Low Standard Error Research Articles

Co-workership: development of an assessment tool

Purpose The purpose of this study was to develop an easy-to-use, theoretically well-founded and psychometrically sound assessment tool of the concept co-workership. Design/methodology/approach Firstly, inductively generated examples of favourable and unfavourable co-worker behaviours were collected, clustered and then expressed as frequency-based Likert-type scale items. Data were obtained from 825 Swedish white collar workers and military personnel. A factor analysis (principal axis factoring with oblique rotation) resulted in a seven-factor solution built up by 30 items and forming the instrument Co-Worker Questionnaire (Co-Worker Q). Findings The factors have a strong resemblance to the content of dominating models of leadership, followership, organizational citizenship behaviour and leader–member exchange. The factor scales had relatively high reliability (high Cronbach’s alpha coefficients and low standard errors of measurement). Regarding discriminability, women scored more favourably on five of the factors, men on one factor and age differences were noted on two factors. Research limitations/implications Shortcomings include the lack of data on possibly related aspects including person factors, such as personality and socio-economic status, and contextual factors such as more detailed data on the type of work environment and organizational culture. Practical implications The instrument has an easy-to-use format and can be used in organization development interventions with a co-workership focus and in individualized coaching or mentoring programmes. Originality/value The co-workership concept has so far mainly been used in the Nordic countries. The development of the Co-Worker Q opens up for broader applications.

A note on the use of rank-ordered logit models for ordered response categories.

Models for rankings have been shown to produce more efficient estimators than comparable models for first/top choices. The discussions and applications of these models typically only consider unordered alternatives. But these models can be usefully adapted to the case where a respondent ranks a set of ordered alternatives that are ordered response categories. This paper proposes eliciting a rank order that is consistent with the ordering of the response categories, and then modelling the observed rankings using a variant of the rank ordered logit model where the distribution of rankings has been truncated to the set of admissible rankings. This results in lower standard errors in comparison to when only a single top category is selected by the respondents. And the restrictions on the set of admissible rankings reduces the number of decisions needed to be made by respondents in comparison to ranking a set of unordered alternatives. Simulation studies and application examples featuring models based on a stereotype regression model and a rating scale item response model are provided to demonstrate the utility of this approach.

16 Genetic Parameter Estimates for Age at First Calving in Simmental and Red Angus Heifers

Abstract The objective of this study was to determine genetic parameter estimates for age at first calving (AFC) in Red Angus and Simmental heifers. The ability for a heifer to calve earlier has implications on calf performance and the heifer's successive re-breeding. Heifer pregnancy data were obtained from International Genetic Solutions, where females with exposure records were included in the population. Females with a subsequent record of calving between 630 and 810 days of age were included in the analysis. Females with embryo transfer or multiple birth progeny were excluded. Records from single-animal and contemporary groups with no variation were eliminated and after data filtering, there were 149,379 Simmental with a mean Simmental breed proportion of 0.58 ± 0.25, and 83,191 Red Angus records with a mean Red Angus breed proportion of 0.80 ± 0.13. A 3-generation pedigree file containing 291,530 Simmental animals with 25,585 unique sires and 161,921 unique dams, and a 3-generation pedigree file containing 174,914 Red Angus animals with 19,733 unique sires and 99,464 unique dams were used for the separate analysis. The mean AFC in Simmental and Red Angus was 724.8 ± 28.64 d, and 724.2 ± 29.93 d, respectively. Data for each breed were modeled separately using a single trait animal model with random additive genetic and residual effects, and the fixed effect of contemporary group using ASReml 3.0. Contemporary group was defined as breeder, herd, year born, birth group and yearling group. The additive, residual, and phenotypic variances for Simmental were 120.08, 520.37, and 640.45 d2, respectively. For Red Angus, 85.67, 543.56, and 629.24 d2 were the additive, residual, and phenotypic variances, respectively. The heritability estimates of AFC for Simmental and Red Angus were 0.19 ± 0.0059 and 0.14 ± 0.0076, respectively. These results demonstrate AFC in days is lowly to moderately heritable. Lower residual and higher additive variance in Simmental compared to Red Angus may suggest the Simmental population has larger variation for underlying fertility influences such as age at puberty. The mean breeding values for AFC in Simmental was 6.1 ± 8.0, with a minimum of -24.4 and maximum of 54.7. Whereas Red Angus breeding values for AFC resulted in a mean of 4.0 ± 5.6 and a minimum and maximum of -16.1, and 37.3, respectively. The comparable heritability estimates, low standard error, and range in breeding values suggest selection for improved AFC can be attained. It is worth further exploring the impact of breed effects and heterosis influences on age at first calving. While this study does not account for heifers that did not calve in their first year, tandem selection for heifer fertility and age at calving should be heavily emphasized due to the economic importance of both traits.

Intra- and Inter-rater Reliability of a Magnetic Resonance Imaging-Based Volumetric Analysis of the Abductor Hallucis Muscle

Background: The muscle volume considerably changes with aging, pathologies, mechanical loading and exercise, and immobilization. It is recognized as an important parameter that can be measured by various methods to evaluate the effectiveness of interventions focusing on muscle strengthening and function. However, before the application of any measurement method, their reliability needs to be investigated and established. Objectives: This study aimed to evaluate the inter- and intra-rater reliability of the manual measurement method of the abductor hallucis muscle volume in feet with hallux valgus deformities using magnetic resonance imaging (MRI). Patients and Methods: The MRI images of the feet of 15 samples with a hallux valgus deformity were selected in this study. The cross-sectional areas of the abductor hallucis muscle were measured in the cuts along the entire length of the foot and multiplied by slice thickness. Two trained raters performed the measurements. The second rater repeated the measurements after five days to eliminate the memory effect. The intra-rater reliability and inter-rater reliability were assessed based on the intraclass correlation coefficient [ICC (2, 1)] to evaluate the extent of agreement between the raters at a 95% confidence interval. Results: The between- and within-rater ICCs were 0.92 (0.79 - 0.97) and 0.99 (0.97 - 0.99), respectively. The standard error of measurements was also small in both inter-rater (6.2%) and intra-rater (2.1%) reliability analyses. Conclusion: The manually outlined slice-by-slice volume measurement of the abductor hallucis muscle based on MRI images showed excellent inter- and intra-rater reliability. The excellent intra-rater reliability, besides the lower standard error percentage of measurements, indicates the superiority of measurements by a single person. However, further studies with a larger sample size are recommended.

Near-Infrared Reflectance Spectrophotometry (NIRS) Application in the Amino Acid Profiling of Quality Protein Maize (QPM).

The accurate quantification of amino acids in maize breeding programs is challenging due to the high cost of analysis using High-Performance Liquid Chromatography (HPLC) and other conventional methods. Using the Near-Infrared Spectroscopic (NIRS) method in breeding to screen many genotypes has proven to be a fast, cost-effective, and non-destructive method. Thus, this study aimed to develop and apply the NIRS prediction models for quantifying amino acids in biofortified quality protein maize (QPM). Sixty-three (63) QPM maize genotypes were used as the calibration set, and another twenty (20) genotypes were used as the validation set. The microwave hydrolysis system coupled with post-column derivatization with 6-amino-quinoline-succinimidyl-carbamate as the derivatization reagent and the HPLC method were used to generate the reference data set used for the calibration development. The calibration models were developed for essential and non-essential amino acids using WINSI Foss software. Good coefficients of determination in calibration (R2cal) of 0.91, 0.93, 0.93, and 0.91 and low standard errors in calibrations (SEC) of 0.62, 0.71, 0.26, and 1.75 were obtained for glutamic acids, alanine, proline, and leucine, respectively, while aspartic acids, serine, glycine, arginine, tyrosine, valines, and phenylalanine had fairly good R2Cal values of 0.86, 0.71, 0.81, 0.78, 0.68, 0.79, and 0.75. In contrast, poor (R2cal) was obtained for histidine (0.07), cystine (0.09), methionine (0.09), lysine (0.20), threonine (0.51), and isoleucine (0.09), respectively. The models’ prediction performances (R2pred) and standard error of prediction (SEP) were reasonably good for certain amino acids such as aspartic acid (0.90), glycine (0.80), arginine (0.94), alanine (0.90), proline (0.80), tyrosine (0.83), valine (0.82), leucine (0.90), and phenylalanine (0.88) with SEP values of 0.24, 0.39,0.24, 0.93, 0.47,0.34, 0.78, 2.20, and 0.77, respectively. However, certain amino acids had their R2pred below 0.50, which could be improved to become useful for screening purposes for those amino acids. Further work is recommended by including a training set representing the sample population’s variance to improve the model’s performance.

Stroke volume and cardiac output during 6 minute-walk tests are strong predictors of maximal oxygen uptake in people after stroke.

The 6-minute walk test (6MWT) is a field test commonly used to predict peak oxygen consumption (VO2peak) in people after stroke. Inclusion of cardiodynamic variables measured by impedance cardiography (ICG) during a 6MWT has been shown to improve prediction of VO2peak in healthy adults but these data have not been considered in people after stroke. This study investigates whether the prediction of VO2peak can be improved by the inclusion of cardiovascular indices derived by impedance cardiography (ICG) during the 6MWT in people after stroke. This was a cross-sectional study. Patients diagnosed with stroke underwent in random order, a maximal cardiopulmonary exercise test (CPET) and 6MWT in separate dates. Heart rate (HR), stroke volume (SV) and cardiac output (CO) were measured by ICG during all tests. Oxygen consumption was recorded by a metabolic cart during the CPET. Recorded data were subjected to multiple regression analyses to generate VO2peak prediction equations. Fifty-nine patients, mean age 50.0±11.7 years were included in the analysis. The mean distance covered in the 6MWT (6MWD) was 294±13 m, VO2peak was 19.2±3.2 ml/min/kg. Mean peak HR, SV and CO recorded during 6MWT were 109±6 bpm, 86.3±8.8 ml, 9.4±1.2 L/min and during CPET were 135±14 bpm, 86.6±9 ml, 11.7±2 L/min respectively. The prediction equation with inclusion of cardiodynamic variables: 16.855 + (-0.060 x age) + (0.196 x BMI) + (0.01 x 6MWD) + (-0.416 x SV6MWT) + (3.587 x CO 6MWT) has a higher squared multiple correlation (R2) and a lower standard error of estimate (SEE) and SEE% compared to the equation using 6MWD as the only predictor. Inclusion of SV and CO measured during the 6MWT in stroke patients further improved the VO2peak prediction power compared to using 6MWD as a lone predictor.

Optimal Design of Complementary Experiments for Parameter Estimation at Elevated Temperature of Food Processing.

Simultaneous estimation of thermal properties can be challenging, especially when the parameters are temperature-dependent. Previous research has shown that by using a complementary experiment, temperature-dependent thermal conductivity can be estimated using a single experiment. The objective of this study was to optimize the complementary experiments that can facilitate the simultaneous estimation of temperature-dependent thermal conductivity and volumetric heat capacity. A theoretical study was conducted with two experiments in a single trial with the sample being kept in a cylindrical sample holder, which had a thin film heater in the center. The first part of the experiment was conducted by keeping the external surface temperature at 50 °C for 300 s and allowing the center temperature to equilibrate with the boundary temperature. Then, the second part of the experiment followed, where the thin film heater was supplied with electrical power to increase the center temperate to 140 °C. Several heating profiles were studied to maximize the information obtained from the complementary experiments, and the best one was the power profile with a sinusoidal function. All four parameters of sweet potato puree temperature-dependent thermal conductivity (0.509 to 0.629 W/mK at 25 °C and 140 °C, respectively) and volumetric heat capacity (3.617 × 106 to 4.180 × 106 J/m3K at 25 °C and 140 °C, respectively) were estimated with low standard errors.

Parents can reliably and accurately detect trunk asymmetry using an inclinometer smartphone app

PurposeAn inclinometer smartphone application has been developed to enable the measurement of the angle of trunk inclination (ATI) to detect trunk surface asymmetry. The objective was to determine the reliability and validity of the smartphone app in the hands of non-professionals.MethodsThree non-professional observers and one expert surgeon measured maximum ATI twice in a study involving 69 patients seen in the spine clinics to rule out scoliosis or for regular follow-up (10-18 y.o., Cobb [0°-58°]). Observers were parents not familiar with scoliosis screening nor use of an inclinometer. They received training from a 4-minute video. Intra and inter-observer reliability was determined using the generalizability theory and validity was assessed from intraclass correlation coefficients (ICC), agreement with the expert on ATI measurements using Bland-Altman analysis, and correct identification of the threshold for consultation (set to ≥6° ATI).ResultsIntra-observer and inter-observer reliability coefficients were excellent ϕ = 0.92. The standard error of measurement was 1.5° (intra-observer, 2 measurements) meaning that a parent may detect a change of 4° between examinations 95% of the time. Comparison of measurements between non-professionals and the expert resulted in ICC varying from 0.82 [0.71-0.88] to 0.84 [0.74-0.90] and agreement on the decision to consult occurred in 83 to 90% of cases.ConclusionThe use of a smartphone app resulted in excellent reliability, sufficiently low standard error of measurement (SEM) and good validity in the hands of non-professionals. The device and the instructional video are adequate means to allow detection and regular examination of trunk asymmetries by non-professionals.

Psychometric properties of Spanish-language MMPI-3 scores in a Puerto Rican parental fitness evaluation setting.

The Minnesota Multiphasic Personality Inventory (MMPI) family of instruments have long been used in child custody and parental fitness evaluation (PFE) contexts, spanning from the original MMPI to the recently released MMPI-3. In addition to updating the English-language normative sample and expanding content coverage, the MMPI-3 was released with a U.S. Spanish-language normative sample. The present study sought to examine the psychometric properties of the Spanish-language MMPI-3, specifically in a PFE context. The sample consisted of individuals who were evaluated for parental fitness at a multisite private practice in Puerto Rico. A combined gender comparison group sample with equal number of men and women (n = 238) produced mean T scores that were within half a standard deviation of the Spanish-language normative sample on all scales. Scores on the Symptom Validity Scale were meaningfully higher among women (n = 247) relative to the normative sample, and the mean juvenile conduct problems score among men (n = 119) was meaningfully higher than that of the normative sample. Reliability estimates were generally adequate, with some reflecting low internal consistency; however, low standard errors of measurement indicated that low alpha estimates were a function of range restriction rather than measurement imprecision. Limitations, including the need for the accumulation of validity evidence, are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Dual-Energy X-Ray Absorptiometry and Anthropometry for Assessment of Nutritional Status at Diagnosis in Children with Cancer: A Single-Center Experience from India

Background The survival of children with cancer has improved owing to advances in chemotherapy and better supportive care, and nutritional support is an important component of the latter especially in low- and middle-income countries like India. Materials and Methods A prospective observational study of 137 newly diagnosed children with cancer aged less than 18 years was planned. Nutritional assessment was done using dual-energy X-ray absorptiometry (DXA), anthropometry, and serum albumin. Patients were followed for 3 months for assessment of treatment-related morbidity. Results Lean body mass (LBM; DXA), mid-upper arm circumference (MUAC), and body mass index detected undernutrition in 44, 45, and 14% patients, respectively. Combination of arm anthropometry (MUAC and triceps skinfold thickness) with serum albumin categorized patients as adequately nourished (32%), moderately depleted (18%), and severely depleted (49%). Patients with hematological malignancy had a higher prevalence of undernutrition but there was no difference in morbidities between the undernourished and adequately nourished children by any parameter. Hypoalbuminemia observed in 25% patients was associated with significant chemotherapy delays (p, 0.01) and interval admissions (p, 0.03). Using LBM as a criterion, linear regression analysis revealed MUAC (R 2 = 0.681) as the best predictor of undernutrition with lowest standard error. Conclusion Our study reports undernutrition among two-fifths of newly diagnosed patients of childhood cancer associated with high prevalence of sarcopenia and adiposity. These findings are of utmost clinical relevance in planning interventional strategies.

Remote Monitoring of Adult Cochlear Implant Recipients Using Digits-in-Noise Self-Testing.

The COVID-19 pandemic has accelerated the uptake and scope of telehealth. This study determined the accuracy and reliability of a smartphone digits-in-noise (DIN) test when conducted by adult cochlear implant (CI) recipients in a simulated home environment compared with a clinic setup. Perceptions of remote monitoring using speech-in-noise (SIN) testing were also explored. Thirty-three adult CI recipients between 18 and 78 years of age (M = 46.7, SD = ±20.4) conducted the DIN test in a simulated home environment and a clinic setup. Test-retest reliability across the two environments and comparisons between test settings were evaluated. A survey explored the perceptions of adult CI recipients regarding remote monitoring and use of the DIN self-test. Mean-aided speech reception thresholds (SRTs) in the clinic and simulated home environment test conditions and clinic and simulated home environment retest conditions did not differ significantly. Mean test-retest SRTs in the clinic and simulated home environment were significantly different (p < .05). High intraclass correlation coefficient and low standard error of measurement scores reflected good and excellent reliability between test-retest measures and between clinic and simulated home environment measures. Most participants were positive about the possibility of using the DIN test at home to self-assess speech perception, although some test adjustments such as including training items and a less adverse starting signal-to-noise ratio may be required. Adult CI recipients can use the smartphone DIN test to self-assess aided SIN performance in a home environment with accuracy and reliability relatively similar to clinic testing. https://doi.org/10.23641/asha.20044418.

Testing protocol for evaluating underhand serve-reception biomechanics in volleyball

A testing protocol for conducting biomechanical underhand serve-reception evaluation in volleyball in match-like conditions is presented. A launcher sends a ball over the net toward the reception zone for the player to pass it to the setter; the ball is tracked with video cameras and the player’s articular information is captured by inertial sensors, force plates, and video cameras. Test-retest reliability and, known-groups and concurrent validity of the test are evaluated. Left knee, right knee, left shoulder, and right shoulder angles were highly reliable (ICC &gt; 0.88), with low standard errors of measurement (%SEM &lt; 13.07). Resultant normalized ground reaction forces were also reliable (ICC: 0.76, %SEM: 9.14). Professional and amateur athletes’ comparisons were statistically significant and non-trivial ( p &lt; 0.05, Cohen’s d &gt; 0.49), with professionals’ body movements presenting small variance and symmetry between left and right limb variables, and amateurs’ presenting higher variance and greater asymmetry. Finally, each athlete’s left limb angles were compared against their corresponding sagittal Kinovea measurements for concurrent validity, obtaining acceptable correlation scores for amateur athletes (PCC &gt; 0.79) and good correlation scores (PCC &gt; 0.83) for professional athletes. The test offers a reliable and valid method for evaluating underhand serve-reception biomechanics in volleyball players.

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Corrigendum

Fabrication of high-performance non-enzymatic sensor by direct electrodeposition of nanomaterials on porous screen-printed electrodes

BackgroundScreen-printed sensors can be easily fabricated and have advantages of cost-effectiveness, low instrument demand, and decentralized fabrication. However, they often suffered from low reproducibility and conductivity, restraining them from practical applications. MethodThis study demonstrated a high-performance sensor with large surface area, high conductivity, wide detection range, and consistent catalytic kinetics using screen printing and electrodeposition. The large surface area was achieved by blending sacrificer into carbon paste to fabricate porous electrodes. Two steps of electrodeposition decorated the porous electrode surface with graphene and nickel nanoparticles to enhance conductivity and enable catalytic reactions of lactate. Significant findingsElectrodeposition achieved consistent size and spatial distributions of graphene and Ni nanoparticles, enabling high conductivity and reactivity. The deposited nickel nanoparticles were a mixture of Ni2+ and Ni3+ derivatives, resulting in a high variation in response currents. By oxidizing the Ni-derivatives NPs to a uniform state of nickel hydroxide, the sensor attained a highly linear detection with an 83% lower standard error. Additionally, the improved sensor had an impressive linear detection range from 0.5 to 60 mM. The fabrication was easy to follow and had a minimum demand for the instrument, making it particularly valuable for practical applications in regions with limited resources.

A novel handheld FT-NIR spectroscopic approach for real-time screening of major cannabinoids content in hemp

A novel approach for rapid (15s) detection and quantification of predominant cannabinoids in hemp was developed using Fourier-transformed near-infrared spectroscopy (FT-NIR), enabling real-time and field-based applications. Hemp samples (n = 91) were obtained from certified online vendors, the OARDC Weed Lab, and a local Ohio farm. Reference data of major cannabinoids content were determined by uHPLC-MS/MS. Spectral data were collected by a miniaturized, battery-operated FT-NIR instrument, and combined with the reference data to generate partial least squares regression (PLSR) models. uHPLC-MS/MS analysis showed two samples had over 0.36% of Δ9-tetrahydrocannabinol (Δ9-THC), and 64% (32 out of 50) of online-bought hemp samples were not in compliance with their total cannabidiol (CBD) content declaration. PLSR prediction models showed excellent correlation (Rpre = 0.91–0.95) and a low standard error of prediction (SEP = 0.02–0.61%). This method could be used as an alternative to traditional methods for in-situ assessment of hemp quality.

Novel metal based nanocomposite for rapid and efficient removal of lead from contaminated wastewater sorption kinetics, thermodynamics and mechanisms

A sol–gel method was utilized to prepare a novel nanocomposite adsorbent (nMgO/bentonite) and was tested for Pb(II) removal from aqueous solutions. The produced nanocomposite was investigated using, SEM–EDX, XRD, and FTIR analyses before and after Pb adsorption. Adsorption equilibrium and kinetic experiments were run in batch system under different conditions of pH, adsorbent dose, competitive cations, contact time and temperature. The results exhibited rapid Pb(II) adsorption by the nanocomposite in the first five min. Experimental lead adsorption equilibrium and kinetics data fitted well to Langmuir and power function models, respectively as indicated from the lowest standard error (SE) values. The calculated Langmuir maximum adsorption capacity (qmax) value of nanocomposite (75 mg g−1) was 4.5 times higher than that of bentonite (16.66 mg g−1). Moreover, the highest quantity of Pb(II) uptake was achieved at temperature of 307 K and pH 9. The Langmuir sorption capacity of the nanocomposite for Pb(II) increased from 75 to 145 mg g−1 with increasing temperature from 287 to 307 K. The thermodynamic parameters of Pb(II) adsorption by the nanocomposite affirm the spontaneous and endothermic nature of the adsorption process. Lead adsorption mechanisms by the nanocomposite were proposed and discussed.

Robust PC with wild bootstrap estimation of linear model in the presence of outliers, multicollinearity and heteroscedasticity error variance

The regression model estimator is considered efficient if it is robust and resistant to the presence of heteroscedasticity variance, multicollinearity or unusual observations called outliers. However, in regard to these problems, the wild bootstrap and robust wild bootstrap are no longer efficient since they could not produce the smallest variance. Hence this research investigates the use of robust PC with wild bootstrap techniques on regression model as an estimator for real and simulation data in a situation where multicollinearity, heteroscedasticity and multiple outliers are present. This paper proposed a robust procedure based on the weighted residuals which combined the Tukey bisquare weighted function, principal component analysis (PCA) to remedy the multicollinearity problems, least trimmed squares (LTS) estimator, robust location and scale, and the wild bootstrap sampling procedure of Wu and Liu that remedy the heteroscedasticity error variance. RPCW Boot Wu and RPCW Boot Liu were obtained through a modified version of R Boot Wu and R Boot Liu. Finally, based on the real data and simulation study, the performance of the RPCW Boot Wu and RPCW Boot Liu is compared with the existing R Boot Wu, R Boot Liu and also with Boot Wu, Boot Liu using the biased, RMSE and standard error. The numerical example and simulation study shows that the RPCW Boot Wu and RPCW Boot Liu techniques have proven to be a good alternative estimator for regression model with lower standard error values.

European pollen-based REVEALS land-cover reconstructions for the Holocene: methodology, mapping and potentials

Abstract. Quantitative reconstructions of past land cover are necessary to determine the processes involved in climate–human–land-cover interactions. We present the first temporally continuous and most spatially extensive pollen-based land-cover reconstruction for Europe over the Holocene (last 11 700 cal yr BP). We describe how vegetation cover has been quantified from pollen records at a 1∘ × 1∘ spatial scale using the “Regional Estimates of VEgetation Abundance from Large Sites” (REVEALS) model. REVEALS calculates estimates of past regional vegetation cover in proportions or percentages. REVEALS has been applied to 1128 pollen records across Europe and part of the eastern Mediterranean–Black Sea–Caspian corridor (30–75∘ N, 25∘ W–50∘ E) to reconstruct the percentage cover of 31 plant taxa assigned to 12 plant functional types (PFTs) and 3 land-cover types (LCTs). A new synthesis of relative pollen productivities (RPPs) for European plant taxa was performed for this reconstruction. It includes multiple RPP values (≥2 values) for 39 taxa and single values for 15 taxa (total of 54 taxa). To illustrate this, we present distribution maps for five taxa (Calluna vulgaris, Cerealia type (t)., Picea abies, deciduous Quercus t. and evergreen Quercus t.) and three land-cover types (open land, OL; evergreen trees, ETs; and summer-green trees, STs) for eight selected time windows. The reliability of the REVEALS reconstructions and issues related to the interpretation of the results in terms of landscape openness and human-induced vegetation change are discussed. This is followed by a review of the current use of this reconstruction and its future potential utility and development. REVEALS data quality are primarily determined by pollen count data (pollen count and sample, pollen identification, and chronology) and site type and number (lake or bog, large or small, one site vs. multiple sites) used for REVEALS analysis (for each grid cell). A large number of sites with high-quality pollen count data will produce more reliable land-cover estimates with lower standard errors compared to a low number of sites with lower-quality pollen count data. The REVEALS data presented here can be downloaded from https://doi.org/10.1594/PANGAEA.937075 (Fyfe et al., 2022).

Trend in BMI z-score among Private Schools’ Students in Delhi using Multiple Imputation for Growth Curve Model

Objective: The aim of the study is to assess the trend in mean BMI z-score among private schools’ students from their anthropometric records when there were missing values in the outcome. Methodology: The anthropometric measurements of student from class 1 to 12 were taken from the records of two private schools in Delhi, India from 2005 to 2010. These records comprise of an unbalanced longitudinal data that is not all the students had measurements recorded at each year. The trend in mean BMI z-score was estimated through growth curve model. Prior to that, missing values of BMI z-score were imputed through multiple imputation using the same model. A complete case analysis was also performed after excluding missing values to compare the results with those obtained from analysis of multiply imputed data. Results: The mean BMI z-score among school student significantly decreased over time in imputed data (β= -0.2030, se=0.0889, p=0.0232) after adjusting age, gender, class and school. Complete case analysis also shows a decrease in mean BMI z-score though it was not statistically significant (β= -0.2861, se=0.0987, p=0.065). Conclusions: The estimates obtained from multiple imputation analysis were better than those of complete data after excluding missing values in terms of lower standard errors. We showed that anthropometric measurements from schools records can be used to monitor the weight status of children and adolescents and multiple imputation using growth curve model can be useful while analyzing such data

Optimization of sample unit size for sampling stink bugs (Hemiptera: Pentatomidae) in soybean

Cost-effective and reliable sampling procedures are crucial for integrated pest management. Sweep net sampling is commonly used for stink bugs (Hemiptera: Pentatomidae) in soybean, with sample size being the number of sets of sweeps, and sample unit size the number of sweeps in each set. Sample unit size has received little attention, but can affect sampling parameters. Here, two sample unit sizes (10 vs. 25 sweeps) were compared for the sampling of stink bug taxa. On average, sampling for stink bugs took 3.6 more minutes with the 25-sweep than with the 10-sweep sample unit size. Generally, estimates of the mean number of stink bugs per sweep were similar between the two sample unit sizes for Euschistus spp. and Chinavia hilaris combined (“combined herbivores”) and Euschistus spp. The 25-sweep sample unit size had a higher probability of detecting combined herbivores, Euschistus spp. and Podisus spp., lower standard errors and relative variance for combined herbivores and Euschistus spp., lower standard errors for C. hilaris, and higher relative net precision [which accounts for sampling cost (i.e., time)] for combined herbivores and Euschistus spp. Taken together, the better probability of detection, precision and efficiency of the 25-sweep sample unit size support the continued use of sampling plans developed for that sample unit size. The optimization of sample unit sizes is an important factor that should be accounted for in the development of sampling plans.