years of experience, educational level, professional status, work schedule, and training on proper HWM. Participants had adequate perceptions regarding the impact of HWM on health and the environment. Linear regression modeling revealed that knowledge score was significantly higher among bachelor level lab workers compared to those with doctoral degrees (p=0.043), full-time schedule workers versus part-timers (p=0.03), and among public university participants as compared to those of the private university (p<0.001).Conclusion: This study showed good knowledge concerning HWM in the scientific laboratoriesof the studied universities in Lebanon and a good awareness of the HWM on health and the environment. It highlights the importance of culture, attitude, and practice on proper HWM in the academic scientific laboratory.

Keywords: hasardous waste, safety measures, waste management, knwoledge score, scientific laboratory workers

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Authors: Kittivate Boonyopakorn

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The purposes of this study were to find the English competence of the public health volunteers and to develop the use of their English. The samples for the study were 41 public health village volunteers at Ban Prasukchai, in Thailand. The findings showed that the sum of all scores for the pre-test was 452, while the score for the post-test was 1,080. Therefore, the results of the experiment confirm that the post-test scores (1,080) significantly are higher than the pre-test (452). The mean score (N=41) for the pre-test was 11.02 while the mean score (N=41) for the post-test was 18.10. The standard deviation for the pre-test was 2.734; however, for the post-test it was 1.934. In addition to the experts-evaluated research tools, the results of the evaluation for the structured interviews (IOC) were 1 in value. The evaluation of congruence for the content with learning objectives (IOC) were 0.66 to 1.00 in value. The evaluation of congruence for the pre and post-test with learning objectives (IOC) are 1 in value.

Keywords: finding the English competency, developing public health, village volunteers

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Authors: Iqbal Pramukti, Mamat Lukman, Hasniatisari Harun, Kusman Ibrahim

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Introduction: People living with HIV had a higher risk of osteoporotic fracture than the general population. The purpose of this study was to predict the 10-year risk of fracture among people living with HIV (PLWH) using FRAX™ and to identify characteristics related to the fracture risk. Methodology: This study consisted of 75 subjects. The ten-year probability of major osteoporotic fractures (MOF) and hip fractures was assessed using the FRAX™ algorithm. A cross-tabulation was used to identify the participant’s characteristics related to fracture risk. Results: The overall mean 10-year probability of fracture was 2.4% (1.7) for MOF and 0.4% (0.3) for hip fractures. For MOF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use showed a higher MOF score than those who were not (3.1 vs. 2.5; 4.6 vs 2.5; and 3.4 vs 2.5, respectively). For HF score, participants with parents’ hip fracture history, smoking behavior and glucocorticoid use also showed a higher HF score than those who were not (0.5 vs. 0.3; 0.8 vs. 0.3; and 0.5 vs. 0.3, respectively). Conclusions: The 10-year risk of fracture was higher among PLWH with several factors, including the parent’s hip. Fracture history, smoking behavior and glucocorticoid used. Further analysis on determining factors using multivariate regression analysis with a larger sample size is required to confirm the factors associated with the high fracture risk.

Keywords: HIV, PLWH, osteoporotic fractures, hip fractures, 10-year risk of fracture, FRAX

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Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

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Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

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Authors: Zeynep Karaçor, Volkan Alptekin, Gökhan Akar, Tuba Akar

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This paper aims to review the phenomenon of triplet deficit which is called interaction of budget balance that make up the overall balance of the economy, investment savings balance and current accounts balance in terms of Turkey. In this paper, triplet deficit state in Turkish economy has been analyzed with vector autoregressive model and Granger causality test using data covering the period of 1980-2010. According to VAR results, increase in current accounts is perceived on public sector borrowing requirement. These two variables influence each other bilaterally. Therefore, current accounts increase public deficit, whereas public deficit increases current accounts. It is not possible to mention the existence of a short-term Granger causality between variables at issue.

Keywords: internal and external deficit, stability, triplet deficit, Turkey economy

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Authors: Oren Shtayermman

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The current investigation expended on research among parents caring for a child who is diagnosed with an autism spectrum disorder (ASD). An online web survey was used to collect data from 253 parents caring for a child with a diagnosis of ASD. Both parents reported on elevated levels of parental stress associated with caring for the child on the spectrum. In addition, lower levels of marital satisfaction were found in both parents. About 13% of the parents in the sample met the diagnostic criteria for Major Depressive Disorder and About 15% of the parents met the diagnostic criteria for Generalized Anxiety Disorder. Although the majority of the sample was females (94%) significant differences were found between males and females in relation to meeting the diagnostic criteria for Major Depressive Disorder and for Generalized Anxiety Disorder. Higher levels of stress were associated with higher number of Generalized Anxiety Disorder symptoms and higher number of Major Depressive Disorder symptoms. Findings from this study indicate how vulnerable parents and especially females are in relation to caring to a child diagnosed with ASD. Educational Objectives: At the conclusion of the paper, the readers should be able to: -Identify levels of stress and marital satisfaction among parents caring for a child diagnosed with autism spectrum disorder, -Recognize the impact of stress on the development of mental health issues, -Name the two most common mood and anxiety related disorders associated with caring for a child diagnosed with an autism spectrum disorder.

Keywords: autism, stress, parents, children

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Authors: Moses Aron, Elias Mwakilama, Jimmy Namangale

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Spending more time on long queues for a basic service remains a common challenge to most developing countries, including Malawi. For health sector in particular, Out-Patient Department (OPD) experiences long queues. This puts the lives of patients at risk. However, using queuing analysis to under the nature of the problems and efficiency of service systems, such problems can be abated. Based on a kind of service, literature proposes different possible queuing models. However, unlike using generalized assumed models proposed by literature, use of real time case study data can help in deeper understanding the particular problem model and how such a model can vary from one day to the other and also from each case to another. As such, this study uses data obtained from one urban HC for BP, Pediatric and General OPD cases to investigate an average queuing time for patients within the system. It seeks to highlight the proper queuing model by investigating the kind of distributions functions over patient’s arrival time, inter-arrival time, waiting time and service time. Comparable with the standard set values by WHO, the study found that patients at this HC spend more waiting times than service times. On model investigation, different days presented different models ranging from an assumed M/M/1, M/M/2 to M/Er/2. As such, through sensitivity analysis, in general, a commonly assumed M/M/1 model failed to fit the data but rather an M/Er/2 demonstrated to fit well. An M/Er/3 model seemed to be good in terms of measuring resource utilization, proposing a need to increase medical personnel at this HC. However, an M/Er/4 showed to cause more idleness of human resources.

Keywords: health care, out-patient department, queuing model, sensitivity analysis

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: Wheyming Tina Song, Chi-Hao Hong

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In this study, we investigate the effect of a new boarding policy - short stay, on the overcrowding efficiency in emergency department (ED). The decision variables are no. of short stay beds for least acuity ED patients. The performance measurements used are national emergency department overcrowding score (NEDOCS) and ED retention rate (the percentage that patients stay in ED over than 48 hours in one month). Discrete event simulation (DES) is used as an analysis tool to evaluate the strategy. Also, common random number (CRN) technique is applied to enhance the simulation precision. The DES model was based on a census of 6 months' patients who were treated in the ED of the National Taiwan University Hospital Yunlin Branch. Our results show that the new short-stay boarding significantly impacts both the NEDOCS and ED retention rate when the no. of short stay beds is more than three.

Keywords: emergency department (ED), common random number (CRN), national emergency department overcrowding score (NEDOCS), discrete event simulation (DES)

Procedia PDF Downloads 353

Authors: Santi Gopal Maji, R. A. J. Syngkon

Abstract:

The changing attitude of the corporate enterprises from maximizing economic benefit to corporate sustainability after the publication of Brundtland Report has attracted the interest of researchers to investigate the sustainability practices of firms and its impact on financial performance. To enrich the empirical literature in Asian context, this study examines the disclosure pattern of corporate sustainability and the influence of sustainability reporting on financial performance of firms from four Asian countries (Japan, South Korea, India and Indonesia) that are publishing sustainability report continuously from 2009 to 2016. The study has used content analysis technique based on Global Reporting Framework (3 and 3.1) reporting framework to compute the disclosure score of corporate sustainability and its components. While dichotomous coding system has been employed to compute overall quantitative disclosure score, a four-point scale has been used to access the quality of the disclosure. For analysing the disclosure pattern of corporate sustainability, box plot has been used. Further, Pearson chi-square test has been used to examine whether there is any difference in the proportion of disclosure between the countries. Finally, quantile regression model has been employed to examine the influence of corporate sustainability reporting on the difference locations of the conditional distribution of firm performance. The findings of the study indicate that Japan has occupied first position in terms of disclosure of sustainability information followed by South Korea and India. In case of Indonesia, the quality of disclosure score is considerably less as compared to other three countries. Further, the gap between the quality and quantity of disclosure score is comparatively less in Japan and South Korea as compared to India and Indonesia. The same is evident in respect of the components of sustainability. The results of quantile regression indicate that a positive impact of corporate sustainability becomes stronger at upper quantiles in case of Japan and South Korea. But the study fails to extricate any definite pattern on the impact of corporate sustainability disclosure on the financial performance of firms from Indonesia and India.

Keywords: corporate sustainability, quality and quantity of disclosure, content analysis, quantile regression, Asian countries

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Authors: Arunee Wongkhao, Suparat Niwitpong, Sa-aat Niwitpong

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In this paper, we propose two new confidence intervals for the difference between the inverse of normal means with known coefficients of variation. One of these two confidence intervals for this problem is constructed based on the generalized confidence interval and the other confidence interval is constructed based on the closed form method of variance estimation. We examine the performance of these confidence intervals in terms of coverage probabilities and expected lengths via Monte Carlo simulation.

Keywords: coverage probability, expected length, inverse of normal mean, coefficient of variation, generalized confidence interval, closed form method of variance estimation

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Authors: Golnush Masghati-Amoli, Paul Chin

Abstract:

Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Amares Chattopadhyay, Akanksha Srivastava

Abstract:

A unified approach to study the reflection of a plane wave in three-dimensional model comprised of the triclinic viscoelastic medium. The phase velocities of reflected qP, qSV and qSH wave have been calculated for the concerned medium by using the eigenvalue approach. The generalized method has been implemented to compute the complex form of amplitude ratios. Further, we discussed the nature of reflection coefficients of qP, qSV and qSH wave. The viscoelastic parameter, polar angle and azimuthal angle are found to be strongly influenced by amplitude ratios. The research article is particularly focused to study the effect of viscoelasticity associated with highly anisotropic media which exhibits the notable information about the reflection coefficients of qP, qSV, and qSH wave. The outcomes may further useful to the better exploration of all types of hydrocarbon reservoir and advancement in the field of reflection seismology.

Keywords: amplitude ratios, three dimensional, triclinic, viscoelastic

Procedia PDF Downloads 237

Authors: Zehra Buyuktuncer, Aylin H. Büyükkaragöz, Tuğçe N. Balcı, Nevin Ergun

Abstract:

Background: Undergoing rigid dietary habits for enhancing athletic performance could lead to eating disorders. High prevalence of eating disorders among female athletes has been already reported. However, the risk of disordered eating among disabled athletes is not known. A better knowledge of the different eating behaviors and their prevalence in disabled athletes would be helpful to understand interactions between eating and health. This study aimed to examine the cognitive restraint, uncontrolled eating and emotional eating behaviors in a disabled athlete population. Method: A total of 70 disabled Turkish national athletes (33 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball) were involved in the study. The cognitive restraint, uncontrolled eating and emotional eating behaviors were assessed using the revised version of Three Factor Eating Questionnaire-R18 (TFEQ-R18). The questionnaires were conducted by dietitian during the preparation camps of athletes. Body weight, height and waist circumference (WC) were measured; and body composition was analyzed by bioelectrical impedance analysis method. Results: The TFEQ scales showed a cognitive dietary restraint score of 13.9±4.2, uncontrolled eating score of 17.7±5.8 and emotional eating score of 4.9±2.5. The mean score of total TFEQ-R18 was 36.5±8.62. Neither total TFEQ-R18 score nor subscale scores differed significantly by gender or sport branches (p>0.05, for each). The scores were also similar in BMI groups (n=63; p>0.05). Total TFEQ, uncontrolled eating and emotional eating scores were significantly higher among the athletes with congenital disabilities compared to the scores of the athletes with acquired disabilities (p<0.05, for each). Moreover, the cognitive dietary restraint score was significantly high in athletes who would like to lose weight (p=0.009). Conclusion: Disabled athletes might have a risk of disordered eating. The different eating behaviors among disabled athletes should be assessed using validated tools to develop personalized nutritional strategies for those athletes.

Keywords: disabled athletes, eating behaviour, three-factor eating questionnaire-r18, body composition

Procedia PDF Downloads 339

Authors: Xin Chen, Xiao Yang, Rongrong Han, Lu Chen, Lingling Gao

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Background: Leisure time physical activity (LTPA) benefits both pregnant women and their fetuses. The guidelines recommended that pregnant women should do at least 150 minutes of moderate-intensity aerobic physical activity throughout the week. The aim of this study was to investigate the rate of LTPA participation among Chinese pregnant women and to identify its predictors based on the health belief model. Methods: A cross-sectional study was conducted from June 2019 to September 2019 in Changchun, China. A total of 225 pregnant women aged 18 years or older with no severe physical or mental disease were recruited in the obstetric clinic. Self-administered questionnaires were used to collect data. LTPA was assessed by a pregnant physical activity questionnaire (PPAQ). A revised pregnancy physical activity health belief scale and social-demographic and perinatal characteristics factors were collected and used to predict LTPA participation. Data were analyzed using descriptive statistics and multivariate logistic regression. Results: The participants had a high level of perceived susceptibility, perceived severity, perceived benefits, and action clues, with mean item scores above 3.5. The predictors of LTPA in Chinese pregnant women were pre-pregnancy exercise habits [OR 3.236 (95% CI:1.632, 6.416)], perceived susceptibility score [OR 2.083 (95% CI:1.002, 4.331)], and perceived barriers score [OR 3.113 (95%CI:1.462, 6.626)]. Conclusions: The results of this study will lead to better identification of pregnant women who may not participate in LTPA. Healthcare professionals should be cognizant of issues that may affect LTPA participation among pregnant women, including pre-pregnancy exercise habits, perceived susceptibility, and perceived barriers.

Keywords: pregnancy, health belief model., leisure time physical activity, factors

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Authors: Elena M. Kopteva, Pavlina Jaluvkova, Zdenek Stuchlik

Abstract:

In spite of the numerous attempts to close the discussion about the influence of cosmological expansion on local gravitationally bounded systems, this question arises in literature again and again and remains still far from its final resolution. Here one of the main problems is the problem of obtaining a physically adequate model of strongly gravitating object immersed in non-static cosmological background. Such objects are usually called ‘cosmological’ black holes and are of great interest in wide set of cosmological and astrophysical areas. In this work the set of new exact solutions of the Einstein equations is derived for the flat space that generalizes the known Lemaitre-Tolman-Bondi solution for the case of nonzero pressure. The solutions obtained are pretending to describe the black hole immersed in nonstatic cosmological background and give a possibility to investigate the hot problems concerning the effects of the cosmological expansion in gravitationally bounded systems, the structure formation in the early universe, black hole thermodynamics and other related problems. It is shown that each of the solutions obtained contains either the Reissner-Nordstrom or the Schwarzschild black hole in the central region of the space. It is demonstrated that the approach of the mass function use in solving of the Einstein equations allows clear physical interpretation of the resulting solutions, that is of much benefit to any their concrete application.

Keywords: exact solutions of the Einstein equations, cosmological black holes, generalized Lemaitre-Tolman-Bondi solutions, nonzero pressure

Procedia PDF Downloads 426

Authors: Sirimanee Banjong

Abstract:

This study aimed to 1) develop pre-service teachers’ leadership skills through camp-based learning, and 2) develop pre-service teachers’ teamwork skills through camp-based learning. An applied research methodology was used. The target group was derived from a purposive selection. It involved 32 fourth-year students in Early Childhood Education Program enrolling in a course entitled Seminar in Early Childhood Education provided during the second semester of the academic year 2013. The treatment was camp-based learning activities which applied a PDCA process including four stages: 1) plan, 2) do, 3) check, and 4) act. Research instruments were a learning camp program, a camp-based learning management plan, a 5-level assessment form for leadership skills and a 5-level assessment form for assessing teamwork skills. Data were analyzed using descriptive statistics. Results were: 1) pre-service teachers’ leadership skills yielded the before treatment average score at ¯("x" )=3.4, S.D.= 0.62 and the after-treatment average score at ¯("x" ) 4.29, S.D.=0.66 pre-service teachers’ teamwork skills yielded the before-treatment average score at ¯("x" )=3.31, S.D.= 0.60 and the after-treatment average score at ¯("x" )=4.42, S.D.= 0.66. Both differences were statistically significant at the .05 level. Thus, the pre-service teachers’ leadership and teamwork skills were significantly improved through the camp-based learning approach.

Keywords: learning camp, leadership skills, teamwork skills, pre-service teachers

Procedia PDF Downloads 362