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Values are the trans-situational goals guiding human attitudes and behavior (Schwartz, 1992). As early socialization agents, teachers have a responsibility to promote democratic values of citizenship to create an inclusive, fair, and sustainable society, necessary for individual and collective well-being (OECD, 2019). By facilitating social and cognitive development through social interactions, the school setting helps spark curiosity, leading to reflection and adaptation. Across the curriculum, teachers use strategies like imitation, modelling, priming, and discussion to help children make sense of the world (Makarova et al., 2024; Oeschger et al., 2022). Yet little empirical evidence exists to support how teachers achieve this. The present study gives voice to educators through the personal experiences of ten UK primary school teachers. Semi-structured interviews were conducted, lasting between 50 and 90 min. Data was analyzed in two stages: First, a deductive structuring content analysis identified how values of self-transcendence versus self-enhancement and openness to change versus conservation, as defined in Schwartz's (1992) model, were reflected in the interview data. Second, an inductive thematic analysis yielded the following themes: mechanisms of value transmission; implicit vs explicit instruction of values; values that are most difficult to teach; value transmission through taught lessons; the role of collective worship and cultural days; opportunities for value transmission in the wider school environment; and the role that a school culture and ethos play in the transmission of values. This study supports the view that values are promoted through a variety of methods and across all areas of the school environment.

Values education within the school context is, among other elements, shaped by a value-related school climate as well as teachers' value-related educational goals. This longitudinal study investigated the interplay between these two elements over fifteen months, starting in March 2021, and including four points of measurement (t1 - t4). The sample consisted of 118 primary school teachers (years 1 and 2) from primary schools in Switzerland. Teachers' value-related educational goals were measured with the "Portrait Values Questionnaire," and teachers' perception of their school climate was measured with the "12-Item School Climate Measure Scale." "Random Intercept Cross-Lagged Panel Models" along with "Multiple Imputation" for missing data were used to investigate the reciprocal relationships along the four dimensions of value-related educational goals represented by Schwartz's "Higher-Order Value Types: Openness to Change, Conservation, Self-Enhancement, and Self-Transcendence" and their corresponding dimensions of a perceived value-related school climate of "Innovation, Stability, Performance, and Support." For the dimensions "Innovation and Openness to Change," the analyses revealed that the perceived value-related school climate of Innovation predicted teachers' value-related educational goals of "Openness to Change" significantly from t1 to t2, while an effect in the opposite direction from t2 to t3 and from t3 to t4 was found. For the dimension "Stability and Conservation," the analyses revealed that the perceived value-related school climate of "Stability" predicted teachers' value-related educational goals of "Conservation" from t3 to t4. These findings are discussed in light of the dynamic processes of values education within the school environment as well as in the context of environmental and societal developments.

The possibility of inducing value change has attracted interest among scholars and practitioners in developmental and social psychology. This study proposes a new web-based intervention aimed at enhancing the importance adolescents ascribe to social-focused values (i.e., self-transcendence and conservation), which was implemented and evaluated in the context of online schooling during the COVID-19 pandemic. Social-focused values primarily regulate how one relates to others and preserve cooperative relations. These values were found to predict positive outcomes, such as adolescents' well-being, school performance, prosocial behavior, and, most recently, COVID-19 preventive behaviors. The intervention was carried out with a group of 140 high school students (Age: M = 16.53, SD = 0.95) living in Italy during the pandemic. The intervention group (N = 84) completed four tasks, which were based on the value-changing mechanisms of priming, consistency maintenance (raising awareness and knowledge of prosociality), or direct persuasion (trying to convince another person to act prosocially). The intervention significantly increased the importance of conservation values (i.e., tradition, conformity, security) but not of self-transcendence values (i.e., universalism, benevolence) in the intervention group in comparison to the control group (N = 56). This result reflects the reality during the pandemic, where prosociality was more easily expressed through behaviors consistent with conservation values instead of self-transcendence values, which emphasize (physical) proximity to others. The effectiveness of the intervention was further supported by a qualitative analysis of adolescents' writings while completing the tasks. Limitations of the study, future research developments, and practical implications for values education in secondary schools are discussed.

This White Paper presents an overview of the current status and future perspective of QCD research, based on the community inputs and scientific conclusions from the 2022 Hot and Cold QCD Town Meeting. We present the progress made in the last decade toward a deep understanding of both the fundamental structure of the sub-atomic matter of nucleon and nucleus in cold QCD, and the hot QCD matter in heavy ion collisions. We identify key questions of QCD research and plausible paths to obtaining answers to those questions in the near future, hence defining priorities of our research over the coming decades.

Abstract Background Sustainable agriculture increasingly emphasizes the importance of microbial communities in influencing plant health and productivity. In viticulture, understanding the impact of management practices on fungal communities is critical, given their role in disease dynamics, grape and wine quality. This study investigates the effects of integrated, organic, and biodynamic management practices on the diversity and function of fungal communities in a vineyard located in Geisenheim, Germany, focusing on above-ground parts such as bark, leaves, and grapes. Results Our findings indicate that while overall fungal species richness did not significantly differ among management systems across various compartments, the composition of these communities was distinctly influenced by the type of management system. In particular, leaf and grape compartments showed notable variations in fungal community structure between integrated and organic/biodynamic management. No differences were observed between organic and biodynamic management. Integrated management demonstrated a significantly higher abundance of mycoparasites in comparison to organic and biodynamic management, primarily attributed to the increased presence of Sporobolomyces roseus, Sporobolomyces ellipsoideus and Rhodotorula glutinis. Conclusions The findings highlight the importance of management practices in shaping fungal community composition and function in vineyards. Although overall species richness remained unaffected, community composition and functional diversity varied, highlighting the potential for strategic microbiome management to enhance vineyard sustainability and plant health.

Abstract In certain kinematic and particle mass configurations, triangle singularities may lead to line-shapes which mimic the effects of resonances. This well-known effect is scrutinized here in the presence of final-state rescattering. The goal is achieved first by utilizing general arguments provided by Landau equations, and second by applying a modern scattering formalism with explicit two- and three-body unitarity.

Abstract This paper introduces three novel approaches to size geothermal energy piles in a MILP, offering fresh perspectives and potential solutions. The research overlooks MILP models that incorporate the sizing of a geothermal borefield. Therefore, this paper presents a new model utilizing a g-function model to regulate the power limits. Geothermal energy is an essential renewable source, particularly for heating and cooling. Complex energy systems, with their diverse sources of heating and cooling and intricate interactions, are crucial for a climate-neutral energy system. This work significantly contributes to the integration of geothermal energy as a vital energy source into the modelling of such complex systems. Borehole heat exchangers help generate heat in low-temperature energy systems. However, optimizing these exchangers using mixed-integer-linear programming (MILP), which only allows for linear equations, is complex. The current research only uses R-C, reservoir, or g-function models for pre-sized borefields. As a result, borehole heat exchangers are often represented by linear factors such as 50 W/m for extraction or injection limits. A breakthrough in the accuracy of borehole heat exchanger sizing has been achieved with the development of a new model, which has been rigorously compared to two simpler models. The geothermal system was configured for three energy systems with varying ground and bore field parameters. The results were then compared with existing geothermal system tools. The new model provides more accurate depth sizing with an error of less than 5 % compared to simpler models with an error higher than 50 %, although it requires more calculation time. The new model can lead to more accurate borefield sizing in MILP applications to optimize energy systems. This new model is especially beneficial for large-scale projects that are highly dependent on borefield size.

Abstract There is growing interest in intercropping as a practice to increase productivity per unit area and ecosystem functioning in agricultural systems. Relay intercropping with soy and winter wheat may benefit soil health due to increased diversity and longer undisturbed soil cover, yet this remains largely unstudied. Using a field experiment in Eastern Germany, we studied the temporal dynamics of chemical, biological, and physical indicators of soil health in the topsoil over a year of cultivation to detect early effects of soy-wheat relay intercropping compared to sole cropping. Indicators included microbial abundance, permanganate-oxidizable carbon, carbon fractions, pH, and water infiltration. Relay intercropping showed no unique soil health benefits compared to sole cropping, likely affected by drought that stressed intercropped soy. Relay intercropping did, however, maintain several properties of both sole crops including an increased MAOM C:N ratio and higher soil water infiltration. The MAOM C:N ratio increased by 4.2 and 6.2% in intercropping and sole soy and decreased by 5% in sole wheat. Average near-saturated soil water infiltration rates were 12.6, 14.9, and 6.0 cm hr−1 for intercropping, sole wheat, and sole soy, respectively. Cropping system did not consistently affect other indicators but we found temporal patterns of these indicators, showing their sensitivity to external changes.

The structures of seven gold(III) halide derivatives of general formula LAuX3 (L = methylpyridines or dimethylpyridines, X = Cl or Br) are presented: trichlorido(2-methylpyridine)gold(III), [AuCl3(C6H7N)], 1 (as two polymorphs 1a and 1b); tribromido(2-methylpyridine)gold(III), [AuBr3(C6H7N)], 2; tribromido(3-methylpyridine)gold(III), [AuBr3(C6H7N)], 3; tribromido(2,4-dimethylpyridine)gold(III), [AuBr3(C7H9N)], 4; trichlorido(3,5-dimethylpyridine)gold(III), [AuCl3(C7H9N)], 5; tribromido(3,5-dimethylpyridine)gold(III), [AuBr3(C7H9N)], 6, and trichlorido(2,6-dimethylpyridine)gold(III), [AuCl3(C7H9N)], 7. Additionally, the structure of 8, the 1:1 adduct of 2 and 6, [AuBr3(C6H7N)]·[AuBr3(C7H9N)], is included. All the structures crystallize solvent-free, and all have Z′ = 1 except for 5 and 7, which display crystallographic twofold rotation symmetry, and 4, which has Z′ = 2. 1a and 2 are isotypic. The coordination geometry at the gold(III) atoms is, as expected, square-planar. Four of the crystals (1a, 1b, 2 and 8) were non-merohedral twins, and these structures were refined using the ‘HKLF 5’ method. The largest interplanar angles between the pyridine ring and the coordination plane are observed for those structures with a 2-methyl substituent of the pyridine ring. The Au—N bonds are consistently longer trans to Br (average 2.059 Å) than trans to Cl (average 2.036 Å). In the crystal packing, a frequent feature is the offset-stacked and approximately rectangular dimeric moiety (Au—X)2, with antiparallel Au—X bonds linked by Au...X contacts at the vacant positions axial to the coordination plane. The dimers are connected by further secondary interactions (Au...X or X...X contacts, `weak' C—H...X hydrogen bonds) to form chain, double chain (`ladder') or layer structures, and in several cases linked again in the third dimension. Only 1b and 7 contain no offset dimers; these structures instead involve C—H...Cl hydrogen bonds combined with Cl...Cl contacts (1b) or Cl...π contacts (7). The packing patterns of seven further complexes LAuX3 involving simple pyridines (taken from the Cambridge Structural Database) are compared with those of 1–8.

Abstract Background Propionate is a food preservative and platform chemical, but no biological process competes with current petrochemical production routes yet. Although propionate production has been described for gut bacteria of the class Bacteroidia, which also carry great capacity for the degradation of plant polymers, knowledge on propionate yields and productivities across species is scarce. This study aims to compare propionate production from glucose within Bacteroidia and characterize good propionate producers among this group. Results We collected published information on propionate producing Bacteroidia, and selected ten species to be further examined. These species were grown under defined conditions to compare their product formation. While propionate, acetate, succinate, lactate and formate were produced, the product ratios varied greatly among the species. The two species with highest propionate yield, B. propionicifaciens (0.39 gpro/ggluc) and B. graminisolvens (0.25 gpro/ggluc), were further examined. Product formation and growth behavior differed significantly during CO2-limited growth and in resting cells experiments, as only B. graminisolvens depended on external-added NaHCO3, while their genome sequences only revealed few differences in the major catabolic pathways. Carbon mass and electron balances in experiments with resting cells were closed under the assumption that the oxidative pentose pathway was utilized for glucose oxidation next to glycolysis in B. graminisolvens. Finally, during pH-controlled fed-batch cultivation B. propionicifaciens and B. graminisolvens grew up to cell densities (OD600) of 8.1 and 9.8, and produced 119 mM and 33 mM of propionate from 130 and 105 mM glucose, respectively. A significant production of other acids, particularly lactate (25 mM), was observed in B. graminisolvens only. Conclusions We obtained the first broad overview and comparison of propionate production in Bacteroidia strains. A closer look at two species with comparably high propionate yields, showed significant differences in their physiology. Further studies may reveal the molecular basis for high propionate yields in Bacteroidia, paving the road towards their biotechnological application for conversion of biomass-derived sugars to propionate.

Bis(2-methylpyridine)gold(I) dibromidoaurate(I), [Au(C6H7N)2][AuBr2], (1), crystallizes in space group C2/c with Z = 4. Both gold atoms lie on twofold axes and are connected by an aurophilic contact. A second aurophilic contact leads to infinite chains of alternating cations and anions parallel to the b axis, and the residues are further connected by a short H...Au contact and a borderline Br...Br contact. Bis(3-methylpyridine)gold(I) dibromidoaurate(I), [Au(C6H7N)2][AuBr2], (2), crystallizes in space group C2/m with Z = 2. Both gold atoms lie on special positions with symmetry 2/m and are connected by an aurophilic contact; all other atoms except for one methyl hydrogen lie in mirror planes. The extended structure is closely analogous to that of 1, although the structures are formally not isotypic. Bis(3,5-dimethylpyridine)gold(I) dichloridoaurate(I), [Au(C7H9N)2][AuCl2], (3) crystallizes in space group P\overline{1} with Z = 2. The cation lies on a general position, and there are two independent anions in which the gold atoms lie on inversion centres. The cation and one anion associate via three short H...Cl contacts to form a ribbon structure parallel to the b axis; aurophilic contacts link adjacent ribbons. Bis(3,5-dimethylpyridine)gold(I) dibromidoaurate(I), [Au(C7H9N)2][AuBr2], (4) is isotypic to 3. Attempts to make similar compounds involving 2-bromopyridine led instead to 2-bromopyridinium dibromidoaurate(I)–2-bromopyridine (1/1), (C5H5BrN)[AuBr2]·C5H4BrN, (5), which crystallizes in space group P\overline{1} with Z = 2; all atoms lie on general positions. The 2-bromopyridinium cation is linked to the 2-bromopyridine molecule by an N—H...N hydrogen bond. Two formula units aggregate to form inversion-symmetric dimers involving Br...Br, Au...Br and H...Br contacts.

Abstract Parkinson’s disease is increasingly prevalent. It progresses from the pre-motor stage (characterised by non-motor symptoms like REM sleep behaviour disorder), to the disabling motor stage. We need objective biomarkers for early/pre-motor disease stages to be able to intervene and slow the underlying neurodegenerative process. Here, we validate a targeted multiplexed mass spectrometry assay for blood samples from recently diagnosed motor Parkinson’s patients (n = 99), pre-motor individuals with isolated REM sleep behaviour disorder (two cohorts: n = 18 and n = 54 longitudinally), and healthy controls (n = 36). Our machine-learning model accurately identifies all Parkinson patients and classifies 79% of the pre-motor individuals up to 7 years before motor onset by analysing the expression of eight proteins—Granulin precursor, Mannan-binding-lectin-serine-peptidase-2, Endoplasmatic-reticulum-chaperone-BiP, Prostaglaindin-H2-D-isomaerase, Interceullular-adhesion-molecule-1, Complement C3, Dickkopf-WNT-signalling pathway-inhibitor-3, and Plasma-protease-C1-inhibitor. Many of these biomarkers correlate with symptom severity. This specific blood panel indicates molecular events in early stages and could help identify at-risk participants for clinical trials aimed at slowing/preventing motor Parkinson’s disease.

Abstract Background Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf area or biomass. A prerequisite for realistic and sharp crop image generation is the integration of multiple growth-influencing conditions in a model, such as an image of an initial growth stage, the associated growth time, and further information about the field treatment. While image-based models provide more flexibility for crop growth modeling than process-based models, there is still a significant research gap in the comprehensive integration of various growth-influencing conditions. Further exploration and investigation are needed to address this gap. Methods We present a two-stage framework consisting first of an image generation model and second of a growth estimation model, independently trained. The image generation model is a conditional Wasserstein generative adversarial network (CWGAN). In the generator of this model, conditional batch normalization (CBN) is used to integrate conditions of different types along with the input image. This allows the model to generate time-varying artificial images dependent on multiple influencing factors. These images are used by the second part of the framework for plant phenotyping by deriving plant-specific traits and comparing them with those of non-artificial (real) reference images. In addition, image quality is evaluated using multi-scale structural similarity (MS-SSIM), learned perceptual image patch similarity (LPIPS), and Fréchet inception distance (FID). During inference, the framework allows image generation for any combination of conditions used in training; we call this generation data-driven crop growth simulation. Results Experiments are performed on three datasets of different complexity. These datasets include the laboratory plant Arabidopsis thaliana (Arabidopsis) and crops grown under real field conditions, namely cauliflower (GrowliFlower) and crop mixtures consisting of faba bean and spring wheat (MixedCrop). In all cases, the framework allows realistic, sharp image generations with a slight loss of quality from short-term to long-term predictions. For MixedCrop grown under varying treatments (different cultivars, sowing densities), the results show that adding these treatment information increases the generation quality and phenotyping accuracy measured by the estimated biomass. Simulations of varying growth-influencing conditions performed with the trained framework provide valuable insights into how such factors relate to crop appearances, which is particularly useful in complex, less explored crop mixture systems. Further results show that adding process-based simulated biomass as a condition increases the accuracy of the derived phenotypic traits from the predicted images. This demonstrates the potential of our framework to serve as an interface between a data-driven and a process-based crop growth model. Conclusion The realistic generation and simulation of future plant appearances is adequately feasible by multi-conditional CWGAN. The presented framework complements process-based models and overcomes their limitations, such as the reliance on assumptions and the low exact field-localization specificity, by realistic visualizations of the spatial crop development that directly lead to a high explainability of the model predictions.