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Conservation of forest resources is a prerequisite for sustainable development of human society, both in the context of preventing negative climate change and for economic growth. The study aims to establish or refute the co-dependence between the level of forest cover in European countries and the production of gross domestic product. The study object is the socio-economic systems of the national economies of European countries in relation to the totality of forest resources of the continent. Studying the dynamics of forest cover indicators (the share of forests in the total area of the country and forest area per capita), weighted within the internationally recognized regions of Europe, it is confirmed that the level of forest cover of European countries is gradually increasing. The analysis of forest fire area maps identifies three main groups by the level of vulnerability to forest fires: safe (Northern European countries), conditionally safe (Western European countries), and dangerous (Eastern and Southern European countries).Denmark, Finland, France, Norway, and Finland show a direct correlation between the level of forest cover of a country’s territory and gross domestic product. The results of cluster analyses based on the data from 2000, 2010, 2015, and 2020 confirm the existence of a stable cluster of European countries (34 countries) in which there is one type of relationship between the production of gross domestic product and the level of forest cover of the territory. AcknowledgmentThis study was funded by the grant support from the Philipp Schwarz Initiative of the Alexander von Humboldt Foundation.

While known to influence visual lexical processing, the semantic information we associate with words has recently been found to influence auditory lexical processing as well. The present work explored the influence of "semantic richness" in auditory lexical decision. Study 1 recreated an experiment investigating semantic richness effects in concrete nouns (Goh et al., 2016). In Study 2, we expanded the stimulus set from 442 to 8,626 items, exploring the robustness of effects observed in Study 1 against a larger data set with increased diversity in both word class and other characteristics of interest. We also utilized generalized additive mixed models to investigate potential nonlinear effects. Results indicate that semantic richness effects become more nuanced and detectable when a wider set of items belonging to different parts of speech is examined. Findings are discussed in the context of models of spoken word recognition.

The development of strategy and tactics for reforms in the energy industry involves the identification of benchmark countries whose experience can form the basis of a quantitative assessment of the main targets of the reforms. The basis for such decisions can be the results of the integrated assessment of energy reforms in the EU countries for 2010–2021. This study aims to cluster these countries according to the integral indicator and determine specific directions in which the respective country needs to make progress in moving to another cluster. Thus, based on a linear model, the Fishburn formula, and variance analysis, 10 energy development indicators were combined into a single indicator that characterizes the effectiveness of energy reforms (for example, in 2021, it was the highest in Austria (0.612), Germany (0.644), and France (0.620); the lowest – in Latvia (0.383) and Croatia (0.369)). Based on this indicator, countries were clustered using the k-means method. Four clusters were formed: representatives of the highest first (Austria, Germany, France, Spain, Sweden, and Luxembourg) are strategic benchmarks for all EU countries, and representatives of other clusters are tactical benchmarks for countries from lower clusters. The average values of all 10 indicators of energy development were calculated. Their low values are a sign that this direction should be a priority when carrying out reforms, and their quantitative estimates can be used as specific targets when setting strategic and tactical tasks (transition to a higher cluster or achieving average values in one’s cluster). AcknowledgmentThe research was funded by a Fellowship agreement for a research fellowship in the framework of the 11th funding round within the Philipp Schwartz Initiative of the Alexander von Humboldt Foundation.

Abstract Barth syndrome (BTHS) is a rare disorder caused by mutations in the TAFAZZIN gene. Previous studies from both patients and model systems have established metabolic dysregulation as a core component of BTHS pathology. In particular, features such as lactic acidosis, pyruvate dehydrogenase (PDH) deficiency, and aberrant fatty acid and glucose oxidation have been identified. However, the lack of a mechanistic understanding of what causes these conditions in the context of BTHS remains a significant knowledge gap, and this has hindered the development of effective therapeutic strategies for treating the associated metabolic problems. In the current study, we utilized tafazzin-knockout C2C12 mouse myoblasts (TAZ-KO) and cardiac and skeletal muscle tissue from tafazzin-knockout mice to identify an upstream mechanism underlying impaired PDH activity in BTHS. This mechanism centers around robust upregulation of pyruvate dehydrogenase kinase 4 (PDK4), resulting from hyperactivation of AMP-activated protein kinase (AMPK) and subsequent transcriptional upregulation by forkhead box protein O1 (FOXO1). Upregulation of PDK4 in tafazzin-deficient cells causes direct phospho-inhibition of PDH activity accompanied by increased glucose uptake and elevated intracellular glucose concentration. Collectively, our findings provide a novel mechanistic framework whereby impaired tafazzin function ultimately results in robust PDK4 upregulation, leading to impaired PDH activity and likely linked to dysregulated metabolic substrate utilization. This mechanism may underlie previously reported findings of BTHS-associated metabolic dysregulation.

Abstract Background The retail market for toddler-specific packaged foods is growing. Many of these products are ultra-processed and high in nutrients of concern for health, yet marketed in ways that may make them appear wholesome. This study aims to assess parents’ responses to claims on unhealthy, ultra-processed toddler food products and test whether removing such claims promotes more accurate product perceptions and healthier product preferences. Methods Parents of toddlers aged 12 to

The study aims to cluster countries worldwide by business practices in the agrosector to reveal trends and specifics in applying sustainable methods in agrobusiness management. The analysis covers 26 countries from the OECD database as of 2021. The Word and k-means clustering methods are based on General Services Support Estimate indicators from the OECD: share of agricultural knowledge and innovation system, share of inspection and control, share of development and maintenance of infrastructure, share of cost of public stockholding, which has a determining, statistically significant influence on the formation of clusters. The first cluster included three Asian countries; China is the leader (share of agricultural knowledge and innovation system – 6,529.7 million USD, share of inspection and control – 3177.9 million USD, share of development and maintenance of infrastructure – 12,874.7 million USD, share of cost of public stockholding – 14,668.5 million USD). The second cluster comprised six countries, with the USA as the leader (share of agricultural knowledge and innovation system – 2,908.4 million USD, share of inspection and control – 1,298.0 million USD, share of development and maintenance of infrastructure – 2,392.5 million USD). The third cluster has 17 countries, with Canada being singled out (share of inspection and control – 631.8 million USD and share of agricultural knowledge and innovation system – 683.1 million USD). The results indicate the diversity of countries’ approaches to support and develop their agrosector. Advanced Asian countries and the US invest significant resources in innovation, infrastructure development, and quality control, underscoring their commitment to food security, efficiency, and sustainability.

Abstract Intergroup bias is the tendency for people to inflate positive regard for their in-group and derogate the out-group. Across two online experiments (N = 922) this study revisits the methodological premises of research on language as a window into intergroup bias. Experiment 1 examined (i) whether the valence (positivity) of language production differs when communicating about an in- vs. out-group, and (ii) whether the extent of this bias is influenced by the positivity of input descriptors that were initially presented to participants as examples of how an in-group or out-group characterize themselves. Experiment 2 used the linear diffusion chain method to examine how biases are transmitted through cultural generations. Valence of verbal descriptions were quantified using ratings obtained from a large-scale psycholinguistic database. The findings from Experiment 1 indicated a bias towards employing positive language in describing the in-group (exhibiting in-group favoritism), particularly in cases where the input descriptors were negative. However, there was weak evidence for increased negativity aimed at the out-group (i.e., out-group derogation). The findings from Experiment 2 demonstrated that in-group positivity bias propagated across cultural generations at a higher rate than out-group derogation. The results shed light on the formation and cultural transmission of intergroup bias.

This paper introduces multi-use applications to unlock behind-the-meter flexibility by integrating grid-serving capabilities with user-oriented control strategies. We deploy a hierarchical flexibility coordination process in a co-simulation research environment and propose a control strategy prioritizing self-consumption optimization with a secondary focus on grid-serving applications. This approach enhances the viability of behind-the-meter technologies, particularly benefiting battery energy storage systems with high investment costs. It also facilitates active grid operation amid the growing presence of distributed energy resources. The research’s key contribution lies in designing an information architecture to efficiently utilize behind-the-meter flexibility for grid-serving processes. The paper demonstrates the feasibility of a multi-use operation, combining user-oriented optimization and grid-serving flexibility provision for local grid congestion management. The implemented control algorithm in a home energy management system achieves grid-serving objectives while maintaining behind-the-meter asset performance. Co-simulation results show that in less than 2.5% of simulated time steps, transformer utilization exceeds operational limits in both scenarios, indicating the viability of multi-use operation for leveraging new value streams and managing grid congestion simultaneously.

Abstract The type VI secretion system (T6SS) of Gram-negative bacteria inhibits competitor cells through contact-dependent translocation of toxic effector proteins. In Proteobacteria, the T6SS is anchored to the cell envelope through a megadalton-sized membrane complex (MC). However, the genomes of Bacteroidota with T6SSs appear to lack genes encoding homologs of canonical MC components. Here, we identify five genes in Bacteroides fragilis (tssNQOPR) that are essential for T6SS function and encode a Bacteroidota-specific MC. We purify this complex, reveal its dimensions using electron microscopy, and identify a protein-protein interaction network underlying the assembly of the MC including the stoichiometry of the five TssNQOPR components. Protein TssN mediates the connection between the Bacteroidota MC and the conserved baseplate. Although MC gene content and organization varies across the phylum Bacteroidota, no MC homologs are detected outside of T6SS loci, suggesting ancient co-option and functional convergence with the non-homologous MC of Pseudomonadota.

During the COVID-19 pandemic, the term “behavioural fatigue” became the centre of policy debates in Great Britain. These debates involved deciding when to go into lockdown and whether behavioural interventions could be effective. Behavioural interventions can only succeed where people’s Capabilities, Opportunities, and Motivations to perform target behaviours are supported. Our retrospective data analyses examine the relationships between people’s Capabilities, Opportunities, Motivations, and Behaviours, i.e., adherence to lockdown guidelines. Our cross-sectional analyses include 17,962 unique participants in Great Britain who completed a survey over the initial 30 days of the first lockdown (April 2020). We examine trends in responses to each scale and then the relationships between the scales using Granger’s causality test with tests for stationarity and cointegration. A mixture of increasing and decreasing trends was identified for Capabilities and Opportunities. Decreasing trends were identified for Motivation and Behaviour. Granger’s causality tests found that Capability forecasts Opportunity and Behaviour and that Motivation forecasts Opportunity. The discussion reiterates that to realise and maintain Behaviour changes, policies surrounding people’s Capabilities, Opportunities, and Motivations must continue to support target behaviours.

Ribwort plantain (Plantago lanceolata L.) is expected to open up new crop cultivation perspectives in arable farming in order to significantly reduce nitrogen losses through leaching, N2O emissions and to increase resilience under drought conditions. Therefore, this study investigated the properties of the roots as an alternative to grasses for forage production under drought conditions. Ten genotypes of ribwort plantain were compared under field conditions in northern Switzerland, focusing on the characteristics of the root system and the aucubin content in the leaves and roots. Aucubin, known for inhibiting the nitrification process in the soil, varied according to genotype and season. All tested genotypes showed higher aucubin content in leaves than in roots, which may indicate the greater importance of leaves in reducing soil nitrification. Dry matter yield and for the first time root characteristics, such as root length density (RLD) and specific root length (SRL), were evaluated at two different soil depths, and at different distances from the plants. The results showed that ribwort is well adapted to acquire water and nutrients in terms of rooting in topsoil. In addition, a second field experiment conducted in eastern Germany (Saxony) confirmed the plant’s ability to root deeply after one year of cultivation, reaching depths of up to even 1.88 m. The obtained results indicate the high capacity of ribwort plantain to take up water and nutrients also from deeper soil layers. To reduce N2O emissions through the cultivation of ribwort plantain, the choice of genotype seems to be of great importance due to varying aucubin contents.

Hybrid positron emission tomography/magnetic resonance imaging (PET/MR) opens new possibilities in multimodal multiparametric (m2p) image analyses. But even the simultaneous acquisition of positron emission tomography (PET) and magnetic resonance imaging (MRI) does not guarantee perfect voxel-by-voxel co-registration due to organs and distortions, especially in diffusion-weighted imaging (DWI), which would be, however, crucial to derive biologically meaningful information. Thus, our aim was to optimize fusion and voxel-wise analyses of DWI and standardized uptake values (SUVs) using a novel software for m2p analyses. Using research software, we evaluated the precision of image co-registration and voxel-wise analyses including the rigid and elastic 3D registration of DWI and [18F]-Fluorodeoxyglucose (FDG)-PET from an integrated PET/MR system. We analyzed DWI distortions with a volume-preserving constraint in three different 3D-printed phantom models. A total of 12 PET/MR-DWI clinical datasets (bronchial carcinoma patients) were referenced to the T1 weighted-DIXON sequence. Back mapping of scatterplots and voxel-wise registration was performed and compared to the non-optimized datasets. Fusion was rated using a 5-point Likert scale. Using the 3D-elastic co-registration algorithm, geometric shapes were restored in phantom measurements; the measured ADC values did not change significantly (F = 1.12, p = 0.34). Reader assessment showed a significant improvement in fusion precision for DWI and morphological landmarks in the 3D-registered datasets (4.3 ± 0.2 vs. 4.6 ± 0.2, p = 0.009). Most pronounced differences were noted for the chest wall (p = 0.006), tumor (p = 0.007), and skin contour (p = 0.014). Co-registration increased the number of plausible ADC and SUV combinations by 25%. The volume-preserving elastic 3D registration of DWI significantly improved the precision of fusion with anatomical sequences in phantom and clinical datasets. The research software allowed for a voxel-wise analysis and visualization of [18F]FDG-PET/MR data as a “combined diffusivity–metabolic index” (cDMI). The clinical value of the optimized PET/MR biomarker can thus be tested in future PET/MR studies.

Despite numerous research findings that support play's positive impact on children's learning, pressure to pass high-stakes tests later in the elementary years has prompted a decrease in the amount of time for kindergarten play. While play proponents work to prioritize play in kindergarten, there is a dilemma. How can educators respond to the academic demands placed on today's kindergartners without compromising essential play practices? There is limited research on how to build kindergarten teachers' capacity to organize and facilitate play in ways that are both developmentally appropriate and effective at accelerating academic outcomes. This investigation reports findings from interviews with seven kindergarten teachers recommended for a play leadership cohort by administrators because of their instructional and leadership skills. Participants engaged in a two-year series of connected professional learning experiences influencing them to expand time and enhance quality of play in their classrooms. Findings from this study extend existing knowledge outlining four dimensions of effective professional learning: cognitive engagement, emotional engagement, social engagement with students, and social engagement with colleagues. This study sheds light on how these dimensions of professional learning are effective in developing kindergarten teachers' capacity for implementing guided play practices. Implications and recommendations for future research are included.

This article describes a randomized controlled trial to evaluate the effectiveness of intervention tools designed to help people save more or spend less money by enhancing their capabilities, motivations, and opportunities. The participants included 177 students from an English University who were randomly allocated to either the Control, Savings-Tool, or Savings+Habit-Tools group. Participants provided with the intervention tool(s) for 4 weeks were more likely to experience improvements in both their financial satisfaction and subjective perceptions than those in the Control group not asked to use either tool. The tools did not significantly affect financial behaviors or objective financial wellness. The discussion examines limitations of the study and discusses avenues for future research such as including a longer follow-up period.

IntroductionDecades of research in population health have established depression as a likely precursor to Alzheimer's disease. A combination of causal estimates and machine learning methods in artificial intelligence could identify internal and external mediating mechanisms that contribute to the likelihood of progression from depression to Alzheimer's disease.MethodsWe developed an integrated predictive model, combining the marginal structural model and an artificial intelligence predictive model, distinguishing between patients likely to progress from depressive states to Alzheimer's disease better than each model alone.ResultsThe integrated predictive model achieved substantial clinical relevance when using the area under the curve measure. It performed better than the traditional statistical method or a single artificial intelligence method alone.DiscussionThe integrated predictive model could form a part of a clinical screening tool that identifies patients who are likely to progress from depression to Alzheimer's disease for early behavioral health interventions. Given the high costs of treating Alzheimer's disease, our model could serve as a cost-effective intervention for the early detection of depression before it progresses to Alzheimer's disease.

The building and construction sector is responsible for a large share of carbon emissions resulting in the need to reduce them to mitigate climate change. Timber construction methods promise to lower emissions combined with biogenic carbon storage in the built environment. While there are several studies comparing the emissions of mineral-based and timber-based buildings, a consistent comparison of different timber-based building assemblies is still missing. This study compares carbon emissions from material production and carbon storage capabilities of four timber-based and two brick and reinforced concrete building assemblies. These assemblies were designed for a residential multi-storey building in Berlin, Germany. To compare and rank the carbon impacts of these assemblies we introduce a carbon storage-to-emission ratio. The calculations were performed using a Carbon Cycle Assessment Model implementation in Python. The results indicate an average reduction in carbon emissions of timber-based building assemblies by 32.6% to “Brick” and 40.4% to “Reinforced Concrete”, respectively. Across the timber-based building assemblies, the carbon emissions range between 85 t and 115 t, leading to an average of 105 t per building. Pronounced differences were observed in carbon storage, with the “Dowel Laminated Timber” building assembly storing more than three times the amount of carbon compared to “Light Weight Timber” assembly. To further reduce emissions from buildings and the construction sector and potentially enhance urban carbon storage, “Glue Laminated Timber” and “Dowel Laminated Timber” building assemblies were identified as the most promising.

Climate warming and drought may alter the progression of sugar accumulation by the grape berry, and contribute to pre-harvest berry shrivel and cell vitality loss which were hypothesised to be associated with solute accumulation cessation and energy status in the berries. To explore the relationship between energy and cultivar-dependent berry cell death, we characterised the variations of pericarp constituents and energy status across five time points, five ripening phases, and three cultivars with various levels of berry shrivel and cell death. Grape berries of Shiraz, Chardonnay and Flame Seedless at the Eichorn-Lorenz stages 33 to 39 were sampled at 5:00, 9:00, 13:00, 17:00 and 21:00 on each sampling day, which were used in the analysis of water percentage, adenosine triphosphate (ATP), ethanol, sugar, L-malic acid, as well as elements with vascular mobility, including potassium (K) and sodium (Na). Shiraz and Chardonnay ceased accumulating sugar and phloem mobile elements during the later ripening phase, while Flame Seedless did not undergo water loss or cease to accumulate solutes in pericarps. Shiraz berry ripening was distinguished by greater pericarp water loss, ATP reduction, increased ion disorder susceptibility as indicated by a lower K/Na ratio, and higher ethanol concentration in the later ripening phase. The Chardonnay pericarp contained the highest ATP concentration and K/Na ratio among the three cultivars. The Flame Seedless pericarp maintained a low but stable K/Na ratio throughout berry ripening. Berry ripening phase impacted the diurnal variations of pericarp water percentage and ATP concentration. The results indicated that energy regulation and ionic homeostasis may be associated with cultivar-dependent grape pericarp hydration, solute accumulation and cell vitality during berry ripening.

Abstract Objectives The present study aimed to identify factors related to knowledge and attitudes that influence primary care clinicians' decision‐making when diagnosing, treating, and managing suspected urinary tract infections (UTIs) in women. Understanding the factors that influence clinicians' decision‐making is important for maximising health outcomes in women and reducing suboptimal use of antibiotics and antimicrobial resistance. Design A qualitative think‐aloud study design was employed. Methods Semi‐structured qualitative interviews were conducted with primary care clinicians in England over Microsoft Teams. Interviews were transcribed and coded in two ways. First, clinicians' responses for each scenario were coded as either following (optimal), not following evidence‐based national guideline or incorrectly citing certain diagnosis, treatment, and management procedures (suboptimal). Second, the knowledge and attitude factors that influenced decision‐making were coded according to an empirically informed umbrella framework. Clinicians external to the study team reviewed the findings to promote their trustworthiness and utility. Results Ten clinicians (six female) took part. Clinicians prescribing decisions were mostly influenced by knowledge rather than attitude factors. Despite clinicians expressing high awareness of relevant evidence‐based guidelines (a knowledge factor) and high confidence (an attitude factor), more than half of their decisions (60%) were suboptimal in some way thereby impacting women's health. Most clinicians relied on their experiential knowledge rather than using evidence‐based guidelines. Our results suggest that knowledge could impede adherence, for example, where local guidelines conflict with national guidelines of when to perform a urine dipstick test. Conclusions Suboptimal prescribing decisions could result from a combination of different knowledge and attitude factors leading to negative outcomes in women's health such as inappropriate treatment of asymptomatic bacteriuria in women over 65 years old. To optimise antibiotic prescribing in women, policy‐level interventions could increase concordance across local and national guidelines, or more tailored individual‐level interventions could help clinicians recognise where their experiential knowledge causes deviations from evidence‐based guidelines when diagnosing, treating and managing UTIs.