ethicalabs/Research-Intent-Collab huggingface dataset:
A multivariate assessment of climate change projections over South America using CMIP5 models

&amp;lt;p&amp;gt;A multivariate assessment of climate model projections over South America from the CMIP5 archive is presented. Change in near-surface temperature, precipitation, evapotranspiration, integrated water vapor transport (IVT), sea level pressure, and wind at multiple pressure levels is quantified across the multi-model suite and an assessment of model-to-model agreement on projected change performed. All models project warming by the mid- and late-21&amp;lt;sup&amp;gt;st&amp;lt;/sup&amp;gt; century throughout the continent, with the highest magnitude projected over tropical regions. The CMIP5 models are in strong agreement that precipitation will decrease in all seasons over portions of Patagonia, especially along the northern portions of the current-climate mid-latitude storm track. This is consistent with a robustly projected poleward shift of the Pacific extratropical high and mid-latitude storm track indicated by a systematic increase in sea level pressure and decrease in westerly wind over Patagonia. Decreased precipitation for the months of September, October, and November is also projected, with strong model agreement, over portions of northern and northeastern Brazil, coincident with decreases in sea level pressure and increases in evapotranspiration. IVT is broadly projected to decrease over southern South America, coincident with the projected poleward shift of the mid-latitude storm track indicators, with increases projected in the vicinity of the South Atlantic Convergence Zone in austral spring and summer. Further decomposition of the thermodynamic and dynamic components to this change in IVT indicate that the projected decreases in the mid-latitudes are primarily driven by changes in circulation (i.e. dynamic) while the sub-tropical and tropical changes have a predominantly thermodynamic origin. Results provide a comprehensive picture of climate change across South America and highlight where projections should be interpreted with the most confidence.&amp;lt;/p&amp;gt;
Integrating Optimal Transport and Structural Inference Models for GRN Inference from Single-cell Data

We introduce a novel gene regulatory network (GRN) inference method that integrates optimal transport (OT) with a deep-learning structural inference model. Advances in next-generation sequencing enable detailed yet destructive gene expression assays at the single-cell level, resulting in the loss of cell evolutionary trajectories. Due to technological and cost constraints, single-cell experiments often feature cells sampled at irregular and sparse time points with a small sample size. Although trajectory-based structural inference models can accurately reveal the underlying interaction graph from observed data, their efficacy depends on the inputs of thousands of regularly sampled trajectories. The irregularly-sampled nature of single-cell data precludes the direct use of these powerful models for reconstructing GRNs. Optimal transport, a classical mathematical framework that minimize transportation costs between distributions, has shown promise in multi-omics data integration and cell fate prediction. Utilizing OT, our method constructs mappings between consecutively sampled cells to form cell-level trajectories, which are given as input to a structural inference model that recovers the GRN from single-cell data. Through case studies in two synthetic datasets, we demonstrate the feasibility of our proposed method and its promising performance over eight state-of-the-art GRN inference methods.
Impact of land use on plant biodiversity and measures for biodiversity conservation in the Loess Plateau in China – a case study in a hilly-gully region of the Northern Loess Plateau

The Loess Plateau is a special natural–cultural unit in northern China. Intensive land use in the past has had, and forestation and grass planting at present will have inevitable impacts on plant biodiversity in the Loess Plateau. Based on the analysis of floristic features within three sampling sites with different land use practices and analysis of species richness among different land use types, we discuss impacts of land use on species richness and floristic features in the Northern Loess Plateau. The results drawn from this case study are as follows: (1) It appears that forestation and grass planting have had a positive influence on the local species diversity, but they have contributed little to the native vegetation in terms of conserving its floristic features. (2) Caragana intermedia shrubland, Pinus tabulaeformis forestland, and natural grassland have made important contributions to supporting indigenous species and maintaining local plant biodiversity. (3) There is a significant positive correlation between land use diversity and species richness. These results imply that practicing biodiversity conservation in situ is feasible and the suitable choice for the Loess Plateau. Concrete measures for biodiversity conservation in the area can include setting up small nature reserves and diversifying land use patterns to maintain as much habitat as possible for native vegetation. The artificial Hippophae rhamnoides shrubland should not be further promoted, considering its negative influence on biodiversity conservation.
Features in the primordial power spectrum: constraints from the cosmic microwave background and the limitation of the 2dF and SDSS redshift surveys to detect them

We allow a more general (step-function) form of the primordial power spectrum than the usual featureless power-law Harrison-Zeldovich (with spectral index n = 1) power spectrum, and fit it to the latest cosmic microwave background data sets. Although the best-fitting initial power spectrum can differ significantly from the power-law shape, and contains a dip at scales k ∼ 0.003 h Mpc -  1 , we find that Ω m  0.24, consistent with previous analyses that assume power-law initial fluctuations. We also explore the feasibility of the early releases of the 2dF and Sloan Digital Sky Survey (SDSS) galaxy redshifts surveys to see these features, and we find that even if features exist in the primordial power spectrum, they are washed out by the window functions of the redshift surveys on scales k < 0.03 h Mpc -  1 .
An Analysis of Memory Based Collaborative Filtering Recommender Systems with Improvement Proposals

Memory Based Collaborative Filtering Recommender Systems have been around for the best part of the last twenty years. It is a mature technology, implemented in nu- merous commercial applications. However, a departure from Memory Based systems, in favour of Model Based systems happened during the last years. The Net ix.com competition of 2006, brought the Model Based paradigm to the spotlight, with plenty of research that followed. Still, these matrix factorization based algorithms are hard to compute, and cumbersome to update. Memory Based approaches, on the other hand, are simple, fast, and self explanatory. We posit that there are still uncomplicated approaches that can be applied to improve this family of Recommender Systems further. Four strategies aimed at improving the Accuracy of Memory Based Collaborative Filtering Recommender Systems have been proposed and extensively tested. The strategies put forward include an Average Item Voting approach to infer missing rat- ings, an Indirect Estimation algorithm which pre-estimates the missing ratings before computing the overall recommendation, a Class Type Grouping strategy to lter out items of a class di erent than the target one, and a Weighted Ensemble consisting of an average of an estimation computed with all samples, with one obtained via the Class Type Grouping approach. This work will show that there is still ample space to improve Memory Based Systems, and raise their Accuracy to the point where they can compete with state- of-the-art Model Based approaches such as Matrix Factorization or Singular Value Decomposition techniques, which require considerable processing power, and generate models that become obsolete as soon as users add new ratings into the system.
Impact of leadership style on job satisfaction and organizational citizenship behavior: The mediating role of management control systems

This research examines the impact of democratic leadership (DL) on job satisfaction (JS) and organizational citizenship behavior (OCB) in the Tunisian telecommunication sector. Results revealed that democratic leadership has a positive effect on job satisfaction and organizational citizenship behavior among the relevant employees. Also, democratic leadership positively affects management control systems in the relevant organizations. The proposed mediation of management control systems on the relationships between democratic leadership, job satisfaction, and organizational citizenship behavior also remained significant. The results remained supportive towards validating the role of democratic leadership in ensuring job satisfaction and organizational citizenship behavior through management control systems. Further, study implications and limitations are discussed accordingly.
Phase transitions in explorations seismology : statistical mechanics meets information theory

n this paper, two different applications of phase transitions to exploration seismology will be discussed. The first application concerns a phase diagram ruling the recovery conditions for seismic data volumes from incomplete and noisy data while the second phase transition describes the behavior of bi-compositional mixtures as a function of the volume fraction. In both cases, the phase transitions are the result of randomness in large system of equations in combination with nonlinearity. The seismic recovery problem from incomplete data involves the inversion of a rectangular matrix. Recent results from the field of "compressive sensing" provide the conditions for a successful recovery of functions that are sparse in some basis (wavelet) or frame (curvelet) representation, by means of a sparsity ($\ell_1$-norm) promoting nonlinear program. The conditions for a successful recovery depend on a certain randomness of the matrix and on two parameters that express the matrix' aspect ratio and the ratio of the number of nonzero entries in the coefficient vector for the sparse signal representation over the number of measurements. It appears that the ensemble average for the success rate for the recovery of the sparse transformed data vector by a nonlinear sparsity promoting program, can be described by a phase transition, demarcating the regions for the two ratios for which recovery of the sparse entries is likely to be successful or likely to fail. Consistent with other phase transition phenomena, the larger the system the sharper the transition. The randomness in this example is related to the construction of the matrix, which for the recovery of spike trains corresponds to the randomly restricted Fourier matrix. It is shown, that these ideas can be extended to the curvelet recovery by sparsity-promoting inversion (CRSI) . The second application of phase transitions in exploration seismology concerns the upscaling problem. To counter the intrinsic smoothing of singularities by conventional equivalent medium upscaling theory, a percolation-based nonlinear switch model is proposed. In this model, the transport properties of bi-compositional mixture models for rocks undergo a sudden change in the macroscopic transport properties as soon as the volume fraction of the stronger material reaches a critical point. At this critical point, the stronger material forms a connected cluster, which leads to the creation of a cusp-like singularity in the elastic moduli, which in turn give rise to specular reflections. In this model, the reflectivity is no longer explicitly due to singularities in the rocks composition. Instead, singularities are created whenever the volume fraction exceeds the critical point. We will show that this concept can be used for a singularity-preserved lithological upscaling.
Analysis of Occupational Health and Safety Risk Management: Hazard Identification, Risk Assessment, and Risk Control-HIRARC for Workers at Health Quarantine Offices in Makassar, Indonesia

Work hazards and risks are closely related to occupational activities and have the potential to cause injuries and occupational diseases. Every workplace carries the risk of accidents, as reflected in data from Indonesia's Work Accident Insurance Program (JKK BPJS Ketenagakerjaan). The number of workers experiencing fatalities due to occupational accidents and diseases decreased from 4,007 cases in 2019 to 3,410 cases in 2020 but increased again to 6,552 cases in 2021. This study aims to assess occupational health and safety risk management using the Hazard Identification, Risk Assessment, and Risk Control (HIRARC) method among workers at the Makassar Health Quarantine Center. This descriptive study involved a population of 133 workers, with a sample of 57 workers selected using simple random sampling. Data were collected using the HIRARC questionnaire and analyzed using univariate analysis. The results showed that the majority of respondents were aged 40–49 years (57.9%), and 73.7% worked more than 8 hours per day when assigned to night shifts. The HIRARC assessment identified that the most common occupational hazard experienced by workers was ergonomic risk, with complaints of back, waist, and shoulder pain, classified as a moderate risk. In conclusion, ergonomic hazards pose a significant issue among workers, categorized as a moderate risk level. Therefore, it is recommended that the Makassar Health Quarantine Center enhance its occupational health and safety risk management and conduct regular evaluations of workplace hazards and risks.
Key methodological features of randomized controlled trials of Alzheimer's disease therapy. Minimal clinically important difference, sample size and trial duration.

The results of clinical trials are routinely presented in terms of statistical significance, which may or may not indicate clinical significance. Analysis of the minimal clinically important difference (MCID) of cognitive scales has received little attention to date.By reviewing the key methodological features (sample size, duration, statistical and clinical significance) of clinical trials examining the efficacy of tacrine in the treatment of Alzheimer's disease (AD), we assessed their ability to detect clinically important changes in cognition.The value for the MCID of the Mini-Mental State Examination (MMSE) was determined by surveying specialists in neurology and geriatric medicine. This value was then used to interpret the clinical significance of the results of published randomized controlled trials (RCTs) assessing the efficacy of tacrine in the treatment of AD and to retrospectively determine their optimal sample size and trial duration.The mean survey MCID for the MMSE was 3.72 (95% confidence interval 3.50-3.95) points. Only 2 of 12 tacrine RCTs using the MMSE found a statistically significant difference in MMSE scores for patients taking tacrine compared with those taking placebo. These improvements were not clinically significant when compared with the survey MMSE MCID. For parallel trials of tacrine in AD, the smallest sample size and minimum trial duration required to demonstrate a clinically significant difference were calculated to be 53 subjects and 1 year, respectively. Five of the 7 parallel trials met the required sample size; however, none of them met the criteria for trial duration.When using the MMSE as an outcome measure, no tacrine trial reported results that were clinically significant as perceived by clinicians working with dementia patients. Application of a range of plausible MCIDs to the parallel design RCTs also demonstrated that 2 of 7 of these trials did not have sufficient sample size, and none had sufficient duration of treatment to reliably detect clinically meaningful changes in cognition. Future clinical trials in this area will need to incorporate the evolving knowledge of MCIDs in order to increase their chance of detecting clinically relevant results. CopyrightCopyright 1999S.KargerAG,Basel
Recent advances in VAT photopolymerization additive manufacturing of battery electrodes: towards high-resolution 3D-printed batteries

Additive manufacturing of battery enables a more versatile battery form factor and design.
Adapting the built environment: the role of gender in shaping vulnerability and resilience to climate extremes in Dhaka

The relationship between the built environment and vulnerability and resilience is a little-studied area of research, and demands an exploration of constraints and windows of opportunity. Given gender roles and the division of labour between women and men within urban poor households, the impacts of climate extremes are likely to be gendered. But conceptualizing gender only in terms of the vulnerability of women can mean overlooking the complex and intersecting power relations that marginalize women and men differently. These power relations are manifested in spatial practices, while spatial relations are manifested in the construction of gender. Thus, the power to make decisions in the built environment based on gender roles, and the nature of gender subordination, rights and entitlements contribute significantly to the capacity to adapt to climate extremes.
Enhancing end-of-life quality metrics: The role of palliative care in a community oncology practice.

85                                   Background:             As value-based payment (VBP) models expand in oncology, care teams adopt innovative strategies to improve outcomes, enhance patient experience, and meet evolving quality metrics (QMs). These changes require reassessing traditional population health QMs to ensure they reflect current practices and continue to incentivize care improvements. End-of-life care is one area where timely access to hospice remains inconsistent—especially in rural and underserved communities—and often outside oncology practices' direct control. Additionally, advances like immunotherapy, which may be well tolerated near end-of-life, challenge the hospice model as the sole supportive care option. NCCN and ASCO guidelines recommend early palliative care in advanced cancers, and many community oncology practices now integrate palliative care-to provide longitudinal, goal-concordant care that supports quality of life throughout treatment. Including palliative care receipt in end-of-life QMs offers a more nuanced, equitable way to evaluate care, ensuring patients receive needed support regardless of geography or treatment stage.             Methods:             We conducted a retrospective analysis of Enhancing Oncology Model (EOM) episodes in Performance Periods 1 and 2 (PP1 and PP2) for patients attributed to Tennessee Oncology, a large community-based practice with embedded palliative care-trained APPs and physicians. The analysis focused on EOM Quality Measure 2 (QM2): the proportion of patients who died and were enrolled in hospice for at least three days before death. To assess the impact of embedded palliative care, we recalculated QM2 with a modified numerator including patients who either enrolled in hospice at least three days before death or had a documented palliative care evaluation and management (E&amp;M) visit at least three days before death, divided by all patients who died during the episode.             Results:             Among 2,135 unique patients attributed to PP1 and PP2, 335 died within their episode timelines. Of these, 47.7% (n = 160) were admitted to hospice, and 34.9% (n = 117) were referred to hospice at least three days before death. When including patients with palliative care E&amp;M visits at least three days before death, the recalculated QM2 increased to 52.8% (n = 177), reflecting a 17.9 percentage point improvement in performance by incorporating palliative care interventions.             Conclusions:             Access to palliative care is critical to improving outcomes, patient satisfaction, and reducing costs. However, common VBP metrics do not fully capture innovations in palliative care delivery within community oncology. Future VBP models should recognize and incentivize these innovations through updated quality measures that are consistent with guidelines.
Episodic cosmic-ray modulation in the heliosphere

Abstract   A newly developed two-dimensional, time-dependent modulation model is applied to the simulation of propagating Forbush decreases (Fd's) in the heliosphere. Compared to a one-dimensional model the recovery time of a Fd is found to be significant less with this model. The magnitude as a function of radial distance is determined by (   1  K     rr    −   K     1   rK     rr    ). In general, results are in reasonable agreement with observations. With drifts included the recovery rate differs significantly compared with the non-drift model, and depends strongly on the polarity of the solar magnetic field.
Human-Centered Design to Enhance the Usability, Human Factors, and User Experience Within Digital Destructive Ecosystems

Human-centered design is an approach that focuses on involving the end user throughout the product development and testing process which can be crucial in ensuring that the product meets the needs and capabilities of the user, particularly in terms of user experience and safety. The structured and iterative nature of human-centered design can often be a challenge for the design team when faced with the necessary, rapid, product development life cycles associated with the competitiveness in the industry. This ensures that the needs of the user are taken into account throughout the design process whilst also maintaining a rapid pace of development, and its rationale before outlining how it was applied to assess and enhance the usability, human factors, and user experience within destructive digital ecosystem era. The authors encouraged a system approach such as human-centered design for prevention on further damages being done on data breaches through the application of each steps of the process.
Subsampling for Knowledge Graph Embedding Explained

In this article, we explain the recent advance of subsampling methods in knowledge graph embedding (KGE) starting from the original one used in word2vec.