Search results for: background noise statistical modeling

Authors: Mohamed Eltarabily, Abdelazim Negm, Chihiro Yoshimura

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Recently, the pollution of groundwater from the use of nitrogenous fertilizer is at the increase. Also, due to the increase in area under cultivation and regular use of fertilizer in irrigated agriculture, groundwater pollution from agricultural activities is becoming a major concern. Because of the high mobility of Nitrate (NO3-) in soil which is governed by electrostatic processes, particularly anion exclusion, nitrate can be intercepted by shallow subsurface drainage pipe systems and then discharged offsite into streams, rivers, and lakes causing many hazards. In order to solve these environmental problems associated with nitrate, a better understanding of how NO3- moves through the soil profile under flow conditions is required. In the present paper, the results of a comparative study between experimental and numerical modeling of Nitrate transport through a saturated soil column are presented and analyzed. In order to achieve that, three water fluxes densities; 0.008, 0.007, and 0.006 m sec-1 and N concentration rates 10 mol cm-3 were used. The same concentrations were used in the simulation using HYDRUS-2D. The physical and chemical properties of the collected soil samples were calculated. Besides, the soil texture was determined which was silty sand. Results showed that HYDRUS-2D can successfully predict the relative behavior of N transport in the present experiment. Nitrate concentrations will reach deeper depth with the increase in the water flux. Overall, it was overestimated in the final concentration of (NO3-) in the soil by numerical simulation than by experimental column test. The column experiment is a useful tool for assessing the nitrate concentrations in the soil profile.

Keywords: groundwater, nitrate leaching, HYDRUS-2D, soil column

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Authors: Orkide Donma, Mustafa M. Donma

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Morbid obesity is a health threatening condition particularly in children. Generally, it leads to the development of metabolic syndrome (MetS) characterized by central obesity, elevated fasting blood glucose (FBG), triglyceride (TRG), blood pressure values and suppressed high density lipoprotein cholesterol (HDL-C) levels. However, some ambiguities exist during the diagnosis of MetS in children below 10 years of age. Therefore, clinicians are in the need of some surrogate markers for the laboratory assessment of pediatric MetS. In this study, the aim is to develop an index, which will be more helpful during the evaluation of further risks detected in morbid obese (MO) children. A total of 235 children with normal body mass index (N-BMI), with varying degrees of obesity; overweight (OW), obese (OB), MO as well as MetS participated in this study. The study was approved by the Institutional Ethical Committee. Informed consent forms were obtained from the parents of the children. Obesity states of the children were classified using BMI percentiles adjusted for age and sex. For the purpose, tabulated data prepared by WHO were used. MetS criteria were defined. Systolic and diastolic blood pressure values were measured. Parameters related to glucose and lipid metabolisms were determined. FBG, insulin (INS), HDL-C, TRG concentrations were determined. Diagnostic Obesity Notation Model Assessment Laboratory (DONMA_LAB) Index [ln TRG/HDL-C*INS] was introduced. Commonly used insulin resistance (IR) indices such as Homeostatic Model Assessment for IR (HOMA-IR) as well as ratios such as TRG/HDL-C, TRG/HDL-C*INS, HDL-C/TRG*INS, TRG/HDL-C*INS/FBG, log, and ln versions of these ratios were calculated. Results were interpreted using statistical package program (SPSS Version 16.0) for Windows. The data were evaluated using appropriate statistical tests. The degree for statistical significance was defined as 0.05. 35 N, 20 OW, 47 OB, 97 MO children and 36 with MetS were investigated. Mean ± SD values of TRG/HDL-C were 1.27 ± 0.69, 1.86 ± 1.08, 2.15 ± 1.22, 2.48 ± 2.35 and 4.61 ± 3.92 for N, OW, OB, MO and MetS children, respectively. Corresponding values for the DONMA_LAB index were 2.17 ± 1.07, 3.01 ± 0.94, 3.41 ± 0.93, 3.43 ± 1.08 and 4.32 ± 1.00. TRG/HDL-C ratio significantly differed between N and MetS groups. On the other hand, DONMA_LAB index exhibited statistically significant differences between N and all the other groups except the OW group. This index was capable of discriminating MO children from those with MetS. Statistically significant elevations were detected in MO children with MetS (p < 0.05). Multiple parameters are commonly used during the assessment of MetS. Upon evaluation of the values obtained for N, OW, OB, MO groups and for MO children with MetS, the [ln TRG/HDL-C*INS] value was unique in discriminating children with MetS.

Keywords: children, index, laboratory, metabolic syndrome, obesity

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Authors: Praveena Sinha

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Context: Diabetes is a global public health burden, particularly affecting postmenopausal women. Insulin resistance (IR) is prevalent in this population, and it is associated with an increased risk of developing type 2 diabetes. Yoga therapy is gaining attention as a complementary intervention for diabetes due to its potential to address stress psychophysiology. This study focuses on the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Research Aim: The aim of this research is to investigate the effect of a 3-month long yoga practice on insulin resistance in early postmenopausal women. Methodology: The study conducted a prospective longitudinal design with 67 women within five years of menopause. Participants were divided into two groups based on their willingness to join yoga. The Yoga group (n = 37) received routine gynecological management along with an integrated yoga module, while the Non-Yoga group (n = 30) received only routine management. Insulin resistance was measured using the homeostasis model assessment of insulin resistance (HOMA-IR) method before and after the intervention. Statistical analysis was performed using GraphPad Prism Version 5 software, with statistical significance set at P < 0.05. Findings: The results indicate a significant decrease in serum fasting insulin levels and HOMA-IR measurements in the Yoga group, although the decrease did not reach statistical significance. In contrast, the Non-Yoga group showed a significant rise in serum fasting insulin levels and HOMA-IR measurements after 3 months, suggesting a detrimental effect on insulin resistance in these postmenopausal women. Theoretical Importance: This study provides evidence that a 12-week yoga practice can attenuate the increase in insulin resistance in early postmenopausal women. It highlights the potential of yoga as a preventive measure against the early onset of insulin resistance and the development of type 2 diabetes mellitus. Regular yoga practice can be a valuable tool in addressing hormonal imbalances associated with early postmenopause, leading to a decrease in morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in this population. Data Collection and Analysis Procedures: Data collection involved measuring serum fasting insulin levels and calculating HOMA-IR. Statistical analysis was performed using GraphPad Prism Version 5 software, and mean values with standard error of the mean were reported. The significance level was set at P < 0.05. Question Addressed: The study aimed to address whether a 3-month long yoga practice could attenuate insulin resistance in early postmenopausal women. Conclusion: The research findings support the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Regular yoga practice has the potential to prevent the early onset of insulin resistance and the development of type 2 diabetes mellitus in this population. By addressing the hormonal imbalances associated with early post menopause, yoga could significantly decrease morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in these subjects.

Keywords: post menopause, insulin resistance, HOMA-IR, yoga, type 2 diabetes mellitus

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Authors: Carla Maria Furuno Rimkus

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The technologies related to virtual reality and augmented reality in combination with mobile technologies, are being more consolidated and used each day. The increasing technological availability along with the decrease of their acquisition and maintenance costs, have favored the expansion of its use in the field of historic heritage. In this context it is focused, in this article, on the potential of mobile applications in the dissemination of the architectural heritage, using the technology of Augmented Reality. From this perspective approach, it is discussed about the process of producing an application for mobile devices on the Android platform, which combines the technologies of geometric modeling with augmented reality (AR) and access to interactive multimedia contents with cultural, social and historic information of the historic building that we take as the object of study: a block with a set of buildings built in the XVIII century, known as "Quarteirão dos Trapiches", which was modeled in 3D, coated with the original texture of its facades and displayed on AR. From this perspective approach, this paper discusses about methodological aspects of the development of this application regarding to the process and the project development tools, and presents our considerations on methodological aspects of developing an application for the Android system, focused on the dissemination of the architectural heritage, in order to encourage the tourist potential of the city in a sustainable way and to contribute to develop the digital documentation of the heritage of the city, meeting a demand of tourists visiting the city and the professionals who work in the preservation and restoration of it, consisting of architects, historians, archaeologists, museum specialists, among others.

Keywords: augmented reality, architectural heritage, geometric modeling, mobile applications

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Lebeza Alemu Tenaw, Fei Wan Ngai

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Background: Postpartum depression is the most common mental health disorder that occurs after childbirth, and it is more prevalent among teenage mothers compared to adults. Although there is emerging evidence suggesting psychosocial interventions can decrease postpartum depression, there are no consistent findings regarding the effectiveness of these interventions, especially for teenage mothers. The current review aimed to investigate the effectiveness of psychosocial interventions in preventing postpartum depression among teenage mothers. Methods: The Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) manual was implemented to select articles from online databases. The articles were searched using the Population, Intervention, Control, and Outcome (PICO) model. The quality of the articles was assessed using the Cochrane Collaboration Risk of Bias assessment tool. The statistical analyses were performed using Stata 17, and the effect size was estimated using the standard mean difference score of depression between the intervention and control groups. Heterogeneity between the studies was assessed through the I2 statistic and Q statistic, while the publication bias was evaluated using the asymmetry of the funnel plot and Egger's test. Results: In this systematic review, a total of nine articles were included. While psychosocial interventions demonstrated in reducing the risk of postpartum depression compared to usual maternal care, it is important to note that the mean difference score of depression was significant in only three of the included studies. The overall meta-analysis finding revealed that psychosocial interventions were effective in preventing postpartum depression, with a pooled effect size of -0.5 (95% CI: -0.95, -0.06) during the final time postpartum depression assessment. The heterogeneity level was found to be substantial, with an I2 value of 82.3%. However, no publication bias was observed. Conclusion: The review findings suggest that psychosocial interventions initiated during the late antenatal and early postnatal periods effectively prevent postpartum depression. The interventions were found to be more beneficial during the first three months of the postpartum period. However, this review also highlighted that there is a scarcity of interventional studies conducted in low-income countries, indicating the need for further studies in diverse communities.

Keywords: teenage pregnancy, postpartum depression, review

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Authors: Mohamed Ali Abdennadher

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Digital rock physics, an emerging field leveraging advanced imaging and numerical techniques, offers a promising approach to investigating the mechanical properties of granular materials without extensive physical experiments. This study focuses on using X-Ray Computed Tomography (CT) to capture the three-dimensional (3D) structure of coarse-grained soil at the particle level, combined with finite element analysis (FEA) to simulate the soil's behavior under compression. The primary goal is to establish a reliable virtual testing framework that can replicate laboratory results and offer deeper insights into soil mechanics. The methodology involves acquiring high-resolution CT scans of coarse-grained soil samples to visualize internal particle morphology. These CT images undergo processing through noise reduction, thresholding, and watershed segmentation techniques to isolate individual particles, preparing the data for subsequent analysis. A custom Python script is employed to extract particle shapes and conduct a statistical analysis of particle size distribution. The processed particle data then serves as the basis for creating a finite element model comprising approximately 500 particles subjected to one-dimensional compression. The FEA simulations explore the effects of mesh refinement and friction coefficient on stress distribution at grain contacts. A multi-layer meshing strategy is applied, featuring finer meshes at inter-particle contacts to accurately capture mechanical interactions and coarser meshes within particle interiors to optimize computational efficiency. Despite the known challenges in parallelizing FEA to high core counts, this study demonstrates that an appropriate domain-level parallelization strategy can achieve significant scalability, allowing simulations to extend to very high core counts. The results show a strong correlation between the finite element simulations and laboratory compression test data, validating the effectiveness of the virtual experiment approach. Detailed stress distribution patterns reveal that soil compression behavior is significantly influenced by frictional interactions, with frictional sliding, rotation, and rolling at inter-particle contacts being the primary deformation modes under low to intermediate confining pressures. These findings highlight that CT data analysis combined with numerical simulations offers a robust method for approximating soil behavior, potentially reducing the need for physical laboratory experiments.

Keywords: X-Ray computed tomography, finite element analysis, soil compression behavior, particle morphology

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Authors: Marzena Trojanczyk, Mariusz Jaworski, Ewa Dmoch Gajzlerska

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Purpose: The purpose of this paper is to assess the relationship between the level of quality of life and willingness to take treatment in patients with eating disorders as anorexia, bulimia and compulsive bingeing. Material and methods: The subjects consisted of 99 women with eating disorders: anorexia, n = 33; bulimia, n = 35; compulsive overeating, n = 31 and 35 women in the control group. The study used an original questionnaire to assess the overall quality of life, as well as selected areas of the physical, mental, social and spiritual satisfaction. The subjects were also asked about the level of motivation for treatment, and the importance of the disease in the lives of patients. Statistical analyses were performed using the statistical program SPSS 18.0. Results: Women with eating disorders in particular groups did not differ with respect to each other in the aspect of overall quality of life, satisfaction with the development of the spiritual, social functioning and mental health. The severity level of the disease in the lives of patients showed a negative correlation with social functioning in women with anorexia nervosa. In the case of patients with compulsive bingeing a positive relationship between the level of importance of the disease and the satisfaction of spiritual development is reported. Conclusions: Concerning the inferior quality of life, there is no relationship between a willingness to take treatment and the importance of the disease in the lives of patients with anorexia, bulimia and compulsive bingeing.

Keywords: anorexia, bulimia, compulsive overeating, quality of life

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Authors: Julia Desiree Velastegui Caceres, Luis Alejandro Velastegui Caceres, Oswaldo Padilla, Eduardo Kirby, Francisco Guerrero, Theofilos Toulkeridis

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It is fundamental to conserve sites of natural and cultural heritage with any available technique or existing methodology of preservation in order to sustain them for the following generations. We propose a further skill to protect the actual view of such sites, in which with high technology instrumentation we are able to digitally preserve natural and cultural heritages applied in Ecuador. In this project the use of laser technology is presented for three-dimensional models, with high accuracy in a relatively short period of time. In Ecuador so far, there are not any records on the use and processing of data obtained by this new technological trend. The importance of the project is the description of the methodology of the laser scanner system using the Faro Laser Scanner Focus 3D 120, the method for 3D modeling of geospatial data and the development of virtual environments in the areas of Cultural and Natural Heritage. In order to inform users this trend in technology in which three-dimensional models are generated, the use of such tools has been developed to be able to be displayed in all kinds of digitally formats. The results of the obtained 3D models allows to demonstrate that this technology is extremely useful in these areas, but also indicating that each data campaign needs an individual slightly different proceeding starting with the data capture and processing to obtain finally the chosen virtual environments.

Keywords: laser scanner system, 3D model, cultural heritage, natural heritage

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Authors: Chansheng He, Zhongfu Wang, Xiao Bai, Jie Tian, Xin Jin

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Heterogeneity of soil hydraulic properties directly affects hydrological processes at different scales. Understanding heterogeneity of soil hydraulic properties such as soil moisture is therefore essential for modeling watershed ecohydrological processes, particularly in hard to access, topographically complex mountainous watersheds. This study maps spatial variations of soil moisture by in situ observation network that consists of sampling points, zones, and tributaries, and monitors corresponding hydrological variables of air and soil temperatures, evapotranspiration, infiltration, and runoff in the Upper Reach of the Heihe River Watershed, a second largest inland river (terminal lake) with a drainage area of over 128,000 km² in Northwest China. Subsequently, the study uses a hydrological model, SWAT (Soil and Water Assessment Tool) to simulate the effects of heterogeneity of soil moisture on watershed hydrological processes. The spatial clustering method, Full-Order-CLK was employed to derive five soil heterogeneous zones (Configuration 97, 80, 65, 40, and 20) for soil input to SWAT. Results show the simulations by the SWAT model with the spatially clustered soil hydraulic information from the field sampling data had much better representation of the soil heterogeneity and more accurate performance than the model using the average soil property values for each soil type derived from the coarse soil datasets. Thus, incorporating detailed field sampling soil heterogeneity data greatly improves performance in hydrologic modeling.

Keywords: heterogeneity, soil moisture, SWAT, up-scaling

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Authors: Michael A. Kraus, Navid Pourmoghaddam, Martin Botz, Jens Schneider, Geralt Siebert

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Fragmentation analysis of tempered glass gives insight into the quality of the tempering process and defines a certain degree of safety as well. Different standard such as the European EN 12150-1 or the American ASTM C 1048/CPSC 16 CFR 1201 define a minimum number of fragments required for soda-lime safety glass on the basis of fragmentation test results for classification. This work presents an approach for the glass breakage pattern prediction using a Voronoi Tesselation over Random Fields. The random Voronoi tessellation is trained with and validated against data from several breakage patterns. The fragments in observation areas of 50 mm x 50 mm were used for training and validation. All glass specimen used in this study were commercially available soda-lime glasses at three different thicknesses levels of 4 mm, 8 mm and 12 mm. The results of this work form a Bayesian framework for the training and prediction of breakage patterns of tempered soda-lime glass using a Voronoi Random Field Tesselation. Uncertainties occurring in this process can be well quantified, and several statistical measures of the pattern can be preservation with this method. Within this work it was found, that different Random Fields as basis for the Voronoi Tesselation lead to differently well fitted statistical properties of the glass breakage patterns. As the methodology is derived and kept general, the framework could be also applied to other random tesselations and crack pattern modelling purposes.

Keywords: glass breakage predicition, Voronoi Random Field Tessellation, fragmentation analysis, Bayesian parameter identification

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Authors: Zsuzsanna Schnell, Francesca Ervas

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Background: Our study aims to clarify how language fosters further cognitive development and how we eventually arrive at the complex human specific skill of pragmatic competence and reveal what levels of mentalization and theory of mind are in place before language. Method: Our experimental pragmatic investigation maps the interaction of mentalization and pragmatic competence. We map the different levels of mentalization that empower different levels of pragmatic meaning construction and evaluate the results with statistical analysis (MannWhitney and ANOVA). Analyzing the comprehension of literal and non-compositional (figurative) utterances, we apply linguistic trials, among them metaphor-, irony-, irony with surface cue-, humor- and the recognition of maxim infringements trial in neurotypical (NT) preschoolers with a coherent and comparative methodology. Results: The findings reveal the relationship and direction of interaction between Language and theory of mind. On the one hand social-cognitive skills enhance, facilitate and provide a basis for language acquisition, and in return linguistic structures (DeVilliers 2000, 2007) provide a framework for further development of mentalizing skills. Conclusions: Findings confirm that this scaffolding becomes a mutually supportive system where language and social cognition develops in interaction. Certain stages in ToM development serve as a precursor of understanding grammatically complex sentences, like embedded phrases which mirror embedded mental states; which, in turn, facilitates the development of pragmatic competence, thus, the social use of language, integrating social, cognitive, linguistic and psychological factors in discourse. Future implications: Our investigation functions as a differential-diagnostic measure, with typically developing results thus serve as a baseline in further empirical research for atypical cases. This enables the study of populations where language and ToM development is disturbed, reveals how language and ToM are acquired and interact, and gives an insight into what this has to do with clinical symptoms. This in turn can reveal the causal link to the syndrome at hand, which can set directions for therapeutic development and training.

Keywords: theory of mind, language development, mentalization, language philosophy, experimental pragmatics

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Authors: Abimbola M. Enitan, J. Adeyemo

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Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.

Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling

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Authors: Oleg Reva, Ilya Korotetskiy, Marina Lankina, Murat Kulmanov, Aleksandr Ilin

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Molecular docking approaches are widely used for design of new antibiotics and modeling of antibacterial activities of numerous ligands which bind specifically to active centers of indispensable enzymes and/or key signaling proteins of pathogens. Widespread drug resistance among pathogenic microorganisms calls for development of new antibiotics specifically targeting important metabolic and information pathways. A generally recognized problem is that almost all molecular targets have been identified already and it is getting more and more difficult to design innovative antibacterial compounds to combat the drug resistance. A promising way to overcome the drug resistance problem is an induction of reversion of drug resistance by supplementary medicines to improve the efficacy of the conventional antibiotics. In contrast to well established computer-based drug design, modeling of drug resistance reversion still is in its infancy. In this work, we proposed an approach to identification of compensatory genetic variants reducing the fitness cost associated with the acquisition of drug resistance by pathogenic bacteria. The approach was based on an analysis of the population genetic of Mycobacterium tuberculosis and on results of experimental modeling of the drug resistance reversion induced by a new anti-tuberculosis drug FS-1. The latter drug is an iodine-containing nanomolecular complex that passed clinical trials and was admitted as a new medicine against MDR-TB in Kazakhstan. Isolates of M. tuberculosis obtained on different stages of the clinical trials and also from laboratory animals infected with MDR-TB strain were characterized by antibiotic resistance, and their genomes were sequenced by the paired-end Illumina HiSeq 2000 technology. A steady increase in sensitivity to conventional anti-tuberculosis antibiotics in series of isolated treated with FS-1 was registered despite the fact that the canonical drug resistance mutations identified in the genomes of these isolates remained intact. It was hypothesized that the drug resistance phenotype in M. tuberculosis requires an adjustment of activities of many genes to compensate the fitness cost of the drug resistance mutations. FS-1 cased an aggravation of the fitness cost and removal of the drug-resistant variants of M. tuberculosis from the population. This process caused a significant increase in genetic heterogeneity of the Mtb population that was not observed in the positive and negative controls (infected laboratory animals left untreated and treated solely with the antibiotics). A large-scale search for linkage disequilibrium associations between the drug resistance mutations and genetic variants in other genomic loci allowed identification of target proteins, which could be influenced by supplementary drugs to increase the fitness cost of the drug resistance and deprive the drug-resistant bacterial variants of their competitiveness in the population. The approach will be used to improve the efficacy of FS-1 and also for computer-based design of new drugs to combat drug-resistant infections.

Keywords: complete genome sequencing, computational modeling, drug resistance reversion, Mycobacterium tuberculosis

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Authors: Jim J. Catina, Jackee M. Gwynn, Jin S. Kang

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Additive manufacturing (AM) for hybrid rocket engines is becoming increasingly attractive due to its ability to create complex grain configurations with improved regression rates when compared to cast grains. However, the presence of microvoids in parts produced through the additive manufacturing method of Fused Deposition Modeling (FDM) results in a lower fuel density and is believed to cause a decrease in regression rate compared to ideal performance. In this experiment, FDM was used to create hybrid rocket fuel grains with a star configuration composed of acrylonitrile butadiene styrene (ABS). Testing was completed to determine the effect of heat treatment as a post-processing method to improve the combustion performance of hybrid rocket fuel grains manufactured by FDM. For control, three ABS star configuration grains were printed using FDM and hot fired using gaseous oxygen (GOX) as the oxidizer. Parameters such as thrust and mass flow rate were measured. Three identical grains were then heat treated to varying degrees and hot fired under the same conditions as the control grains. This paper will quantitatively describe the amount of improvement in engine performance as a result of heat treatment of the AM hybrid fuel grain. Engine performance is measured in this paper by specific impulse, which is determined from the thrust measurements collected in testing.

Keywords: acrylonitrile butadiene styrene, additive manufacturing, fused deposition modeling, heat treatment

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Authors: Xue Junwei

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In the global economy, multinational corporations face challenges due to cultural differences impacting consumer behavior. Understanding these influences is vital for effective business decisions in the Chinese market. This study aims to analyze how cultural differences affect consumer behavior when multinational corporations enter the Chinese market, using cultural dimensions theory to derive marketing mix strategies. The study employs statistical analysis of cultural dimensions to investigate the impact on consumer behavior and derive marketing strategies for multinational corporations entering the Chinese market. Furthermore, this study enhances the study by incorporating qualitative data to complement the statistical analysis, providing a more comprehensive understanding of cultural impacts on consumer behavior. The study reveals significant implications of cultural differences on consumer behavior and provides insights into tailored marketing mix strategies for multinational corporations in the Chinese market. This research contributes to the theoretical understanding of how cultural dimensions influence consumer behavior and provides practical implications for multinational corporations entering the Chinese market. Data on cultural dimensions are collected and analyzed statistically and qualitatively to understand their impact on consumer behavior and derive effective marketing strategies. This study concludes that cultural differences have a profound impact on consumer behavior in the Chinese market, and understanding these nuances is crucial for the success of multinational corporations. Tailored marketing strategies are essential for navigating these cultural challenges.

Keywords: marketing, multinational company, globalization, cultural differences

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Authors: Muhammad Asif Syed, Mirza Amir Baig

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Background: Pakistan is one of the two remaining polio-endemic countries, posing a significant public health challenge for global polio eradication due to failure to interrupt polio transmission. Country specific seroprevalence studies help in the evaluation of immunization program performance, the susceptibility of population against polio virus and identification of existing level of immunity with factors that affect seroconversion of the oral polio vaccine (OPV). The objective of the study was to find out factors associated with seroconversion of the OPV among children 6-59 months in Pakistan. Methods: A Hospital based cross-sectional serosurvey was undertaken in May-June 2015 at District Mirpurkhas, Sindh-Pakistan. Total 180 children aged 6–59 months were selected by using systematic random sampling from Muhammad Medical College Hospital, Mirpurkhas. Demographic, vaccination history and risk factors information were collected from the parents/guardian. Blood sample was collected and tested for the detection of poliovirus IgG antibodies by using ELISA Kit. The IgG titer <10 IU/ml, 50 to <150 IU/ml and >150 IU/ml was defined as negative, weak positive and positive immunity respectively. Pearson Chi-square test was used to determine the difference in seroprevalence in univariate analysis. Results: A total of 180 subjects were enrolled mean age was 23 months (7 -59 months). Off these 160 (89%) children were well and 18 (10%) partially protected against polio virus. Two (1.1%) children had no protection against polio virus as they had <10 IU/ml poliovirus IgG antibodies titer. Both negative cases belong from the female gender, age group 12-23 months, urban area and BMI <50 percentile. There was a difference between normal and the wasting children; it did attain statistical significance (χ2= 35.5, p=0.00). The difference in seroconversion was also observed in relation to the gender (χ2=6.23, p=0.04), duration of breast feeding (χ2=18.6, p=0.04), history of diarrheal disease before polio vaccine administration (χ2=7.7, p=0.02), and stunting (χ2= 114, p=0.00). Conclusion: This study demonstrated that near 90% children achieve seroconversion of OPV and well protected against polio virus. There is an urgent need to focus on factors like duration of breast feeding, diarrheal diseases and malnutrition (acute and chronic) among the children as an immunization strategy.

Keywords: seroconversion, oral polio vaccine, Polio, Pakistan

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Authors: T. Yu, L. Audibert, J. F. Chaix, D. Komatitsch, V. Garnier, J. M. Henault

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Linear Ultrasonic Techniques play a major role in Non-Destructive Evaluation (NDE) for civil engineering structures in concrete since they can meet operational requirements. Interpretation of ultrasonic measurements could be improved by a better understanding of ultrasonic wave propagation in a multiple scattering medium. This work aims to develop a 2D numerical model of ultrasonic wave propagation in a heterogeneous medium, like concrete, integrating the multiple scattering phenomena in SPECFEM software. The coherent field of multiple scattering is obtained by averaging numerical wave fields, and it is used to determine the effective phase velocity and attenuation corresponding to an equivalent homogeneous medium. First, this model is applied to one scattering element (a cylinder) in a homogenous medium in a linear-elastic system, and its validation is completed thanks to the comparison with analytical solution. Then, some cases of multiple scattering by a set of randomly located cylinders or polygons are simulated to perform parametric studies on the influence of frequency and scatterer size, concentration, and shape. Also, the effective properties are compared with the predictions of Waterman-Truell model to verify its validity. Finally, the mortar viscoelastic behavior is introduced in the simulation in order to considerer the dispersion and the attenuation due to porosity included in the cement paste. In the future, different steps will be developed: The comparisons with experimental results, the interpretation of NDE measurements, and the optimization of NDE parameters before an auscultation.

Keywords: attenuation, multiple-scattering medium, numerical modeling, phase velocity, ultrasonic measurements

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Authors: Behzad Hajalilou, Nasim Hajalilou, Saeid Ansari

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The study area is located in East Azerbaijan province, north of Ahar city, and 1/100000 geological map of Varzgan. This region is located in the middle of Iran zone. Ali Javad Porphyry copper-gold ore deposit has been created in a magmatic complex containing intrusive masses, combining Granodiorite and quartz Monzonite that penetrates into the Eocene volcanic aggregate. The most important mineralization includes primary oxides minerals (magnetite), sulfide (pyrite, chalcopyrite, Molybdenite, Bornite, Chalcocite, Covollite), secondary oxide or hydroxide minerals (hematite, goethite, limonite), and carbonate (malachite and Azurite). The mineralization forms into the vein-veinlets and scattered system. The alterations observed in the region include intermediate Argillic, advanced Argillic, Phyllic, silica, Propylitic, chlorite and Potassic. The 3D model of mineralization of the Alijavad is provided by Data DATAMINE software and based on the study of 700 polished sections of 32 drilled boreholes in the region. This model is completely compatible with the model provided by Lowell and Gilbert for the mineralization of porphyry copper deposits of quartz Monzonite type. The estimated cumulative residual value of copper for Ali Javad deposit is 81.5 million tons with 0.75 percent of copper, and for gold is 8.37 million tons with 1.8 ppm.

Keywords: porphyry copper, mineralization, Ali Javad, modeling, reserve estimation

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Authors: Suzan Duygu Bedir Erişti

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The present study tried to make a general evaluation of the dissertations conducted in the last decade in the field of art education in the Department of Fine Arts Education in the Institutes of Education Sciences in Turkey. In the study, most of the universities which involved an Institute of Education Sciences within their bodies in Turkey were reached. As a result, a total of a hundred dissertations conducted in the departments of Fine Arts Education at several universities (Anadolu, Gazi, Ankara, Marmara, Dokuz Eylul, Ondokuz Mayıs, Selcuk and Necmettin Erbakan) were determined via the open access systems of universities as well as via the Thesis Search System of Higher Education Council. Most of the dissertations were reached via the latter system, and in cases of failure, the dissertations were reached via the former system. Consequently, most of the dissertations which did not have any access restriction and which had appropriate content were reached. The dissertations reached were examined based on document analysis in terms of their research topics, research paradigms, contents, purposes, methodologies, data collection tools, and analysis techniques. The dissertations conducted in institutes of Education Sciences could be said to have demonstrated a development, especially in recent years with respect to their qualities. It was also found that a great majority of the dissertations were carried out at Gazi University and Marmara University and that a similar number of dissertations were conducted in other universities. When all the dissertations were taken into account, in general, they were found to differ a lot in their subject areas. In most of the dissertations, the quantitative paradigm was adopted, while especially in recent years, more importance has been given to methods based on the qualitative paradigm. In addition, most of the dissertations conducted with quantitative paradigm were structured based on the general survey model and experimental research model. In terms of statistical techniques, university-focused approaches were used. In some universities, advanced statistical techniques were applied, while in some other universities, there was a moderate use of statistical techniques. Most of the studies produced results generalizable to the levels of postgraduate education and elementary school education. The studies were generally structured in face-to-face teaching processes, while some of them were designed in environments which did not include results generalizable to the face-to-face education system. In the present study, it was seen that the dissertations conducted in the departments of Fine Arts Education at the Institutes of Education Sciences in Turkey did not involve application-based approaches which included art-based or visual research in terms of either research topic or methodology.

Keywords: fine arts education, dissertations, evaluation of dissertations, research trends in fine arts education

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Authors: Latif Adnane, Benaatou Wafa, Pla Vicent

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Handover is of great significance to achieve seamless connectivity in wireless networks. This paper gives an impression of the main factors which are being affected by the soft and the hard handovers techniques. To know and understand the handover process in The Universal Mobile Telecommunications System (UMTS) network, different statistics are calculated. This paper focuses on the quality of service (QoS) of soft and hard handover in UMTS network, which includes the analysis of received power, signal to noise radio, throughput, delay traffic, traffic received, delay, total transmit load, end to end delay and upload response time using OPNET simulator.

Keywords: handover, UMTS, mobility, simulation, OPNET modeler

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Authors: Martin Kittel, Alexander Roth

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The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

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Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

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The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

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Authors: Eva L. Sanjuán, Jacinto Martín, M. Isabel Parra, Mario M. Pizarro

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In Extreme Value Theory, inference estimation for the parameters of the distribution is made employing a small part of the observation values. When block maxima values are taken, many data are discarded. We developed a new Bayesian inference model to seize all the information provided by the data, introducing informative priors and using the relations between baseline and limit parameters. Firstly, we studied the accuracy of the new model for three baseline distributions that lead to a Gumbel extreme distribution: Exponential, Normal and Gumbel. Secondly, we considered mixtures of Normal variables, to simulate practical situations when data do not adjust to pure distributions, because of perturbations (noise).

Keywords: bayesian inference, extreme value theory, Gumbel distribution, highly informative prior

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Authors: Filipa Cortez, Vanessa Pereira

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Introduction: The main challenge of obesity treatment is long-term weight loss maintenance. The 3 phases method is a weight loss program that combines a low carb and moderately high-protein diet, food supplements and a weekly one-to-one consultation with a certified nutritionist. Sustained weight control is the ultimate goal of phase 3. Success criterion was the minimum loss of 10% of initial weight and its maintenance after 12 months. Objective: The aim of this study was to identify factors associated with successful weight loss maintenance after 12 months at the end of 3 phases method. Methods: The study included 199 subjects that achieved their weight loss goal (phase 3). Weight and body mass index (BMI) were obtained at the baseline and every week until the end of the program. Therapeutic adherence was measured weekly on a Likert scale from 1 to 5. Subjects were considered in compliance with nutritional recommendation and supplementation when their classification was ≥ 4. After 12 months of the method, the current weight and number of previous weight-loss attempts were collected by telephone interview. The statistical significance was assumed at p-values < 0.05. Statistical analyses were performed using SPSS TM software v.21. Results: 65.3% of subjects met the success criterion. The factors which displayed a significant weight loss maintenance prediction were: greater initial percentage weight loss (OR=1.44) during the weight loss intervention and a higher number of consultations in phase 3 (OR=1.10). Conclusion: These findings suggest that the percentage weight loss during the weight loss intervention and the number of consultations in phase 3 may facilitate maintenance of weight loss after the 3 phases method.

Keywords: obesity, weight maintenance, low-carbohydrate diet, dietary supplements

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Authors: S. Blanchard, D. Beladjine, K. Beddiar

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Since 2015, the arrival of BIM in the building sector in France has turned the corporation world upside down. Not only constructive practices have been impacted, but also the uses and the men who have undergone important changes. Thus, the new collaborative mode generated by the BIM and the digital model has challenged the supremacy of some construction actors because the process involves working together taking into account the needs of other contributors. New BIM tools have emerged and actors in the act of building must take ownership of them. It is in this context that under the impetus of a European directive and the French government's encouragement of new missions and job profiles have. Moreover, concurrent engineering requires that each actor can advance at the same time as the others, at the whim of the information that reaches him, and the information he has to transmit. However, in the French legal system around public procurement, things are not planned in this direction. Also, a consequent evolution must take place to adapt to the methodology. The new missions generated by the BIM in France require a good mastery of the tools and the process. Also, to meet the objectives of the BIM approach, it is possible to define a typical job profile around the BIM, adapted to the various sectors concerned. The multitude of job offers using the same terms with very different objectives and the complexity of the proposed missions motivated by our approach. In order to reinforce exchanges with professionals or specialists, we carried out a statistical study to answer this problem. Five topics are discussed around the business area: the BIM in the company, the function (business), software used and BIM missions practiced (39 items). About 1400 professionals were interviewed. These people work in companies (micro businesses, SMEs, and Groups) of construction, engineering offices or, architectural agencies. 77% of respondents have the status of employees. All participants are graduated in their trade, the majority having level 1. Most people have less than a year of experience in BIM, but some have 10 years. The results of our survey help to understand why it is not possible to define a single type of BIM Manager. Indeed, the specificities of the companies are so numerous and complex and the missions so varied, that there is not a single model for a function. On the other hand, it was possible to define 3 main professions around the BIM (Manager, Coordinator and Modeler) and 3 main missions for the BIM Manager (deployment of the method, assistance to project management and management of a project).

Keywords: BIM manager, BIM modeler, BIM coordinator, project management

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: batch bulk methyl methacrylate polymerization, adaptive sampling, machine learning, large margin nearest neighbor regression

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Authors: Jefferson S. Galanza, Jewel An Mischelle R.Camcam, Alyssa Karryl C. Co, Stephanie P. De Guzman, Jet Jet K. Dongui-is, Rodolfo Dane C. Frias, Ovelle C. Jueco, Harvey L. Matbagan, Victoria Luzette T. Rillon, Christelle Romyna H. Saruca, Jeanette Roma M. Villasper

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Background: Amidst numerous studies conducted on learning styles of students from a variety of courses, levels and school, a recent study recommended a great need for research on learning styles of student nurses. Moreover, related literatures have not been found exploring both the learning and teaching style of student nurses. Aims: The study aimed to determine the learning and teaching styles of student nurses and if there is an association between them. It also intended to discover whether student nurses are unimodal or multimodal in their styles and identified which faculty teaching style affords maximum outcome for student’s learning styles. Methods: Quantitative Descriptive-Correlational design was used. Participants were randomly selected 312 student nurses at School of Nursing X, Baguio City, Philippines. The questionnaire utilized a modified version of an adopted tool from Fleming’s VARK learning style version 7.2 (Visual, Auditory, Reader/Writer, Kinaesthetic) and Grasha’s teaching styles (Formal Authority, Demonstrator, Facilitator, Delegator). SPSS 19 was used for statistical treatment of data, where Chi square was used for the correlation of unimodal learning and teaching styles. Results/Finding: Majority of student nurses’ learning style is Kinesthetic and their teaching style is Demonstrator, which was also found to be significantly associated. Moreover, 8 out of 10 students are Unimodal in their learning and teaching modalities. In general, their preferred faculty teaching style is similar to their teaching style, which supports the concept, that teachers teach the way they learn. Conclusion: Study concludes that student nurses’ learning styles and teaching styles are varied, which exemplifies the uniqueness of every learner.This diversity in styles provided more evidence that a variety of mode of teaching and learning should be used by faculty and students to increase learning outcome and academic achievement. Recommendation: Future studies could be carried out in various schools of nursing utilizing faculty as respondents. Conduct assessment of learning style at the onset of classes/clinical placements so that faculty will become aware of the diversity of learners leading them to deliver diverse teaching methods.

Keywords: learning, learning styles, teaching styles, student nurses

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Authors: Gareth Baxter

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We use a mathematical model of language change to examine two recently observed patterns of language change: one in which most speakers change gradually, following the mean of the community change, and one in which most individuals use predominantly one variant or another, and change rapidly if they change at all. The model is based on Croft’s Utterance Selection account of language change, which views language change as an evolutionary process, in which different variants (different ‘ways of saying the same thing’) compete for usage in a population of speakers. Language change occurs when a new variant replaces an older one as the convention within a given population. The present model extends a previous simpler model to include effects related to speaker aging and interspeaker variation in behaviour. The two patterns of individual change (one more centralized and the other more polarized) were recently observed in historical language changes, and it was further observed that slower changes were more associated with the centralized pattern, while quicker changes were more polarized. Our model suggests that the two patterns of change can be explained by different balances between the preference of speakers to use one variant over another and the degree of accommodation to (propensity to adapt towards) other speakers. The correlation with the rate of change appears naturally in our model, and results from the fact that both differential weighting of variants and the degree of accommodation affect the time for change to occur, while also determining the patterns of change. This work represents part of an ongoing effort to examine phenomena in language change through the use of mathematical models. This offers another way to evaluate qualitative explanations that cannot be practically tested (or cannot be tested at all) in a real-world, large-scale speech community.

Keywords: agent based modeling, cultural evolution, language change, social behavior modeling, social influence

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Authors: Chante Van Tonder, Bart Bossink, Chris Schachtebeck, Cecile Nieuwenhuizen

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Small and Medium-Sized Enterprises (SMEs) play a key role in national economies around the world, being contributors to economic and social well-being. Due to this, the success, growth and competitiveness of SMEs are critical. However, there are many factors that undermine this, such as resource constraints, poor information communication infrastructure (ICT), skills shortages and poor management. The Fourth Industrial Revolution offers new tools and opportunities such as digital transformation and business model innovation (BMI) to the SME sector to enhance its competitiveness. Adopting and leveraging digital technologies such as cloud, mobile technologies, big data and analytics can significantly improve business efficiencies, value proposition and customer experiences. Digital transformation can contribute to the growth and competitiveness of SMEs. However, SMEs are lagging behind in the participation of digital transformation. Extant research lacks conceptual and empirical research on how digital transformation drives BMI and the impact it has on the growth and competitiveness of SMEs. The purpose of the study is, therefore, to close this gap by developing and empirically validating a conceptual model to determine if SMEs are achieving BMI through digital transformation and how this is impacting the growth, competitiveness and overall business performance. An empirical study is being conducted on 300 SMEs, consisting of 150 South-African and 150 Dutch SMEs, to achieve this purpose. Structural equation modeling is used, since it is a multivariate statistical analysis technique that is used to analyse structural relationships and is a suitable research method to test the hypotheses in the model. Empirical research is needed to gather more insight into how and if SMEs are digitally transformed and how BMI can be driven through digital transformation. The findings of this study can be used by SME business owners, managers and employees at all levels. The findings will indicate if digital transformation can indeed impact the growth, competitiveness and overall performance of an SME, reiterating the importance and potential benefits of adopting digital technologies. In addition, the findings will also exhibit how BMI can be achieved in light of digital transformation. This study contributes to the body of knowledge in a highly relevant and important topic in management studies by analysing the impact of digital transformation on BMI on a large number of SMEs that are distinctly different in economic and cultural factors

Keywords: business models, business model innovation, digital transformation, SMEs

Procedia PDF Downloads 245