Significance Tests Research Articles

Scalable test of statistical significance for protein-DNA binding changes with insertion and deletion of bases in the genome

Scalable test of statistical significance for protein-DNA binding changes with insertion and deletion of bases in the genome

Effects of dietary mangosteen peel powder and extract on the growth performance, meat quality and indicators for immunity, gut health and antioxidant activity in broiler chicks

The objective of this study was to evaluate the effects of dietary mangosteen peel preparations, either powdered (MspP) or ethanolic extract (MspE), on the growth performance, meat quality, immune response, gut health, serum biochemical profiles, and antioxidant activity of broiler chicks. A total of 480 day-old straight-run broiler chicks (Ross 308) were randomly placed into four treatments, with eight replicates of 12 chicks each, and subjected to one of the four experimental diets for 21 days. The corn and soybean meal-based diet was supplemented with 2% MspP (20 g per kg of diet) or 0.05% and 0.1% MspE (0.5 g and 1.0 g per kg of diet). Data were analyzed using analysis of variance, and post hoc comparisons of treatments were performed using Tukey's Honestly Significant Difference test. From days 0 to 21, dietary mangosteen peel preparations did not affect growth performance (body weight gain, feed intake, and feed conversion ratio), thigh meat and tibia characteristics, serum markers of innate immunity (interferon-r, interleukin-10, alpha-1-acid glycoprotein, and nitric oxide), and ileal morphology in broiler chicks (P > 0.05). Dietary mangosteen peel preparations increased the percentage of high-density lipoprotein cholesterol and decreased the relative concentrations of isobutyrate and branched-chain fatty acids in the cecal digesta compared with the control chickens. Notably, dietary mangosteen peel preparations altered the antioxidant characteristics of the serum, liver, and thigh meat. Dietary MspE increased glutathione peroxidase (P = 0.039) and catalase (P = 0.008) in the serum and catalase in the liver (P = 0.05) and thigh meat (P = 0.01) compared to the control group. In addition, dietary MspP increased catalase levels in thigh meat compared to those in the control diet-fed chickens (P = 0.01). The concentration of malondialdehyde, an indicator of lipid peroxidation, was lower in all chicks-fed diets containing mangosteen peel preparations; however, statistical significance was only noted in the serum samples (P < 0.0001). Collectively, our study shows that dietary mangosteen peel preparations are potent natural antioxidants that can be used as functional dietary additives to effectively mitigate oxidative stress in broiler chicks.

A novel approach for the replacement of accuracy and precision measurements with the visual instrument agreement scale (VIAS) in evaluating the performance of four intraoral scanners and one shade measurement device

ObjectivesThe terms 'accuracy' and 'precision' are tightly defined in color science but are often used ambiguously in dental research. This study introduces the visual instrument agreement scale (VIAS), a new method for determining visual-instrumental agreement in dental colorimetry by comparing visually perceived and measured color differences. Materials and MethodsIn-vivo tooth color measurements were taken from 16 participants using four intraoral scanners (Primescan, Medit i700, Carestream CS3700, Trios 3) and one spectrophotometer (Vita Easyshade V). Visual shade assessment was also performed by one expert observer using the 3D Master shade guide. Statistical significance testing was conducted using the STRESS index to calculate VIAS, and the F-statistic was used to evaluate device performance. ResultsCarestream CS3700 achieved the highest visual-instrumental agreement with a VIAS score of 82%, performing significantly better than the other devices. Primescan, Medit i700, and Trios 3 showed scores of 76%, 75%, and 72%, respectively, with no significant differences between them. Vita Easyshade V scored 57%, performing significantly worse than the other devices. ConclusionsThe overall performance of the intraoral scanners was strong, with Carestream CS3700 approaching excellent performance. The VIAS method offers a practical, color science-based framework for evaluating visual-instrumental agreement and can be easily replicated using the freely available toolbox. Clinical SignificanceIntraoral scanners performed surprisingly better than a spectrophotometer specifically designed for tooth color measurement and which is often regarded as the gold standard. Additionally, VIAS offers a new, scientifically grounded approach for testing visual-instrumental agreement in dental colorimetry.

The Effect of Entrepreneurship Education, Creativity and Entrepreneurial Motivation on Entrepreneurial Interest in the Millennial Generation in Makassar City

This study aims to determine the effect of entrepreneurship education, creativity and entrepreneurial motivation on interest in entrepreneurship in the millennial generation in Makassar City. This research is a quantitative descriptive study with a sample of 224 respondents and then analyzed based on multiple linear regression analysis. Data obtained through observation, documentation, and questionnaires. Based on the results of the study, the three factors (X) simultaneously have a significant influence on the millennial generation's entrepreneurial interest in Makassar City. However, based on a partially significant test, the entrepreneurship education variable (X1) does not have a significant effect on entrepreneurial interest (Y). While the creativity variable (X2) and the entrepreneurial motivation variable (X3) have a significant influence on the millennial generation's entrepreneurial interest (Y).

How the ESG practices increase the job satisfaction?

Purpose This study aims to investigate the impact of environmental, social and corporate governance (ESG) factors on job satisfaction within the context of small and medium-sized enterprises (SMEs), addressing a notable gap in understanding these relationships. Design/methodology/approach Data were collected from 97 full-time and part-time employees using a tailored survey instrument. Control variables included demographic factors, such as gender, age, marital status and hierarchical position. The study postulated four moderation hypotheses, conducted rigorous significance tests and demonstrated strong model reliability and validity, along with highly satisfactory fit parameters. Findings The findings confirm a positive association between the E, S and G factors and job satisfaction perceptions. Marital status was identified as a moderator in the relationship between social dimensions and job satisfaction. In addition, the multigroup analysis revealed variations in the associations between ESG dimensions and job satisfaction across different age groups, marital statuses and hierarchical positions. Originality/value The main contribution of this research lies in filling a significant gap in the understanding of how sociodemographic variables influence the relationship between employees and socially responsible behavior in SMEs.

Correlation of the FIB-4 Liver Biomarker Score with the Severity of Heart Failure

Background and Objectives: Heart failure is associated with high morbidity and mortality and linked with several pre-existing health conditions and risk factors. Early detection and prompt management in heart failure improves patient outcomes. Liver involvement is associated with heart failure disease progression, and hence liver biomarkers and liver fibrosis may have a prognostic impact. Several blood test based markers and scoring systems estimate liver fibrosis and hence can be useful prognostic tools. Materials and Methods: We retrospectively analyzed a series of 303 patients with decompensated heart failure in a city in western Romania over a period of 6 months. Several biochemical parameters were measured, the FIB-4 score was estimated and echocardiography was performed. Results for targeted variables are presented using descriptive statistics. Patients were analyzed based on their LVEF categories. Statistical analysis was based on ANOVA one-way tests for continuous variables and Chi-square tests for categorical variables. Pairwise comparisons were performed based on Bonferroni adjusted significance tests. The correlations between FIB-4 score, LVEF and NT-pro BNP in patients with and without diabetes and hypertension were explored using Spearman’s correlation coefficient. Result: Age, gender, NYHA class, death, history of (h/o) type 2 diabetes mellitus (T2DM), h/o coronary artery disease (CAD), h/o arrhythmias, sodium, potassium, creatinine, eGFR, uric acid, NT-pro BNP, left atrial volume, LDL, HDL, and TG were analyzed by LVEF categories using ANOVA one-way tests, Chi-square tests, and Bonferroni correction comparisons. We found a strong statistically significant correlation between each of NT-pro BNP, left atrial volume, LDL, and HDL with the LVEF categories. Discussion: Early detection of cardiac dysfunction leads to better management in patients with cardiovascular risk factors including diabetes and hypertension. High LDL and low HDL levels contribute to a reduction in left ventricular (LV) function. Available literature suggests the FIB-4 score as superior to other non-invasive markers of fibrosis. It utilizes the patient’s age, platelet count, AST, and ALT, which can be available retrospectively, making it an easy and inexpensive tool. FIB-4 score has a few limitations. Conclusions: Our study has shown a statistically significant positive correlation between severity categories of LVEF and FIB-4 score for heart failure patients with and without diabetes, and for heart failure patients with or without hypertension. We propose the implementation of FIB-4 score as a prognostic tool for heart failure.

Analysis of the Existing Air Emissions Detection Methods for Stationary Pollution Sources Monitoring

The application of coal technologies for energy generation leads to high pollutant emissions. Thus, governmental and international organizations have created new programs and laws for monitoring emissions. Recently, the government of Kazakhstan has introduced regulations for the measurement of emissions produced by factories and power plants. However, the requirements and Corecommendations for the monitoring methods have not been defined. Therefore, this article addresses the problem and focuses on determining the measurement errors made by optical SGK510 and electrochemical POLAR devices used for coal power plants. The hypothesis is based on the fact that there are currently no systems for monitoring probe drying, and its implementation is expensive. The main methods are analyzed, namely their operation, taking into account the presence of water particles in samples, and the possibility of using adjustment coefficients is considered. The main pollutants chosen for analysis are CO, NO, NO2, NOx, SO2, and O2. Using the Broich–Pagan test, homoscedasticity was determined, and the Fisher test showed the possibility of using tuning coefficients. The data for the optical method were compared to measurements taken using Inspector 500. The error for SO2 determination was 7.19% for NO, 44.0985% for NO2, 733.26% for NOx, 7.39% for O2, 2.75% for CO, 60.81%. The comparison between SGK510 and POLAR demonstrated the following errors: for CO—1.5%, for NOx—82.4405%, for SO2—41.17%, for O2—11.61%. According to the Fisher criteria analysis of the optical method, only SO2 and CO values measured by SGK510 in comparison to Inspector 500 had close similarity, while others demonstrated high deviations. The significance tests were carried out by Fisher’s, t-test, and ANOVA methods. For the electrochemical measurement, only CO values had close similarity. In the future, methods will be proposed to improve the accuracy of the system while reducing maintenance costs, as well as cleaning sampling systems. The multicomponent analysis application for accuracy improvement with the exhaust gas humidity, temperature, and flow consideration was recommended as a possible solution.

On Bayes factors for hypothesis tests.

We develop alternative families of Bayes factors for use in hypothesis tests as alternatives to the popular default Bayes factors. The alternative Bayes factors are derived for the statistical analyses most commonly used in psychological research - one-sample and two-sample ttests, regression, and ANOVA analyses. They possess the same desirable theoretical and practical properties as the default Bayes factors and satisfy additional theoretical desiderata while mitigating against two features of the default priors that we consider implausible. They can be conveniently computed via an R package that we provide. Furthermore, hypothesis tests based on Bayes factors and those based on significance tests are juxtaposed. This discussion leads to the insight that default Bayes factors as well as the alternative Bayes factors are equivalent to test-statistic-based Bayes factors as proposed by Johnson. Journal of the Royal Statistical Society Series B: Statistical Methodology, 67, 689-701. (2005). We highlight test-statistic-based Bayes factors as a general approach to Bayes-factor computation that is applicable to many hypothesis-testing problems for which an effect-size measure has been proposed and for which test power can be computed.

Binary Logistic Regression Modeling on Household Poverty Status in Bengkulu Province

Binary logistic regression is a statistical method used to analyze the relationship between one or more predictor variables and a binary or dichotomous response variable. Poverty is an issue in every province in Indonesia. One of the provinces with a relatively high poverty rate is Bengkulu Province, ranking seventh in Indonesia with a poverty rate of 14.62%. The Central Bureau of Statistics of Bengkulu Province (2023) explains that efforts to reduce poverty must involve all levels of society. Various government programs and policies in various fields such as health, social, and other areas are continuously being implemented to reduce the number of households classified as poor. Identifying the characteristics of households in Bengkulu Province by poverty status is important to study, as it serves as a reference to ensure that government programs are implemented according to the target. One method that can be used to identify household characteristics is binary logistic regression. This study aims to model the poverty status of households in Bengkulu Province using binary logistic regression and to identify the factors that influence it. The data used are social and economic household data from March 2022. The response variable used is household poverty status (poor and not poor), while the predictor variables include the ownership of toilet facilities, the source of lighting, floor area, family size, and per capita calorie consumption. Modeling is done using binary logistic regression with simultaneous and partial parameter significance tests, as well as model fit tests. The analysis results show that the factors significantly influencing household poverty status in Bengkulu Province are the ownership of toilet facilities, the source of household lighting, floor area, family size, and per capita calorie consumption. The formed binary logistic regression model has a classification accuracy of 89.98% with a sensitivity of 18.34% and a specificity of 98.61%.

Differential Item Functioning Effect Size Use for Validity Information.

There has been an emphasis on effect sizes for differential item functioning (DIF) with the purpose to understand the magnitude of the differences that are detected through statistical significance testing. Several different effect sizes have been suggested that correspond to the method used for analysis, as have different guidelines for interpretation. The purpose of this simulation study was to compare the performance of the DIF effect size measures described for quantifying and comparing the amount of DIF in two assessments. Several factors were manipulated that were thought to influence the effect sizes or are known to influence DIF detection. This study asked the following two questions. First, do the effect sizes accurately capture aggregate DIF across items? Second, do effect sizes accurately identify which assessment has the least amount of DIF? We highlight effect sizes that had support for performing well across several simulated conditions. We also apply these effect sizes to a real data set to provide an example. Results of the study revealed that the log odds ratio of fixed effects (Ln ) and the variance of the Mantel-Haenszel log odds ratio ( ) were most accurate for identifying which test contains more DIF. We point to future directions with this work to aid the continued focus on effect sizes to understand DIF magnitude.

Analysis of Bacterial Metabolites in Breath Gas of Critically Ill Patients for Diagnosis of Ventilator-Associated Pneumonia—A Proof of Concept Study

Bacterial infection of the lower respiratory tract frequently occurs in mechanically ventilated patients and may develop into life-threatening conditions. Yet, existing diagnostic methods have moderate sensitivity and specificity, which results in the overuse of broad-spectrum antibiotics administered prophylactically. This study aims to evaluate the suitability of volatile bacterial metabolites for the breath-based test, which is used for diagnosing Ventilator-Associated Pneumonia (VAP). The in vitro experiments with pathogenic bacteria most prevalent in VAP etiology (i.e., Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa) were performed to identify bacteria-derived metabolites using a specially designed cultivation system enabling headspace sampling for GC-MS analysis. Thirty-nine compounds were found to be significantly metabolized by tested species and, therefore, selected for monitoring in the exhaled breath of critically ill, mechanically ventilated (MV) patients. The emission of volatiles from medical respiratory devices was investigated to estimate the risk of spoiling breath results with exogenous pollutants. Bacterial metabolites were then evaluated to differentiate VAP patients from non-infected MV controls using Receiver Operating Characteristic (ROC) analysis, with AUC, sensitivity, and specificity calculated. Nine bacterial metabolites that passed verification through a non-parametric ANOVA test for significance and LASSO penalization were identified as key discriminators between VAP and non-VAP patients. The diagnostic model achieved an AUC of 0.893, with sensitivity and specificity values of 87% and 82.4%, respectively, being competitive with traditional methods. Further validation could solidify its clinical utility in critical care settings.

Why multiple hypothesis test corrections provide poor control of false positives in the real world.

Most scientific disciplines use significance testing to draw conclusions about experimental or observational data. This classical approach provides a theoretical guarantee for controlling the number of false positives across a set of hypothesis tests, making it an appealing framework for scientists seeking to limit the number of false effects or associations that they claim to observe. Unfortunately, this theoretical guarantee applies to few experiments, and the true false positive rate (FPR) is much higher. Scientists have plenty of freedom to choose the error rate to control, the tests to include in the adjustment, and the method of correction, making strong error control difficult to attain. In addition, hypotheses are often tested after finding unexpected relationships or patterns, the data are analyzed in several ways, and analyses may be run repeatedly as data accumulate. As a result, adjusted p values are too small, incorrect conclusions are often reached, and results are harder to reproduce. In the following, I argue why the FPR is rarely controlled meaningfully and why shrinking parameter estimates is preferable to p value adjustments. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Compatibility of Velum® (Synthetic Nematicide) with Endophytic Colletotrichum nigrum and Commercial Trichoderma asperellum against Root-Knot Nematodes on Tree Tomato

Root-knot nematodes (RKNs) hinder agricultural production worldwide. Many methods of managing RKNs have been used. However, an approach of combining velum® with endophytic fungi and commercial Trichoderma asperellum has not been tested against RKNs. This study was carried out between September 2022 to February 2023 to evaluated compatibility of Velum® with endophytic Colletotrichum nigrum isolated from roots of tree tomato and commercial Trichoderma asperellum to contain RKNs in vitro and in the greenhouse on tree tomato. Leading mycelial discs from the colony of C. nigrum and T. asperellum were removed using a cork borer and inoculated onto PDA media amended with Velum® and incubated for seven days at 25oC. Colletotrichum nigrum and T. asperellum alone and in combinations with Velum® were tested for their efficacy against second stage juveniles (J2s) of RKN in the greenhouse. In vitro and greenhouse tests were replicated four times in Completely Randomized Design. Data was analyzed by Anova SAS, 9.2 and significant means separated by Tukey's Honestly Significant Differences test at P ≤ 0.05. There was no significant inhibition in the colony growth of C. nigrum and T. asperellum by Velum® in vitro and therefore were found to be compatible. Colletotrichum nigrum combined with Velum® significantly (P≤0.05) reduced the RKN J2s, nematode reproduction factor, galling and egg mass indices in both experiments more than when applied alone. There was also a significant increase in plant growth parameters of tree tomato treated with C. nigrum combined with Velum®. This study has shown that combining Velum® with C. nigrum and T. asperellum successfully controlled RKNs on tree tomato. These findings could be used to promote integrated nematode management using less toxic nematicides and biocontrol agents.

Evaluation of the pod yield and quality of okra (Abelmoschus esculentus L. Moench) varieties cultivated on mulching materials in northwestern Ethiopia

Okra (Abelmoschus esculentus L.) is a versatile warm-season vegetable cultivated year-round in Ethiopia. Moreover, the demand of okra pod is very high however; its yield and quality is hindered by limited adoption of improved varieties and soil moisture stress. To address these issues, a dry season experiment was conducted at Gorgora Horticultural Research Site, University of Gondar, Ethiopia from February to May 2023 to assess the pod yield and quality of okra varieties on different mulching materials. The study involved three okra varieties (Beles, Qenqes, and Wayka) and three mulching materials (rice straw, sawdust, and water hyacinth), plus a control, in a randomized complete block design with three replicates. Statistical analysis was employed using SAS software version 9.4 and significance were determined using least significant difference tests at a 5% probability level. The results revealed both varieties and mulches had significant influence on yield and quality of okra pod. Variety Wayka cultivated with water hyacinth or rice straw mulch showed more number of pod harvests; on the other hand Qenqes cultivated with water hyacinth had greater (22.21 g/100 g) fiber content. Variety Qenqes recorded early (52.43 days) pod setting with maximum (32.31 g) pod weight, (15.28 cm) pod length, (2.54 cm) pod diameter, (9.85%) total ash and minimum (89.80%) moisture content, whereas Wayka had the greatest pod yield (13.40 t/ha). In case of mulching materials, water hyacinth mulch achieved maximum pod weight and pod length, in addition to this it improved early pod setting, pod diameter and pod yield at par with rice straw mulch. This study tentatively suggested the use of variety Qenqes for early quality pods and variety Wayka for more pod yields production. Moreover, water hyacinth or rice straw mulches improved earliness, pod yield and quality. For the future, it is better to repeate the study in different location and season with incorporation of other varieties.

The Resilience and Lived Experiences of the Parents of Children With Autism in India: A Mixed-method Study

Background and Objectives: Families dealing with autism spectrum disorder (ASD) children try to adapt with different strategies. 1) To assess the resilience of parents dealing with children having ASD and its associated factors. 2) To explore the perspective and strategies of families dealing with children having ASD Methods: This was a mixed-methods study done over a period of 3 months among parents having children diagnosed with ASD; undergoing institutional therapy for more than 6 months in duration. Data collection was done using the PREQ questionnaire and key informant interviews (KII). Informed consent was taken prior to each interview and audio recordings. Relevant tests of significance and deductive analysis followed. Results: There was an equal divide observed between the low (50%) and high resilience (50%) groups. Binary logistic regression showed that the upper socio-economic class showed higher odds of better resilience (OR=4.038, 95% CI, 2.857%, 4.894%) as compared to the lower socio-economic class, and those with higher levels of education showed better resilience (OR=9.903, 95% CI, 2.502%, 3.483% than the lesser educated. KII explored different perspectives on personal experiences, concerns, challenges, attitudes, etc. where both perspectives such as benefits and hardships were addressed on an individual as well as a family basis, respectively Conclusion: Education and socio-economic backgrounds played a role in mending the resilience and other active measures such as peer support mechanisms and self-coping strategies also influenced the attitude and improved determination of parents dealing with children having ASD.

Assessing Urinary Para-Hydroxyphenylacetic Acid as a Biomarker Candidate in Neuroendocrine Neoplasms.

The management of neuroendocrine neoplasms (NENs) involves the measurement of serum chromogranin A (s-CGA), serum neuro-specific enolase (s-NSE), and urinary 5-hydroxindolacetic acid (5-HIAA). Urinary para-hydroxyphenylacetic acid (u-pHPAA), a metabolite of tyrosine, has been proposed as a potential biomarker for these diseases. This study aims to evaluate the effectiveness of u-pHPAA and tyrosine as biomarkers. We measured the levels of s-CgA, s-NSE, u-5-HIAA, u-pHPAA, and tyrosine in blood or 24 h urine samples collected at baseline (T0) and after 1 year of follow-up (T1) from a limited cohort of patients enrolled at Istituto Nazionale Tumori-IRCCS-Fondazione "G. Pascale". Biomarker values were normalized using the ratios between T1 and T0 values (T1/T0 parameters). The T1/T0 ratios for s-CgA and u-pHPAA were significantly associated with the outcome of death (p = 0.044 and p = 0.022, respectively). An ROC curve analysis demonstrated outstanding performances for these biomarkers (AUC = 0.958 and AUC = 1.00, respectively) and the Kaplan-Meier survival analysis showed significant Log-rank test results (p = 0.001 and p < 0.001, respectively). Additionally, T0 serum tyrosine correlated with the outcome of death (p = 0.044), with the ROC curve showing good performance (AUC = 0.958) and the Kaplan-Meier analysis yielding significant Log-rank test results (p = 0.007). Our study confirms the role of s-CgA in the management of NEN patients and highlights the potential roles of u-pHPAA and serum tyrosine as biomarkers. Further research is needed to validate our findings in larger populations.

The Evolution of Wisteria Vein Mosaic Virus: A Case Study Approach to Track the Emergence of New Potyvirus Threats.

Wisteria vein mosaic virus (WVMV, Potyvirus wisteriae), a virus belonging to the genus Potyvirus, is responsible for Wisteria vein mosaic disease (WMD), a severe disease that affects Wisteria, a genus of garden plants acclaimed worldwide. Although probably originating in the Far East, WVMV infection was first reported in the US, and subsequently in numerous countries. Following the first molecular detection of an Italian isolate, WVMV Bari, its full-length genome was achieved using NGS barcoding technology. A PhyML phylogenetic analysis, supported by clustering algorithm validation, identified a clear separation between two phylogroups. One major clade comprised WVMV strains isolated from Wisteria spp. A second clade grouped three highly divergent strains, at the borderline species threshold, all found in non-wisteria hosts. Relying on a Relative Time Dated Tips (RTDT) molecular clock, the first emergence of WVMV clades has been traced back to around the 17th century. A network inference analysis confirmed the sharp separation between the two host-related phylogroups, also highlighting the presence of potential intermediate variants. Inter-population genetic parameters revealed a very high genetic differentiation in both populations, which was made reliable by statistically significant permutation tests. The migrant number (Nm) and fixation index (FST) evidenced a restricted gene flow and strong population structures. According to the dN/dS ratio and negative neutrality tests, it was derived that purifying selection at the expense of non-silent variants is underway within WVMV populations. Targeting WVMV evolutionary traits, the present effort raised interesting questions about the underestimated potential of this culpably neglected species to spread in economically relevant crops. The main intention of our study is, therefore, to propose an evolution-based analysis approach that serves as a case study to investigate how other potyviruses or newly emerging viruses may spread.

Effect of different polishing systems on surface roughness and gloss values of single-shade resin composites

BackgroundThe aim of this study was to evaluate variations in the surface roughness and gloss of different single-shade resin composites after polishing with a range of systems.MethodsIn total, 120 specimens were prepared from three different types of single-shade resin composites (supra-nanospherical—Omnichroma, nanohybrid—Charisma Diamond One, and microhybrid— Essentia Universal). The specimens were placed in distilled water and stored at 37 °C for 24 h. Each resin composite (n = 40) was divided into four groups (n = 10) according to the finishing/polishing (F/P) system: Mylar strip (control), Sof-Lex (multi-step), Twist Dia (two-step), and OneGloss (one-step). Surface roughness and gloss were measured. Surface characteristics were evaluated by atomic force microscopy (AFM) and a scanning electron microscope (SEM). A two-way analysis of variance (ANOVA) and Tukey’s honestly significant difference test were used for statistical analysis (p < 0.05).ResultsAmong all the composites, both the highest surface roughness and lowest gloss values were obtained in the groups treated with the OneGloss polishing system (p < 0.05). Compared with all the composites, Omnichroma had the lowest surface roughness and highest gloss values (except Twist Dia) both unpolished and after polishing with all the F/P systems (p < 0.05). All composites treated with the Twist Dia F/P system had similar gloss values. The results of the AFM and SEM analyses were consistent with the surface roughness measurements.ConclusionsThe gloss values of both the microhybrid and nanohybrid composites after F/P using the two-step system was superior to that of the traditional multistep system. The surface of the supra-nanofilled resin-based composite was smoother than that of both the microhybrid and nanohybrid composites.

The Effect of Virtual Laboratories on the Academic Achievement of Undergraduate Chemistry Students: Quasi-Experimental Study.

Experimentation is crucial in chemistry education as it links practical experience with theoretical concepts. However, practical chemistry courses typically rely on real laboratory experiments and often face challenges such as limited resources, equipment shortages, and logistical constraints in university settings. To address these challenges, computer-based laboratories have been introduced as a potential solution, offering electronic simulations that replicate real laboratory experiences. This study examines the effect of virtual laboratories on the academic achievement of undergraduate chemistry students and evaluates their potential as a viable alternative or complement to traditional laboratory-based instruction. A quasi-experimental design was implemented to examine the cause-and-effect relationship between instructional methods and student outcomes. The study involved 60 fourth-year BSc chemistry students from Dilla University, divided into 3 groups: a real laboratory group (n=20), which performed real laboratory experiments; a virtual group (n=20), which used virtual laboratory simulations; and a lecture group (n=20), which received lecture-based instruction. Quantitative data were collected through tests administered before and after the intervention to assess academic performance. The data analysis used descriptive and inferential statistics, such as means and SDs, 1-way ANOVA, the Tukey honestly significant difference test, and independent-sample t tests (2-tailed), with a P value of .05 set for determining statistical significance. Before the intervention, the results indicated no significant differences in academic achievement among the 3 groups (P=.99). However, after the intervention, notable differences were observed in student performance across the methods. The real laboratory group had the highest mean posttest score (mean 62.6, SD 10.7), followed by the virtual laboratory group (mean 55.5, SD 6.8) and the lecture-only group, which had the lowest mean score (mean 43.7, SD 11.5). ANOVA results confirmed significant differences between the groups (F2,57=18.429; P<.001). The Tukey post hoc test further revealed that the real laboratory group significantly outperformed the lecture-only group (mean difference 18.88; P<.001), while the virtual laboratory group also performed significantly better than the lecture-only group (mean difference 11.7; P=.001). However, no statistically significant difference was found between the real laboratory and virtual laboratory groups (mean difference 7.12; P=.07). In addition, gender did not significantly influence performance in the virtual laboratory group (P=.21), with no substantial difference in posttest scores between male and female students. These findings suggest that computer-based laboratories are a viable and effective alternative when real laboratories are unavailable, enhancing learning outcomes when compared with traditional lecture-based methods. Therefore, universities should consider integrating computer-based laboratories into their practical chemistry curricula to provide students with interactive and engaging learning experiences, especially when physical laboratories are inaccessible.

Assessing CMIP Models’ Ability to Detect Observed Surface Warming Signals Related to Climate Change

Abstract Assessing if CMIP models can detect observed climate change signals is crucial for evaluating their realism and strengthening confidence in future projections. These signals can only be compared once distinguishable from the background climate “noise.” Built for impact studies but not detection purpose, the time of emergence (ToE) estimates when this occurs using a fixed signal-to-noise ratio. To more accurately assess models’ ability to reproduce observed climate change signals, we introduce the time of detection (ToD), which employs a statistical significance test of the nonlinear trend, accounting for the time series length. ToD and ToE are computed for sea surface temperature (SST) and relative SST (RSST) across four observational and 69 CMIP5/6 historical and shared socioeconomic pathways 5–8.5 (SSP5–8.5) scenario datasets. ToD precedes ToE and is less sensitive to the chosen threshold. While already detectable in most of the tropics, SST warming in the equatorial Pacific is detectable in ∼90% of models but only one out of four observational datasets, due to a stronger modeled warming. Because RSST signals are weaker than SST signals, they do not emerge anywhere but are detectable in two regions. The enhanced warming in the western Indian Ocean, detected in ∼45% of models, is not robust in observations when excluding pre-1960 dubious data. Conversely, the subdued southeast Pacific warming detected in observations and ∼80% of models is robust and consistent with a poleward extension of the Southern Hemisphere Hadley cell. The ToD’s ability to detect subtle signals allows for assessing the realism of the CMIP warming pattern in this region. Significance Statement Recent studies emphasize the importance of the climate change warming pattern and its apparent discrepancy between climate models and observations in the equatorial Pacific. We argue that our newly proposed time of detection (ToD) is better suited than the well-known time of emergence (ToE) for investigating where modeled and observed warming patterns can be confidently compared. In agreement with previous studies, our analysis indicates model–observations disagreement over the equatorial Pacific. Using ToD instead of ToE allows for detecting a robust subdued warming (i.e., weaker than the tropical average) in the southeast Pacific and therefore confirms the realism of the CMIP warming pattern in this region.