ConspectusAccurate equilibrium geometries are fundamental to predictive spectroscopy, reliable thermochemistry, and rational molecular design. Yet achieving high accuracy beyond small molecules remains a formidable challenge. High-level wave function methods, while exceptionally accurate, are computationally prohibitive for systems containing dozens of atoms. Density functional approaches, though efficient, often lack consistent reliability across diverse chemical environments. Though reduced-scaling strategies have enabled precise energy calculations for large systems, equivalent progress in the determination of equilibrium structures has been slower, leaving a persistent gap between the predictive accuracy and computational feasibility.This Account presents an integrated framework that tries to bridge this gap by combining composite quantum-chemical methods, data-driven corrections and fragment-based modeling. At its core lie explicitly correlated composite schemes capable of delivering mÅ/mrad accuracy (usually referred to as spectroscopic accuracy) for the geometrical parameters of molecules with up to about 20 atoms. These methods underpin the construction of a benchmark-quality geometry library (LCB25), comprising nearly 400 fragments encompassing all major functional groups and ring systems relevant to chemical, biological and pharmaceutical applications.Building on this reference, systematic bond-based corrections derived from LCB25 transfer spectroscopic-level accuracy to more affordable double-hybrid and hybrid functionals. Linear regressions suffice for double-hybrid models, while machine-learning Δ-corrections extend the same accuracy to hybrid functionals. Together, these refinements lead to geometries of near-spectroscopic accuracy for medium and large molecules (50-100 atoms) at a fraction of the cost of high-level composite methods. For larger architectures, the Nano-LEGO platform automates the assembly of accurate molecular geometries from preoptimized fragments, preserving the local structural fidelity within complex frameworks.Within this modular and hierarchical approach, continuous chemically meaningful descriptors known as synthons serve as the common language linking fragment-based modeling, data-driven corrections, and machine-learning predictions. This representation facilitates the transfer of local structural information across chemical families and supports the exploration of vast regions of chemical space with controlled accuracy.The same principles extend naturally to the design of functional and sustainable materials. Spectroscopically accurate yet affordable structural predictions are instrumental in the rational development of organocatalysts, molecular components for optoelectronic devices and supramolecular frameworks for applications aligned with the goals of circular economy.These methodological advances are complemented by efficient optimization algorithms, vibrational corrections based on second-order vibrational perturbation theory, and fully interoperable workflows that ensure scalability and robustness. Collectively, they establish a hierarchical data-enriched ecosystem delivering accurate, transferable, and cost-effective molecular geometries. Applications range from atmospheric and astrochemical intermediates to biomolecules, pharmaceuticals, and sustainable molecular materials, paving the way for predictive spectroscopy and structure-based design. All components of this framework are openly available through web platforms and GitHub, promoting transparency, accessibility, and community development.
Acute Achilles tendon ruptures (AATRs) are devastating injuries for athletes, yet outcomes in elite rugby union players remain poorly characterized. Elite rugby union players who sustain AATRs will demonstrate significantly reduced performance metrics postinjury compared with preinjury levels. Retrospective case series. Level 4. A retrospective review of elite rugby union players who sustained Achilles ruptures from 2013 to 2025 was performed. Data, including player demographics, injury characteristics, and performance metrics, were collected from rugby databases and media reports. A Wilcoxon signed rank test was used to compare pre- and postrupture performance metrics. Effect size was calculated using matched-pairs rank-biserial correlation, with median paired differences and 95% CIs. A P value <0.05 was determined as statistically significant. A total of 52 elite rugby union players with a median age of 28 years were identified. Overall, 80.8% of players returned to play (RTP) at a median time of 8.5 months. In the season immediately after injury, games played, tries, tries per game, points, and points per game were all significantly lower than preinjury values (all P ≤ 0.003; r = -0.49 to -0.61). Across all seasons, games per season, tries per season, tries per game, points per season, and points per game were significantly lower after injury (all P < 0.001; r = -0.47 to -0.72). AATRs in elite rugby union players were associated with significant declines in performance metrics in both the immediate postinjury season and across subsequent seasons. These findings highlight the substantial performance impact of AATRs and support the need for improved position-specific prevention strategies and targeted postinjury rehabilitation protocols. Clinicians can use these findings to counsel rugby athletes and teams on prognosis, treatment decisions, and realistic performance expectations after AATRs.
Many countries use geographical funding formulae to distribute public funds for health care to local planning areas in proportion to need. In England, these aim to distribute resources in proportion to all healthcare needs regardless as to whether these are currently met or unmet. The National Health Service also has an additional objective to allocate resources to reduce health inequalities (i.e. differences in health between socioeconomic groups). Adjusting for unmet needs could help achieve this second objective, if a greater proportion of needs are unmet in disadvantaged socioeconomic groups with poorer health compared to more advantaged socioeconomic groups. Alternatively, if there are greater unmet needs for relatively expensive conditions that tend to affect older age groups (e.g. cancer), this could lead to a greater proportion of needs being unmet in more advantaged socioeconomic groups, who will tend to be older due to greater life expectancy. Adjusting for unmet needs would then lead to allocation of a greater share of resources to these more affluent populations with better health, potentially increasing health inequalities. It is, however, unclear how met and unmet healthcare needs should be measured in these formulae and how better accounting for unmet needs influences health inequalities. We outline a framework for estimating the relative need in geographical healthcare resource allocation and show how the distribution of needed resources between local health planning areas in England changes when accounting for unmet needs due to underdiagnosis for 11 long-term conditions. We derive a synthetic data set for all people aged ≥ 30 years in England, in 2018, including age, sex, socioeconomic deprivation, region, local health planning area and whether people have diagnosed or undiagnosed long-term conditions. We calculated the annual primary and secondary care costs for each condition using linked electronic healthcare record data, then estimated needed expenditure for each health planning area for two scenarios: (1) when only accounting for diagnosed cases and (2) including all cases (diagnosed and undiagnosed). We examine how the distribution of need between places changes between these scenarios and the consequences of this for health inequalities. Based on the estimates of underdiagnosis used, areas with the lowest overall needs tended to have a greater proportion of their needs unmet. Adjusting resource allocation by accounting for these unmet needs due to underdiagnosis would move resources from areas with the highest level of needs to areas with lower overall needs. Moving to this 'fair share distribution' would tend to benefit less deprived areas more than more deprived areas, potentially widening health inequalities. We show how accounting for unmet needs due to underdiagnosis in allocating resources could widen health differences between more and less deprived areas when underdiagnosis and treatment costs increase with age. Further research is needed to confirm our provisional estimates, but we provide a useful framework for improving assessments of relative need for healthcare resource allocation. Alternative approaches are likely to be needed where resource allocation policy additionally aims to reduce health inequalities. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number NIHR130258. Many countries share out healthcare funding to local areas so that places with greater needs get more money than places with fewer needs. The National Health Service aims to account for unmet needs, for example undiagnosed conditions, in this process. The National Health Service also tries to share out resources to reduce the gap in health between more deprived and more affluent populations. It is unclear how providing a greater share of resources to those places with more undiagnosed conditions might influence this health gap. For 11 serious health conditions, we estimate the number of people diagnosed and undiagnosed and the costs of treating these conditions for each local health planning area in England. We estimate the share of the National Health Service budget that each area would receive in two scenarios. Firstly, providing each area with sufficient resources to treat the number of people diagnosed, and secondly, providing each area with sufficient resources to treat the number of people diagnosed or undiagnosed. We assess the likely effect on the gap in health between more deprived and more affluent populations of moving from the first to the second scenario. We estimate that more affluent areas would receive a greater share of National Health Service resources when the number of undiagnosed people were considered compared to when only diagnosed people were taken into account. This would widen the health gap between more deprived and more affluent populations. This is because, diseases that were more prevalent in older populations were estimated to be less likely to be diagnosed and more expensive to treat, and more affluent places tend to have older populations. Estimates of the number of people with undiagnosed conditions in each area are, however, very uncertain and better data are required to improve the accuracy. We provide a framework for improving these estimates.
Pulmonary arterial hypertension (PAH) is a severe disease characterised by a progressive thickening and obliteration of pulmonary vessels, resulting in increased vascular resistance, elevated pulmonary artery pressures, and right heart failure. Among the various conditions associated with PAH, systemic sclerosis (SSc) is the most common in Western countries. Compared to other forms of PAH, SSc-PAH presents with a more aggressive clinical course, poorer response to conventional therapies and a worse prognosis. However, despite these differences, the overall management of SSc-PAH remains close to idiopathic PAH; and therefore, there is a crucial need for treatment strategies dedicated to this disease. To help fill this gap, we assessed the level of evidence currently available on SSc-PAH management in a systematic literature review that compiled data regarding conventional therapies, immunosuppressants, nonconventional drugs and surgical/interventional procedures. For each study, we highlighted the results specific to the connective tissue disease or SSc subgroups, the haemodynamic characteristics of the patients, and their comorbidities. By doing so, we identified critical gaps in the field, consisting mostly of the lack of studies focusing on SSc-PAH, a substantial heterogeneity in haemodynamic severity (with notable scarcity of data for mild PAH) and the systematic exclusion of relevant comorbidities (such as interstitial lung disease). Building on these data and our cumulative experience, we provide pragmatic, experience-based suggestions tailored to the management of SSc-PAH, that tries to capture the full scope of clinical situations encountered in these patients and help clinicians manage difficult cases where robust data are lacking.
Caregiving can be time-consuming, and it can be challenging for caregivers to combine caregiving tasks with other obligations. While we know a lot about the problems of combining informal care with employment and family obligations, past employment and family histories are seldom discussed. This study tries to fill this gap by examining the association between employment and family histories and caregiving in later life. We used pooled data from the Survey of Health, Ageing and Retirement in Europe (SHARE, waves 1 and 2) and the English Longitudinal Study of Ageing (ELSA, waves 2 and 3) and combined them with the life history interviews from both surveys conducted in wave 3. First, we used sequence analysis and cluster analysis to analyze employment, partnership, and children histories between 25 and 50 years of age, separately for men and women. Then, we used logistic regression analysis to examine the relationships between these clusters and informal caregiving at ages 50 and above. Results indicate that women who stayed home (homemakers) and those who were self-employed were more likely to provide informal care in later life. Partnership histories matter only for men. Men who were separated were less involved in in-household caregiving and more in care provision outside of the household. Furthermore, childless men and women were more likely to be caregivers. Finally, differences in long-term care policies across countries significantly affected the likelihood of informal caregiving for men and women.
The history of the German Society for Experimental and Clinical Pharmacology and Toxicology (DGPT), which has played an important role in pharmacology in Germany and Europe for more than 100 years, is examined in this article. Many studies have addressed parts of this history, but they usually focus on short periods or specific topics. This article tries to bring together and explain the main sources on the DGPT and the development of pharmacology in German-speaking countries. Important references include early works by Philippu and Seifert, chronological surveys by Lindner, and the multi-volume histories by Philippu. Personal and institutional sources, such as Wolfgang Heubner's diaries and the DGPT Archive curated by Erich Muscholl, are also discussed. Using the sources of the archive, several articles about the DGPT's history have been published. The society's history during the Nazi era, the division of Germany after 1945, the reunification of German pharmacology, and the development of its journals and organizational structure are reviewed. Rather than providing a full historical account, this article offers a clear guide to the most relevant sources and lays the groundwork for future research on the DGPT.
There has been a persistent lack of synthesized knowledge on mental health treatment models that attune to the realities of low-income countries at large. To address this significant mental health knowledge gap, this scoping review tries to identify and synthesize the literature on psychological intervention models developed for or adapted to these contexts. After conducting a thorough search of academic databases, we went through a two-stage screening process to identify relevant articles. From those eligible studies, we collected and organized data on various theoretical and therapeutic counseling models, synthesizing the information into clear themes. The 42 included articles revealed five primary model categories: (1) Task-Shifting and Simplification, (2) Indigenous and Culturally-Grounded, (3) Systems-Level and Meta-Models, (4) Cultural Adaptation Frameworks, and (5) Technology-Based Delivery. The results indicate evidence base for the effectiveness of task-shifting simplified Western therapies and a growing movement toward validating indigenous psychologies. The findings demonstrate a clear shift toward pragmatic and culturally grounded interventions. Task-shifting is proven to be a promising approach in the field, but its effectiveness depends on having intense supervision. It is vital for research to focus on making the strategies sustainable for the long run, assessing their economic effectiveness, and comparing different models to see what works best for low-income nations.
This study investigated how young Australians experience sexuality education in schools and what can be done to make it better. Sexuality education is important because it helps young people learn about sexual health, relationships, and how to protect themselves from things like sexually transmitted infections (STIs) and unplanned pregnancies.Although Australia’s national curriculum tries to cover these topics, it often falls short. The quality, delivery and content of sex education seem to vary a lot depending on the school and the teacher, with many students feeling it does not meet their needs. At the same time, STIs remain common among young Australians, and more adults need help to have children through medical treatments.To better understand what young people want and need from sex education, researchers talked with teens aged 15–18 in focus groups. A Youth Advisory Group also helped analyse the results and come up with practical suggestions based on both the focus group findings and their own experiences.Three main issues came up: the way sex is viewed in society, what's actually taught in sex ed classes, and where young people learn about sex outside of school. These areas are deeply connected and highlight why Australia’s current approach isn’t working well.The study provides valuable insights into how sex education can be improved in Australia by making it more relevant, inclusive, and reflective of young people's real experiences.
Environmental and indoor air pollution causes respiratory infection related morbidity and mortality. Hence, the study tries to explore the relationship of environmental PM2.5 and indoor air pollution with the prevalence of Lower Respiratory Infection (LRIs) related neonatal (NMR) and under-five child mortality (U5MR) in India. The study extracted NMR, U5MR, PM2.5 and other environmental data from Global Burden of Disease (GBD) database (2021), and collected state level indoor air pollution and socioeconomic information of the child, mothers, and community from the fifth round of the National Family Health Survey (NFHS-5), 2019–21 dataset. The investigation employed join point regression analysis, Ordinary Least Square (OLS) regression models and spatial analysis technique to establish the relationship between PM2.5, indoor pollution and NMR or U5MR caused by LRIs in India. The trend analysis indicates that NMR and U5MR declined significantly by 66% and 74%, respectively from 1990 to 2021 in India. OLS regression models highlighted significantly positive association of PM2.5 pollution, indoor air pollution, unclean cooking fuel use, and absence of ventilation and separate kitchen in the houses on the prevalence of NMR and U5MR attributed to LRIs in India. Besides, spatial analysis reveals significant concentration and spatial association of PM2.5 and NMR or U5MR in some northern, and central Indian states like Rajasthan, Haryana, Uttar Pradesh, Madhya Pradesh, and Bihar. The study revealed that elevated PM2.5 concentrations are likely linked to contributing factors for higher child mortality, particularly in the Indo-Gangetic Plain (IGP) region. To address this issue, the study suggests increasing public awareness and implementing targeted policies to reduce neonatal and under-five mortality across India. [Image: see text]
High degree conductive disorders (CD) requiring permanent pacemaker implantation (PPI) have modestly decreased over time and remain the main complications of TAVR. Furthermore, management strategies for CD occurring after TAVR remain controversial. We proposed a review evaluating mechanisms and risk of CD after TAVR, focusing on the role of ECG evaluation but also on the importance of anatomic parameters analyzed in multi-slice computed tomography (MSCT), as well as regarding procedural aspects. Considering the lack of clear recommendations for the evaluation of risk of CD and indications of PPI, this review tries to summarize strategies to anticipate and detect the risk of high degree CD, to decrease incidence of CD and to optimize PPI indications. Perspectives regarding ambulatory monitoring, use of machine learning and new pacing techniques are proposed. This review was narrative and included selection of literature using key words including: conductive disorders, TAVR and pacemaker implantation.
The execution of clinical trials in wound care significantly differs from, and is frequently more challenging than, those involving pharmaceutical agents. Populations presenting with wounds (such as trauma and ulcers) are typically heterogeneous, and often exhibit a range of comorbidities and secondary factors that influence both the nature of the lesion itself and the trajectory of wound healing. Typical comorbidities in patients with ulcers include diabetes and chronic obstructive pulmonary disease, and polypharmacy is common. Trauma-related complications, such as haemodynamic or septic shock, are frequently observed in extensive burns and other major trauma. Such complexity presents substantial obstacles to generating statistically robust and reliable outcomes, either because a consistent patient cohort is difficult to find, or extensive stratification may be necessary when different cohorts of patients with different types of lesions are put together into a single trial population. This article highlights several of the methodological and operational challenges that can arise when conducting a wound care study and tries to create some upfront awareness of the pitfalls for such studies. The author has been a chief medical officer and independent consultant to the wound care industry for >35 years, and some statements in this article are based on his personal experience and observations.
The formation of oil-bearing pores in tight tuff has attracted considerable attention from petroleum geologists since the discovery of industrial oil.Devitrification may be an important cause for the formation of these pores; however, the relevant geological circumstance for devitrification still remains unclear. This study tries to decipher the formation of devitrification pores in the tight tuff in the Tiaohu Formation,the Santanghu Basin, Xinjiang, NW China. The result shows that the oil-bearing pore size in tuff is mainly in the range of micrometers to a few nanometers, and the porosity is mainly distributed between 0.10% and 26.71%; the permeability is mainly distributed between 0.17 and 1.20 mD. After high-temperature soaking, the oil-bearing tight tuff illustrated devitrification under both acidic and alkaline circumstances, with glassy tuff showing the greatest variation in porosity, followed by crystal pyroclast glassy tuff, while the mudstone tuff and silicified tuff show relatively small variations in porosity. The 140 °C threshold marks the optimal thermal window for devitrification-driven porosity: it coincides with the smectite-illite transition and the main hydrocarbon-generation stage in the Santanghu Basin. Porosity in all tuff varieties peaks at this temperature, recording a net gain of up to 16.31%; above 140 °C, porosity declines progressively. Devitrification proceeds in three successive stages: (1) neo-mineral nucleation, (2) metasomatic replacement, and (3) dissolution.
This paper describes the events leading up to the discovery of the place cells in 1971 for which the author received the Nobel Prize in Physiology and Medicine in 2014, together with May-Britt and Edvard Moser. In addition, it explores some of the ideas and influences that contributed to the interpretation of that finding as evidence for the Hippocampus as a Cognitive Map. Crucial to the acceptance of the idea of place cells and cognitive maps has been the development of recording technologies, and some of these are covered in the middle section. The final section tries to draw some lessons that the author has reached from his experiences.
Current food systems present several shortcomings that hinder their long-term sustainability leading to depletion of natural resources, land degradation and biodiversity loss. Circular Economy (CE) promises to mitigate these problems, by regenerating the ecosystems, enhancing production efficiency, and alleviating ecological pressures. Farms implement circularity in agriculture through renewable resources use, food waste prevention, biomasses valorization and regenerative practices. In particular, food waste prevention alleviates ecological pressures from production by enhancing output efficiency per unit of input. Farm level data are essential for understanding the mechanisms guiding CE diffusion, yet data availability is limited. This study tries to fill the knowledge gap by providing a new representative dataset on Italian farms. Data were collected through a structured survey administered to 1,200 farms. The dataset comprises 443 variables covering farm characteristics, surplus and waste generation and valorization, regenerative practices, use of circular inputs, and food waste performance providing the first granular overview of CE and food waste management practices in agriculture.
Over the past two decades, advances in the understanding of epigenetic mechanisms-driven by the rapid expansion of omics technologies-have catalyzed a major paradigm shift in biology: from the genetic determinism and linear causality of the Central Dogma toward the dynamic, networked complexity of systems biology and multilevel regulation. This reconceptualization extends to inheritance itself, highlighting the crucial role of the epigenome as a molecular interface between the genome and the exposome-the cumulative set of internal and external environmental influences experienced across the lifespan. Within this evolving framework, neurodevelopmental disorders exemplify the deep entanglement between genetic predisposition, environmental exposure, and epigenetic modulation. Their increasing global prevalence and frequent comorbidities underscore the need for an integrated etiological understanding that transcends reductionist models. This review tries to synthesize current evidence on the shared molecular and systemic mechanisms underlying neurodevelopmental spectrum disorders and examines how environmental and epigenetic factors jointly shape neurodevelopmental trajectories across generations. Finally, it discusses the broader implications of this paradigm shift for early diagnosis, prevention, and public health policies aimed at fostering healthy brain development in future generations.
A comprehensive computational investigation of bonding, electronic structure, and stability of homoleptic 18-electron sandwich complexes of iron (Fe) and chromium (Cr) with [5]- and [6]-peristylanes, and their aza- and oxo-substituted derivatives, is carried out. Utilizing the density functional theory (DFT) methodology, optimization and vibrational frequency analyses at the PBE0-D4/def2-TZVPP and ωB97M-V/def2-QZVPP levels of theory, and analyses of the nature of the metal-ligand interactions with the natural adaptive orbital (NAdO), the extended transition state-natural orbitals for chemical valence (ETS-NOCV), and the quantum theory of atoms in molecules (QTAIM) analyses have been carried out. The study reveals these complexes to possess partial covalent character, and the eclipsed conformation is more stable than the staggered one. The work tries to deepen the theoretical understanding of transition metal sandwich complexes with strained organic molecules like the peristylanes.
Wireless sensor networks (WSNs) are the backbone of IoT-enabled smart manufacturing, environmental monitoring, and industrial automation. However, their broadcast nature makes communication links vulnerable to eavesdropping, routing manipulation, and denial-of-service attacks. Strategically placing monitor nodes to check each link is an effective approach to protect against attacks, but energy, connectivity, and capacity constraints should be considered while picking monitor nodes. In this paper, we tackle the Minimum-Weighted Connected Capacitated Vertex Cover (MWCCVC) problem, which minimizes monitoring costs, ensures backbone connectivity, and adheres to per-node capacity constraints. Unlike prior works that consider weighted vertex cover, connectivity constraints, or capacitated variants separately, the proposed MWCCVC model jointly integrates all three dimensions within a single vertex cover-based monitoring framework. We first provide a Branch-and-Bound (B&B) solver with linear programming relaxation bounds and constraint-based pruning strategies that produces optimum solutions. Three constructive greedy heuristics (GD, GR, GW) and two hybrid genetic algorithms (HGA, HGA-v2) that combine parameterized greedy decoders with evolutionary search are proposed; all methods guarantee full edge coverage, induced-subgraph connectivity, and max-flow-validated capacity feasibility. Tests on 130 small, 160 medium, and 19 large benchmark instances show that HGA matches B&B optima on every small instance, beats the time-limited B&B by 6.6% on medium instances, where the percentage is computed based on the relative difference in average total weight with respect to B&B, and stays the best on large graphs with up to 1000 nodes. The HGA-v2 tries to balance the quality and speed, with only a 3.1% difference at 10× faster execution.
The negative connection between short-video excessive usage habits and students' learning is becoming increasingly prominent in the field of education. With the excessive use of short videos, a phenomenon known as the "TikTok brain" has emerged. However, the research on the "TikTok brain" variable and its understanding are still at the initial exploration stage. This study tries to propose seven research hypotheses and build a corresponding theoretical model based on the self-determination theory, attempting to explore the relationship and transmission path between the TikTok brain, declined attention, and learning burnout. students are both the main users of short videos and the high-risk group for learning burnout. Therefore, this study collected 500 valid questionnaires to verify the above research hypotheses. Among them, there are 243 male students (48.6%) and 257 female students (51.4%). (1) There is a significant positive correlation between the TikTok brain and declined attention; (2) The TikTok brain is also significantly positively correlated with learning burnout; (3) Declined attention plays an effective mediating role between the TikTok brain and learning burnout. This study concludes that the immediate satisfaction cognitive model formed by short-video excessive usage will further intensify students' learning burnout through consuming their attention resources. This also provides an insight into educational practice. In the educational scenario, paying attention to guiding and intervening in students' digital usage habits to help them cultivate and maintain a sustainable learning state is necessary.
Rangelands play a vital role in supporting livelihoods, biodiversity, and ecological balance across arid and semi-arid regions. However, these fragile ecosystems are increasingly threatened by overexploitation, land degradation, and unsustainable management practices. Understanding the human and behavioral dimensions of rangeland conservation has therefore become an urgent priority. Many of the world’s rangelands, including those in Iran, have recently been exposed to destruction and serious damage. Collaboration among various stakeholders (especially pastoralists) in sustainable land use and management is considered a key factor in reducing this degradation. Guided by the Theory of Planned Behavior (TPB), this study tries to identify and analyze the behavioral nudges for the sustainable land use and management in Iran. This research employed a cross-sectional survey design involving 248 pastoralists in Fars Province, southern Iran, selected through simple random sampling. An extended version of the TPB was applied, incorporating two additional constructs—awareness of consequences and moral norms—to enhance its explanatory power in predicting sustainable land use intentions. Behavioral nudges, such as increased awareness of consequences, strengthening moral norms, perceived behavioral control, and attitudes, can lead pastoralists to sustainable land use and management, thereby helping to conserve rangelands. To operationalize the research, a cross-sectional survey of 248 pastoralists with livestock grazing certificates, who were selected using simple random sampling, was used. The results of the research showed that the constructs of attitude towards sustainable land use and management had a positive and significant effect on the intention towards sustainable land use and management (Beta = 0.292; T = 4.239; Sig = 0.001). The direct effects of two variables, awareness of consequences of rangelands’ destruction (Beta = 0. 335; T = 3.333; Sig = 0.001) and moral norms of sustainable land use and management (Beta = 0. 323; T = 2.791; Sig = 0.005), were positive and significant on Intention. In addition, the results of this study showed that moral norms not only act as a constructive factor in the intention of the pastoralists towards sustainable land use and management, but also can play a mediating role for some other variables such as awareness of consequences of rangeland destruction. The results of SEM analysis showed that the extended TPB can explain 75% of the variance of pastoralists’ behavioral intention, which shows the high explanatory power of the model. These findings provide practical insights for policymakers and land managers by emphasizing the need to design interventions that enhance moral and environmental awareness, promote participatory management, and align behavioral policies with local cultural norms. However, as this study is based on a cross-sectional design, causal inferences should be made cautiously, and future longitudinal research is recommended to validate these relationships over time. The online version contains supplementary material available at 10.1038/s41598-026-39511-6.
As people engage in tasks over extended periods, their psychological states change systematically due to factors such as practice, learning, and/or boredom. However, the dominant frameworks for modeling cognitive processes, such as evidence accumulation models, only consider a single estimate of a process across the duration of an experiment. Our study describes, develops, and assesses the ParAcT-DDM framework: the Parameters Across Time Diffusion Decision Model, which unifies previous modeling efforts from practice and decision-making research. Specifically, our framework models time-varying changes to diffusion decision model parameters by assuming that rather than being constant across time, their estimates follow theoretically informed time-varying (e.g., trial-varying or block-varying) functions. Focusing on two diffusion model parameters: drift rate (task efficiency) and threshold (caution), our empirical results show that ParAcT-DDM variants vastly outperform the standard diffusion model in four existing data sets, including one where participants completed a practice block before data recording began, suggesting that time-varying cognitive processes often occur in typical cognitive experiments, even when the experimental design explicitly tries to remove practice effects. Finally, we find that the existence of time-varying processes causes systematic biases in the parameter estimates of the standard diffusion model, suggesting that our ParAcT-DDM framework can be crucial to ensuring the robustness of inferences against time-varying changes, regardless of whether these changes are of direct interest. (PsycInfo Database Record (c) 2026 APA, all rights reserved).