Method For Quantitative Analysis Research Articles

WHY ARE INTERNATIONAL TOURISTS SATISFIED WITH ECOTOURISM IN THE MEKONG DELTA, VIETNAM?

The satisfaction of tourists plays a crucial role in the success of a tourist destination. This study aims to demonstrate factors influencing the satisfaction of international tourists with ecotourism in the Mekong Delta, Vietnam. The study employs a convenient sampling combined with direct interviews of 256 international tourists who have experienced ecotourism services in the Mekong Delta region of Vietnam. Quantitative analysis methods used in the study include testing the reliability of the scale using Cronbach’s alpha, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and covariance-based structural equation modeling (CB-SEM). The research results have proven 06 factors influencing the satisfaction of international tourists with ecotourism in the Mekong Delta, including trust, responsiveness, assurance, empathy, tangible facilities, and local characteristics. Among these, the local characteristic factor has the most impact on the satisfaction of international tourists with ecotourism in the Mekong Delta. The research results will provide managerial implications to enhance service quality and improve the satisfaction of international tourists with ecotourism in the Mekong Delta region, Vietnam.

Establishment and evaluation of a 3D quantitative analysis method for dental plaque based on an intraoral scanner technique.

Quantitative dental plaque evaluation is necessary for clinical and scientific work. The present study aimed to examine the reliability of a 3D image analysis method by digitally analyzing the color 3D images obtained from an intraoral scanner (IOS) and then detecting and quantifying the plaque information and comparing it with the clinical examination results. A total of 140 teeth from five subjects with a standard dentition were enrolled. Plaque examination was performed at two different time points: after 24 h without oral hygiene (T1), and after habitual brushing (T2). At each time point, the Quigley-Hein Plaque Index (PI) of each tooth surface was recorded separately, followed by color 3D images obtained using an IOS, and image analysis and calculation using Geomagic Wrap 2021 software. The percentage of plaque staining area calculated from the 3D image analysis correlated well with the PI recorded during the clinical examination: the Spearman correlation coefficients were 0.9136 and 0.9061 (P < 0.001) for all tooth surfaces at T1 and T2, respectively. The measurements of the three investigators were in good agreement, with intraclass correlation coefficients of 0.989 and 0.992 (P < 0.001) for the vestibular and lingual surfaces at T1, respectively, and 0.964 and 0.983 (P < 0.001) for the vestibular and lingual surfaces at T2, respectively. In the present study, a digital 3D evaluation system of dental plaque suitable for research and clinical practice was initially developed and its reliability demonstrated.

A modified perturbation method for global dynamic analysis of generalized mixed Rayleigh–Liénard oscillator with cubic and quintic nonlinearities

Deriving analytical relationship between the system parameters and amplitude of the limit cycle is a meaningful and challenging task. Currently, numerous existing analytical approximate methods struggle to achieve this goal when expressions of restoring force or nonlinear damping is complicated. To overcome this shortcoming, this study proposes a modified generalized harmonic function perturbation method. Using the proposed method, a generalized mixed RayleighLiénard oscillator with cubic and quintic nonlinearities was investigated. The analytical relationships between the system parameters and amplitude of the limit cycle, as well as the expression of its characteristic quantity, were derived. By employing these analytical relationships, the existence, stability, number, position, and amplitude of each limit cycle are quantitatively analysed. The homoclinic and heteroclinic bifurcations were also predicted using the above analytical relationships. Additionally, analytical approximate solutions for this oscillator were calculated using the proposed method. All results obtained in this study were subsequently confirmed numerically to demonstrate their feasibility and validity. Consequently, the proposed method can be considered an effective supplement to perturbation-based methods. This also implies that the work presented in this paper has a certain theoretical significance and application value in the research area of quantitative analysis methods for strongly nonlinear oscillators.

Quantitative cellular pathology of the amygdala in temporal lobe epilepsy and correlation with magnetic resonance imaging volumetry, tissue microstructure, and sudden unexpected death in epilepsy risk factors.

Amygdala enlargement can occur in temporal lobe epilepsy, and increased amygdala volume is also reported in sudden unexpected death in epilepsy (SUDEP). Apnea can be induced by amygdala stimulation, and postconvulsive central apnea (PCCA) and generalized seizures are both known SUDEP risk factors. Neurite orientation dispersion and density imaging (NODDI) has recently provided additional information on altered amygdala microstructure in SUDEP. In a series of 24 surgical temporal lobe epilepsy cases, our aim was to quantify amygdala cellular pathology parameters that could predict enlargement, NODDI changes, and ictal respiratory dysfunction. Using whole slide scanning automated quantitative image analysis methods, parallel evaluation of myelin, axons, dendrites, oligodendroglia, microglia, astroglia, neurons, serotonergic networks, mTOR-pathway activation (pS6) and phosphorylated tau (pTau; AT8, AT100, PHF) in amygdala, periamygdala cortex, and white matter regions of interest were compared with preoperative magnetic resonance imaging data on amygdala size, and in 13 cases with NODDI and evidence of ictal-associated apnea. We observed significantly higher glial labeling (Iba1, glial fibrillary acidic protein, Olig2) in amygdala regions compared to cortex and a strong positive correlation between Olig2 and Iba1 in the amygdala. Larger amygdala volumes correlated with lower microtubule-associated protein (MAP2), whereas higher NODDI orientation dispersion index correlated with lower Olig2 cell densities. In the three cases with recorded PCCA, higher MAP2 and pS6-235 expression was noted than in those without. pTau did not correlate with SUDEP risk factors, including seizure frequency. Histological quantitation of amygdala microstructure can shed light on enlargement and diffusion imaging alterations in epilepsy to explore possible mechanisms of amygdala dysfunction, including mTOR pathway activation, that in turn may increase the risk for SUDEP.

EXPLORING AI-BASED TECHNOLOGIES TO IMPROVE STUDENTS’ INSPIRATION IN STUDYING INTERCULTURAL COMMUNICATION - ONE OF THE COMPULSORY SUBJECTS AT THE FACULTY OF ENGLISH – HANOI OPEN UNIVERSITY

These days, chatbots play a crucial role in students' lives and are utilized in various settings. As a result, we are interested in integrating these tools into the teaching process to use their advantages, help and mentor students as they try to avoid problems like plagiarism, and primarily increase students' motivation. The qualitative and quantitative analysis methods have been applied, together with the documents, the result of research works of previous scholars, and results from the questionnaires obtained from 100 students (course 2021-2025) who have studied the subject of Intercultural Communication at the Faculty of English for the academic year 2022-2023. The purpose of this research is to investigate whether using an AI-based chatbot agent as a teaching tool makes students more motivated or not, evaluate the advantages and disadvantages of these conversational chatbots, show how vital chatbots may be for raising student motivation, and improve teaching techniques in the process of studying the subject of Intercultural Communication.

Rapid quantitative analysis of multiple rare earth elements in NdFeB alloys based on laser-induced breakdown spectroscopy (LIBS) and random forest (RF)

NdFeB material has excellent comprehensive magnetic properties, which plays a crucial role in the field of rare earth magnetic materials, and is one of the important basic materials to support modern high-tech industries. In the production of NdFeB alloys, the control of rare earth elements (REEs) is directly related to the quality and resource utilization efficiency of NdFeB materials. Therefore, the prediction of REEs content in NdFeB alloys is of great research significance and application value for the quality control of products, the enhancement of production efficiency and reduction of energy consumption by the rare earth material industry. In this study, a combination of laser-induced breakdown spectroscopy (LIBS) and random forest (RF) was used to investigate the quantitative analysis of four REEs (Nd, Pr, Tb and Dy) in NdFeB alloys. Firstly, the original LIBS spectra were screened by principal component analysis-mahalanobis distance (PCA-MD). Then, the effects of different data processing methods on the screened LIBS spectra were explored, and next, the feature variables were extracted from the preprocessed spectral data by the variable importance measurement (VIM). In order to further verify the prediction performance of the model, the prediction results of the RF models based on the different methods were compared. Finally, a PCA-VIM-RF calibration model was established on the basis of the optimized spectra, selected feature variables and parameters. Leave-one-out cross validation (LOOCV) was used to optimize the parameters of PCA-MD method, spectral preprocessing method and variable importance thresholds during the construction of the calibration model. The results show that the PCA-VIM-RF model has better prediction performance than the RF calibration model based on the raw spectra. For the PCA-VIM-RF calibration method of Nd, Pr, Tb and Dy elements, the values of R2CV are 0.9991, 0.9998, 0.9986, and 0.9984, respectively, the values of RMSECV are 0.06296%, 0.02788%, 0.04647% and 0.05252%, respectively. The values of R2P are 0.9508, 0.9975, 0.9691 and 0.9457, respectively, and the values of RMSEP are 0.6082%, 0.09205%, 0.5776% and 0.2631%, respectively.The above results indicate that LIBS combined with PCA-VIM-RF algorithm is a promising method for rapid quantitative analysis of REEs in NdFeB alloys without complicated sample preparation, which can provide some new ideas or strategies for the future research, development and quality control of rare earth materials.

On Gender Equality in Junior High School English Textbooks: A Case Study of the Chinese PEP Eighth-Grade Textbooks

With the development of society, the consciousness of female subjectivity has gradually awakened, and the issue of gender equality in the field of education has also attracted more and more attentions. Education plays an important role in constructing students’ concept of gender equality, and textbooks, as an important medium for students to receive education, are an important part of promoting educational equality. In addition, the junior high school stage is a critical period for students to develop values, and textbooks, as an educational medium, should help students establish a correct understanding of gender roles. However, previous studies have shown that there is an implicit bias of gender inequality in teaching materials. This study conducts an in-depth study on gender equality in the PEP eighth-grade English textbooks. It adopts the literature review method to sort out the relevant research at home and abroad, and uses the content analysis method to comprehensively analyze the gender roles, illustrations, and language use in the textbooks. It also combines quantitative and qualitative analysis methods to discuss the current situation and causes of gender equality. The study finds that there are gender stereotypes and gender discrimination in textbooks, which have an impact on students’ gender perception and self-perception. Concerning these issues, this paper proposes improvement countermeasures, aiming to promote the fairness of junior high school English education, to help students establish correct gender concepts and self-awareness, and to provide references and suggestions for the compilation of teaching materials.

Quantitative Raman and x-ray photoelectron spectroscopy of mixed-phase indium selenide films

Indium selenide is a polymorphous material system that has attracted considerable attention due to the outstanding electronic, optical, ferroelectric, and antiferroelectric properties of its various crystalline phases; however, this polymorphism adds a layer of complexity to the analysis of Raman and x-ray photoelectron (XPS) data of these materials. In this report, a method of quantitative analysis of combined Raman and XPS data is developed to determine the stoichiometry of indium selenide thin films, as well as the phase fraction of β-In2Se3, γ-In2Se3, and κ-In2Se3 within the films. A 13:1 ratio of the indium to selenium sensitivity factors (σIn/σSe = 13) was found to yield the most accurate stoichiometry results. Further structural characterization of the κ-In2Se3 film was performed and points to its existence in these films as a distinct phase, rather than strained γ-In2Se3.

Probabilistic design and optimization of thermal protection system with variable thickness based on non-uniform aerodynamic heating

Thermal Protection System (TPS) is a critical component of space vehicles to protect them from damage by extreme aerothermal heating conditions. The uncertainty of the aerothermal heating conditions, including approaching velocities, atmospheric density, pressure, etc., significantly affects the aerothermal heating imposed on the TPS, vastly changing the initial design conditions. In this study, we developed a new uncertainty quantitative (UQ) analysis method to comprehensively consider all the uncertainty of TPS materials, structures, and aerothermal heating conditions. To address the challenges of a massive amount of input and determined optimization parameters, we first induced the response surface method and Monte Carlo algorithm to produce a large number of analysis samples for Probabilistic Design. Then, the key affecting factors, not all the input design parameters, were chosen for optimization with sequential optimization and reliability assessment (SORA) strategy by a sensitivity analysis. With such improvements, the optimization for UQ analysis becomes practical. We used this new UQ method to analyze the effects of uncertainty of the aerothermal heating conditions on the thermal protection layer. A variable thickness design is proposed to adapt the non-uniform aerothermal heating conditions for the TPS. The results show that significant light-weighting can be achieved without the reliability penalty. The optimized structure also reduces internal temperature gradients and facilitates a more uniform temperature field distribution for the TPS. This study provides a new UQ engineering design approach for the system with many designed parameters.

Prospects and current scenario of industry 4.0 in Bangladeshi textile and apparel industry

This study aims to explore the scopes and challenges, rank the challenges, and provide strategic solutions for adopting Industry Revolution 4.0 (IR 4.0) in Bangladesh's textile and apparel industry. A random survey was administered to a total of 142 factories in Bangladesh. Both quantitative and qualitative methods of analysis were used in this study. The survey includes questions on important study variables, such as big data, smart factories, cyber-physical systems (CPS), the Internet of Things (IoT), interoperability, textile production, and industry performance. The Variable Destination Multiple Access (VDMA) Model has been adopted to design the questionnaire, focusing on qualitative and quantitative questions. The survey dataset was investigated through SmartPLS 4.0 by normality and confirmatory tests. Likert scale data have been analyzed through IBM SPSS software version 26.0 by the exploratory factor analysis method to rank the IR 4.0 adoption variables. Analysis of the survey data indicates the level of adoption of Industry 4.0 in terms of organizational strategy, investment, infrastructure, IT (Information Technology), Ready Made Garments (RMG) skilled workers, smart operations, and smart factories. The study shows that the variable “Review of the strategy using indicators” got the highest ranking in the external factor, 0.791. This clearly indicates that strategy formulation is the topmost priority among other IR 4.0 adoption variables. Consequently, “digital integration” got the lowest loading at 0.620, as IR 4.0 digital technology adoption is very low. The overall maturity level for IR 4.0 adoption in the Bangladesh textile and apparel industry is 1.91 on a 5-point scale, indicating a low adoption level. This study can help concerned policymakers and industrialists who want to implement Industry 4.0 in the textile and RMG sectors to stay competitive in the global market. Alongside this study, it also summarizes the IR 4.0 adoption level in 9 broad categories.

In vitro evaluation of the percutaneous absorption of progesterone in anhydrous permeation-enhancing base using the Franz skin finite dose model and mass spectrometry

Progesterone is used for hormone replacement therapy through various routes of administration. This study was conducted to (a) evaluate the stability of progesterone in a proprietary anhydrous permeation-enhancing base (APEB) and the efficiency of its skin permeation, and (b) determine the appropriateness of mass spectrometry as a method of analysis for permeated progesterone. Using a proven stability-indicating ultra-performance liquid chromatographic method, the compounded hormone (100 mg progesterone/g APEB gel) was determined to be physically and chemically stable at room temperature for six months. Skin permeation analysis using the Franz skin finite dose model and mass spectrometry imaging showed an optical density of 1699 for the permeated progesterone compounded in APEB and 550 for the permeated progesterone in a water containing VBC, which is a statistically significant different (P = 0.029). The study suggests that APEB can be used as a compounding base for effective skin permeation of progesterone, and mass spectrometry is a reliable method for visualization and quantitative analysis of permeated progesterone.

Quantitative Analysis Method of the Organizational Characteristics and Typical Types of Landscape Spatial Sequences Applied with a 3D Point Cloud Model

(1) Background: Sequential landscape changes give people experiences of dynamic beauty, and the key to creating spatial sequences lies in the organization of spatial changes. The purpose of this study is to use a 3D point cloud model to achieve a refined description of spatial sequences’ organizational characteristics from information acquisition to description and explore the quantitative interpretation methods of typical sequence organizational characteristics. (2) Methods: The proposed model contains three main steps: data acquisition and extraction, characteristic index system construction and data processing, and quantitative characterization analysis. A typology research method that combines quantitative induction with qualitative statistical verification is proposed. (3) Results: Seventy-two spatial sequence point cloud models of study cases are obtained; 4 indicators are established; 3 typical organization types are summarized, namely fluctuating, reversal and moderate type; and the characterization factors and threshold intervals for each sequence organization type are analyzed to validate the type classification result. (4) Conclusions: This research improves the accuracy of spatial data, the comprehensiveness of sequence organization characterization factors, and the reliability of classification results. It supplements the existing spatial sequence theoretical knowledge system and provides parameters that can be referred to in practical design.

Research on batch multi-element rapid quantitative analysis based on standard curve assisted CF-LIBS method

Abstract This paper proposes a batch rapid quantitative analysis method for multi-element by combining the advantages of standard curve (SC) and calibration-free laser induced breakdown spectroscopy (CF-LIBS) technology to achieve synchronous, rapid, and accurate measurement of elements in a large number of samples, namely SC-assisted CF-LIBS. Al alloy standard samples, divided into calibration and test samples, were applied to validate the proposed method. The SC was built on the basis of the characteristic line of Pb, Cr in the calibration sample, and the content of Pb, Cr in the test sample was thereby calculated with a relative error of 6% and 4%, respectively. The SC built by Cr with multiple characteristic lines has better calculation results. The relative contents of 10 elements were calculated by CF-LIBS in the test sample. Subsequently, the SC-assisted CF-LIBS was executed, with the majority of calculation relative errors falling within the range of 2%–5%. Finally, the contents of Al, Na were predicted in the Al alloy. The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multi-element after a single element SC analysis of the tested samples. Furthermore, this quantitative analysis method was successfully applied to soil and astragalus samples, realizing the accurate calculation of the contents of multi-element. It is thus important to advancing LIBS quantitative analysis and its related applications.

ReactomeGSA: new features to simplify public data reuse.

ReactomeGSA is part of the Reactome knowledgebase and one of the leading multi-omics pathway analysis platforms. ReactomeGSA provides access to quantitative pathway analysis methods supporting different 'omics data types. Additionally, ReactomeGSA can process different datasets simultaneously, leading to a comparative pathway analysis that can also be performed across different species. We present a major update to the ReactomeGSA analysis platforms that greatly simplifies the reuse and direct integration of public data. In order to increase the number of available datasets, we developed the new grein_loader Python application that can directly fetch experiments from the GREIN resource. This enabled us to support both EMBL-EBI's Expression Atlas and GEO RNA-seq Experiments Interactive Navigator within ReactomeGSA. To further increase the visibility and simplify the reuse of public datasets, we integrated a novel search function into ReactomeGSA that enables users to search for public datasets across both supported resources. Finally, we completely re-developed ReactomeGSA's web-frontend and R/Bioconductor package to support the new search and loading features, and greatly simplify the use of ReactomeGSA. The new ReactomeGSA web frontend is available at https://www.reactome.org/gsa with an built-in, interactive tutorial. The ReactomeGSA R package (https://bioconductor.org/packages/release/bioc/html/ReactomeGSA.html) is available through Bioconductor and shipped with detailed documentation and vignettes. The grein_loader Python application is available through the Python Package Index (pypi). The complete source code for all applications is available on GitHub at https://github.com/grisslab/grein_loader and https://github.com/reactome.

Impact of Influencer Marketing on Customer Buying Journey: A Study on Global Fashion Brands

The research aimed at assessing the degree of the impact of influencer marketing on the consumer buying journey from the perspective of the global fashion industry. Four factors are identified by the researcher that are affecting the consumer buying journey in the global fashion industry which are enhancing awareness, generating interest, creating desire, and shaping action. The research has followed the conclusive research design, survey research strategy, quantitative data analysis method, simple random sampling technique, primary information source (100 customers of the global fashion industry), positivist philosophy, and regression analysis technique. It determined that influencers are having a 42.2% impact on the consumer buying journey. In every stage of the customer buying journey, influencers are playing an extremely crucial role. However, some recommendations have been given at the end which include picking the appropriate influencer and not controlling the words of influencers.

Media framing on news of the Hartal Doktor Kontrak (HDK) movement in Malaysia: a quantitative content analysis of two Malaysian newspapers

Hartal Doktor Kontrak (HDK) Movement first surfaced in June 2021 following prolonged dissatisfaction towards the contract appointment policy of medical doctors in Malaysia. On the 26th of July 2021, an unprecedented strike (Hartal) was organised by contract doctors across Malaysia. It generated major media attention. This study sought to evaluate how the HDK movement was framed in the mainstream media and to analyse the framing trend in conjunction with the chronology of HDK movement events. A total of 109 news articles in two major national newspapers were analysed from 1st June 2021 until 28th February 2022 using quantitative content analysis method. The five-dimension media frame (responsibility, human interest, conflict, morality, and economic consequences) by Semetko & Valkenburg was applied to determine the trend of media framing. MANOVA test was performed to scrutinise the differences in frame portrayal before and after Hartal. Overall, the responsibility frame was the most used (76.2%) both pre- and post-strike, with the most frequently highlighted items being solutions to the HDK issue and the roles played by the government. The human interest frame and conflict frame followed next, with at least one item of each frame being featured in 33.0 and 32.1% of all news articles. Despite more news articles published post-strike, the aggregate mean scores of all the frames were higher during the pre-strike period, demonstrating how media framing in the earlier period significantly affected the subsequent events of the HDK movement and its impact on the contract appointment policy. In this case, media framing set an agenda for stakeholders to implement necessary policy changes to prevent subsequent strikes and to seek long-term solutions. Lastly, this study presents a novel approach to evaluating certain controversial matters that may not be suitably addressed by the conventional research method such as primary quantitative data collection or qualitative interviews.

CurveMEF: Multi-exposure fusion via curve embedding network

Multi-exposure image fusion (MEF) aims to combine multiple images with different exposures into a single image to improve visual quality and preserve details. This paper proposes a curve embedding network for MEF (CurveMEF), which formulates the MEF task as estimating optimal fusion curves based on state feedback using pixel intensities as state variables. The fusion curve is embedded into CurveNet, a lightweight deep network, as a physical prior constraint. Leveraging the proposed physical informed MEF method, the fusion curve can adaptively adjust the pixel distribution of overexposed and underexposed regions based on the pixel intensities, and distinguish the importance of source images. CurveMEF supports both RGB and luminance channel inputs, demonstrating its flexibility. Experimental results show that CurveMEF achieves competitive performance compared to state-of-the-art methods in both qualitative and quantitative analysis. Moreover, CurveNet requires significantly fewer parameters and training data, enabling fast training and inference. The proposed method delivers high-speed and high-quality fusion while significantly reducing computational, providing an efficient and cost-effective solution. The code is publicly available at: https://github.com/PiratePai/CurveMEF.

Application of the DEMATEL method for quantitative analysis of risk factors for railway investments in Poland.

The paper presents the results of research on the influence of risk factors on the implementation of railway investments in Poland (build stage) and deals with a detailed diagnosis of relation between factors. The application of DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method for the analyses allowed to develop a cause-and-effect model of key factors and analyse the importance of the factors. Eleven factors identified in eariel studies as the most important risk factors were examined. It was found that the factors: errors in the preparation of tender documents (10.38%), errors in project documentation (10.02%), improperly estimated time of completion of the investment by the Employer (9.82%), internal regulations of PKP Polskie Koleje Państwowe S.A. (Polish State Railways) not coordinated with the provisions of contracts (9.51%) have the highest degree of importance. Factors: too many external institutions involved in the investment process and internal regulations of PKP Polskie Koleje Państwowe S.A. (Polish State Railways) not coordinated with the provisions of contracts, have the greatest net impact on the other factors. The relations between the factors and factors importance are valuable knowledge for engineers, enabling the project to be implemented according to the planned schedule and investment cost.

A Novel Approach for the Detection and Severity Grading of Chronic Obstructive Pulmonary Disease Based on Transformed Volumetric Capnography.

Chronic Obstructive Pulmonary Disease (COPD), as the third leading cause of death worldwide, is a major global health issue. The early detection and grading of COPD are pivotal for effective treatment. Traditional spirometry tests, requiring considerable physical effort and strict adherence to quality standards, pose challenges in COPD diagnosis. Volumetric capnography (VCap), which can be performed during natural breathing without requiring additional compliance, presents a promising alternative tool. In this study, the dataset comprised 279 subjects with normal pulmonary function and 148 patients diagnosed with COPD. We introduced a novel quantitative analysis method for VCap. Volumetric capnograms were converted into two-dimensional grayscale images through the application of Gramian Angular Field (GAF) transformation. Subsequently, a multi-scale convolutional neural network, CapnoNet, was conducted to extract features and facilitate classification. To improve CapnoNet's performance, two data augmentation techniques were implemented. The proposed model exhibited a detection accuracy for COPD of 95.83%, with precision, recall, and F1 measures of 95.21%, 95.70%, and 95.45%, respectively. In the task of grading the severity of COPD, the model attained an accuracy of 96.36%, complemented by precision, recall, and F1 scores of 88.49%, 89.99%, and 89.15%, respectively. This work provides a new perspective for the quantitative analysis of volumetric capnography and demonstrates the strong performance of the proposed CapnoNet in the diagnosis and grading of COPD. It offers direction and an effective solution for the clinical application of capnography.

INSUFFICIENT PHYSICAL ACTIVITY AND ITS IMPACT ON NATIONAL ECONOMY AND SECURITY

Healthy and active people not only strengthen the health of the population of Latvia, prolong life in good health, prevent premature mortality, but also make an important contribution to the economic development and security of the country. Unfortunately, Latvia ranks among the last places in a number of areas among the EU member states. Latvian Health and Fitness Association (LVFA) has adapted the “Deloitte Research” global study on the preventive impact of physical activity on the national economy to the circumstances in Latvia, revealing that the Latvian economy suffers significant losses every year due to physically inactivity among the population. Furthermore, insufficient physical fitness also affects the internal and external security of the country. Must be concluded also across the globe governments face rising healthcare costs and the increasing prevalence of lifestyle diseases. This raises questions as to how bet improve the health of populations, while keeping healthcare and security costs under control. The aim of the article is to study the impact of insufficient physical activity on the national economy and security, to recommend directions for policy development in this field, and to propose improvements of the legal framework. Analytical method, comparative method, as well as the method of qualitative and quantitative data analysis were used in the development of the article.