Cabral, Giorgione G.;de Souza, Ana C. Dantas;Barbosa, Isabelle R.;Jerez-Roig, Javier;Souza, Dyego L.B.
Safety and Health at Work
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v.10
no.4
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pp.393-399
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2019
Objective: This study investigates the impact of multimorbidity on work through a literature review of longitudinal studies. Methods: A systematic review was carried out in the databases Lilacs, SciELO, PAHO, PubMed/Medline, Scopus, Web of Science, and Cochrane. There were no restrictions regarding the year of publication or language to maximize the identification of relevant literature. The quality of studies was assessed by the protocol STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). Results: An initial database search identified 7522 registries, and at the end of the analysis, 7 manuscripts were included in the review. Several studies have demonstrated direct and indirect impacts of multimorbidity on the health of workers. For this, the number of missed days due to health-related issues was evaluated, as well as the reduction in work productivity of the unhealthy worker, vulnerability of the worker with multimorbidity regarding higher indices of dismissal and recruitment difficulties, and incidence of early retirement and/or receipt of benefits due to disabilities. Conclusions: Multimorbidity has a negative impact on work, with damages to quality of life and work productivity, worsening the absenteeism/presenteeism indices, enhancing the chances of temporary or permanent leaves, and lowering employability and admission of individuals with multimorbidity.
The current study assessed the utility of acoustic analyses the most commonly used in routine clinical voice assessment including perturbation, nonlinear dynamic analysis, and Spectral/Cepstrum analysis based on signal typing of dysphonic voices and investigated their applicability of clinical acoustic analysis methods. A total of 70 dysphonic voice samples were classified with signal typing using narrowband spectrogram. Traditional parameters of %jitter, %shimmer, and signal-to-noise ratio were calculated for the signals using TF32 and correlation dimension(D2) of nonlinear dynamic parameter and spectral/cepstral measures including mean CPP, CPP_sd, CPPf0, CPPf0_sd, L/H ratio, and L/H ratio_sd were also calculated with ADSV(Analysis of Dysphonia in Speech and VoiceTM). Auditory perceptual analysis was performed by two blinded speech-language pathologists with GRBAS. The results showed that nearly periodic Type 1 signals were all functional dysphonia and Type 4 signals were comprised of neurogenic and organic voice disorders. Only Type 1 voice signals were reliable for perturbation analysis in this study. Significant signal typing-related differences were found in all acoustic and auditory-perceptual measures. SNR, CPP, L/H ratio values for Type 4 were significantly lower than those of other voice signals and significant higher %jitter, %shimmer were observed in Type 4 voice signals(p<.001). Additionally, with increase of signal type, D2 values significantly increased and more complex and nonlinear patterns were represented. Nevertheless, voice signals with highly noise component associated with breathiness were not able to obtain D2. In particular, CPP, was highly sensitive with voice quality 'G', 'R', 'B' than any other acoustic measures. Thus, Spectral and cepstral analyses may be applied for more severe dysphonic voices such as Type 4 signals and CPP can be more accurate and predictive acoustic marker in measuring voice quality and severity in dysphonia.
Purpose: The purpose of this study was to describe levels of multiple stress factors and depression, and to examine the effects of the stress factors on depression among female marriage immigrants in Korea. Methods: Participants were 322 female marriage immigrants currently residing in Korea, who migrated from China, Vietnam, the Philippines, and other Asian countries. Stress of female marriage immigrants was measured on the SMFMI (Stress Measure of Female Marriage Immigrants in Korea), consisting of 21 items in four factors (cultural, household economic, emotional, and parenting and discrimination stress). CES-D was used to assess depression among marriage immigrants. Descriptive statistics, t-test, ANOVA with Scheffe's post hoc tests, and multiple regressions were performed for data analyses. Results: The average score for stress was 1.34 (SD=.98, theoretical range: 0-4) and the average score for depression was 17.07 (SD=10.09) in these female marriage immigrants. Adjusting for household income, employment status, duration since immigration, and Korean language proficiency, household economic stress (p<.001) was identified as the strongest predictor in explaining depression of female marriage immigrants (Adjusted $R^2=.331$). Conclusion: Health care professionals should prioritize intervention strategies to alleviate household economic stress for mental health promotion in female marriage immigrants in Korea.
Objective: The purpose of this study was to identify genes related to bladder cancer with samples from normal and disease cases by microarray chip. Methods: After downloading the gene expression profile GSE3167 from Gene Expression Omnibus database which includes 50 bladder samples, comprising 9 normal and 41 disease samples, differentially expressed genes were identified with packages in R language. The selected differentially expressed genes were further analyzed using bioinformatics methods. Firstly, molecular functions, biological processes and cell component analysis were researched by software Gestalt. Then, software String was used to search interaction relationships among differentially expressed genes, and hub genes of the network were selected. Finally, by using plugins of software Cytoscape, Mcode and Bingo, module analysis of hub-genes was performed. Results: A total of 221 genes were identified as differentially expressed by comparing normal and disease bladder samples, and a network as well as the hub gene C1QBP was obtained from the network. The C1QBP module had the closest relationship to production of molecular mediators involved in inflammatory responses. Conclusion: We obtained differentially expressed genes of bladder cancer by microarray, and both PRDX2 and YWHAZ in the module with hub gene C1QBP were most significantly related to production of molecular mediators involved in inflammatory responses. From knowledge of inflammatory responses and cancer, our results showed that, the hub gene and its module could induce inflammation in bladder cancer. These related genes are candidate bio-markers for bladder cancer diagnosis and might be helpful in designing novel therapies.
Background: To explore the molecular mechanisms of metastatic osteosarcoma (OS) by using the microarray expression profiles of metastatic and non-metastatic OS samples. Materials and Methods: The gene expression profile GSE37552 was downloaded from Gene Expression Omnibus database, including 2 human metastatic OS cell line models and 2 two non-metastatic OS cell line models. The differentially expressed genes (DEGs) were identified by Multtest package in R language. In addition, functional enrichment analysis of the DEGs was performed by WebGestalt, and the protein-protein interaction (PPI) networks were constructed by Hitpredict, then the signal pathways of the genes involved in the networks were performed by Kyoto Encyclopaedia of Genes and Genomes (KEGG) automatic annotation server (KAAS). Results: A total of 237 genes were classified as DEGs in metastatic OS. The most significant up- and down-regulated genes were A2M (alpha-2-macroglobulin) and BCAN (brevican). The DEGs were significantly related to the response to hormone stimulus, and the PPI network of A2M contained IL1B (interleukin), LRP1 (low-density lipoprotein receptor-related protein 1) and PDGF (platelet-derived growth factor). Furthermore, the MAPK signaling pathway and focal adhesion were significantly enriched. Conclusions: A2M and its interactive proteins, such as IL1B, LRP1 and PDGF may be candidate target molecules to monitor, diagnose and treat metastatic OS. The response to hormone stimulus, MAPK signaling pathway and focal adhesion may play important roles in metastatic OS.
Purpose: Prostate cancer caused by the abnormal disorderly growth of prostatic acinar cells is the most prevalent cancer of men in western countries. We aimed to screen out differentially expressed genes (DEGs) and explore small molecule drugs for prostate cancer. Materials and Methods: The GSE3824 gene expression profile of prostate cancer was downloaded from Gene Expression Omnibus database which including 21 normal samples and 18 prostate cancer cells. The DEGs were identified by Limma package in R language and gene ontology and pathway enrichment analyses were performed. In addition, potential regulatory microRNAs and the target sites of the transcription factors were screened out based on the molecular signature database. In addition, the DEGs were mapped to the connectivity map database to identify potential small molecule drugs. Results: A total of 6,588 genes were filtered as DEGs between normal and prostate cancer samples. Examples such as ITGB6, ITGB3, ITGAV and ITGA2 may induce prostate cancer through actions on the focal adhesion pathway. Furthermore, the transcription factor, SP1, and its target genes ARHGAP26 and USF1 were identified. The most significant microRNA, MIR-506, was screened and found to regulate genes including ITGB1 and ITGB3. Additionally, small molecules MS-275, 8-azaguanine and pyrvinium were discovered to have the potential to repair the disordered metabolic pathways, abd furthermore to remedy prostate cancer. Conclusions: The results of our analysis bear on the mechanism of prostate cancer and allow screening for small molecular drugs for this cancer. The findings have the potential for future use in the clinic for treatment of prostate cancer.
Kim, Hyeon-Seok;Im, Gang-Won;Lee, Yeong-In;Nam, Du-Hui
Journal of Korean Society of Transportation
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v.25
no.4
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pp.109-121
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2007
In this study, an imputation model using circular probability distribution was developed in order to overcome problems of missing data from a traffic survey. The existing ad-hoc or heuristic, model-based and algorithm-based imputation techniques were reviewed through previous studies, and then their limitations for imputing missing traffic volume data were revealed. The statistical computing language 'R' was employed for model construction, and a mixture of von Mises probability distribution, which is classified as symmetric, and unimodal circular probability were finally fitted on the basis of traffic volume data at survey stations in urban and rural areas, respectively. The circular probability distribution model largely proved to outperform a dummy variable regression model in regards to various evaluation conditions. It turned out that circular probability distribution models depict circularity of hourly volumes well and are very cost-effective and robust to changes in missing mechanisms.
KSII Transactions on Internet and Information Systems (TIIS)
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v.14
no.7
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pp.2769-2784
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2020
This paper aims to compare the scenic images of four ancient Chinese cities including Lijiang, Pingyao, Huizhou and Langzhong, so as to provide specific development strategies for the ancient cities. In this paper, the ancient cities' scenic images are divided into three sub-indexes and eight evaluation dimensions. Based on this, the study first uses Python software to collect tourists' online comments on the four ancient cities. Then, the social network analysis method is used to build a high-frequency keywords matrix of tourist comments and the R language is used to generate a visual network graph. After this, the entropy weight method is used to determine the weights and values of eight evaluation dimensions. Finally, the tourists' overall satisfaction indexes of the four ancient cities are calculated accordingly. The results show that (1) the overall satisfaction of Lijiang is the highest, while that of Huizhou is the lowest; (2) from the weight of each evaluation dimension, it can be seen that tourists care more about the national culture and historical culture; (3) from tourists' satisfaction index on each evaluation dimension of the four ancient cities, we can find that the four ancient cities has their own advantages and disadvantages in tourism development. (4) local tourism-related institutions should strengthen their advantages and improve their deficiencies so as to enhance tourists' overall image of the ancient city.
Cam plays very important roles due to continuous requirement for the high-speed and automation of the machinery. A large number of studies of cam curve were carried out by many researchers, and CNC milling and machining center for manufacturing cam have been widely used recently. The purpose of this study was to develop a CAD/CAM system for cam using QuickBasic language in 16-bit PC for application of cam design and manufacturing. Results obtained were as follows : 1. It was possible to input data by entering cam angle and its corresponding R, from 0 to 360 deg. of cam angle. The tediousness at entering data was minimized because of the same data format for both cylindrical cam and disc cam, and free format used for data file. 2. It was possible to design cam by choosing only the number of cam curve because of developing the CAD/CAM program with dimensionless method of cam curves including widely used 19 kinds. After selecting the number of the cam curve, the CAD/CAM system automatically shows the characteristics of cam motion enough to help a designer to decide : displacement, velocity, acceleration and jerk. 3. It was possible to execute, in an efficient way, both the cam profile synthesis and the generation of NC program for CNC machining center by using the input data. 4. This NC program generated by the CAD/CAM system developed here, was evaluated as positive in relation with actual manufacturing experiments and thought to be useful in its application without any modification. It can be said that this CAD/CAM system could be used by the beginners to design and manufacture the cam automatically as the system consists of very simple dialogue methods. In addition, self-developed QuickBasic would be would used as a basic tool for further stuides in this area of research, together with application.
Journal of the Korean Institute of Intelligent Systems
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v.25
no.5
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pp.470-476
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2015
Big data has been used in diverse areas. For example, in computer science and sociology, there is a difference in their issues to approach big data, but they have same usage to analyze big data and imply the analysis result. So the meaningful analysis and implication of big data are needed in most areas. Statistics and machine learning provide various methods for big data analysis. In this paper, we study a process for big data analysis, and propose an efficient methodology of entire process from collecting big data to implying the result of big data analysis. In addition, patent documents have the characteristics of big data, we propose an approach to apply big data analysis to patent data, and imply the result of patent big data to build R&D strategy. To illustrate how to use our proposed methodology for real problem, we perform a case study using applied and registered patent documents retrieved from the patent databases in the world.
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