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The purpose of this study was to determine Turkish physical education (PE) teachers' level of technological innovation use and attitudes regarding their applications and diffusion. This study consisted of 678 Turkish PE teachers. In total, 265 (39.1%) of the PE teachers were female, and 413 (60.9%) were male. A sequential explanatory mixed-methods design was used in this study. "The Applying and Diffusing Technological Innovations Scale for Teachers" was used for data collection. The results showed that the main obstacles the PE teachers face in using technological innovations were the cost of products; security and privacy problems; the need for new versions and technical support; the lack of time; the lack of interest; difficulty in accessing technology; and the lack of understanding. Moreover, there was a significant difference in the tendency to apply and diffuse technological innovations in terms of gender, school type, and school level. We found that the "ability to use innovations" sub-dimension affects the PE teachers' tendencies to apply and diffuse technology. As a result, we recommend providing various training programs on technological innovations to the older/longer-serving PE teachers, especially those working in public schools and secondary schools. [ABSTRACT FROM AUTHOR]

AbstractThis exploratory inquiry examined how a recent national external staff audit carried out on behalf of the Ghanaian government is perceived by the teaching staff of Ghanaian Technical Universities (TUs); particularly, in terms of the assessors, the assessment processes, and the effects on the TUs and the individual staff within them. The population for the study was all the teaching staff of the TUs. However, a total number of 212 teaching staff from seven out of the eight TUs in the country were selected to answer the semi-structured questionnaire using simple stratified random sampling techniques. The quantitative data was evaluated using descriptive statistics and factor analysis while the qualitative data was analyzed using thematic analysis. The quantitative and qualitative results were then triangulated at the discussion section. The main highpoints of the study were that the assessors were definitely not from the (sister) TUs and that their neutrality and training could not be guaranteed. Of course, the audit led to a new sense of concern for enhancing teaching, learning, research; and an increase in the number of policies, higher qualifications and promotions. Nevertheless, it impacted negatively on the health, job satisfaction and social life of individual staff. For policy makers and practitioners, the importance of extensive consultations with stakeholders for instance, in the selection of assessors, standards and the realism of an appropriate level of compliance is suggested.

Cookies do not make purchase decisions; individuals do. Cookie-level analyses are problematic—use first-party individual data instead. Retargeted advertising is a popular form of digital advertising that algorithmically delivers ads to users who previously visited an advertiser's website. We empirically investigate the challenge of estimating individual-level advertising response when the data stem from a field experiment randomized at the cookie level. Such experiments are common in the industry. We investigate how cookie-level randomization manifests itself at the individual level and the role it plays in measuring retargeted advertising effectiveness. We show that cookie-based analyses to assess retargeted advertising effectiveness are flawed. Cookie randomization breaks down because of the presence of individuals who have both treatment and control cookies—these individuals are more engaged and spend more. Because of the cookie propagation effect we uncover, individual assignment to the treatment and control groups is not random. Individual-level analyses, in conjunction with first-party data, paint a more complete picture of the impact of retargeted advertising. We detect an increase in offline sales that cookie-based analyses fail to capture. Although many marketers are apprehensive about the cookie-less world of the future, we show that cookie-based analyses can be misleading. Individual data, obtained with consent while protecting identity, are better and overcome many of these problems with cookie-based analyses. History: Catherine Tucker served as the senior editor. Supplemental Material: Data and the online appendix are available at https://doi.org/10.1287/mksc.2023.1453. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine Turkish physical education (PE) teachers’ level of technological innovation use and attitudes regarding their applications and diffusion. This study consisted of 678 Turkish PE teachers. In total, 265 (39.1%) of the PE teachers were female, and 413 (60.9%) were male. A sequential explanatory mixed-methods design was used in this study. “The Applying and Diffusing Technological Innovations Scale for Teachers” was used for data collection. The results showed that the main obstacles the PE teachers face in using technological innovations were the cost of products; security and privacy problems; the need for new versions and technical support; the lack of time; the lack of interest; difficulty in accessing technology; and the lack of understanding. Moreover, there was a significant difference in the tendency to apply and diffuse technological innovations in terms of gender, school type, and school level. We found that the “ability to use innovations” sub-dimension affects the PE teachers’ tendencies to apply and diffuse technology. As a result, we recommend providing various training programs on technological innovations to the older/longer-serving PE teachers, especially those working in public schools and secondary schools.

In this paper, the spatial dynamic panel data (SDPD) model with fixed effects is extended to a non-parametric form by relaxing the linear or nonlinear parameter structure of explanatory variables. The non-parametric spatial dynamic panel data (NSDPD) model with fixed effects not only retains the advantages of the SDPD model which can deal with spatial and/or temporal individual characteristics and spatio-temporal dependencies but also solves the limitation that may lead to specification errors. It also enhances the flexibility and practicability of the spatial econometric model. Since the model to be estimated contains unknown functions, we propose this profile maximum likelihood (PML) method to solve the problem of the incidental parameters in the estimation. Under the assumption that the spatial coefficients are known, we first eliminate the influence of the time effect by substitution and then use the local polynomial estimation to preliminarily estimate the unknown function so as to transform the model into the parametric form for solving. We derive the asymptotic properties of PMLEs and find that under certain regularity conditions, both parametric and non-parametric estimators are consistent. The Monte Carlo results show that the estimators have good finite sample performance. We illustrate the empirical relevance of the model by applying it to examine the impact of tourism dynamics on economic development in the Yangtze River Delta region of China. [ABSTRACT FROM AUTHOR]

Soil fauna plays a key role in regulating biogeochemical cycles, but how multiple global change factors (GCFs) may affect faunal communities remains poorly studied. We conducted a meta‐analysis using 1154 observations to evaluate the individual and combined effects of elevated CO2, nitrogen (N) addition, warming, increased rainfall and drought on soil fauna density and diversity. Here we show that, overall, individual and combined effects of GCFs had negligible effects on soil fauna density and diversity, except that density was negatively affected by drought (−27.4%) and positively affected by increased rainfall individually (+24.9%) and in combination with N addition (+67.3%) or warming (+70.4%). GCF effects varied among taxonomic groups both in magnitude and direction. Variables such as latitude, elevation and experimental setting significantly impacted both individual and combined effects. Our results suggest that soil fauna density is affected by changed rainfall regimes, while diversity is resistant against individual and combined effects of multiple GCFs. [ABSTRACT FROM AUTHOR]

The human cerebral cortex is organized into functionally segregated but synchronized regions bridged by the structural connectivity of white matter pathways. While structure-function coupling has been implicated in cognitive development and neuropsychiatric disorders, it remains unclear to what extent the structure-function coupling reflects a group-common characteristic or varies across individuals, at both the global and regional brain levels. By leveraging two independent, high-quality datasets, we found that the graph neural network accurately predicted unseen individuals' functional connectivity from structural connectivity, reflecting a strong structure-function coupling. This coupling was primarily driven by network topology and was substantially stronger than that of the correlation approaches. Moreover, we observed that structure-function coupling was dominated by group-common effects, with subtle yet significant individual-specific effects. The regional group and individual effects of coupling were hierarchically organized across the cortex along a sensorimotor-association axis, with lower group and higher individual effects in association cortices. These findings emphasize the importance of considering both group and individual effects in understanding cortical structure-function coupling, suggesting insights into interpreting individual differences of the coupling and informing connectivity-guided therapeutics., Competing Interests: DECLARATION OF COMPETING INTERESTS The authors declare no competing interests.

Background: Spontaneous Adverse Event Reporting (SAER) databases play a crucial role in post-marketing drug surveillance. However, the traditional model-free disproportionality analysis has been challenged by the insufficiency in investigating subgroup and confounders. These issues result in significant low-precision and biases in data mining for SAER., Methods: The Model-Driven Reporting Odds Ratio (MD-ROR) was proposed to bridge the gap between SAER database and explainable models for exploring individual and confounding effects. MD-ROR is grounded in a well-designed model, rather than a 2 × 2 cross table, for estimating AE-drug signals. Consequently, individual and confounding effects can be parameterized based on these models. We employed simulation data and the FDA Adverse Event Reporting System (FAERS) database., Result: The simulated data indicated the subgroup effects estimated by MD-ROR were unbiased and efficient. Moreover, the adjusted-MD-ROR demonstrated greater robustness against confounding biases than the crude ROR. Applying our method to the FAERS database suggested higher occurrences of drug interactions and cardiac adverse events induced by Midazolam in females compared to males., Conclusion: The study underscored that MD-ROR holds promise as a method for investigating individual and confounding effects in SAER databases.

In this paper, the spatial dynamic panel data (SDPD) model with fixed effects is extended to a non-parametric form by relaxing the linear or nonlinear parameter structure of explanatory variables. The non-parametric spatial dynamic panel data (NSDPD) model with fixed effects not only retains the advantages of the SDPD model which can deal with spatial and/or temporal individual characteristics and spatio-temporal dependencies but also solves the limitation that may lead to specification errors. It also enhances the flexibility and practicability of the spatial econometric model. Since the model to be estimated contains unknown functions, we propose this profile maximum likelihood (PML) method to solve the problem of the incidental parameters in the estimation. Under the assumption that the spatial coefficients are known, we first eliminate the influence of the time effect by substitution and then use the local polynomial estimation to preliminarily estimate the unknown function so as to transform the model into the parametric form for solving. We derive the asymptotic properties of PMLEs and find that under certain regularity conditions, both parametric and non-parametric estimators are consistent. The Monte Carlo results show that the estimators have good finite sample performance. We illustrate the empirical relevance of the model by applying it to examine the impact of tourism dynamics on economic development in the Yangtze River Delta region of China.

Conventional OLS fixed-effects and GLS random-effects estimators of dynamic models that control for individual-effects are known to be biased when applied to short panel data (T ≤ 10). GMM estimators are the most used alternative but are known to have drawbacks. Transformed-likelihood estimators are unused in political science. Of these, orthogonal reparameterization estimators are only tangentially referred to in any discipline. We introduce these estimators and test their performance, demonstrating that the unused orthogonal reparameterization estimator in particular performs very well and is an improvement on the commonly used GMM estimators. When T and/or N are small, it provides efficiency gains and overcomes the issues GMM estimators encounter in the estimation of long-run effects when the coefficient on the lagged dependent variable is close to one. [ABSTRACT FROM AUTHOR]

The article addresses the difference between regional inflation rates, and criteria that determine such variations. Moreover, it examines whether inflation differences in the Russian regions significantly affect a unified monetary policy targetting a 4 per cent inflation. Using panel econometric methods with instrumental variables, we identified the factors creating regional inflation difference: a) output gap, b) inflation expectations, c) exchange rate pass-through, d) and regional price convergence. Then, we explained how these factors influence regional inflation, using the modern theoretical models that are based on the neo-Keynesian logic. Additionally, we discussed the problems caused by regional inflation differences. Since the convergence of price levels to the average Russian level is the key factor influencing regional inflation differences, such differences do not constitute a problem for the unified monetary policy aimed at a 4% inflation target. In the study, we have determined the causes of inflation differences in the Russian regions, the majority of which result from the new Keynesian Phillips curve. The obtained results can be applied for developing regional economic policies aimed at synchronizing inflation in the Russian regions, as well as for modelling the consequences of monetary policy for regional economies.

In recent years, there has been great interest in using network structure to improve classic statistical models in cases where individuals are dependent. The network vector autoregressive (NAR) model assumes that each node's response can be affected by the average of its connected neighbors. This article focuses on the problem of individual effects in NAR models, as different nodes have different effects on others. We propose a penalty method to estimate the NAR model with different individual effects and investigate some theoretical properties. Two simulation experiments are performed to verify effectiveness and tolerance compared with the original NAR model. The proposed model is also applied to an international trade data set. [ABSTRACT FROM AUTHOR]

Background: To determine if tuberculosis (TB) screening improves patient outcomes, we conducted two systematic reviews to investigate the effect of TB screening on diagnosis, treatment outcomes, deaths (clinical review assessing 23 outcome indicators); and patient costs (economic review). Methods: Pubmed, EMBASE, Scopus and the Cochrane Library were searched between 1/1/1980-13/4/2020 (clinical review) and 1/1/2010-14/8/2020 (economic review). As studies were heterogeneous, data synthesis was narrative. Findings: Clinical review: of 27,270 articles, 18 (n=3 trials) were eligible. Nine involved general populations. Compared to passive case finding (PCF), studies showed lower smear grade (n=2/3) and time to diagnosis (n=2/3); higher pre-treatment losses to follow-up (screened 23% and 29% vs PCF 15% and 14%; n=2/2); and similar treatment success (range 68-81%; n=4) and case fatality (range 3-11%; n=5) in the screened group. Nine reported on risk groups. Compared to PCF, studies showed lower smear positivity among those culture-confirmed (n=3/4) and time to diagnosis (n=2/2); and similar (range 80-90%; n=2/2) treatment success in the screened group. Case fatality was lower in n=2/3 observational studies; both reported on established screening programmes. A neonatal trial and post-hoc analysis of a household contacts trial found screening was associated with lower all-cause mortality. Economic review: From 2841 articles, six observational studies were eligible. Total costs (n=6) and catastrophic cost prevalence (n=4; range screened 9-45% vs PCF 12-61%) was lower among those screened. Interpretation: We found very limited patient outcome data. Collecting and reporting this data must be prioritised to inform policy and practice. Funding: WHO and EDCTP.

The article provides an overview of racism discourses in research and clinical practice in the health sector and discusses the individual and institutional effects of racism and discrimination on mental health. In addition, suggestions are provided as to which racism critical transformations in healthcare structures for mentally ill persons are necessary in order to enable equitable participation for people affected by discrimination and racism. [ABSTRACT FROM AUTHOR]

For centuries, tail duplications in reptiles have attracted human curiosity, and publications on anecdotal observations of supernumerary tails have grown considerably over recent years. However, there is no recent review on the occurrence of supernumerary tails in reptiles and the consequent effects on individuals. We provide new data on the frequency of supernumerary tails, including unprecedented frequencies and observations of tail triplication and quintuplication, from our own studies in arid Australia and from literature reviews. Our observations include data for a gecko species (Gehyra variegata) and three species of skinks (Eremiascincus richardsonii, Lerista punctatovittata, Morethia boulengeri) for which supernumerary tails have not been reported so far. We assume that hyperregeneration (following injuries inflicted by predators, sharp-edged window glass, and unknown factors) was the cause for the cases observed by us. Our review spans two millennia of published works describing supernumerary tails in 146 identified species of reptiles and up to 16 unidentified species. We assess the taxonomic and geographic distributions and the microhabitats of these 146 species, while also commenting on the potential causes and effects of supernumerary tails. The identified species belong to 16 families of lizards, one of amphisbaenians, three of snakes, the tuatara (Sphenodon punctatus), three turtle families, and one family of crocodiles. The geographic patterns of supernumerary tails are difficult to interpret due to an imbalance in published works from the major geographic areas. The vast majority of the species affected have a terrestrial lifestyle, followed by arboreal species. The frequency of supernumerary tails is low, with multiple tails having been reported only for 59 individuals, including our new data. Little is known about the effects of supernumerary tails on their carriers. In our study, there was no indication of them affecting mobility or increasing mortality. Some authors reported handicapped movement, whereas others did not find such effects, and both males and females with tail bifurcation/duplication were able to mate successfully. Most cases of supernumerary tails are likely to be due to hyperregeneration as a reaction to injuries or incomplete breaks of vertebral fracture planes. However, only one study statistically identified the culprits as predatory mammals. In captivity, such injuries were also inflicted through attacks by conspecifics and during copulation. The few cases in natural populations that were not due to hyperregeneration were presumably caused by unknown teratogenic factors to which the individuals were exposed during ontogeny; in one case this was most likely to be radioactive contamination. [ABSTRACT FROM AUTHOR]

This paper investigates the role of the regional context with regard to the influence of human capital and knowledge spillovers on SMEs' financial soundness. Our empirical setting is based on a multilevel analysis of panel data, which allows superior treatment of hierarchical data. The analysis is applied to SMEs belonging to the manufacturing sector and operating in four European countries over the period 2010–2015. We find that a combination of individual and regional‐level characteristics explains firm soundness better than individual features alone. Furthermore, we find that a high local educational level and knowledge spillovers improve firm soundness and that their effects vary according to the regional level of knowledge. These results are confirmed by several robustness tests. [ABSTRACT FROM AUTHOR]

This paper develops an alternative estimator for linear dynamic panel data models based on parameterizing the covariances between covariates and unobserved time-invariant effects. A GMM framework is used to derive an optimal estimator based on moment conditions in levels, with no efficiency loss compared to the classic alternatives like (Arellano, M., and S. Bond. 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations." Review of Economic Studies 58 (2): 277–297), (Ahn, S. C., and P. Schmidt. 1995. "Efficient Estimation of Models for Dynamic Panel Data." Journal of Econometrics 68 (1): 5–27) and (Ahn, S. C., and P. Schmidt. 1997. "Efficient Estimation of Dynamic Panel Data Models: Alternative Assumptions and Simplified Estimation." Journal of Econometrics 76: 309–321). Still, we show analytically and by Monte Carlo simulations that the new procedure leads to efficiency improvements for certain data generating processes. The framework also leads to a very simple test for unobserved effects. [ABSTRACT FROM AUTHOR]

The acidification liquid of waste activated sludge (WAS) could be used as the additional carbon source of biological nutrient removal. Recently, the optimization of operating conditions for the acidification metabolites has attracted much attention. In this study, a three-factor Box-Behnken design (BBD) was applied to determine the relative importance of the various factors and the optimum operating during acidification using response surface method (RSM). The importance of the individual variables on the production of soluble chemical oxygen demand (SCOD) was suspended solids (SS) > shaking rate > initial oxidation-reduction potential (ORP). The increase on SS content led to a decrease on the acidification degree. Low SS could promote mass exchange and microbial activity. The maximum SCOD yield (9288.5 mg/L) was predicted under the optimum condition at 8.0 g/L SS, 144.0 mV initial ORP, and 60.0 r/min shaking rate. Also, the releasing of soluble protein and carbohydrate was calculated as responses. The individual effect of shaking rate and initial ORP had significant effect on soluble protein and carbohydrate releasing, respectively. This study would provide valuable information for increasing the efficiency of acidification. [ABSTRACT FROM AUTHOR]

As an endocrine disruptor, tyrosine kinase inhibitor, and DNA methyltransferase inhibitor, genistein can interfere with breast cancer development. However, as the results of numerous studies are contradictory, it is unclear whether genistein plays a positive or negative role. Retrospective epidemiological studies have indicated that high genistein intake is related to reduced breast cancer risk, but this protective effect has not been reported in clinical trials. Additionally, rodent and cellular studies show that genistein promoted breast cancer progression. Obviously, genistein's bioactivities do not solely depend upon the dose, and simply discussing the overall effects of genistein without considering individual factors is unrealistic. The purpose of this review was to collect relevant studies (over 164) on genistein and breast cancer that were published on PubMed from 1984 to 2019 and to summarize the impact of key individual factors on the bioactivities of genistein in breast cancer prevention and treatment. Furthermore, the related potential molecular mechanisms were explored to explain the contradictions in genistein-breast cancer studies. Our results showed that the intake mode and metabolic characteristics of genistein, as well as the menopausal status, estrogen receptor expression pattern, and gene mutations of the patient, are important factors that should be included when discussing the bioactivities of genistein. A better understanding of the influence of individual factors may enable the precise prediction of personalized responses to dietary genistein exposure. Given that the current information on genistein is mostly restricted to the cellular level, more comprehensive human studies should be performed to clarify the relationship between genistein and breast cancer. [ABSTRACT FROM AUTHOR]

Aim: We sought to understand how the individual and combined effects of multiple environmental change drivers differentially influence terrestrial nitrogen (N) concentrations and N pools and whether the interactive effects of these drivers are mainly antagonistic, synergistic or additive. Location: Worldwide. Time period: Contemporary. Major taxa studied: Plants, soil, and soil microbes in terrestrial ecosystems. Methods: We synthesized data from manipulative field studies from 758 published articles to estimate the individual, combined and interactive effects of key environmental change drivers (elevated CO2, warming, N addition, phosphorus addition, increased rainfall and drought) on plant, soil, and soil microbe N concentrations and pools using meta‐analyses. We assessed the influences of moderator variables on these effects through structural equation modelling. Results: We found that (a) N concentrations and N pools were significantly affected by the individual and combined effects of multiple drivers, with N addition (either alone or in combination with another driver) showing the strongest positive effects; (b) the individual and combined effects of these drivers differed significantly between N concentrations and N pools in plants, but seldom in soils and microbes; (c) additive effects of driver pairs on N concentrations and pools were much more common than synergistic or antagonistic effects across plants, soils and microbes; and (d) environmental and experimental factors were important moderators of the individual, combined and interactive effects of these drivers on terrestrial N. Main conclusions: Our results indicate that terrestrial N concentrations and N pools, especially those of plants, can be significantly affected by the individual and combined effects of environmental change drivers, with the interactive effects of these drivers being mostly additive. Our findings are important because they contribute to the development of models to better predict how altered N availability affects ecosystem carbon cycling under future environmental changes. [ABSTRACT FROM AUTHOR]

Abstract Neonicotinoid insecticides have been used in a wide range of crops through seed treatment, soil and foliar applications and a large database exists on both their lethal and sub-lethal effects on honey bees under controlled laboratory conditions. However, colony-level studies on the effects of neonicotinoids in field studies are limited, primarily due to their complexity and the resources required. This paper reports the combined results of two large-scale colony-feeding studies, each with 6 weeks of continuous dosing of 12 colonies per treatment (24 control) to 12.5, 25, 37.5, 50 or 100 ng thiamethoxam/g sucrose solution. Exposure continued beyond dosing with residues present in stored nectar and bee-bread. The studies were conducted in an area with limited alternative forage and colonies were required to forage for pollen and additional nectar The studies provide colony-level endpoints: significant effects (reductions in bees, brood) were observed after exposure to the two highest dose rates, colony loss occurred at the highest dose rate, but colonies were able to recover (2–3 brood cycles after the end of dosing) after dosing with 50 ng thiamethoxam/g sucrose. No significant colony-level effects were observed at lower dose rates. The data reported here support the conclusions of previous colony-level crop-based field studies with thiamethoxam, in which residues in pollen and nectar were an order of magnitude below the colony-level NOEC of 37.5 ng thiamethoxam/g sucrose. The feeding study data are also compared to the outcomes of regulatory Tier 1 risk assessments conducted using guidance provided by the USA, Canada, Brazil and the EU regulatory authorities. We propose an adaptation of the European chronic adult bee risk assessment that takes into account the full dataset generated in laboratory studies while still providing an order of magnitude of safety compared with the colony feeding study NOEC. Graphical abstract Unlabelled Image Highlights • Study aimed to determine long-term impact of dosing (6 weeks) thiamethoxam (TMX). • Dosing 100 ng TMX/g feed resulted in significant colony-level adverse effects. • Significant effects occurred after dosing with 50 ng TMX/g feed, but colonies recovered within 2–3 brood cycles. • At ≤37.5 ng TMX/g feed there were no colony-level effects before or after winter. • EU risk assessment requires field studies at residues >30 fold lower than NOEC. [ABSTRACT FROM AUTHOR]

Abstract Stratum ventilation is more energy-efficient as compared with mixing ventilation for cooling applications. However, due to the short development history of stratum ventilation, few studies on its heating applications are available. The heating operation of stratum ventilation is different from the cooling operation due to the distinct airflow patterns. This study comprehensively investigates the effects of the operation parameters on heating performances of stratum ventilation, using experimentally validated Computational Fluid Dynamics (CFD) simulations. The operation parameters include controllable supply vane angle, supply airflow rate and supply air temperature, and uncontrollable outdoor weather condition. The ventilation performance indices adopt local mean age of air (LMAA), CO 2 removal efficiency (CRE), Predicted Mean Vote (PMV), vertical air temperature difference between head and ankle levels (Δ T) and energy utilization coefficient (EUC). By evaluating the individual effects of the operation parameters on the ventilation performances, the relative importance (i.e., relative sensitivity) of the operation parameters for each ventilation performance is identified. By comparing the individual effects and combined effects of the operation parameters on the ventilation performances, it is found that the variations of LMAA, CRE, PMV, Δ T and EUC caused by the combined effects can be accounted by the corresponding most important operation parameters by 86.5%, 85.6%, 78.8%, 65.7% and 70.2% respectively. Moreover, the outdoor weather condition does not significantly affect LMAA, CRE and EUC, but can transfer PMV and Δ T to discomfort level. Lastly, to facilitate heating applications of stratum ventilation, the constant-air-volume system is recommended and a simplified operation strategy is proposed. Highlights • Experiments of stratum ventilation for heating are used to validate CFD simulations. • Individual and combined effects of four operation parameters on ventilation performances are analyzed. • Relative importance of the operation parameters for each ventilation performance is identified. • Ventilation performances are mainly determined by corresponding most important operation parameters. • Control strategy is proposed to simplify heating operation of stratum ventilation. [ABSTRACT FROM AUTHOR]

Over the past two decades, social media have become a crucial and omnipresent cultural and economic phenomenon, which has seen platforms come and go and advance technologically. In this study, we explore the further development of social media regarding interactive technologies, platform development, relationships to news media, the activities of institutional and organizational users, and effects of social media on the individual and the society over the next five to ten years by conducting an international, two-stage Delphi study. Our results show that enhanced interaction on platforms, including virtual and augmented reality, somatosensory sense, and touch- and movement-based navigation are expected. AIs will interact with other social media users. Inactive user profiles will outnumber active ones. Platform providers will diversify into the WWW, e-commerce, edu-tech, fintechs, the automobile industry, and HR. They will change to a freemium business model and put more effort into combating cybercrime. Social media will become the predominant news distributor, but fake news will still be problematic. Firms will spend greater amounts of their budgets on social media advertising, and schools, politicians, and the medical sector will increase their social media engagement. Social media use will increasingly lead to individuals’ psychic issues. Society will benefit from economic growth and new jobs, increased political interest, democratic progress, and education due to social media. However, censorship and the energy consumption of platform operators might rise.

Bilinguals have been shown to perform worse than monolinguals in a variety of verbal tasks. This study investigated this bilingual verbal cost in a large-scale picture-naming study conducted in Spanish. We explored how individual characteristics of the participants and the linguistic properties of the words being spoken influence this performance cost. In particular, we focused on the contributions of lexical frequency and phonological similarity across translations. The naming performance of Spanish-Catalan bilinguals speaking in their dominant and non-dominant language was compared to that of Spanish monolinguals. Single trial naming latencies were analyzed by means of linear mixed models accounting for individual effects at the participant and item level. While decreasing lexical frequency was shown to increase naming latencies in all groups, this variable by itself did not account for the bilingual cost. In turn, our results showed that the bilingual cost disappeared when naming words with high phonological similarity across translations. In short, our results show that frequency of use can play a role in the emergence of the bilingual cost, but that phonological similarity across translations should be regarded as one of the most important variables that determine the bilingual cost in speech production. Low phonological similarity across translations yields worse performance in bilinguals and promotes the bilingual cost in naming performance. The implications of our results for the effect of phonological similarity across translations within the bilingual speech production system are discussed. [ABSTRACT FROM AUTHOR]

This paper considers the estimation of Kumbhakar et al. (J Prod Anal. doi:, ) (KLH) four random components stochastic frontier (SF) model using MLE techniques. We derive the log-likelihood function of the model using results from the closed-skew normal distribution. Our Monte Carlo analysis shows that MLE is more efficient and less biased than the multi-step KLH estimator. Moreover, we obtain closed-form expressions for the posterior expected values of the random effects, used to estimate short-run and long-run (in)efficiency as well as random-firm effects. The model is general enough to nest most of the currently used panel SF models; hence, its appropriateness can be tested. This is exemplified by analyzing empirical results from three different applications. [ABSTRACT FROM AUTHOR]

This article proposes asymptotically unbiased estimators of autocovariances and autocorrelations for panel data with both individual and time effects. We show that the conventional autocovariance estimators suffer from the bias caused by the elimination of individual and time effects. The bias related to individual effects is proportional to the long-run variance, and it related to time effects is proportional to the value of the estimated autocovariance. For the conventional autocorrelation estimators, the elimination of time effects does not cause a bias while the elimination of individual effects does. We develop methods to estimate the long-run variance and propose bias-corrected estimators based on the proposed long-run variance estimator. We also consider the half-panel jackknife estimation for bias correction. The theoretical results are given by employing double asymptotics under which both the number of observations and the length of the time series tend to infinity. Monte Carlo simulations show that the asymptotic theory provides a good approximation to the actual bias and that the proposed bias-correction methods work well. [ABSTRACT FROM AUTHOR]

Invasive zebra mussels ( Dreissena polymorpha) often colonize dragonfly larvae, especially spawling species whose survivorship to emergence as terrestrial predators is consequently reduced. Using individuals of the sprawler, Macromia illinoiensis, as their own controls, we compared the burying behavior of penultimate instar larvae before (i.e. baseline) and after their colonization by zebra mussels under ambient conditions. Individuals that took longer to bury themselves when mussel-free had a higher rate of colonization by mussels over a five-day period compared to those that buried faster. In contrast, the depth at which individuals buried when mussel-free was not predictive of subsequent colonization rate. Although mean bury time did not differ between baseline and when an individual carried one or more mussels, colonized larvae buried more shallowly than when mussel-free. Moreover, attached mussels increased the risk of subsequent colonization by zebra mussels. After naturally losing all of their attached mussels, bury time and depth of individuals did not differ from their baseline behavior, indicating that the changes in the behavior of colonized individuals were due to mussel loads and not their time in captivity. Under natural conditions, the positive feed-back between mussel attachment and increasing vulnerability to colonization helps explain how mussel loads, which are lost at molting, can accumulate quickly over the duration of the final larval stadium. Because zebra mussel attachment decreases the crypsis that that a M. illinoiensis gains from burying, the invasive mussel may also make dragonfly larvae more detectable to visual predators. [ABSTRACT FROM AUTHOR]

Performance differences between firms are generally attributed to organizational factors rather than to differences among the individuals who make up firms. As a result, little is known about the part that individual firm members play in explaining the variance in performance among firms. This paper employs a multiple membership cross-classified multilevel model to test the degree to which organizational or individual factors explain firm performance. The analysis also examines whether individual differences among middle managers or innovators best explain firm performance variation. The results indicate that variation among individuals matter far more in organizational performance than is generally assumed. Further, variation among middle managers has a particularly large impact on firm performance, much larger than that of those individuals who are assigned innovative roles. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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Plausibility of high variability in treatment effects across individuals has been recognized as an important consideration in clinical studies. Surprisingly, little attention has been given to evaluating this variability in design of clinical trials or analyses of resulting data. High variation in a treatment's efficacy or safety across individuals (referred to herein as treatment heterogeneity) may have important consequences because the optimal treatment choice for an individual may be different from that suggested by a study of average effects. We call this an individual qualitative interaction (IQI), borrowing terminology from earlier work—referring to a qualitative interaction (QI) being present when the optimal treatment varies across “groups” of individuals. At least three techniques have been proposed to investigate treatment heterogeneity: techniques to detect a QI, use of measures such as the density overlap of two outcome variables under different treatments, and use of cross-over designs to observe “individual effects.” We elucidate underlying connections among them, their limitations, and some assumptions that may be required. We do so under a potential outcomes framework that can add insights to results from usual data analyses and to study design features that improve the capability to more directly assess treatment heterogeneity. [ABSTRACT FROM AUTHOR]

Lundberg O, Fritzell J, Åberg Yngwe M, Kölegård ML. The potential power of social policy programmes: income redistribution, economic resources and health Int J Soc Welfare 2010: ••: ••–••© 2010 The Author(s), Journal compilation © 2010 Blackwell Publishing Ltd and International Journal of Social Welfare. This Supplement includes a number of articles dealing with the role of social policy schemes for public health across the life course. As a key social determinant of health, poverty and its consequences have historically been at the forefront of the public health discussion. But also in rich countries today, economic resources are likely to be important for health and survival, both on an individual and an aggregate level. This introductory article serves as a background for the more specific analyses that follow. The focus is on why income and income inequality could have an effect on individual and population health. We discuss relationships between the individual and population levels and between income and health, and some of the possible mechanisms involved. We also present arguments for why welfare state institutions may matter. [ABSTRACT FROM AUTHOR]

The article presents a study which investigates the relative influence of maternal traits, seasonal demands of pup-rearing, and foraging behavior in 27 female Antarctic fur seals at Cape Shirreff, Livingstone Island in Antarctica. The relationship between foraging and allocation is investigated through the use of time depth recorders with pup growth serving as an indicator of parental investment. Results of the study shows that while the diving behavior of female fur differs between years, trip duration is below the 10 year mean. The study also found that study year and maternal age contribute to the diving characteristics while maternal mass affects the parameters related to night dive effort.

This paper investigates the relationship between patents and research and development expenditures using new longitudinal patent data at the firm level for the U.S. manufacturing sector from 1982 to 1992. The paper also develops a new class of count panel data models based on series expansion of the distribution of individual effects. Estimation results from various distributed lag and dynamic multiplicative panel count data models show that the contemporaneous relationship between patenting and R&D expenditures continues to be strong, accounting for over 60% of the total R&D elasticity. The lag effects are higher than have previously been found for the 1970s data. [ABSTRACT FROM AUTHOR]

Understanding the manner in which changes in disturbance regimes will affect forest biodiversity is an important goal of global change research. Prevailing theories of recruitment after disturbance center on the role of pioneer species; predictions of forest biodiversity focus almost exclusively on dispersal and shade tolerance while vegetative reproduction is virtually omitted from models and serious discussions of the topic. However, the persistence of live damaged trees increases understory shade, generates fine-scale environmental heterogeneity, and moderates ecosystem responses to damage, while the sprouting of damaged trees offers a shortcut to reestablishment of the canopy. While a number of studies document snapshots of post-disturbance vegetative reproduction, we lack an understanding of the underlying demographic processes needed in order to both comprehend and predict observed patterns. In this study we quantify. the abundance, competitive ability, and interspecific variability of vegetative reproduction in 18 replicated experimental gaps in the southern Appalachians and Carolina Piedmont, USA, in order to assess the potential role of sprouting in driving gap dynamics. Annual rates of damaged adult survival, sprout initiation, growth, and mortality were monitored over four years and compared to the performance of gap-regenerating saplings. Recruitment from sprouts was found to constitute 26-87% of early gap regeneration and forms the dominant pathway of regeneration for some species. Sprouts from recently damaged trees also grow significantly faster than the saplings with which they compete. For all measured demographic rates (damaged tree survival, sprout initiation, number, growth, and survival) differences among species are large and consistent across sites, suggesting that vegetative reproduction is an important and non-neutral process in shaping community composition. Sprouting ability does not correlate strongly with other life-history trade-offs, thus sprouting potentially provides an alternate trait axis in promoting diversity. [ABSTRACT FROM AUTHOR]

Abstract: The processes underlying the positive effect exerted by woody species on other plant species can be grouped into a physical effect due to the canopy itself (mainly amelioration of temperature and light extremes), and an edaphic effect (nutrient enrichment). Both groups of effects are present in the savanna-like systems originated by Retama sphaerocarpa in the Iberian Peninsula. The consequences of these shrubs for the spatial heterogeneity induced in the herbaceous community are not well known. The herbaceous community was sampled by means of radial transects around 20 adult shrubs, from the canopy centre to the open areas among the shrubs, both northwards and southwards. Floristic composition, diversity and pasture mean height change both along the inside–outside gradient, and from north to south. As a nutrient enriched environment, the centre of the understorey showed the lowest species richness and evenness, and the highest standing crop. In contrast, the environmentally stressful open areas showed the highest number of species and evenness, and the lowest standing crop. This general effect is only partially due to nutrient availability, and is not homogeneous around the shrub, as open area conditions penetrate into the understorey driving the herbaceous community towards that of open areas. An individual shrub effect is also suggested by our results. Different conditions are thus provided by R. sphaerocarpa understoreys, favouring different subsets of species from the general pool, and therefore defining shrub canopies as sources of spatial heterogeneity in the whole savanna-like system. [Copyright &y& Elsevier]