Distinctive Variables Research Articles

Advancing short-term solar irradiance forecasting accuracy through a hybrid deep learning approach with Bayesian optimization

The optimization of solar energy integration into the power grid relies heavily on accurate forecasting of solar irradiance. In this study, a new approach for short-term solar irradiance forecasting is introduced. This method combines Bayesian Optimized Attention-Dilated Long Short-Term Memory and Savitzky-Golay filtering. The methodology is implemented to analyze data obtained from a solar irradiance probe situated in Douala, Cameroon. Initially, the unprocessed data is augmented by integrating distinctive solar irradiation variables, and the Savitzky-Golay filter with Bayesian Optimization is used to enhance its quality. Subsequently, multiple deep learning models, including Long Short-Term Memory, Bidirectional Long Short-Term Memory, Artificial Neural Networks, Bidirectional Long Short-Term Memory with Additive Attention Mechanism, and Bidirectional Long Short-Term Memory with Additive Attention Mechanism and Dilated Convolutional layers, are trained and evaluated. Out of all the models considered, the proposed approach, which combines the attention mechanism and dilated convolutional layers, demonstrates exceptional performance with the best convergence and accuracy in forecasting. Bayesian Optimization is further utilized to fine-tune the polynomial and window size of the Savitzky-Golay filter and optimize the hyperparameters of the deep learning models. The results show a Symmetric Mean Absolute Percentage Error of 0.6564, a Normalized Root Mean Square Error of 0.2250, and a Root Mean Square Error of 22.9445, surpassing previous studies in the literature. Empirical findings highlight the effectiveness of the proposed methodology in enhancing the accuracy of short-term solar irradiance forecasting. This research contributes to the field by introducing novel data pre-processing techniques, a hybrid deep learning architecture, and the development of a benchmark dataset. These advancements benefit both researchers and solar plant managers, improving solar irradiance forecasting capabilities.

Development and validation of a diagnostic model to differentiate spinal tuberculosis from pyogenic spondylitis by combining multiple machine learning algorithms.

This study focused on the development and validation of a diagnostic model to differentiate between spinal tuberculosis (STB) and pyogenic spondylitis (PS). We analyzed a total of 387 confirmed cases, out of which 241 were diagnosed with STB and 146 were diagnosed with PS. These cases were randomly divided into a training group (n = 271) and a validation group (n = 116). Within the training group, four machine learning (ML) algorithms (least absolute shrinkage and selection operator [LASSO], logistic regression analysis, random forest, and support vector machine recursive feature elimination [SVM-RFE]) were employed to identify distinctive variables. These specific variables were then utilized to construct a diagnostic model. The model's performance was subsequently assessed using the receiver operating characteristic (ROC) curves and the calibration curves. Finally, internal validation of the model was undertaken in the validation group. Our findings indicate that PS patients had an average platelet-to-neutrophil ratio (PNR) of 277.86, which was significantly higher than the STB patients' average of 69.88. The average age of PS patients was 54.71 years, older than the 48 years recorded for STB patients. Notably, the neutrophil-to-lymphocyte ratio (NLR) was higher in PS patients at 6.15, compared to the 3.46 NLR in STB patients. Additionally, the platelet volume distribution width (PDW) in PS patients was 0.2, compared to 0.15 in STB patients. Conversely, the mean platelet volume (MPV) was lower in PS patients at an average of 4.41, whereas STB patients averaged 8.31. Hemoglobin (HGB) levels were lower in PS patients at an average of 113.31 compared to STB patients' average of 121.64. Furthermore, the average red blood cell (RBC) count was 4.26 in PS patients, which was less than the 4.58 average observed in STB patients. After evaluation, seven key factors were identified using the four ML algorithms, forming the basis of our diagnostic model. The training and validation groups yielded area under the curve (AUC) values of 0.841 and 0.83, respectively. The calibration curves demonstrated a high alignment between the nomogram-predicted values and the actual measurements. The decision curve indicated optimal model performance with a threshold set between 2% and 88%. In conclusion, our model offers healthcare practitioners a reliable tool to efficiently and precisely differentiate between STB and PS, thereby facilitating swift and accurate diagnoses.

Relative age effect

The aim of this study was to examine relative age effect (RAE) on distinctive variables and age groups in recreational football. Participants (N = 79,249) included male (n = 63,540) and female (n = 15,709) players aged 2 to 12 years. Data were gathered through an official database containing all licensed players in Denmark. Birthdate distributions were split by age category, sex, club size, year group size, and birth quarter (Q1 = January to March, Q4 = October to December). RAEs were calculated using chi-square analysis. Significant RAEs existed in all age categories (except females in U6 and below). The effect was most pronounced at the entry level among both males and females. Club size was not associated with RAEs, but were shown in smaller and midsized year groups, but were absent in larger year groups. The results of this study show that RAEs are present from early sport participation.

Craving as a Nexus Of Gaming Disorder, its Assessment Scarcity and Role in Therapy Response: a Case Series

Gaming disorder (GD) is a recently recognized mental health disorder and has been garnering international attention. It shares core concepts with other addiction disorders and arguably the craving criterion. Craving has been well studied in substance and gambling addiction, with specific instruments for more objective measurement and distinctive contextual variables pertaining the craving. We present, for the first time, a series of four cases from the Indonesian national addiction clinic that demonstrated certain levels of craving might impede therapeutics response, the difficulty in assessing craving level on distinct scenarios, and the various variables influencing craving. The first two cases displayed low improvement and poorer prognosis compared to the two latter cases. Overall, these cases posited a great need of focus to measure, monitor, and manage craving among GD patients.

Public Chronic Pain Stigma and the Role of Pain Type and Patient Gender: An Experimental Vignette Study

Research exploring the specific manifestations of chronic pain (CP) public stigma is scarce. One potential factor influencing public stigma manifestations may be the CP type, that is, the presence (secondary CP) or absence (primary CP) of a clearly identifiable pathophysiology. Furthermore, patient gender may play a key role, whereby pain-related gender stereotypes may evoke distinct gender role expectations towards men and women experiencing CP. The aim of the research was 2-fold. First, by means of an experimental vignette design, the general population’s cognitive, affective, and behavioral responses were investigated, both towards primary versus secondary CP and towards men versus women. Second, a potential interaction was examined between CP type and patient gender. The research is divided into 2 separate samples: individuals with CP (N = 729) and individuals without CP (N = 283). Factorial ANOVA models were estimated with CP type, patient gender, and participant gender included as factors, age as control variable. The findings support, partly, the general hypothesis of higher (perceived) public stigma towards individuals with primary (vs secondary) CP. No main effects of patient gender were observed. Gender bias in stigmatizing manifestations only emerged in certain contextual circumstances (ie, pain type and participant gender). Different interaction effects (with a combination of gender, patient gender, or CP type) were significant for the distinctive outcome variables. Interestingly, throughout the findings, different patterns of results are found in both samples. The study contributes to the literature on CP stigma, as well as the psychometric examination of items assessing stigmatizing manifestations. PerspectiveThis study examined the role of contextual factors chronic pain type and patient gender into cognitive, affective, and behavioral stigmatizing manifestations coming from the general population towards individuals with chronic pain through an experimental vignette study. The study contributes to the chronic pain stigma literature, as well as the psychometric examination of items assessing stigmatizing manifestations.

Identification of nutritional composition and antioxidant activities of fruit peels as a potential source of nutraceuticals.

Fruit peels comprise several biologically active compounds, but their nutritional composition and antioxidant potential of different fruit varieties are limited. This study aimed to determine the nutritional composition and antioxidant properties of 12 peels of different fruit varieties such as apples, pomegranates, guavas, strawberries, grapes, and citrus fruits using a ultraviolet-visible (UV-Vis) spectrophotometer, an inductively-coupled plasma atomic emission spectroscopy (ICP-AES), and an amino acid analyzer. The highest values of TPC, TFC, lycopene, ascorbic acid [total carotenoids and total antioxidant capacity (TAC)], reducing sugars, non-reducing sugars, and total soluble proteins were reported in grapes (Black seedless) 54,501.00 ± 0.82 μM/g dry wt., guava (Gola) 198.19 ± 0.46 Rutin equivalent dry wt., strawberry (Candler) 7.23 ± 0.33 mg/g dry wt., citrus (Mausami) 646.25 ± 0.96 ug/g dry wt., apple (Kala kulu-Pak) 14.19 ± 0.38 mg/g dry wt. and 12.28 ± 0.39 μM/g dry wt., strawberry (Candler) 25.13 ± 0.40 mg/g dry wt., pomegranate (Badana) 9.80 ± 0.43 mg/g dry wt., apple (Kala kullu-Irani) 30.08 ± 0.11 mg/g dry wt., and guava (Gola) 638.18 ± 0.24 mg/g dry wt. compared with its opponent peels of fruits, respectively. All 12 peels of the fruit verities had 20 amino acids and presented as dry matter basis%. The highest trend of glutamic acid + glutamine, glycine, and aspartic acid + asparagine was observed in pomegranate (Badana) 1.20 DM basis%, guava (Surhai and Gola) 1.09 and 1.09 DM basis%, and strawberry (Desi/local and Candler) 1.15 and 1.60 DM basis% in response to other fruit peels, respectively. Regarding the mineral profile, the highest values of nitrogen (764.15 ± 0.86 mg/100 g), phosphorus (53.90 ± 0.14 mg/100 g), potassium (3,443.84 ± 0.82 mg/100 g), ferric (1.44 ± 0.00 mg/100 g), magnesium (1.31 ± 0.00 mg/100 g), and manganese (0.21 ± 0.00 mg/100 g) were found in pomegranate (Badana), grapes (Black seedless), apple (Kala kulu-Pak), and pomegranate (Badana), respectively, in context to other fruit peels' extract. Principal component analysis (PCA) and agglomerative hierarchical clustering (AHC) were analyzed for determining the correlation among different peels of fruits. Significantly, high levels of variation were noticed among different variables of peels of fruit. Fruit variety and its peels have been distinctive variables in selecting genotypes. The dendrogram obtained from cluster analysis was distributed into two groups and consisted of eight varieties in the same group, and four fruit varieties were in second group. Overall, the results conclude that fruit peels have the abundant antioxidants and some minerals, which can effectively be utilized for nutraceuticals as well as for food security.

Optimisation-driven design in the architectural, engineering and construction industry

Digital tools and services relying on digital technology are becoming more pervasive, and are widespread in many different stages of the design process of structures. In this study, design optimisation from the perspective of architectural and structural engineering design is explored. Although, until recently, optimisation was recognised as a ‘tough’ mathematical tool, its evolution in terms of usability and efficiency have made it attractive for improving architectural design from the earliest stages of the design approach. Specialised digital tools that are able to support all structural engineering optimising requirements are somewhat difficult to develop; instead, customised structural design optimisation services have recently appeared. This work presents different strategies for parametrising distinctive variables involved in the definition of each architectural synthesis, which are defined as the main goal in architectural design optimisation and the structural design optimisation. A review of optimisation processes and optimisation tools in the field of architecture, engineering and construction is then provided. Recent paradigms from the built environment where parametric optimisation procedures have been applied in real-world design practice are also presented.

Free energy landscape of wrapping of lipid nanocluster by polysaccharides

Wrapping of a 20-mer cholesterol nano-cluster (CHL-nanoC) by two widely different types of β-glucan polysaccharides (23–25 mers) having significantly varying glycosidic linkage patterns and side chains is studied by Well-Tempered MetaDynamics (WT-MetaD) simulations. The problem has its relevance in the faecal sterol and bile acid excretion in humans and the role of dietary fibres in aiding the process and combating dyslipidemia. Additionally, the distinctive collective variables studied here can be extended for modeling of polymer wrapped soft clusters/nano-particles in general. The wrapping ability is observed to be significantly correlated to the bending of the polysaccharide chain, an attribute of the glycosidic linkage type. By biasing two unique collective variables, the radius of gyration of the polysaccharide (Rg, poly) and the second order Legendre polynomial of the segment orientation parameter, θ, we could successfully observe the wrapping process. This work compares in detail the physical properties of the polysaccharide encapsulated CHL-nanoC by probing the radius of curvature (Rcurv, poly) of the polysaccharides, their coordination number with respect to the CHL-nanoC (CN), fractional CHL-nanoC surface coverage and the electrostatic surface potentials of the complex assembly. Results indicate that the β-glucan having 1–4 glycosidic linked monomers with intermittent 1–3 linkage is able to wrap the CHL-nanoC more effectively. The 1–3 glycosidic linked β-glucan with 1–6 glycosidic bonds in side chains is significantly curled up and appears to be less efficient in wrapping the nanoC. This work provides a comparative molecular level picture of mutual interaction between two major dietary polysaccharide variants and lipid globules as indicated by numerous clinical level studies involving mice and human models.

Differentiation and seasonality in suitable microsites of seed dispersal by an assemblage of omnivorous mammals

In endozoochorous seed dispersal, the ecological characteristics of each disperser determine the quantitative and qualitative aspects of the dispersal mechanism. To understand the role of different frugivores in multispecies seed dispersal networks, it is necessary to focus on the community structure and investigate where in the landscape seed deposition occurs. The aim of this research was to assess the quantitative and qualitative aspects of a mammalian endozoochorous seed dispersal network in a temperate forest ecosystem and identify the seasonal dispersal niche of each member of the assemblage. We hypothesized that differences among dispersers and seasons would occur in (H1) the proportion of scats that contain seeds, seed abundance in scats, and the number of seed species dispersed per scat, and in (H2) the probability of dispersing seeds to suitable microsites for germination of each species and seed abundance. We also hypothesized (H3) that the microhabitat variables of deposition sites would vary among dispersers, and (H4) that complementary structures would occur in terms of dispersers, dispersed species, and deposition sites. From summer (June–August) to autumn (September–November) in 2003 and 2004, we collected scats of five mammalian frugivorous species and recorded eight microhabitat variables at each deposition site in central Japan. We recorded the presence and number of seeds in scats and identified all seed at the species level. We considered a deposition site as suitable when the habitat type (interior forest, treefall gap, forest edge, and outside the forest) at a deposition site matched the microhabitat required for the for the dispersed species to germinate and survive as seedlings. A total of 341 scats containing seeds of 16 fleshy-fruited species were collected. Among these, 213 (62.5 %) scats were dispersed to suitable habitats (summer: 68.8 %, autumn: 54.8 %). We found that the seed abundance in the scat varied among dispersers and was higher in autumn (H1–2). The probability of dispersing seeds to suitable microsites switched among dispersers from summer to autumn (H2). The distinctive microhabitat variables and variation in microhabitat at deposition sites differed among dispersers across seasons (H3). Disperser-plant and disperser-deposition site networks were specialized and modular in structure compared to random networks during both seasons, but there was a less nested structure in summer compared to autumn (H4). The five mammal species showed differences and seasonality in seed dispersal niches. Because of these differences, these mammal species may play redundant and complementary roles in the seed dispersal network.

Influence of process variables on shoe polish viscosity

Valourisation of non-biodegradable wastes into value added products like shoe polish can indeed be an effective tool for waste management and climate change mitigation. However, having appropriate shoe polish viscosity is important for customer satisfaction as too thick or too thin shoe polish may not result in desired customer satisfaction. The aim of this study was to investigate the effects of process variables (water repellant nature, process temperature, carbon black source and particle size, as well as, composition type and quantity) on shoe polish viscosity. The viscosity values of the various samples of shoe polish produced using carbon black pigments from batteries, pyrolytic rubber tyres, plastic bottle and water sachets wastes were determined. From the results obtained, it could be observed that shoe polish samples that had almost the same value of dynamic viscosity (η = 0.2389) with that of the commercial Kiwi shoe polish included the shoe polish with used vegetable oil as water repellant and the shoe polish with dye sourced from discarded batteries and plastic bottle wastes but with particle sixe of 0.80 mm. On comparison of the viscosity values of other shoe polish samples with that of the Kiwi shoe polish, it was observed that all shoe polish samples evaluated for all the distinctive process variables except temperature had comparable viscosity with that of Kiwi shoe polish. The real difference in viscosities of the shoe polish samples was observed when the process temperature was below 60 °C. This indicates that temperature as a process variable is the main determining factor regarding the viscosity of the shoe polish samples.

The Choice of Urban Spaces in the COVID-19 Era

The spread of infectious diseases is a spatial process, including Coronavirus disease 2019 (COVID-19). Cluster infections of COVID-19 have arisen globally in various urban spaces, implying that tracking the spread necessitates a spatial approach to understanding the dynamics of the disease. In this study, we employ an online survey in the Seoul metropolitan area in South Korea to examine changes in the use of urban spaces and factors that affect individual’s choice in using urban spaces in the COVID-19 era. We classify various urban spaces into three activity types according to the previous studies: spaces for mandatory activities, maintenance activities, and discretionary activities. The results show that every type of urban space is visited less than before the COVID-19 outbreak. Factors involved in the use of spaces for mandatory activities include the preference for offline consumption, gender, and risk perception of COVID-19. In the case of non-mandatory activity spaces, factors that commonly influence the use of the spaces are compliance with social distancing regulations, preference for offline consumption, refraining from outdoor activities, risk perception of COVID-19, and perceived safety in the city concerning COVID-19. The present study is significant as it identified not only different factors affecting the choice of mandatory and non-mandatory activity spaces but also distinctive variables determining the choice of urban spaces for maintenance activity and discretionary activity. From the analysis, this study draws policy implications to effectively prevent and control infectious disease in the context of urban spaces.

Heat Transfer Analysis and Magnetohydrodynamics Effect on Peristaltic Transport of Ree–Eyring Fluid in Rotating Frame

This paper discusses Ree–Eyring fluid’s peristaltic transport in a rotating frame and examines the impacts of Magnetohydrodynamics (MHD). The results deal with systematically (analytically) applying each of the governing equations of Ree–Eyring fluid, the axial and secondary velocities, flow rate due to auxiliary stream, and bolus. The effects of some distinctive variables, such as Hartman number, heat source/sink, and amplitude ratio, are taken under consideration and illustrated through graphs.

High biogeographic and latitudinal variability in gastropod drilling predation on molluscs along the eastern Indian coast: Implications on the history of fossil record of drillholes.

Studies on the large-scale latitudinal patterns of gastropod drilling predation reveal that predation pressure may decrease or increase with increasing latitude, or even show no trend, questioning the generality of any large-scale latitudinal or biogeographic pattern. Here, we analyze the nature of spatio-environmental and latitudinal variation in gastropod drilling along the Indian eastern coast by using 76 samples collected from 39 locations, covering ~2500 km, incorporating several ecoregions, and ~15° latitudinal extents. We find no environmental or latitudinal gradient. In fact, drilling intensity varies highly within the same latitudinal bin, or oceanic sub-basins, or even the same ecoregions. Moreover, different ecoregions with their distinctive biotic and abiotic environmental variables show similar predation intensities. However, one pattern is prevalent: some small infaunal prey taxa, living in the sandy-muddy substrate—which are preferred by the naticid gastropods—are always attacked more frequently over others, indicating taxon and size selectivity by the predators. The result suggests that the biotic and abiotic factors, known to influence drilling predation, determine only the local predation pattern. In the present case, the nature of substrate and prey composition determines the local predation intensity: soft substrate habitats host dominantly small, infaunal prey. Since the degree of spatial variability in drilling intensity within any time bin can be extremely high, sometimes greater than the variability across consecutive time bins, temporal patterns in drilling predation can never be interpreted without having detailed knowledge of the nature of this spatial variability within a time bin.

Potential Role of Clinical Trial Eligibility Criteria in Electronic Phenotyping.

2,719 distinctive phenotyping variables from 176 electronic phenotypes were compared with 57,150 distinctive clinical trial eligibility criteria concepts to assess the phenotype knowledge overlap between them. We observed a high percentage (69.5%) of eMERGE phenotype features and a lower percentage (47.6%) of OHDSI phenotype features matched to clinical trial eligibility criteria, possibly due to the relative emphasis on specificity for eMERGE phenotypes and the relative emphasis on sensitivity for OHDSI phenotypes. The study results show the potential of reusing clinical trial eligibility criteria for phenotyping feature selection and moderate benefits of using them for local cohort query implementation.

Three-Dimensional Finite Element Modeling and Response Surface Based Multi-response Optimization During Silica Drilling with Closed-Loop ECDM

Electrochemical discharge machining (ECDM) is recognized as a successful method for processing non-conductive materials through thermal erosion and chemical dissolution. This article aims at the development of a finite element modeling (FEM) based three-dimensional (3D) thermal model for estimating the temperature distribution for scrutinizing the material removal rate (MRR) in electrochemical discharge drilling of silica glass material. The predicted FEM results are verified against existing literature and experimental results during micro-drilling operation. Simulations for evaluating the parametric studies such as the effect of applied voltage, electrolyte concentration, electrolyte type, energy partition on MRR is performed. Results revealed that the experimental values of MRR exhibit fare agreement with the predicted FEA results. Experiments are performed using adaptive tool feed based closed-loop ECDM machining that retracts the tool in an upward direction once its contact is detected with the work material. Tool contacts often result in a high tool wear rate (TWR). Moreover, the response surface methodology (RSM) based mathematical models are established to correlate the input variable’s relationship with the response parameters. Tool feed rate, applied voltage, and electrolyte concentration are chosen as numerical input variables while electrolyte type and tool material are chosen as categorical variables. MRR, TWR, and a number of tool contacts (NTC) are chosen as response parameters. A number of tool contacts are selected since it influences both MRR and TWR. The model’s adequacy is checked using the analysis of variance (ANOVA) and found significant for all the responses. The multi-response optimization of distinctive input variables is acquired by utilizing the desirability function (obtained 0.8646) for maximizing the MRR and minimizing the both TWR and NTC.

Extending the Theory of Planned Behavior to Explore the Influence of Residents’ Dependence on Public Transport

The accurate depiction and understanding of the influence mechanism of residents’ dependence on public transport (RDPT) is an important foundation for increasing the proportion of green trips and alleviating urban traffic congestion. To explore the influence mechanism of RDPT, this paper extends the theory of planned behavior (TPB) by introducing objective factors of attributes, environment, and travel characteristics. The agglomerative nesting clustering algorithm and multiple structural equation modeling (SEM) are then developed to identify the RDPT levels and analyze the influence relationships between the integrated influencing factors and RDPT based on travel survey data. The results indicate that the objective variables have indirect impacts on RDPT by influencing psychological variable attitudes, subjective norms and perceived control and travel intention. The residents’ self-selection (RSS) effects of different clusters are all detected under normal conditions, and the environment on RDPT is still significant after controlling for this effect. The findings reflect that the influence mechanisms of the three SEMs for different clusters are distinct, unlike those of the baseline model, and distinctive observation variables have dissimilar explanatory abilities for the travel intention of different residents. Therefore, some beneficial policy implications are proposed for residents, especially those who retain low and relatively low public transport dependence levels, to increase public transport usage while reduce the car usage based on the significant findings.

New diagnostic approach of the different types of isolated craniosynostosis

In this study, we diagnose skull shape deformities by analysing sinusoid curves obtained from standardized computed tomography (CT) slices of the skull for the common craniosynostoses (scaphocephaly, brachycephaly, trigonocephaly, right- and left-sided anterior plagiocephaly). Scaphocephaly has a high forehead peak and low troughs, in contrast to brachycephaly. Anterior plagiocephaly has asymmetry and shifting of the forehead peak. Trigonocephaly has a high and narrow frontal peak. Control patients have a symmetrical skull shape with low troughs and a high and broader frontal peak. Firstly, we included 5 children of every group of the common craniosynostoses and additionally 5 controls for extraction and calculation of characteristics. A diagnostic flowchart was developed. Secondly, we included a total of 51 craniosynostosis patients to validate the flowchart. All patients were correctly classified using the flowchart.Conclusion: Our study proposes and implements a new diagnostic approach of craniosynostosis. We describe a diagnostic flowchart based on specific characteristics for every type of craniosynostosis related to the specific skull deformities and control patients. All variables are expressed in number; therefore, we are able to use these variables in future research to quantify the different types of craniosynostosis.What is Known:• Premature fusion of one or more cranial sutures results in a specific cranial shape.• Clinical diagnosis is relatively simple; however, objective diagnosis based on distinctive values is difficult.What is New:• Using external landmarks and curve analysis, distinctive variables, and values for every type of craniosynostosis related to the specific skull deformities were determined and used to create a diagnostic flowchart for diagnosis.• Validation with an independent data set of 51 patients showed that all patients were correctly classified.

Social Support, Self-Efficacy, and Psychological Wellbeing of Adults with Type 2 Diabetes.

Social support improves self-efficacy, which in turns enhances self-management that lead to better psychological outcomes of persons with type 2 diabetes (T2D). The purpose of this study was to examine the relationship between social support and psychological outcomes of adults with T2D. A cross-sectional design was used to recruit a sample of 339 participants from a diabetes clinic. The participants responded to a series of questionnaires on demographics, social support dimensions, and self-management; self-efficacy; and psychological outcomes. The function and quality of social support were positively associated with self-efficacy. Self-efficacy was significantly associated with both self-management and psychological outcomes. In addition, self-efficacy demonstrated successful mediation role in the relationship between social support and psychological outcomes of T2D, however, self-management failed to mediate this relationship. The quality and functionality of social support are distinctive variables that should be recognized to promote social support interventions to reduce or prevent T2D-related psychological outcomes.

Feature Selection in Text Clustering Applications of Literary Texts: A Hybrid of Term Weighting Methods

The recent years have witnessed an increasing use of automated text clustering approaches and more particularly Vector Space Clustering (VSC) methods in the computational analysis of literary data including genre classification, theme analysis, stylometry, and authorship attribution. In spite of the effectiveness of VSC methods in resolving different problems in these disciplines and providing evidence-based research findings, the problem of feature selection remains a challenging one. For reliable text clustering applications, a clustering structure should be based on only and all the most distinctive features within a corpus. Although different term weighting approaches have been developed, the problem of identifying the most distinctive variables within a corpus remains challenging especially in the document clustering applications of literary texts. For this purpose, this study proposes a hybrid of statistical measures including variance analysis, term frequency-inverse document frequency, TF-IDF, and Principal Component Analysis (PCA) for selecting only and all the most distinctive features that can be usefully used for generating more reliable document clustering that can be usefully used in authorship attribution tasks. The study is based on a corpus of 74 novels written by 18 novelists representing different literary traditions. Results indicate that the proposed model proved effective in the successful extraction of the most distinctive features within the datasets and thus generating reliable clustering structures that can be usefully used in different computational applications of literary texts.

The scenario of e-education in covid-19 pandemic: A study on some selected Colleges of Bangladesh

The study is based on primary data collected from 30 (thirty) students, 10 (ten) online tutors, and 10 (ten) administrators of 5 (five) renowned colleges in Jashore area of Bangladesh. This paper tries to analyze their responses towards the 5 (five) distinctive variables such asfamily environment, online related costs, nature of the devices, online platforms, and related challenges of the education running in the dangerous virus called Covid-19 crisis.Findings of the study revealed that most of the respondents belong in a peaceful and calm atmosphere at home that is essential for conducting e-education, people are moderately interested to spend money on e-education purposesand amazingly habituated with mobile technology for performing their e-education during lockdown for the Covid-19 period. The study also depicted that Facebook Live is amore popular eeducation platform followed by the Zoom platform during the current pandemic situation. Based onresponses of the respondents the study identified that online tutors, learners, and administrators are unable to perform better in the e-education platform due to frequent load-shading, poor networking, operating error, and accessing error. The study suggests that concerned officials must practice easily operated online teaching mechanism, used a simple handled platform, ensure the uninterrupted electricity supply, issue a cost-effective internet package, enhance the speed of the networking system, and arrange online conferences occasionally with the participation of respective persons, etcto achievethe better scenario of e-education during the new normal situation.Small sample size and minor sample units are the major limitations of this study, thus further research is recommended to conduct focusing on large sample size as well as the representative sample units.