Multiple R2 Research Articles

Kontribusi Penerapan Motivasi Intrinsik dan Ekstrinsik terhadap Komitmen Organisasi Karyawan Tetap

This study aims to determine the effect of intrinsic motivation and extrinsic motivation on the organizational commitment of permanent employees at the Bondowoso Regency PDAM office. The research method used is quantitative research. Data collection techniques using observation, interviews and questionnaires to 98 respondents with census techniques. The analytical tools used in this research are validity test, reliability test, classical assumption test, multiple linear regression analysis, T test, and R2 test. The results showed, a) there was a positive and significant effect between intrinsic motivation on organizational commitment with a significance level of 0.000 (p<0.05); b) there is a positive and significant influence between extrinsic motivation on organizational commitment with a significance level of 0.000 (p <0.05). In conclusion, the independent variables (X1, X2) together have a positive and significant effect on the dependent variable (Y) of organizational commitment to permanent employees of the Bondowoso Regency PDAM Office.
 Keywords: Organizational Commitment, Extrinsic Motivation, Intrinsic Motivation

Optimization of inhibition efficiencies process of polyvinylpyrrolidone using response surface methodology

Inhibition efficiencies (IE) process in polyvinylpyrrolidone (PVP) which is influenced by independent factors, concentration and size of PVP, temperature, time of immersion, and perchloric acid concentration was investigated in this paper. The relationship between factors and their responses is established by the concept of response surface methodology (RSM) explicitly through regression statistical analysis and probabilistic analysis is used in this work. The concept is a combination of mathematical and statistical techniques allowing the modeling and problems analysis by experimental design. In this study, the results based on statistical analysis showed that the quadratic models for the inhibition efficiencies (IE) were significant at the value of probability P < 0.0001 and the coefficient of multiple regressions R2=0.9997, for further validation of the model, R2Adj=0.9993 indicated a good model. The observed experimental values were in good agreement with predicted ones and the model washighly significant with Q2= 0.9884. The optimal conditions of inhibition efficiencies (IE) obtained are 104.301% for a concentration of 3.55×10−3 mol/L, temperature of 20.15°C, immersion time of 2h, size of PVP 58000 g/mol, and acid concentration of 0.5 mol/L.

Interindividual variation in maximum aerobic metabolism varies with gill morphology and myocardial bioenergetics in Gulf killifish.

This study asked whether interindividual variation in maximum and standard aerobic metabolic rates of the Gulf killifish, Fundulus grandis, correlates with gill morphology and cardiac mitochondrial bioenergetics, traits reflecting critical steps in the O2 transport cascade from the environment to the tissues. Maximum metabolic rate (MMR) was positively related to body mass, total gill filament length and myocardial oxygen consumption during maximum oxidative phosphorylation (multiple R2=0.836). Standard metabolic rate (SMR) was positively related to body mass, total gill filament length and myocardial oxygen consumption during maximum electron transport system activity (multiple R2=0.717). After controlling for body mass, individuals with longer gill filaments, summed over all gill arches, or greater cardiac respiratory capacity had higher whole-animal metabolic rates. The overall model fit and the explanatory power of individual predictor variables were better for MMR than for SMR, suggesting that gill morphology and myocardial bioenergetics are more important in determining active rather than resting metabolism. After accounting for body mass, heart ventricle mass was not related to variation in MMR or SMR, indicating that the quality of the heart (i.e. the capacity for mitochondrial metabolism) was more influential than heart size. Finally, the myocardial oxygen consumption required to offset the dissipation of the transmembrane proton gradient in the absence of ATP synthesis was not correlated with either MMR or SMR. The results support the idea that interindividual variation in aerobic metabolism, particularly MMR, is associated with variation in specific steps in the O2 transport cascade.

Added Sugars Intake Explained by Amino Acid Carbon Isotope Ratio Profiles in a Controlled Feeding Study of U.S. Adults

ObjectivesTo evaluate an amino acid carbon stable isotope ratio (CIRAA) biomarker of added sugars (AS) intake in a controlled feeding study of men and women across age and BMI groups.MethodsWe conducted a 15-d feeding study in Phoenix, AZ, of men and women (N = 100, aged 18–70 y, BMI 17.9–35.0) who were recruited across sex, age, and BMI groups. Participants were provided personalized diets that resembled their habitual intakes, based on 2 consecutive 7-d food records. We measured CIRAAs in serum samples (N = 99) collected at the end of the feeding period and determined correlations with dietary intakes. We used forward selection to construct a model to explain AS intake using participant characteristics and 14 measured CIRAAs. This model was internally validated using a bootstrap optimism correction.ResultsMedian (25th, 75th percentile) AS intake was 65.2 g/d (44.7, 81.4) and 9.5% (7.2%, 12.4%) of energy. The CIR of alanine had the highest, though still modest, correlation with AS intake (Pearson r = 0.32, P = 0.001). Serum CIRAAs were more highly correlated with animal food intakes, especially the ratio of animal to total protein intake (APR). The highest correlations were between the APR and the CIRs of phenylalanine (Pearson r = 0.85, P < 0.001) and leucine (Pearson r = 0.84, P < 0.001). The model of AS intake included participant sex and body weight and the CIRs of 6 AAs: alanine, valine, lysine, glutamic acid, serine, and glycine. This model had modest explanatory power (multiple R2 = 0.38), and the optimism-corrected R2 for the model was lower (R2 = 0.15).ConclusionsThe observed association between serum CIRAAs and AS intake in the U.S. diet is encouraging; however, further investigation in populations with wider ranges of AS intake is warranted.Funding SourcesNational Cancer Institute; Institutional Development Award (IDeA) from the National Institutes of General Medical Sciences.

Analysis of Influencing Factors to Increase Product Selling Value During the Covid-19 Pandemic (Case Study of Small and Medium Enterprises (Smes) in Kampung Sejahtera Mandiri Teras Pancasila Tangerang, Banten)

Analysis of factors that influence To Increase Product Selling Value During the Covid 19 Pandemic, in this case how much both / individually and jointly between independent variables (price, location, promotion and service) affect the dependent variable (Decision Making Purchasing Products During the Covid 19 Pandemic). This research was carried out by Small and Medium Enterprises (UKM) at Kampung Sejahtera Mandiri Teras Pancasila, Tangerang City, Banten by distributing questionnaires to questions while the research sample was used by simple random sampling . Data collection by field studies (interviews, observations, questionnaires) was shown to small and medium enterprises, small businesses. Medium (UKM) Kampung Sejahtera Mandiri Teras Pancasila in Tangerang City, Banten with a total of 100 SME consumers. Statistical data analysis used reliability, validity, normality, autocorrelation, multicollinearity heteroscedasticity, coefficient determination, individual tests (t-test) and joint tests (f-test), with the SPSS 25 statistical tool. The t shows that the independent variables both have a positive and significant influence on the dependent variable. A case study on Small and Medium Enterprises (UKM), Kampung Sejahtera Mandiri Teras Pancasila, Tangerang City, Banten with the results obtained that the t value of the 2.001 price is &gt; ttable 1 .65 and probability .0048 &lt; 0.05, the t value 1.774 for location is. &gt; ttable 1.65 and . probability 0039 &lt; 0.05, the value of t count promotion is 5.823. &gt; ttable 1.65 and .probability 0000 &lt; 0.05 and the value of t count service is 7.401. &gt; )ttable 1.65 and . probability 0000 &lt; 0.05 The result of F count is 172,359 level significance 0.000 then F count &gt; F table (94,925 &gt; 3,87 significance level 0.000 &lt;0.05, the independent variable simultaneously has a positive and significant influence on the dependent variable in the case study on Small and Medium Enterprises (UKM), Kampung Sejahtera Mandiri Teras Pancasila, Tangerang City, Banten and the value of the coefficient of multiple determination R2 is 87.9, % explained the independent variable factors (price, location, promotion and service) and the remaining 100%-87, 9% = 12.1% the results obtained from other variables are not included from the independent variable.

A comprehensive method for improvement of water quality index (WQI) models for coastal water quality assessment

Here, we present an improved water quality index (WQI) model for assessment of coastal water quality using Cork Harbour, Ireland, as the case study. The model involves the usual four WQI components – selection of water quality indicators for inclusion, sub-indexing of indicator values, sub-index weighting and sub-index aggregation – with improvements to make the approach more objective and data-driven and less susceptible to eclipsing and ambiguity errors. The model uses the machine learning algorithm, XGBoost, to rank and select water quality indicators for inclusion based on relative importance to overall water quality status. Of the ten indicators for which data were available, transparency, dissolved inorganic nitrogen, ammoniacal nitrogen, BOD5, chlorophyll, temperature and orthophosphate were selected for summer, while total organic nitrogen, dissolved inorganic nitrogen, pH, transparency and dissolved oxygen were selected for winter. Linear interpolation functions developed using national recommended guideline values for coastal water quality are used for sub-indexing of water quality indicators and the XGBoost rankings are used in combination with the rank order centroid weighting method to determine sub-index weight values. Eight sub-index aggregation functions were tested - five from existing WQI models and three proposed by the authors. The computed indices were compared with those obtained using a multiple linear regression (MLR) approach and R2 and RMSE used as indicators of aggregation function performance. The weighted quadratic mean function (R2 = 0.91, RMSE = 4.4 for summer; R2 = 0.97, RMSE = 3.1 for winter) and the unweighted arithmetic mean function (R2 = 0.92, RMSE = 3.2 for summer; R2 = 0.97, RMSE = 3.2 for winter) proposed by the authors were identified as the best functions and showed reduced eclipsing and ambiguity problems compared to the others.

Quality of Life in Patients with Chronic Psychotic Disorders: A Practical Model for Interventions in Romanian Mental Health Centers.

Background and Objectives: Current psychiatric care is increasingly focusing on patients’ quality of life (QoL). Research is still trying to determine the main factors which influence QoL. The present study aims to assess the QoL of patients with chronic psychotic-spectrum disorders, as well as its relation to symptomatology, functionality, adaptive behavior, and perceived level of recovery. Materials and Methods: The study included a sample of 78 patients with chronic psychosis. Symptomatology and illness severity were assessed with the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impression Scale-Severity (CGI-S) scales, respectively. The Global Assessment of Functioning Scale (GAFS) and the Adaptive Behavior Assessment System II (ABAS-II)-Adult Form were used for the assessment of patients’ functionality, and the Quality-of-Life Inventory (QOLI) scale was applied for the evaluation of QoL. Results: According to the CGI-Severity scale, 20.5% of the patients were borderline mentally ill, and 24.4% were mildly ill. The highest number of patients (34.6%) were moderately ill, while 14.1% and 2.6% were markedly ill and severely ill, respectively. Among the moderately ill patients, more than half (63%) were patients with schizophrenia, 18.5% were patients with delusional disorder, and 18.5% were patients with schizoaffective disorder. Most of the patients (43.6%) presented moderate functioning deficiency, while 38.5% of the patients presented severe deficiency, according to the GAFS score. When assessed with the ABAS, we observed that almost half of the patients (44.9%) showed an average functioning across skill areas in the conceptual, social, and practical domains. A percent of 67.9% of the patients presented an average QoL, while 15.4% and 12.8% showed a very low and low QoL. QoL was not influenced by the patients’ symptomatology, gender, and education level. Having children, family support, better social and conceptual skills, and a higher perceived level of recovery was correlated with an increased QoL, hierarchical multiple regression R2 = 0.379, F(9, 68) = 2.616, and p = 0.012. Conclusions: Psychiatric interventions in psychosis should focus not only on symptoms’ control, but also on improving social and family support, as well as adaptive skills to increase the patients’ QoL.

Effects of Interest Rate on Access to Agro-credit by Farmers in Adamawa State, Nigeria

This study examined the effect of interest rates on access to agro-credit by farmers in Adamawa state. Respondents’ sources of credit, amount of credit obtained, factors affecting the volume of credit sourced by, factors affecting the volume of credit sourced by farmers, problems encountered in obtaining loans from formal and informal sources were investigated. Findings of the study reveals that majority of the farmers, 65% from Personal Savings. About 40% of the respondents obtained credit at the range of N100, 001-400,000. Regression analysis shows a co-efficient of multiple determination R2 value of 0.65 of the total variations in volume of credit sourced by farmers were accounted by actions of independent variables, namely; age, level of education, interest rate, credit awareness and farm income was statistically significant at various levels of probabilities.

COGNITIVE ABILITY, INTRINSIC MOTIVATION, AND SELF EFFICIENCY TOWARDS EMPLOYEE PERFORMANCE

This study aimed to analyze cognitive abilities, intrinsic motivation, and self-efficacy towards the employees performance of PT. Bank Danamon Sub Branch Office Sutomo, Medan. This study used quantitative methods with several tests namely classical assumption test, multiple linear regression, hypothesis testing and R2 test. Based on the results of the regression obtained the equation: Y = 0.948 + 0.425 X1 + 0.470 X2 + 0.668 X3. Partially, the tcount value of this study is 3.28 and it is known that the cognitive ability variable (X1) has a ttable of 1.70. When compared with tcount, the result was 3.28&gt; 1.70, so it can be concluded that the cognitive ability variable (X1) has a positive and significant effect on the employee performance variable (Y). The intrinsic motivation variable (X2) has a tcount of 2.53. When compared with ttable, the results were 2.53&gt; 1.70, so it can be concluded that the intrinsic motivation variable (X2) has a positive and significant effect on the employee performance variable (Y). The self-efficacy variable (X3) has a tcount of 4.63 and when compared with ttable the results were 4.63&gt; 1.70, so it can be concluded that the self-efficacy variable (X3) has a positive and significant effect on the employee performance variable (Y). Simultaneously, the variables of cognitive ability, intrinsic motivation, and self-efficacy have a positive and significant influence on employee performance. This means that the hypothesis in this study is accepted, as evidenced by the value of Fcount &gt; Ftable (13,837&gt;2,93). Cognitive ability, intrinsic motivation, and self-efficacy have an influence on employee performance variables by 55.4%, while the remaining 44.6% was influenced by other variables not examined in this study

Explanation of BMI data using Linear Regression Model in R

Abstract: This paper describes the regression analysis between different variable like Weight &amp; BMI, Weight &amp; Height, and Height &amp; BMI using Linear Regression Model &amp; data visualization techniques in R Programming from a sample data of 68 students of BCA. The collected data were analyzed for underweight, overweight, obese personalities by using conditional statements. The result of the model will give Residual Standard Error, Multiple R2 , Adjusted R2 , F-statistic and p-value. There is visualization of data using ggplot() and geom() in last steps. Keywords: BMI, Multiple R2 , Adjusted R2 , F-statistic, p-value, R, ggplot, geom.

Source Analysis of Ambient PM2.5 in Wuhan City Based on Random Forest Model

Based on the online monitoring data of fine particle(PM2.5) mass concentration, carbonaceous components, ionic constituents, and elemental components in an urban site of Wuhan from December 2019 to November 2020, the chemical characteristics of PM2.5 were analyzed. In addition, seasonal source apportionment of PM2.5 was conducted using the principal component analysis(PCA) method and random forest(RF) algorithm model. The results indicated that ρ(PM2.5) was the highest in winter[(61.33±35.32) μg·m-3] and the lowest in summer[(17.87±10.06) μg·m-3]. Furthermore, organic carbon(OC), with a concentration of(7.27±3.51) μg·m-3, accounted for the major proportion compared with that of elemental carbon(EC) in the carbonaceous component of PM2.5. NO3-, SO42-, and NH4+ had the highest proportion in ionic components, with concentrations of (11.55±3.86),(7.55±1.53), and (7.34±1.99) μg·m-3, respectively. K, Fe, and Ca were the main elements in elemental components, with concentrations of (752.80±183.98),(542.34±142.55), and (459.70±141.99) ng·m-3, respectively. Relying on main factor extraction by PCA and quantitative analysis by RF, five emission sources were ultimately confirmed. The seasonal concentration distribution of these emission sources was as follows:coal burning and secondary sources(46%, 39%, 41%, and 52% for spring, summer, autumn, and winter, respectively) made the highest contribution to PM2.5, followed by vehicle emission sources(22%, 28%, 27%, and 21%), industrial emission sources (14%, 18%, 17%, and 13%), dust sources (10%, 8%, 6%, and 6%), and biomass burning sources (8%, 7%, 9%, and 8%). The valuation of the RF model was evaluated using multiple indicators, including RMSE, MSE, and R2. The evaluation results showed that the model for winter had the best performance (R2=0.974, RMSE=3.795 μg·m-3, MAE=2.801 μg·m-3), the models for spring (R2=0.936, RMSE=3.512 μg·m-3, MAE=2.503 μg·m-3) and autumn (R2=0.937, RMSE=4.114 μg·m-3, MAE=3.034 μg·m-3) performed with moderate-fitting goodness, and the summer model showed a relatively weak-fitting performance (R2=0.866, RMSE=5.665 μg·m-3, MAE=3.889 μg·m-3). The RF model had a satisfactory performance in PM2.5 source apportionment and had excellent prospects in analyzing massive historical data of air pollutants.

Assessing Pelvic Tilt in Patients Undergoing Total Hip Arthroplasty Using Sensor Technology

BackgroundThe purpose of our study was to assess the accuracy of a commercially available wearable sensor in replicating pelvic tilt movement in both the sitting and standing position in patients before total hip arthroplasty.MethodsThis prospective study evaluated patients undergoing a primary unilateral total hip arthroplasty by a single surgeon. Patients were excluded if they had a body mass index (BMI) greater than 40 kg/m2. Two sensors were adhered directly to patients’ skin at S2 and T12. The S2 angle was recorded on the sensor at maximum flexion and extension angles and compared with pelvic tilt measurements on both sitting and standing radiographs. The primary outcomes recorded were patients’ pelvic tilts measured using radiographs (PT-RAD) and sensors (PT-SEN), with Pearson correlation coefficients and intraclass correlation coefficients (ICCs) calculated.ResultsSixty-one patients (35 males and 26 females) with an average age of 61.5 ± 8.5 years and BMI of 26.9 ± 4.1 kg/m2 were analyzed. The mean prestanding PT-RAD and PT-SEN were 1.5 ± 8.3 and 1.0 ± 8.1, respectively, with an ICC of 0.98 (95% confidence interval, 0.96-0.99). The mean presitting PT-RAD and PT-SEN were -21.9 ± 12.5 and -20.9 ± 11.7, respectively, with an ICC of 0.97 (95% confidence interval, 0.95-0.98). The multiple R2 was 0.95 for the prestanding and presitting comparisons. The R2 for all comparisons between PT-RAD and PT-SEN was >0.85, regardless of BMI or sex.ConclusionsAlthough the use of wearable technology may have limitations, based on our results, a wearable sensor is accurate in replicating pelvic tilt movement.

In silico evaluation of molecular interactions between macrocyclic inhibitors with the HCV NS3 protease. Docking and identification of antiviral pharmacophore site

An array of computational approaches DFT/QSAR/POM methods has been used for a better understanding of drug properties regarding 13 inhibitor derivatives containing either P2 cyclopentane P1 carboxylic acid moiety (1-9) or a P1 cyclopropyl acyl sulfonamide (10-13). To further recognize binding interactions and their activity trends, molecular docking studies were carried out with the use of HCV, which can be used to accurately predict the interactions of ligands with the receptor. The QSAR models are developed through the use of Multiple Linear Regression (MLR) together with Principal Component Analysis (PCA) methods. The statistical results indicate the multiple correlation coefficient R2 = 0.840, which shows favorable estimation stability, as well as showing a significant correlation between the HCV NS3 protease of the studied compounds and their electron-accepting ability. The POM analysis of the Physico-chemical properties of compounds 1-13, shows that they are bearing (O1, O2) and/or (O1, O2, O3) antiviral pockets, whereby all oxygen atoms are Osp2 and bearing negative charges. Similar to the reference ligand (F9K), the most active compound 10 was bound deeply into the binding cavity of NS3 protease making interactions with the residues Gly137, His57, Ala157, and His528. The anti-hepatitis pharmacophore site is similar to the anti-HIV pharmacophore site. Communicated by Ramaswamy H. Sarma

Prediction of Local Government Revenue using Data Mining Method

Local Government Revenue or commonly abbreviated as PAD is part of regional income which is a source of regional financing used to finance the running of government in a regional government. Each local government must plan Local Government Revenue for the coming year so that a forecasting method is needed to determine the Local Government Revenue value for the coming year. This study discusses several methods for predicting Local Government Revenue by using data on the realization of Local Government Revenue in the previous years. This study proposes three methods for forecasting local Government revenue. The three methods used in this research are Multiple Linear Regression, Artificial Neural Network, and Deep Learning. In this study, the data used is Local Revenue data from 2010 to 2020. The research was conducted using RapidMiner software and the CRISP-DM framework. The tests carried out showed an RMSE value of 97 billion when using the Multiple Linear Regression method and R2 of 0,942, the ANN method shows an RMSE value of 135 billion and R2 of 0.911, and the Deep Learning method shows the RMSE value of 104 billion and R2 of 0.846. This study shows that for the prediction of Local Government Revenue, the Multiple Linear Regression method is better than the ANN or Deep Learning method. Keywords— Local Government Revenue, Multiple Linear Regression, Artificial Neural Network, Deep Learning, Coefficient of Determination

A designed experiment for CdS-AgBr photocatalyst toward methylene blue.

A boosted photocatalytic activity was observed for the CdS-AgBr nanocomposite in the degradation of methylene blue (MB). The experimental design method based on the response surface methodology (RSM) approach used to study the simultaneous interaction effects between the influencing variables. Analysis of variance (ANOVA) of the results confirmed a significant model for processing the data because an F value of 32.34 for the suggested model was higher than that of the critical value of F0.05, 14, 13 = 2.55 at 95% confidence interval. This analysis also showed a non-significant lack of fit (LOF) (as a measure of the randomness of the deviations around the obtained data) because the LOF F value of 8.27 was smaller than that of the critical value of F0.05, 10, 3 = 8.79. R2 values near to unity were achieved (the multiple correlation coefficients R2 (R2 = 0.9627), adjusted R2 (adj-R2 = 0.9226), and predicted R2 (pred-R2 = 0.7423)). Six center points suggested by the model included the following conditions: pH, 6.1; CMB, 3.5mg/L; a dose of the catalyst, 0.68g/L; and irradiation time, 40.5min. During the center point runs, the degradation efficiencies were obtained in the range of 38 to 43%. The optimal run included pH, 9; catalyst dosage, 1g/L; irradiation time, 60min; and CMB, 2mg/L, and the best removal efficiency of 98% was achieved during these conditions.

Evaluation of the elastic modulus of pavement layers using different types of neural networks models

Introduction. This paper studies the capability of different types of artificial neural networks (ANN) to predict the modulus of elasticity of pavement layers for flexible asphalt pavement under operating conditions. The falling weight deflectometer (FWD) was selected to simulate the dynamic traffic loads and measure the flexural bowls on the road surface to obtain the database of ANN models.Materials and Methods. Artificial networks types (the feedforward backpropagation, layer-recurrent, cascade back- propagation, and Elman backpropagation) are developed to define the optimal ANN model using Matlab software. To appreciate the efficiency of every model, we used the constructed ANN models for predicting the elastic modulus values for 25 new pavement sections that were not used in the process of training, validation, or testing to ensure its suitability. The efficiency measures such as mean absolute error (MAE), the coefficient of multiple determinations R2, Root Mean Square Error (RMSE), Mean Absolute Percent Error (MAPE) values were obtained for all models results.Results. Based on the performance parameters, it was concluded that among these algorithms, the feed-forward model has a better performance compared to the other three ANN types. The results of the best four models were compared to each other and to the actual data obtained to determine the best method.Discussion and Conclusions. The differences between the results of the four best models for the four types of algorithms used were very small, as they showed the closeness between them and the actual values. The research results confirm the possibility of ANN-based models to evaluate the elastic modulus of pavement layers speedily and reliably for using it in the structural assessment of (NDT) flexible pavement data at the appropriate time.

PENGARUH PERILAKU PIMPINAN, DISIPLIN KERJA, DAN GAJI TERHADAP KINERJA KARYAWAN PADA DEPARTEMEN PRODUKSI PT. GEMBIRA BATAM

The purpose of this study was to determine: (1) To determine the effect of leadership behavior on employee performance at PT. Gembira Batam. (2) To determine the effect of work discipline on employee performance at PT. Gembira Batam. (3) To determine the effect of salary on employee performance at PT. Gembira Batam. (4) To determine the effect of leadership behavior, work discipline and salary simultaneously affecting employee performance at PT. Gembira Batam. The dependent variable of this study is employee performance (Y). The independent variables include: leadership behavior (X1), work discipline (X2), and salary (X3). The research method used is quantitative research methods. The sampling technique used purposive sampling method with a total sample of 67 people. The data collection technique uses a questionnaire that has been tested for validity and reliability. The data analysis technique used to answer the hypothesis is multiple regression, t test, F test, and R2. The results of this study indicate that: (1). There is an influence of leadership behavior on employee performance at PT. Gembira Batam is evidenced by the t value of 2.478 with a significant value of 0.000 &lt;0.05 and a regression coefficient of 0.023, (2). There is an effect of work discipline on employee performance at PT. Gembira Batam is evidenced by the t value of 5.794 with a significant value of 0.000 &lt;0.05 and a regression coefficient of 0.392, (3). There is an effect of salary on employee performance at PT. Gembira Batam is evidenced by the t value of 9.973 with a significant value of 0.000 &lt;0.05 and a regression coefficient of 0.584, and (4). There is an influence of leadership behavior (X1), work discipline (X2), and salary (X3) simultaneously. on employee performance at PT. Gembira Batam. evidenced by the calculated F value of 58.027 with a significant value of 0.000 &lt;0.05.

Determinants of Emerging Capital Markets Development: A Case of Dar Es Salaam Stock Exchange

This study aims to assess determinants of emerging capital markets development with particular reference to Dar es Salaam Stock Exchange (DSE). Specifically, the study aimed to analyze influence of legal and institutional framework, influence of political and macroeconomic stability and effects of broadening the investors’ base on capital markets development. The study employed time series research design. Data from statistical observations were recorded in a duration of 10 years (2011-202) on capital market development in relation to macroeconomic factors including liquidity in the stock market, investment, banking sector expansion and foreign direct investment. The regression findings correspondingly showed that the multiple determination coefficient R2 is 0.9272. The result showed that the exogenous variables (INTR, INFL, EXCHR, NINFA and LFW) are explained by 92.72% of the variations in dependent variable (CMD) while remaining 7.28 % are attributed to other factors not considered in the model are to blame. In addition, Durbin Watson (DW) statistics of 1 were disclosed in the results. The study recommends that small and medium businesses, which play a significant role in Tanzania's economy, should also be encouraged to engage in the stock market. A systematic and comprehensive investment promotion and facilitation plan that suits Tanzania's interests is required. Savings habit must be encouraged in the country by government policies that favour it. Also, as a country attracts foreign investment, more jobs become available, and individuals have more money to save. In addition, foreign direct investment adds management and technology transfer capabilities.

城市基质对城市遗存自然山体植物群落物种多样性的影响--以贵阳市为例

PDF HTML阅读 XML下载 导出引用 引用提醒 城市基质对城市遗存自然山体植物群落物种多样性的影响--以贵阳市为例 DOI: 10.5846/stxb202101070069 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(32060367)；贵州省科学技术基金重点项目(黔科合基础[2020]1Z011)；贵州省科技支撑项目(黔科合支撑[2021]一般458) Exploring the relationship between the plant diversity of the urban remnant mountains and its surrounding urban matrix characteristics：A case study of Guiyang City Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:多山地区城市扩展过程中,建成区内遗存有大量自然山体,形成城市人工基质"海"中的遗存山体"岛屿生境",这些城市遗存山体长期受到来自城市人工环境的各种间接或直接的干扰。为探索城市基质与城市遗存自然山体植物群落多样性之间的关系,以黔中地区典型的喀斯特多山城市--贵阳为研究区域,按不同规模选择15座城市遗存山体,每座样山按坡向+坡位组合方式设置群落调查样地,共设置143个样地;以样山边界为基准,100 m为步长向外设置20个缓冲区,总宽度为2000 m,计算缓冲区总不透水表面积(PTIA)、植被覆盖度(VC)、破碎化指数(FI)、土地利用(LU)4个城市基质特征指标。运用Pearson相关分析和线性回归模型分析了城市基质特征指标与城市遗存山体植物群落物种多样性之间的相关关系。结果表明:①PTIA对不同规模城市遗存山体整体植物多样性的影响都存在明显空间尺度效应,在2000 m时相关性最高,呈显著正相关;不同规模城市遗存山体整体植物多样性与单个或多个LU类型存在显著相关性,但影响效应存在显著差异;VC、FI与城市遗存山体整体植物多样性无显著相关关系;②不同规模城市遗存山体各层次植物多样性与城市基质特征 4个指标在不同的空间尺度上均存在显著相关性;③城市遗存山体植物多样性Shannon-Wiener指数(H')与每个城市基质特征指标一元线性回归拟合度高,而多元回归R2为0。探明城市基质特征对城市遗存山体植物多样性具有一定的影响,但影响规律不一致且存在空间尺度差异,说明城市人工环境对城市遗存山体植物多样性维持的影响非常复杂,需要从不同的角度开展深入的研究,才有可能揭示城市遗存山体植物多样性的城市化响应机制,进而指导城市遗存山体保护规划与管理。 Abstract:In the process of urban expansion in mountainous areas, there are a large number of natural mountains remained in the urban built-up area, forming the urban remnant mountain "island habitat" in the urban artificial matrix "sea". These urban remnant mountains (URMs) have long been affected by a variety of indirect or direct interference from the urban artificial environment. To explore the relationship between the plant diversity of the URMs and its surrounding urban matrix characteristics, taking the urban built-up area of Guiyang, a typical karst mountainous city in central Guizhou, as the research area, fifteen URMs were selected according to different sizes as research objects in this study. The sample spots of each URM were set by the combination way of slope direction and slope position. A total of 143 plant diversity survey plots were set up on the fifteen URMs. Taking the edge line of sample URMs as datum, buffer zones were set successively outward at step lengths of 100 m and 20 buffer zones were set with a total width of 2000 m. The proportion of total impervious surface area (PTIA), vegetation coverage (VC), fragmentation index (FI) and land use (LU) of each zone were calculated. The correlation between the urban matrix characteristic indices and the species diversity indices of the URMs plant communities was analyzed using the Pearson correlation analysis and the linear regression model. The results showed that: (i) the influence of PTIA on the overall plant diversity of different size URMs had obviously spatial scale effects, with the highest correlation and significantly positive correlation at 2000 m; The overall plant diversity of different size URMs were significantly associated with a single or multiple LU types, but the impact effects were significantly different; There was no significant relationship between VC and FI and the overall plant diversity of URMs. (ii) The plant diversity indices of all plant levels of different size URMS were correlated with the four indices of urban matrix characteristics at different spatial scales. (iii) The Shannon-Wiener index (H') had a high linear regression fit to each urban matrix index, however the multiple regression R2 was 0. In this study, it was explored that the urban matrix characteristics had some influence on the plant diversity of URMs in different scales, but the influence laws were inconsistent. It shows that the impact of urban artificial environment on the maintenance of plant diversity of URMs is very complex. It is very necessary to conduct in-depth research from different perspectives to reveal the urbanization response mechanism of plant diversity of URMs, and then guide the protection planning and management of URMs. 参考文献 相似文献 引证文献

Prediction of SPAD values for paddy leaves using smartphone-based direct contact imaging method

The Soil Plant Analysis Development (SPAD) value obtained from the SPAD meter is directly related to leaf chlorophyll content. The chlorophyll content is related to nitrogen content means the amount of fertilizer of a crop. Therefore, determining SPAD value is directly involved with crop health. Minolta SPAD meter can directly measure this value, and this is a well-established method in the research field for measuring chlorophyll content. Still, this instrument is too costly, which is beyond a farmers’ reach in the perspective of Bangladesh. The purpose of this study is to predict the SPAD value for paddy leaves using the smartphone-based direct contact imaging method to estimate the chlorophyll content of a paddy leaf. Numerous features were extracted from each image to predict the SPAD values. The features were then used as parameters in the multiple linear regression model. The models' performance was evaluated using images captured from a paddy field using a Minolta SPAD-502 Chlorophyll Meter. The multiple linear regression model's R2 and root mean square error (RMSE) values were 0.71 and 3.6512, respectively. Therefore, this result confirms that the direct digital contact imaging method has the potential to quantify the SPAD value of paddy leaves accurately. However, these results could be more accurate if the image acquisition was made from the seedling to mature stage of the paddy. In the future, an android app will be developed using this value which can directly measure the chlorophyll content of paddy leaves.