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Pharmacology, medicine, psychology, and the animal sciences all employ repeated measurement designs (RMDs). However, RMDs may experience carryover effects, which are the primary cause of bias in treatment effect estimation. In order to eliminate the carryover effects for odd v (the number of treatments), minimal circular balanced and strongly balanced repeated measurement designs (RMDs) are the ones that should be used. The minimal circular partially balanced and weakly balanced RMDs are used for even v. In order to obtain these important classes of minimal circular RMDs in periods of equal, two, and three different sizes, an R-based algorithm is developed in this article. The newly developed algorithm has made so simple the construction of balanced RMDs and their generalized classes. As a result, it is a novel piece of research. [ABSTRACT FROM AUTHOR]

In cities, the creation of public transport infrastructure such as light rails can cause changes on a very detailed spatial scale, with different stories unfolding next to each other within the same urban neighbourhood. We study the direct effect of a light rail line built in Florence (Italy) on the retail density of the street where it was built and its spillover effect on other streets in the treated street's neighbourhood. To this aim, we investigate the use of the synthetic control group (SCG) methods in panel comparative case studies where interference between the treated and the untreated units is plausible, an issue still little researched in the SCG methodological literature. We frame our discussion in the potential outcomes approach. Under a partial interference assumption, we formally define relevant direct and spillover causal effects. [ABSTRACT FROM AUTHOR]

Successful invasive species commonly depend on the establishment of mutualistic interactions with native and nonnative biota. In turn, invasive species can affect native mutualisms and community stability. Here, we examine different forms of mutualist acquisition by invasive species and the causes and consequences of mutualism abandonment for invasion processes. Additionally, we delve into the quantitative and qualitative effects of invaders on native biota via mutualism disruption that can occur through direct and diverse indirect pathways. These effects of invasive species on native biota via mutualistic interactions can often be a consequence of the invaders' abundance, which should be considered a prime predictor when evaluating the impact of invasive species on native mutualisms and community stability. We propose that the ecological as well as the evolutionary consequences of mutualism disruption and switches caused by invasive species can play crucial roles in determining future biodiversity. [ABSTRACT FROM AUTHOR]

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Why does a beneficial treatment effect on a longitudinal biomarker not translate into overall treatment benefit on survival, when the biomarker is in fact a prognostic factor of survival? In a recent exploratory data analysis in oncology, we were faced with this seemingly paradoxical result. To address this problem, we applied a theoretically principled methodology called dynamic path analysis, which allows us to perform mediation analysis with a longitudinal mediator and survival outcome. The aim of the analysis is to decompose the total treatment effect into a direct treatment effect and an indirect treatment effect mediated through a carefully constructed mediation path. The dynamic nature of the underlying methodology enables us to describe how these effects evolve over time, which can add to the mechanistic understanding of the underlying processes. In this paper, we present a detailed description of the dynamic path analysis framework and illustrate its application to survival mediation analysis using simulated and real data. The use case analysis provides clarity on the specific exploratory question of interest while the methodology generalizes to a wide range of applications in drug development where time‐to‐event is the primary clinical outcome of interest. [ABSTRACT FROM AUTHOR]

The role of non-cognitive skills in academic achievement has garnered increasing attention in educational research. This study explores the impact of non-cognitive skills on academic achievement in STEM and non-STEM subjects in secondary education. Survey data from 795 teachers and 12,965 students across 20 STEM schools in Kazakhstan were analyzed to examine the impact of 26 non-cognitive skills on performance in math, physics, first language, and history. Regression and mediation analyses were conducted to investigate how students' self-assessment of non-cognitive skills directly affects academic achievement and how these effects are mediated by teachers' assessments. The findings indicate that non-cognitive skills exhibit varying direct and total effects, with mediated effects showing greater consistency across different subjects. In math and physics, information processing skill and grit show the strongest direct and total effects on academic achievement. In first language and history, responsibility management and teamwork skill are most influential. Except for capacity for optimism and growth mindset, all skills demonstrated mediated effects across the four subjects. This research informs curriculum development and equitable policies by showing how non-cognitive skills impact academic performance across subjects. It studies the case of Kazakhstan, adding to global education discourse and offering valuable insights for enhancing STEM education. [ABSTRACT FROM AUTHOR]

Access to higher education depends on the interaction between social origins and academic performance: background resources boost academic skills; but even when controlling for performance, privileged students are more likely to make ambitious choices and further transitions. Recent literature has shown that inequality in educational choices is heterogeneous across countries. However, it is still not well understood how different institutional designs within countries may affect the workings of those effects and how they can strengthen or weaken the inequality of educational opportunities. Using high-quality register data from the Brazilian higher education system, our work contributes to this understanding by investigating how SES and performance interact and drive students' choice between three different tracks: not entering higher education, entering the private system, or entering the public system. We developed a strategy to encompass multinomial choices and decompose the inequalities into primary and secondary effects. Using the Shapley Value decomposition strategy, we correct an intrinsic asymmetry that biased previous results. Our findings suggest affluent students enjoy dual advantages: high exam performance amplifies access to public universities (indirect effect) and family resources offset subpar performance, ensuring private university access (direct effect). We found no signs of multiplicative advantages.

Ecological theory and empirical research show that both direct lethal effects and indirect non-lethal effects can structure the composition of communities. While the direct effects of grazers on marine phytoplankton communities are well studied, their indirect effects are still poorly understood. Direct and indirect effects are inherently difficult to disentangle in plankton food webs. In this study we evaluate the indirect effects of copepod grazers on community function and structure using isolated chemical alarm signals, copepodamides. We expose intact summer and spring communities to direct grazing from copepods, or to chemical alarm cues without the presence of grazers in controlled experiments. The effects of direct grazing on ecosystem function were moderate in both experiments as indicated by levels of chlorophyll and primary production. Indirect and direct effects resulted in changes in the composition of both the eukaryote and prokaryote communities as shown by metabarcoding of 18S and 16S rRNA. Size structure analysis suggests that direct grazing and copepodamide exposure both favoured smaller organisms (< 10–15 μm) corroborating the size-structuring effect of copepod grazers. We conclude that the well-established effect of copepods on phytoplankton communities results from a combination of direct and indirect effects. This is a first attempt to isolate indirect effects of copepods on community structure and the results suggest that a full mechanistic understanding of the structuring effect of copepods will require insights to both direct and indirect effects of consumers as demonstrated for other ecosystems components. [ABSTRACT FROM AUTHOR]

Access to higher education depends on the interaction between social origins and academic performance: background resources boost academic skills; but even when controlling for performance, privileged students are more likely to make ambitious choices and further transitions. Recent literature has shown that inequality in educational choices is heterogeneous across countries. However, it is still not well understood how different institutional designs within countries may affect the workings of those effects and how they can strengthen or weaken the inequality of educational opportunities. Using high-quality register data from the Brazilian higher education system, our work contributes to this understanding by investigating how SES and performance interact and drive students' choice between three different tracks: not entering higher education, entering the private system, or entering the public system. We developed a strategy to encompass multinomial choices and decompose the inequalities into primary and secondary effects. Using the Shapley Value decomposition strategy, we correct an intrinsic asymmetry that biased previous results. Our findings suggest affluent students enjoy dual advantages: high exam performance amplifies access to public universities (indirect effect) and family resources offset subpar performance, ensuring private university access (direct effect). We found no signs of multiplicative advantages. [ABSTRACT FROM AUTHOR]

Despite the abundance of research on reducing carbon emissions, there is a significant gap in understanding the influence of macroeconomic factors on carbon dioxide (CO2) emissions from a spatial-structural perspective. This study aims to contribute to the literature by investigating the impact of macroeconomic factors on carbon dioxide emissions in six East African countries between 1989 and 2020. Using spatial econometric panel models, the study analyzed spatial dependence among the variables. The empirical findings indicate that gross domestic product (GDP) per capita and electricity consumption have positive direct and indirect effects on carbon emissions, while fuel prices and exports have negative direct effects, but positive spillover effects on neighboring countries. Imports have a positive impact on local economies, but negative spillover effects. Additionally, the urban population has no significant impact on the environment. These findings provide important policy implications for optimizing spatial growth patterns and achieving a low-carbon economy in East African countries. [ABSTRACT FROM AUTHOR]

Temperature and resource availability are pivotal factors influencing phytoplankton community structures. Numerous prior studies demonstrated their significant influence on phytoplankton stoichiometry, cell size, and growth rates. The growth rate, serving as a reflection of an organism's success within its environment, is linked to stoichiometry and cell size. Consequently, alterations in abiotic conditions affecting cell size or stoichiometry also exert indirect effects on growth. However, such results have their limitations, as most studies used a limited number of factors and factor levels which gives us limited insights into how phytoplankton respond to environmental conditions, directly and indirectly. Here, we tested for the generality of patterns found in other studies, using a combined multiple‐factor gradient design and two single species with different size characteristics. We used a structural equation model (SEM) that allowed us to investigate the direct cumulative effects of temperature and resource availability (i.e., light, N and P) on phytoplankton growth, as well as their indirect effects on growth through changes in cell size and cell stoichiometry. Our results mostly support the results reported in previous research thus some effects can be identified as dominant effects. We identified rising temperature as the dominant driver for cell size reduction and increase in growth, and nutrient availability (i.e., N and P) as dominant factor for changes in cellular stoichiometry. However, indirect effects of temperature and resources (i.e., light and nutrients) on species' growth rates through cell size and cell stoichiometry differed across the two species suggesting different strategies to acclimate to its environment. [ABSTRACT FROM AUTHOR]

Traditional linear mediation analysis has inherent limitations when it comes to handling high-dimensional mediators. Particularly, accurately estimating and rigorously inferring mediation effects is challenging, primarily due to the intertwined nature of the mediator selection issue. Despite recent developments, the existing methods are inadequate for addressing the complex relationships introduced by confounders. To tackle these challenges, we propose a novel approach called DP2LM (Deep neural network-based Penalized Partially Linear Mediation). This approach incorporates deep neural network techniques to account for nonlinear effects in confounders and utilizes the penalized partially linear model to accommodate high dimensionality. Unlike most existing works that concentrate on mediator selection, our method prioritizes estimation and inference on mediation effects. Specifically, we develop test procedures for testing the direct and indirect mediation effects. Theoretical analysis shows that the tests maintain the Type-I error rate. In simulation studies, DP2LM demonstrates its superior performance as a modeling tool for complex data, outperforming existing approaches in a wide range of settings and providing reliable estimation and inference in scenarios involving a considerable number of mediators. Further, we apply DP2LM to investigate the mediation effect of DNA methylation on cortisol stress reactivity in individuals who experienced childhood trauma, uncovering new insights through a comprehensive analysis. [ABSTRACT FROM AUTHOR]

Repeated measurement designs (RMDs) are economical and commonly utilized in pharmacology, psychology, and animal science experiments. However, RMDs might have carryover effects, which become the main source of bias in estimation of treatment effects. Carry over effects can economically be controlled with the use of minimal balanced RMDs, strongly balanced RMDs or their generalized classes. No general procedure is available in literature to obtain these important classes of RMDs. An R-Package has been developed in this article to check the given values v and p for the possible existence of minimal circular balanced and strongly balanced RMDs (along with their generalized classes), generate the sets of shifts for possible designs, and to calculate the efficiency of separability and carry over effects for the generated design. [ABSTRACT FROM AUTHOR]

AbstractIn experiments related to agriculture, psychology, medicine, animal sciences, pharmacology, and other fields, repeated measurements designs (RMDs) are utilized which are economical design. However, the use of these designs may result in carryover effects, which are the primary cause of bias. Balanced or strongly balanced RMDs can control these effects. Strongly balanced RMDs estimate the direct effects and carryover effects independently; therefore, these designs have an edge over the balanced RMDs. In this article, therefore, some general procedures are presented to obtain minimal circular strongly and nearly strongly balanced RMDs in periods of k different sizes with high efficiency of Separability and of carryover effects. [ABSTRACT FROM AUTHOR]

Introduction: This exploratory study delves into the relationships between noncognitive skills and academic achievement within the unique context of STEM schools in Kazakhstan. Methods: Survey data were collected from 109 teachers and 395 students at a STEM secondary school in Kazakhstan. Correlational, regression and path analyses were conducted to explore the relationship between non-cognitive skills and academic performance in Mathematics, Computer Science, Physics, and Chemistry classes. Results: The results showed that out of the 26 skills, eight had a direct impact, 12 had an indirect impact, and six had no impact on academic achievement of students in the four STEM subjects. Discussion: This study is the first to explicitly examine the impact of one group of non-cognitive skills on academic achievement of students in STEM subjects mediated by another group of these skills. Teachers are encouraged to integrate non-cognitive skill development into curricula, tailored to subject-specific needs. Policymakers can use findings to inform equitable skill development policies. [ABSTRACT FROM AUTHOR]

BackgroundPeople with HIV (PWH) are at increased risk for invasive pneumococcal disease (IPD). Thirteen-valent pneumococcal conjugate vaccine (PCV13) was recommended for use in US children in 2010 and for PWH aged 19 years or older in 2012. We evaluated the population-level impact of PCV13 on IPD among PWH and non-PWH aged 19 years or older.MethodsWe identified IPD cases from 2008 to 2018 through the Active Bacterial Core surveillance platform. We estimated IPD incidence using the National HIV Surveillance System and US Census Bureau data. We measured percent changes in IPD incidence from 2008 to 2009 to 2017-2018 by HIV status, age group, and vaccine serotype group, including serotypes in recently licensed 15-valent (PCV15) and 20-valent (PCV20) PCVs.ResultsIn 2008-2009 and 2017-2018, 8.4% (552/6548) and 8.0% (416/5169) of adult IPD cases were among PWH, respectively. Compared with non-PWH, a larger proportion of IPD cases among PWH were in adults aged 19-64 years (94.7%-97.4% vs. 56.0%-60.1%) and non-Hispanic Black people (62.5%-73.0% vs. 16.7%-19.2%). Overall and PCV13-type IPD incidence in PWH declined by 40.3% (95% confidence interval: -47.7 to -32.3) and 72.5% (95% confidence interval: -78.8 to -65.6), respectively. In 2017-2018, IPD incidence was 16.8 (overall) and 12.6 (PCV13 type) times higher in PWH compared with non-PWH; PCV13, PCV15/non-PCV13, and PCV20/non-PCV15 serotypes comprised 21.5%, 11.2%, and 16.5% of IPD in PWH, respectively.ConclusionsDespite reductions post-PCV13 introduction, IPD incidence among PWH remained substantially higher than among non-PWH. Higher-valent PCVs provide opportunities to reduce remaining IPD burden in PWH.

An experiment was carried out during Kharif 2020 at wetland farm of Sri Venkateswara Agricultural College, Tirupati using 30 inbred lines of maize to assess the trait association for 16 yield and yield attributes. It revealed that ear length, number of kernels per row, plant height, ear girth, SPAD chlorophyll meter reading, 100 kernel weight, number of kernel rows per ear, specific leaf area, harvest index and tassel length had notable positive correlation with kernel yield per plant suggesting that selecting these characters simultaneously lead to an increase in kernel yield per plant. Path analysis revealed a significant and positive direct influence of ear length on the kernel yield per plant. Hence, ear length could be considered during selection in maize for improving kernel yield.

The present study illustrates the outcomes of a simultaneous equation modelling that investigates the relationship between competitiveness and corruption both directly and indirectly, considering the interlinkages with the broader social structure in a sample of 110 world countries. The empirical results justify a separate analysis of the sample according with the level of human development, and outline the importance of existing income inequalities in addition to economic and social development. In high human development countries, the net effect of competitiveness on corruption is greater than its direct effect due to the indirect (positive) correlation of competitiveness with income inequality. On the contrary, in low human development countries, the final effect of competitiveness on corruption is lower than its direct effects and, therefore, the ensuing improvement on the level of corruption is reduced substantially. This finding may be ascribed to the indirect negative effect stemming from income inequalities, which exacerbate social turbulence and collisions whereas they impinge on social cohesion and institutional resilience. These issues, which are particularly intense under low social development conditions, reduce the direct, non-linear effect of competitiveness on corruption, suggesting the importance of indirect effects. [ABSTRACT FROM AUTHOR]

Minimal circular balanced and strongly balanced neighbor designs (MCBNDs & MCSBNDs) are popular to control neighbor effects and to estimate neighbor and direct effects independently. In this article, an R-coded algorithm is presented to obtain efficient MCBNDs and MCSBNDs for odd v (number of treatments), and its four generalized classes for v even. Developed algorithm has made the construction of the efficient circular designs robust to neighbor effects so easy in blocks of equal and unequal sizes. [ABSTRACT FROM AUTHOR]

Cross-Over Designs or Repeated Measurements Designs are experimental designs in which treatments (e.g., medicines, fertilizers, diets) are applied to experimental units (usually humans) in different time periods. A common problem is to find the distribution of n experimental units in order to find the optimal experimental design for the well-known criteria of optimality (A, D, E optimality, etc.). If there is only one parameter of interest, the criterion is the minimization of the variance of the parameter estimator. In this case, a Repeated Measurements Design with one parameter of interest (the direct effect of the treatment) is examined and the distribution of n which minimizes the variance of that parameter is found. The objective of the research is the estimation of the variance of the Ordinal Least-Squares estimators of the Repeated Measurements Design model for two treatments and five periods. Heydayat and Afsarinejad introduced the basic model which is used. The optimal Repeated Measurements Designs are derived for n experimental units. Optimality criterion is the minimization of the variance of the estimated direct effects. [ABSTRACT FROM AUTHOR]

Summary: Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability predictors (LC models with external predictors), and/or score conditional probability predictors (LC regression models). In such cases, their distribution is not of interest. Class‐specific distribution is of interest in the distal outcome model, when the distribution of the external variables is assumed to depend on LC membership. In this paper, we consider a more general formulation, that embeds both the LC regression and the distal outcome models, as is typically done in cluster‐weighted modelling. This allows us to investigate (1) whether the distribution of the external variables differs across classes, (2) whether there are significant direct effects of the external variables on the indicators, by modelling jointly the relationship between the external and the latent variables. We show the advantages of the proposed modelling approach through a set of artificial examples, an extensive simulation study and an empirical application about psychological contracts among employees and employers in Belgium and the Netherlands. [ABSTRACT FROM AUTHOR]

The mediation analysis methodology of the cause-and-effect relationship through mediators has been increasingly popular over the past decades. The human microbiome can contribute to the pathogenesis of many complex diseases by mediating disease-leading causal pathways. However, standard mediation analysis is not adequate for microbiome data due to the excessive number of zero values and the over-dispersion in the sequencing reads, which arise for both biological and sampling reasons. To address these unique challenges brought by the zero-inflated mediator, we developed a novel mediation analysis algorithm under the potential-outcome framework to fill this gap. The proposed semiparametric model estimates the mediation effect of the microbiome by decomposing indirect effects into two components according to the zero-inflated distributions. The bootstrap algorithm is utilized to calculate the empirical confidence intervals of the causal effects. We conducted extensive simulation studies to investigate the performance of the proposed weighting-based approach and some model-based alternatives, and our proposed model showed robust performance. The proposed algorithm was implemented in a real human microbiome study of identifying whether some taxa mediate the relationship between LACTIN-V treatment and immune response. [ABSTRACT FROM AUTHOR]

Climate change represents a growing ecological challenge. The (sub) arctic and boreal regions of the world experience the most rapid warming, presenting an excellent model system for studying how climate change affects mammals. Moose (Alces alces) are a particularly relevant model species with their circumpolar range. Population declines across the southern edge of this range are linked to rising temperatures. Using a long-term dataset (1988–1997, 2017–2019), we examine the relative strength of direct (thermoregulatory costs) and indirect (food quality) pathways linking temperature, precipitation, and the quality of two important food items (birch and fireweed) to variation in moose calf mass in northern Sweden. The direct effects of temperature consistently showed stronger relationships to moose calf mass than did the indirect effects. The proportion of growing season days where the temperature exceeded a 20 °C threshold showed stronger direct negative relationships to moose calf mass than did mean temperature values. Finally, while annual forb (fireweed) quality was more strongly influenced by temperature and precipitation than were perennial (birch) leaves, this did not translate into a stronger relationship to moose calf weight. The only indirect path with supporting evidence suggested that mean growing season temperatures were positively associated with neutral detergent fiber, which was, in turn, negatively associated with calf mass. While indirect impacts of climate change deserve further investigation, it is important to recognize the large direct impacts of temperature on cold-adapted species. [ABSTRACT FROM AUTHOR]

Social skills and vocabulary are important areas of development involved in early reading achievement, yet little attention has been given to understanding the dynamic associations among them during the elementary years. This study examined the relations among three dimensions of social skills-cooperation, assertion, and self-control-vocabulary and developing reading comprehension (RC) skills in a longitudinal sample of first graders (n = 468). Using Structural Equation Modeling, reciprocal effects were observed between vocabulary and RC as well as direct effects among social skills, vocabulary, and RC after controlling for the influence of problem behaviors. This study highlights the reciprocal nature of students' vocabulary and RC skills as well as provides preliminary evidence suggesting that social skills play a role in developing vocabulary and RC skills, and further, vocabulary and RC skills play a role in social development during middle childhood. Implications for policy and practice are discussed.

The purpose of this article is to determine and construct ϕ -optimal designs over the class of all circular cross-over designs with two treatments when the number of both periods and experimental subjects is even. We are interested in estimating the contrasts of both direct and carry-over effects jointly, and minimizing the variances of the best linear unbiased estimators of contrasts of direct as well as carry-over effects. These results enrich already existing works in the present literature, strengthening this of Magda (1980), and extending these of Kunert (1984) and Chasiotis and Kounias (2020). [ABSTRACT FROM AUTHOR]

Minimal neighbour designs (NDs) are used when a response of a treatment (direct effect) is affected by the treatment(s) applied in the neighbouring units. Minimal generalised NDs are preferred when minimal NDs cannot be constructed. Through the method of cyclic shifts (Rule I), the conditions for the existence of minimal circular generalised NDs are discussed, in which v/2 unordered pairs do not appear as neighbours. Certain generators are also developed to obtain minimal circular generalised NDs in blocks of two different sizes, where k2 = 3, 4 and 5. All these designs are constructed using i sets of shifts for k1 and two for k2. [ABSTRACT FROM AUTHOR]

Simultaneously defending against predators, stymieing competitors, and generating immune responses can impose conflicting demands for host species caught in the entanglement of a food web. Host immunity is not only shaped by direct interactions among species, but also many indirect cascading effects. By reducing competition, predators in particular can affect resource acquisition necessary for hosts to mount energetically costly immune responses. However, identifying the links between predators and host immune responses determined by resource acquisition is a complex affair, because predators can (1) reduce host density and thus competition among hosts, (2) exert non-consumptive trait-mediated effects on host resource acquisition behavior, and (3) generate natural selection on host resource acquisition behavior. To examine the relative contributions of these potential predator driven density- and trait-mediated effects on a key aspect of immune function (total phenoloxidase activity, total PO), we conducted mesocosm and field experiments with larval damselflies (Enallagma signatum) and their dominant fish predator (Lepomis macrochirus). Although we expected to observe declines in total PO activity with increases in damselfly density, we found no relationship between density and total PO activity. We also found no support for the prediction that total PO activity would vary as a result of either non-consumptive trait-mediated effects or selection on damselfly foraging activity underlying resource acquisition. Despite the lack of trait- or density-mediated effects, we did find that total PO activity increased with damselfly prey density among lakes, implying resource limitation for this aspect of immune function. These unexpected results point to the need to better understand the ecological conditions whereby predators and competitors constrain immune functions necessary for species to defend themselves in complex food webs. [ABSTRACT FROM AUTHOR]

Although sociologists have devoted considerable attention to studying the role of education in intergenerational social class mobility using log-linear models for contingency tables, indings in this literature are not free from rescaling or non-collapsibility bias caused by adjusting for education in these models. Drawing on the methodological literature on inverse probability reweighting, I present a straightforward standardization approach free from this bias. The approach reweighs in an initial step the mobility table cell frequencies to create a pseudo-population in which social class origins and education are independent of each other, after which one can apply any loglinear model to the reweighted mobility table. In contrast to the Karlson-Holm-Breen method, the approach yields coefficients that are comparable across different studies because they are unaffected by education's predictive power of class destinations. Moreover, the approach is easily applied to models for various types of mobility patterns such as those in the core model of fluidity; it yields a single summary measure of overall mediation; and it can incorporate several mediating variables, allowing researchers to control for additional merit proxies such as cognitive skills or potential confounders such as age. I illustrate the utility of the approach in four empirical examples.

Neighbor designs (NDs) are used to balance out the neighbor effects. Among these designs, minimal NDs are economical, therefore, these are preferred by experimenters. Unfortunately, minimal NDs cannot be constructed for all combinations of v (number of treatments) and k (block sizes). Minimal weakly balanced NDs (WBNDs) are recommended in the situations where minimal NDs could not be constructed. In this article, some generators are developed to obtain minimal circular WBNDs (MCWBNDs) in blocks of two different sizes. In our proposed designs, 3v/2 unordered pairs of distinct treatments appear twice as neighbors while all other pairs appear once. In these designs, we lose [ 300 / (v − 1) ] % neighbor balance while saving at least [ 50 (v − 4) / (v − 1) ] % experimental material. [ABSTRACT FROM AUTHOR]

Causal mediation analysis aims at disentangling a treatment effect into an indirect mechanism operating through an intermediate outcome or mediator, as well as the direct effect of the treatment on the outcome of interest. However, the evaluation of direct and indirect effects is frequently complicated by non-ignorable selection into the treatment and/or mediator, even after controlling for observables, as well as sample selection/outcome attrition. We propose a method for bounding direct and indirect effects in the presence of such complications using a method that is based on a sequence of linear programming problems. Considering inverse probability weighting by propensity scores, we compute the weights that would yield identification in the absence of complications and perturb them by an entropy parameter reflecting a specific amount of propensity score misspecification to set-identify the effects of interest. We apply our method to data from the National Longitudinal Survey of Youth 1979 to derive bounds on the explained and unexplained components of a gender wage gap decomposition that is likely prone to non-ignorable mediator selection and outcome attrition. [ABSTRACT FROM AUTHOR]

• Rotavirus vaccination is expected to reduce rotavirus mortality by 49% globally. • These benefits are present for countries at all income levels. • Most impact is due to direct benefits, but indirect effects also enhance impact. • To sustain this benefit, a complete vaccine series is needed. Rotavirus vaccination has been shown to reduce rotavirus burden in many countries, but the long-term magnitude of vaccine impacts is unclear, particularly in low-income countries. We use a transmission model to estimate the long-term impact of rotavirus vaccination on deaths and disability adjusted life years (DALYs) from 2006 to 2034 for 112 low- and middle-income countries. We also explore the predicted effectiveness of a one- vs two- dose series and the relative contribution of direct vs indirect effects to overall impacts. To validate the model, we compare predicted percent reductions in severe rotavirus cases with the percent reduction in rotavirus positivity among gastroenteritis hospital admissions for 10 countries with pre- and post-vaccine introduction data. We estimate that vaccination would reduce deaths from rotavirus by 49.1 % (95 % UI: 46.6–54.3 %) by 2034 under realistic coverage scenarios, compared to a scenario without vaccination. Most of this benefit is due to direct benefit to vaccinated individuals (explaining 69–97 % of the overall impact), but indirect protection also appears to enhance impacts. We find that a one-dose schedule would only be about 57 % as effective as a two-dose schedule 12 years after vaccine introduction. Our model closely reproduced observed reductions in rotavirus positivity in the first few years after vaccine introduction in select countries. Rotavirus vaccination is likely to have a substantial impact on rotavirus gastroenteritis and its mortality burden. To sustain this benefit, the complete series of doses is needed. [ABSTRACT FROM AUTHOR]

Neighbor designs (NDs) are used in the experiments where neighbor effects may arise. Neighbor designs neutralize these effects and are, therefore, considered to be robust against neighbor effects. Minimal neighbor designs are always most economical among the neighbor designs and are, therefore, preferred by the experimenters. Method of cyclic shifts provides these designs in circular blocks only for odd v (number of treatments). For v even, minimal circular generalized neighbor designs in which only v/2 unordered pairs of distinct treatments that do not appear as neighbors will be the better alternate to the minimal neighbor designs. In this article, such minimal generalized neighbor designs are constructed in circular blocks for v even. [ABSTRACT FROM AUTHOR]

As the pace of global warming accelerates, so do the threats to human health, urgent priority among them being antibiotic-resistant infections. In the context of global warming, this review summarises the direct and indirect effects of rising surface water temperatures on the development of bacterial antibiotic resistance. First, the resistance of typical pathogens such as E. coli increased with average temperature. This is not only related to increased bacterial growth rate and horizontal gene transfer frequency at high temperatures but also heat shock responses and cumulative effects. Secondly, the acceleration of bacterial growth indirectly promotes antibiotic residues in surface water, which is conducive to the growth and spread of resistant bacteria. Furthermore, the cascading effects of global warming, including the release of nutrients into the water and the resulting increase of bacteria and algae, indirectly promote the improvement of resistance. Water treatment processes exposed to high temperatures also increase the risk of resistance in surface water. The fitness costs of antibiotic resistance under these dynamic conditions are also discussed, concluding the relationship between various factors and resistance persistence. It was expected to provide a comprehensive basis for mitigating antibiotic resistance in the face of global warming. [Display omitted] [ABSTRACT FROM AUTHOR]

Childhood trauma tends to influence cortisol stress reactivity through the mediating effects of DNA methylation. Houtepen et al. conducted a study to investigate the role of DNA methylation in cortisol stress reactivity and its relationship with childhood trauma. The study collected a dataset consisting of 385,882 DNA methylation loci, cortisol stress reactivity, one-dimensional score on a childhood trauma questionnaire and several covariates for 85 healthy individuals. Of great scientific interest is to identify the active mediating loci out of the 385,882 ones. Houtepen et al. conducted 385,882 linear mediation analyses, in each of which one locus was considered, and identified three active mediating loci. More recently, van Kesteren and Oberski proposed a coordinate-wise mediation filter (CMF) and applied it to the same dataset. They identified five active mediating loci. Unfortunately, the three loci identified by Houtepen et al. are completely different from the five loci identified by van Kesteren and Oberski, probably because both Houtepen et al. and van Kesteren and Oberski did not consider all loci jointly in their analyses. The high dimensional DNA methylation loci indeed necessitate new techniques for identifying active mediating loci and testing the direct and indirect effects of the early life traumatic stress on later cortisol alteration. Motivated by the contradictory results in the aforementioned two scientific works, we develop a new estimating and testing procedure, and apply it to the same dataset as that analyzed by the two works. We identify three new loci: cg19230917, cg06422529 and cg03199124, and their effect sizes and p-values are 321.196 (p-value = 0.035965), 418.173 (p-value = 0.000234) and 471.865 (p-value = 0.001691), respectively. These three loci possess both reasonably neurobiological interpretations and statistically significant effects via our proposed tests. Based on our new procedure, we further confirm that the childhood trauma does not have significant direct effects on cortisol change—it only indirectly affects cortisol through DNA methylation, and the indirect effect is negative. for this article are available online. [ABSTRACT FROM AUTHOR]

Plant essential oils (EOs) are gaining interest as biopesticides for crop protection. EOs have been recognized as important ingredients of plant protection products including insecticidal, acaricidal, fungicidal, and nematicidal agents. Considering the growing importance of EOs as active ingredients, the domestication and cultivation of Medicinal and Aromatic Plants (MAPs) to produce chemically stable EOs contributes to species conservation, provides the sustainability of production, and decreases the variations in the active ingredients. In addition to these direct effects on plant pests and diseases, EOs can induce plant defenses (priming effects) resulting in better protection. This aspect is of relevance considering that the EU framework aims to achieve the sustainable use of new plant protection products (PPPs), and since 2020, the use of contaminant PPPs has been prohibited. In this paper, we review the most updated information on the direct plant protection effects of EOs, focusing on their modes of action against insects, fungi, and nematodes, as well as the information available on EOs with plant defense priming effects. [ABSTRACT FROM AUTHOR]

Typically, the explanatory variables included in a regression model, in conjunction with the omitted relevant regressors implied by the usual error term, have both direct and indirect effects on the dependent variable. Attempts to obtain their separate estimates have been plagued with simultaneity issues. To circumvent these problems, this paper defines their sum as "total effects", develops a time-varying coefficients methodology for their estimation without simultaneity bias, and applies these techniques to estimate the total effects of commercial bank credit per-capita on real GDP per-capita in Mauritius. An innovation is the introduction of extraneous variables that act as "coefficient drivers" chosen on the basis of best predictive performance, as measured by the smallest value of Theil's U-statistic we were able to locate in the estimation. [ABSTRACT FROM AUTHOR]