Standard Error Research Articles

Sleep duration among breastfed, goat milk-based or cow's milk-based infant formula-fed infants: Post hoc analyses from a double-blind RCT.

To determine total, night- and daytime sleep duration and waking frequency among infants exclusively fed goat milk-based infant formula (GMF) or cow's milk-based infant formula (CMF) enroled in a randomised controlled trial and compare these to a human milk (HM) fed reference group. Post hoc analysis from a double-blind randomised controlled trial in 304 healthy term infants was performed. Formula-fed infants were randomly assigned to receive exclusively GMF or CMF for a period of 112 days and compared to a reference group fed HM. Sleep was assessed using a 3-day 24-h diary before the five visits throughout the trial. The association between feeding type and sleep was studied longitudinally and cross-sectionally at the five visits. All models were adjusted for infant sex and study site of enrolment. For associations between formula-fed infants and the non-randomised HM group, additional adjustments were made. Total sleep duration slowly and similarly decreased over the course of study duration for all groups, with a decrease of about an hour between the first and last measurement. Longitudinally, daytime sleep duration was significantly longer for GMF (mean 8.6 h, standard error [SE] 0.17) and HM (8.8, 0.18) fed infants as compared to CMF (8.1, 0.17; p < 0.05). Cross-sectional analyses show that infants fed GMF or HM had higher total sleep duration than infants fed CMF at all visits, with significant differences between the groups at Visits 3 and 4. In infants fed GMF a significantly longer daytime sleep duration and a non-significant trend towards a longer total sleep duration were found when compared to infants fed CMF. These findings suggest that nutrition plays a role in sleep duration.

Engineer CEOs and corporate investment efficiency

Purpose This paper aims to examine whether CEOs with an engineering background increase corporate investment efficiency (CIE). The authors further investigate the role of engineering directors on boards of the above association. Design/methodology/approach Drawing from upper-echelon theory, which suggests that corporate outcomes are a reflection of its top management characteristics, the authors hypothesise a positive association between engineer CEOs and CIE and a positive moderation role of the proportion of engineer directors on boards in the above association. The authors examine this link using a sample of Australian Securities Exchange 200 firms from 2015 to 2022. Engineer CEO data is hand-collected from corporate annual report biographies and investment efficiency is a measure that captures whether the investments are maintained at optimal levels relative to industry-year benchmarks, following the approaches of Biddle et al. (2009), Chen et al. (2011) and the average values of both models. Findings The results indicate support for the hypotheses, revealing that firms managed by engineer CEOs have higher investment efficiency than their counterpart firms. This association is exacerbated in the presence of a higher proportion of engineer directors on boards. The results are robust to year and industry-fixed effects, propensity score matching, alternative measures of investment efficiency and robust standard errors. Our results also remain valid for an industry sub-sample using certain industries in which engineering expertise maybe more desirable (e.g. metals and mining). Research limitations/implications By showing that engineer CEOs are significantly associated with CIE, the authors contribute to upper-echelon literature examining the link between CEO characteristics and corporate outcomes, particularly, investment decision efficiency. The influence of engineering background on corporate outcomes is less examined in the literature; thus, the authors contribute to this thin literature. Originality/value The findings are informative to potential investors in evaluating firms’ investment efficiency before investing in firms. For example, firms with engineer CEOs are likely to maintain efficient investment levels in future years.

Efficacy and safety of switching to insulin glargine 300 U/mL in people with type 2 diabetes uncontrolled on basal insulin in China: A post hoc subpopulation analysis of the INITIATION study.

To evaluate the efficacy and safety of insulin glargine 300 U/mL (Gla-300) in people with uncontrolled type 2 diabetes (T2D) switching from another basal insulin (BI). INITIATION was an interventional, single-arm, phase IV study conducted in China. In this post hoc subpopulation analysis, the efficacy and safety of switching to Gla-300 was investigated in individuals with uncontrolled T2D (HbA1c 7.5%-11.0% [58-97 mmol/mol]) with previous BI. The primary endpoint was HbA1c change at week 24. Other measures of glycaemia, hypoglycaemia, insulin dose and weight change were assessed. Three hundred and two participants switched to Gla-300 from another BI, including 232 from insulin glargine 100 U/mL (Gla-100) and 55 from insulin degludec (IDeg). At week 24, the mean ± standard error (SE) HbA1c change from baseline was -0.87% ± 0.06% (-9.5 ± 0.7 mmol/mol; p <0.001). Significant reductions in fasting plasma glucose (least-squares mean [LSM] change -1.13 mmol/L) and fasting self-measured blood glucose (LSM change -1.36 mmol/L) were also observed (both p <0.001). The mean daily BI dose increased from 18.86 U (0.27 U/kg) at baseline to 28.83 U (0.41 U/kg) at week 24. During the 24-week treatment period, the incidence of any hypoglycaemia was 43.8% for all hypoglycaemia and 15.1% for nocturnal hypoglycaemia; the incidence of severe hypoglycaemia was low (0.7%). Minimal body weight change was documented. Gla-300 improved glycaemic control with a relatively low hypoglycaemia risk and minimal weight gain in Chinese people with T2D uncontrolled on previous BI.

Impact of tourism, globalization, and technological patents on ecological footprint in ASEAN countries: static and dynamic panel regression approaches

This study aims to investigate the intricate relationship between multiple socioeconomic, human capital, and technological factors and their impacts on the ecological footprint within the ASEAN region. Focusing on eight ASEAN nations (Brunei, Cambodia, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) for the period between 1990 and 2020, this study employs Driscoll Kraay Standard Error (DKSE) and Quantile Regression methodologies to examine this phenomenon comprehensively. The findings reveal that the Human Capital Index (HCI) and technological patents exhibit negative coefficients, suggesting their beneficial impact on reducing ecological footprint by 0.162% and 0.027% sequentially in the DKSE approach. By contrast, population, GDP, tourism, globalization, and trade openness show positive coefficients, indicating their potential to exacerbate environmental degradation. Notably, population emerged as the most detrimental factor. Meanwhile, HCI demonstrated the most potent beneficial effect on environmental quality, suggesting that ASEAN nations should continue investing in their people to safeguard the environment. The implications of this study are critical for policymakers and stakeholders in the ASEAN region, highlighting the need for strategic interventions that balance economic and technological advancements with environmental preservation.

Headache Disability Questionnaire: cross-cultural adaptation and validation of the Turkish version

BackgroundThe Headache Disability Questionnaire (HDQ) evaluates pain intensity, daily activities, work/school disruptions, and the impact on recreational activities. It was aimed to translate the HDQ into Turkish and evaluate its reliability and validity.MethodsThis study included 130 participants, consisting of 105 females and 25 males. The original HDQ was translated into Turkish language using Beaton guidelines. Reliability was assessed using internal consistency and Intraclass Correlation Coefficient. Exploratory (EFA) and Confirmatory Factor Analysis (CFA) were conducted to evaluate the structural validity. For convergent validity, the Turkish version of the HDQ, along with the Headache Impact Test-6 (HIT-6) and Migraine Disability Assessment Scale (MIDAS), was administered to individuals with headaches. The HDQ was retested one week later to assess its reliability.ResultsThe Turkish version of the HDQ demonstrated good reliability, with ICC and Cronbach’s α values of 0.842 and 0.914, respectively. Standard error measurement (SEM) and Minimal Detectable Change (MDC) values were 5.89 and 16.33 units. Bland-Altman plots confirmed a high level of agreement between initial and retest scores EFA revealed a two-factor structure, clustering items into Factor 1 (items 1, 2, 5, 7, and 9) and Factor 2 (items 3, 4, 6, and 8), which was subsequently confirmed by CFA. Convergent validity was confirmed through good correlations with HIT-6, and MIDAS. No ceiling or floor effects were observed.ConclusionsThe study demonstrates that the Turkish version of the HDQ is a valid and reliable instrument for evaluating the effect of headaches on daily living, exhibiting strong internal consistency and test-retest reliability, making it suitable for both clinical practice and research purposes.Trial registrationTrial registration date is January 30, 2021 (NCT04736654).Clinical trials registration numberNCT04736654.

Relation of skinfold thickness with the serum lipids, glucose and blood pressure among Indian sedentary office workers

Background:Serum glucose, cholesterol, triglycerides and high-density lipoproteins (HDL) are established cardiovascular disease (CVD) markers, however accessibility to these markers is less in individuals from low-middle income countries. The non-invasive CVD risk marker especially skinfold measured fat percentages are less explored for its relevance with established serum biochemistry markers.Methods:A cross-sectional study was conducted in 70 sedentary office workers (aged 30–40 years) who were healthy. Peripheral fat percentages were estimated from four skinfold thickness measurements and biochemistry markers were measured and analysed using standard laboratory measurements. Blood pressure was also measured. Multivariate linear regression models were drawn to establish the association between the non-invasive and invasive CVD risk markers.Results:The skinfold measured fat percentage was negatively associated with the HDL (coefficient β = -0.15, standard error SE = 0.07, p < 0.05). No significant relation between the other biochemistry parameters with the skinfold thickness. Age and BMI were found to be mediating the above relationship.Conclusions:Skinfold thickness derived fat percentage is associated with the few of the CVD markers (especially HDL). Age and BMI are crucial mediating factors for the fat measurement. Skinfold measurements could be included as part of routine primary care screening for CVD risk, alongside invasive biochemistry parameters.

Examining soccer skill performance using a dual task paradigm

The purpose of this study was to evaluate the reliability and validity of a holistic test (Soccer Skills and Cognitive Aptitude Test [SoSCAT]) that assesses soccer skills and performance in a dual-task (DT) context. A total of 73 male soccer players aged 12–18 years joined in this study. They were playing in three official Spanish regional leagues, and were divided according to their age into under 14 (U14, n = 25), under 16 (U16, n = 26), and under 18 (U18, n = 22). Additionally, players were categorized dichotomously into high-talented (n = 20) and lower-talented (n = 53) groups. Several soccer-skill and cognitive tests were evaluated. Regarding absolute reliability, the standard error of measurement (SEM) was 2.27 (5.30%) and the minimal detectable change (MDC) was 4.17 (9.75%). In relative reliability, the intra-class correlation coefficient was 0.908 (95% confidence interval [CI] = 0.826–0.951, p &lt; 0.001). By category, the U18 group showed a higher performance in SoSCAT (p &lt; 0.001) than U16 and U14. In addition, the DT cost (DTC) and ΔTime were the lowest in the U18 group (p = 0.041). Moreover, the high-talent group showed the best performance in SoSCAT (p = 0.001), DTC (p &lt; 0.001), and in ΔTime (p &lt; 0.001). To sum, the SoSCAT is a reliable tool for use under the DT context and it discriminates between levels of players and determines several variables that are relevant to soccer performance and that could help to early identify soccer talent.

Socioeconomic status and sleep duration among a representative, cross-sectional sample of US adults

BackgroundSleep is a crucial determinant of physical and mental health outcomes, and insufficient sleep is highly prevalent among United States adults. Although some risk factors of poor sleep have been extensively studied, including substance use, age, health behaviors, and others, the associations between socioeconomic status (SES) and sleep remain inconclusive. There is limited evidence on SES and sleep duration among the US adult population. This study analyzed the relationships between three SES indicators (poverty, education, and food security), and sleep duration.MethodsWe used responses from the 2017-March 2020 National Health and Nutrition Examination Survey (NHANES). Respondents younger than 25 years old were excluded. Sleep duration was classified using self-reported sleep time and stratified by work vs. non-workdays. SES was operationalized using three indicators: poverty-income ratio, educational attainment, and food security status. We imputed missing data for socioeconomic status and outcome variables using multiple imputation. Weighted Poisson regression models with robust standard errors were used to calculate the crude and adjusted prevalence ratios for insufficient sleep duration (< 7 h of self-reported sleep) on workdays and non-workdays separately by each of the three SES indicators.ResultsWe included a total of 8,457 individuals. In the adjusted model, participants with lower income, educational status, and food security had significantly higher prevalence of insufficient sleep duration on both workdays and non-workdays. For example, low-income individuals (poverty-income ratio < 1) had 1.22 (95% CI 1.04–1.44) and 2.08 (95% CI 1.61–2.67) higher prevalence of insufficient sleep as compared to high income individuals on workday and non-workdays, respectively. In general, we found larger differences by level of SES indicator for the non-workday than for the workday outcome. There were no major differences in gender-stratified analysis. We also found that lower SES was associated with higher prevalence of excessive sleep (≥ 9 h).ConclusionSocioeconomic status indicators are significantly associated with sleep duration in the US adult population. Lower SES correlates with increased prevalence of insufficient sleep duration, which has implications for the overall wellbeing of US adults with lower SES. Targeted interventions and further research are needed to reduce this disparity.

The Effects of Technology and Innovation Adoption on Firm Performance among Small and Medium Enterprises: Evidence from Vietnam’s Logistics Sector

In Industry 4.0, technology and innovation constitute a driver for enhancing firms’ performance, particularly for small and medium-sized enterprises (SMEs). Our study aims to examine whether that statement is correct for SMEs in a developing country. We develop a generic model and employ multiple regression techniques, including ordinary least-squares, robust standard errors and weighted least squares, to test this hypothesis and address heteroskedasticity. Using a micro-level dataset including 11,630 SMEs in Vietnam’s logistics sector, an emerging logistics market in a developing country, our results reveals that the effects of technology on firm performance may differ depending on particular metrics of this performance. Furthermore, not all forms of innovation significantly affect SME performance. Control variables such as “firm’s age”, “firm’s size”, “state ownership”, “education of the manager” and “foreign activities” also play a significant role in SME performance, underscoring the importance of both internal capabilities and external technological elements.

Changes in retail cigarette price after tax increase: Findings from the 2018-2020 ITC Vietnam surveys.

No longitudinal study has investigated the impact of cigarette tax increases on retail prices in Vietnam. This study aims to describe changes in the purchase price of cigarettes following an excise tax increase from 70% to 75% in January 2019. Data were collected from people who currently smoke cigarettes in the longitudinal ITC Vietnam surveys: 1870 participants in Wave 1 (pre-increase), 1564 in Wave 2 (post-increase), and 1308 in Wave 3 (post-increase). Weighted mean self-reported prices of a cigarette pack (with standard error) were calculated for participants who were successfully followed up across three waves. These mean prices were calculated for domestic and international brands, categorized by specific cigarette brands. Percentage changes in mean prices were also measured, and significant differences in mean prices between follow-up waves (Waves 2 and 3) and the baseline (Wave 1) were assessed using paired t-tests. For brands with very small sample sizes, we used non-parametric tests, specifically the Wilcoxon signed-rank test instead of paired t-tests. The weighted mean price of a cigarette pack remained low and stable: VND 12330 (US$0.54) in 2018, VND 12700 (US$0.55) in 2019, and VND 12120 (US$0.53) in 2020 (1000 Vietnamese Dongs about US$0.04345, at 2018). International brands were substantially more expensive than domestic brands, but prices for both remained constant across all waves. Among domestic brands, Thang Long and Sai Gon showed slight price increases of around 3% and 5%, respectively (p<0.05). Among international brands, no statistically significant increase in mean prices was observed. The retail price of cigarettes remains low, indicating that the slight tax increase was insufficient to raise the current retail price significantly. Therefore, a substantial increase in cigarette prices by adding a specific tax is necessary.

Spatial Prediction of Soil Total Phosphorus in a Karst Area: Comparing GWR and Residual-Centered Kriging

Accurate soil total phosphorus (TP) prediction is essential to support sustainable agricultural practices and formulate ecological conservation protection policies, particularly in complex karst landscapes with high spatial variability and high phosphorus and cadmium content and interactions, complicating nutrient management. This study uses GIS and geostatistical methods to analyze the spatial distribution, influencing factors, and predictive modeling of soil TP in the karst region of northern Mashan County, Guangxi, China. Using 427 surface soil samples, we developed five predictive models: ordinary kriging (OK), regression kriging (RK) and geographically weighted regression kriging (GWRK) combined with environmental variables such as land uses, soil types, and topographic factors; residual mean-centered kriging (MM_OK), and residual median-centered kriging (MC_OK). Our results indicate that higher TP levels were observed in agricultural lands (paddy fields and dry land, at 766 and 913 mg·kg−1, respectively) may due to fertilization, while forests and shrublands showed lower TP levels (383 and 686 mg·kg−1, respectively), reflecting natural phosphorus cycling. The high-value areas of soil TP concentration are in the karst areas in the west and east of the study area, and the low-value area is in the Hongshui River valley in the north of Mashan. The spatial distribution of soil TP is affected by land use, soil type, and topography. The GWRK model exhibited superior accuracy (80.6%), with predicted concentration of TP closely aligning with observed TP values, effectively capturing fine spatial variations, and showing the lowest mean standardized error, average standard error, and mean absolute error. GWRK also achieved the highest R2 (0.67), demonstrating robust predictive capability. MM_OK and MC_OK models performed well and showed smoother spatial transitions, while the OK model displayed the lowest predictive accuracy (62%). By utilizing spatially adaptive weighting, GWRK and its residual-centered kriging method improve soil TP’s prediction accuracy and smoothness in karst areas, providing a reference for targeted soil conservation and sustainable agricultural practices in spatially complex karst environments.

Diameter Growth of Melia azedarach var. umbraculifera

The objective of this work was to model the diametric growth of Melia azedarach trees, in the region of Campanha, state of Rio Grande do Sul. 31 trees that showed no signs of pruning were randomly selected. Three increment borers per tree were removed, the first being 30 cm from the ground for age development and the other two orthogonal at 1.3 m (dbh) for growth analysis. Linear models with and without intercept were fitted to estimate the diameters with bark (y) as a function of the diameter without bark (x), using several transformations of the independent variables (x). In the modeling, the stepwise method was used for variable selection, being kept in the models only as a variable with the highest adjusted R² and with a significant F value at 5%. Next, multicollinearity was resisted through the variance survival value (VSV), being kept in the models only as the most significant variables by the t-test and with VSV less than 10. The selection of the best ones considered was based on the Standard Error of Estimation in percentage (Syx%), Coefficient of Determination adjusted (adjusted R²) and, in the case of diametric growth lines, the Akaike Information Criterion (AIC) was also used. The species presents moderate to fast growth and reaches sufficient dimensions for the production of wooden parts for joinery and carpentry. Among the medications used to describe diametric growth, the Chapman-Richards medication presented the best result, with statistics that allow its safe use under the conditions of this study.

A Two-Parameter Ridge Estimator for Handling Extreme Multicollinearity Problems in Logistic Regression

This paper introduces a robust two-parameter ridge estimator that is customized for logistic regression models, which tend to be sensitive to extreme multicollinearity problems. Inflated standard errors and unreliability in the results stem from the problem of multicollinearity characterized by high correlations among predictor variables in logistic regression model. Traditional approaches like the Maximum Likelihood Estimator (MLE) and one-parameter ridge-type estimators often perform poorly under these settings, thus calling for the development of more robust approaches. This new proposal is called New Biased Two Parameter (NBTP), which extends the ridge regression framework by introducing additional biasing parameters customized for an extreme multicollinearity problem. The paper combines a theoretical analysis with extensive Monte Carlo simulations and real application to Pena data. It demonstrates that the new estimator, New Biased Two Parameter (NBTP), provides much more stable and accurate parameter estimates than previous methods. The results underscore the importance of using robust estimation methods within logistic regression, especially when multicollinearity may be widespread in fields such as medical research, finance, and the social sciences.

Integration of Drone and Satellite Imagery Improves Agricultural Management Agility

Effective agricultural management hinges upon timely decision-making. Here, we evaluated whether drone and satellite imagery could improve real-time and remote monitoring of pasture management. Using unmanned aerial systems (UAS), we quantified grassland biomass through changes in sward height pre- and post-grazing by sheep. As optical spectral data from Sentinel-2 satellite imagery is often hindered by cloud contamination, we assessed whether machine learning could help improve the accuracy of pasture biomass prognostics. The calibration of UAS biomass using field measurements from sward height change through 3D photogrammetry resulted in an improved regression (R2 = 0.75, RMSE = 1240 kg DM/ha, and MAE = 980 kg DM/ha) compared with using the same field measurements with random forest-machine learning and Sentinel-2 imagery (R2 = 0.56, RMSE = 2140 kg DM/ha, and MAE = 1585 kg DM/ha). The standard error of the mean (SEM) for the field biomass, derived from UAS-measured sward height changes, was 1240 kg DM/ha. When UAS data were integrated with the Sentinel-2-random forest model, SEM reduced from 1642 kg DM/ha to 1473 kg DM/ha, demonstrating that integration of UAS data improved model accuracy. We show that modelled biomass from 3D photogrammetry has significantly higher accuracy than that predicted from Sentinel-2 imagery with random forest modelling (S2-RF). Our study demonstrates that timely, accurate quantification of pasture biomass is conducive to improved decision-making agility, and that coupling of UAS with satellite imagery may improve the accuracy and timeliness of agricultural biomass prognostics.

Site-based and Digital Cohort Participation Among Transgender Women in the Eastern and Southern USA: Findings from the LITE Study.

Transgender women (TW) are highly burdened by HIV. There is increasing interest in digital (i.e., through internet-based interfaces) HIV research; yet few studies have assessed potential biases of digital compared to site-based data collection. This study examined differences in characteristics between TW participating via site-based versus digital-only modes in an HIV incidence cohort. Between March 2018-Aug 2020, a multisite cohort of 1,312 adult TW in the eastern and southern USA was enrolled in site-based and exclusively digital modes. We evaluated differences in baseline demographics, socio-structural vulnerabilities, healthcare access, gender affirmation, mental health, stigma, social support, and HIV acquisition risk comparing site-based vs digital modes using chi square tests and Poisson regression modeling with robust standard errors. The overall median age was 28 (interquartile range=23-35) years and over half identified as people of color (15% Black, 13% Multiracial, 12% Another Race, 18% Latina/e/x). A higher proportion of site-based (vs. digital mode) participants resided in the Northeast, were younger, identified as people of color, experienced socio-structural vulnerabilities, had a regular healthcare provider, received medical gender affirmation, endorsed mental health symptoms and stigma, reported HIV acquisition risk but also greater experience with biomedical HIV prevention (pre-exposure and post-exposure prophylaxis), and had larger social networks (all p<0.05). Site-based and digital approaches enrolled TW with different demographics, life experiences, and HIV acquisition risks. A hybrid cohort model may achieve a more diverse and potentially representative sample of TW than either site-based or online cohorts alone for HIV research.

Pengaruh Institusi Terhadap Derajat Desentralisasi Fiskal di Indonesia

The main issue underlying this research is the significant disparity in the degree of fiscal decentralization among provinces in Indonesia, particularly between provinces in Java and outside Java, and the persistently high fiscal dependency of several regions on the central government. This study aims to analyze the influence of democracy, economic growth, Gini ratio, and population size on the degree of fiscal decentralization in Indonesia. Using panel data from 32 provinces during the 2012-2023 period, this research applies a Random Effect Model (REM) with robust standard error. The results show that democracy, economic growth, and population size have positive and significant effects on the degree of fiscal decentralization, while the Gini ratio shows no significant influence. These findings imply that improvements in democratic quality, economic growth, and optimization of demographic potential can strengthen regional fiscal independence. This research recommends that local governments focus their policies on strengthening democratization, increasing economic growth, and optimizing human resource potential to enhance regional fiscal independence.

Population-specific equations for stature estimation using forearm bones: insights from Northeastern Thailands diverse ethnic landscape.

Stature estimation from skeletal remains is crucial in forensic anthropology. This study aimed to develop population-specific equations for stature estimation using ulna and radius measurements in a Northeastern Thai population, a region known for its ethnic diversity. A total of 400 ulnae and 400 radii (200 of each bone from each sex) were analyzed from dry bone specimens. The study objectives were to: (1) develop and validate regression equations for stature estimation, (2) investigate sex differences in the relationship between forearm bone lengths and stature, and (3) compare the accuracy of these equations with existing formulae for other populations. Results showed significant sexual dimorphism in stature and bone lengths. The mean stature was 164.93 ± 6.54 cm for males and 156.21 ± 5.81 cm for females (p < 0.05). Positive correlations were observed between bone lengths and stature, with stronger correlations in males (ulna: r = 0.670; radius: r = 0.663) compared to females (ulna: r = 0.402; radius: r = 0.393). Regression equations for the pooled sample yielded coefficients of determination (r²) of 0.516 for ulna and 0.509 for radius. Sex-specific equations demonstrated higher accuracy, particularly for males. The standard error of estimate ranged from 4.87 cm to 5.35 cm across all equations. These findings suggest that ulna and radius lengths are reliable predictors of stature in the Northeastern Thai population, with sex-specific equations offering improved accuracy. This study contributes to the development of population-specific standards in forensic anthropology and highlights the importance of considering sexual dimorphism in stature estimation. The results have significant implications for forensic investigations and archaeological studies in the region.

Machine learning derived physical activity in preschool children with developmental coordination disorder.

To compare the device-measured physical activity behaviours of preschool children with typical motor development to those with probable developmental coordination disorder (pDCD) and at risk for developmental coordination disorder (DCDr). A total of 497 preschool children (4-5 years) in the Coordination and Activity Tracking in CHildren (CATCH) study completed repeated motor assessments and wore an ActiGraph GT3X on the right hip at baseline for 1 week. We calculated physical activity metrics from raw accelerometer data using a validated random forest classification machine learning model for preschool-age children. Analysis of variance (ANOVA) and linear regression models compared physical activity between typically developing children, children at risk for DCDr, and those with pDCD identified based on motor scores at baseline and averaged over time, accounting for age, sex, and accelerometer wear time. We found no differences in daily time spent sedentary, in light physical activity, or moderate-to-vigorous physical activity between typically developing children, children at risk for DCDr, and those with pDCD. However, children in the DCD groups spent less time doing ambulatory activities (walking/running) than typically developing children. Analysis of variance: baseline classification, DCDr to typically developing, run: F = 5.34, p = 0.005, classification averaged over time, DCDr to typically developing, walk: F = 5.82, p = 0.003. Regressions: DCDr compared to typically developing for walk: B = -3.47 (standard error 1.05), p < 0.001, pDCD compared to typically developing for run: B = -1.82 (standard error 0.62), p = 0.004. Designing interventions for preschool children with motor difficulties targeting specific physical activity types (walk/run) may help mitigate physical activity intensity differences observed later in childhood.

Designing hypothesis of substituted naphthyridines as anti-HIV agent: A QSAR Approach

HIV-1 Integrase is a validated drug target for anti-HIV therapy. It is an essential enzyme required for replication of the AIDS-virus. 1,3,4-oxadiazole substituted naphthyridine derivatives act against HIV integrase and thus have the potential to become a part of anti-HIV drug regime. In present study, we have carried out QSAR study of 1,3,4-oxadiazole substituted naphthyridine derivatives. Stepwise multiple linear regression analysis was performed to derive QSAR models and was evaluated for statistical significance and predictive power. The best QSAR model was selected for anti-HIV activity, having correlation coefficient (R) = 0.862, standard error of estimation (SEE) = 0.271 and cross validated squared correlation coefficient (Q2) = 0.676. The QSAR model indicates that shape index, partition coefficient and solvent accessible surface area play an important role in the anti-HIV activities of 1,3,4-oxadiazole substituted naphthyridine derivatives. The results of the present study may be useful in designing more potent analogues.

Kinetics of Non-exchangeable Potassium Release in Rice-groundnut Cropping System under Alluvial Soils of Odisha, India

Non exchangeable K release can very much influence soil K fertility. The experiment was carried out to investigate the amount of non-exchangeable potassium released from Inceptisols with rice-groundnut cropping system and to use various kinetic equations to describe the release. Release rates of non-exchangeable potassium were determined for five different soils collected from rice-groundnut cropping system fertilized @ 0 and 40 kg K ha-1 over three years. The non-exch K release rate was studied by successive extraction with 0.01M CaCl2 methods. The results show that the proportion of exch.K and non-exch.K to total K varied between 2.76 to 4.95% and 8.39 to 9.95%, respectively. Per cent of clay or silt+clay correlated significantly with water soluble, exch. and non-exch. K. Five mathematical models (elovich equation, power function, parabolic diffusion, first and zero order equation) were used to describe cumulative K release pattern. The elovich and parabolic equation described the K release kinetics satisfactory as evidenced by the highest correlation coefficients and lowest values of standard error of estimates (SEE). The release of Step-K and CR-K was higher in state recommend dose (SRD) than K control which concluded that the SRD of K (40 kgha-1) is adequate to sustain the productivity of intensive rice-ground nut cropping system in alluvial soils of Odisha.