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This study explores the development and validation of an airflow model to support climate prediction for Citrus Under Protective Screens (CUPS) in California. CUPS is a permeable screen structure designed to protect a field of citrus trees from large insects including the vector that causes the devastating citrus greening disease. Because screen structures modify the environmental conditions (e.g., temperature, relative humidity, airflow), farm management and treatment strategies (e.g., pesticide spraying events) must be modified to account for these differences. Toward this end, we develop a model for predicting wind speed and direction in a commercial-scale research CUPS, using a computational fluid dynamics (CFD) model. We describe the model and validate it in two ways. In the first, we model a small-scale replica CUPS under controlled conditions and compare modeled and measured airflow in and around the replica structure. In the second, we model the full-scale CUPS and use historical measurements to back test the models accuracy. In both settings, the modeled airflow values fall within statistical confidence intervals generated from the corresponding measurements of the conditions being modeled. These findings suggest that the model can aid decision support and smart agriculture solutions for farmers as they adapt their farm management practices for CUPS structures.

An increasing amount of Californias landscape has burned in wildfires in recent decades, in conjunction with increasing temperatures and vapor pressure deficit due to climate change. As the wildland-urban interface expands, more people are exposed to and harmed by these extensive wildfires, which are also eroding the resilience of terrestrial ecosystems. With future wildfire activity expected to increase, there is an urgent demand for solutions that sustain healthy ecosystems and wildfire-resilient human communities. Those who manage disaster response, landscapes, and biodiversity rely on mapped projections of how fire activity may respond to climate change and other human factors. California wildfire is complex, however, and climate-fire relationships vary across the state. Given known geographical variability in drivers of fire activity, we asked whether the geographical extent of fire models used to create these projections may alter the interpretation of predictions. We compared models of fire occurrence spanning the entire state of California to models developed for individual ecoregions and then projected end-of-century future fire patterns under climate change scenarios. We trained a Maximum Entropy model with fire records and hydroclimatological variables from recent decades (1981 to 2010) as well as topographic and human infrastructure predictors. Results showed substantial variation in predictors of fire probability and mapped future projections of fire depending upon geographical extents of model boundaries. Only the ecoregion models, accounting for the unique patterns of vegetation, climate, and human infrastructure, projected an increase in fire in most forested regions of the state, congruent with predictions from other studies.

There is an urgent need for strategies to reduce the negative impacts of a warming climate on human health. Cooling urban neighborhoods by planting trees and vegetation and increasing albedo of roofs, pavements, and walls can mitigate urban heat. We used synoptic climatology to examine how different tree cover and albedo scenarios would affect heat-related morbidity in Los Angeles, CA, USA, as measured by emergency room (ER) visits. We classified daily meteorological data for historical summer heat events into discrete air mass types. We analyzed those classifications against historical ER visit data to determine both heat-related and excess morbidity. We used the Weather Research and Forecasting model to examine the impacts of varied tree cover and albedo scenarios on meteorological outcomes and used these results with standardized morbidity data algorithms to estimate potential reductions in ER visits. We tested three urban modification scenarios of low, medium, and high increases of tree cover and albedo and compared these against baseline conditions. We found that avoiding 25% to 50% of ER visits during heat events would be a common outcome if the urban environment had more tree cover and higher albedo, with the greatest benefits occurring under heat events that are moderate and those that are particularly hot and dry. We conducted these analyses at the county level and compared results to a heat-vulnerable, working-class Los Angeles community with a high concentration of people of color, and found that reductions in the rate of ER visits would be even greater at the community level compared to the county.

In the centuries following Christopher Columbuss 1492 voyage to the Americas, transoceanic travel opened unprecedented pathways in global pathogen circulation. Yet no biological transfer is a single, discrete event. We use mathematical modeling to quantify historical risk of shipborne pathogen introduction, exploring the respective contributions of journey time, ship size, population susceptibility, transmission intensity, density dependence, and pathogen biology. We contextualize our results using port arrivals data from San Francisco, 1850 to 1852, and from a selection of historically significant voyages, 1492 to 1918. We offer numerical estimates of introduction risk across historically realistic ranges of journey time and ship population size, and show that both steam travel and shipping regimes that involved frequent, large-scale movement of people substantially increased risk of transoceanic pathogen circulation.

Leaf litter microbes collectively degrade plant polysaccharides, influencing land-atmosphere carbon exchange. An open question is how substrate complexity-defined as the structure of the saccharide and the amount of external processing by extracellular enzymes-influences species interactions. We tested the hypothesis that monosaccharides (i.e. xylose) promote negative interactions through resource competition, and polysaccharides (i.e. xylan) promote neutral or positive interactions through resource partitioning or synergism among extracellular enzymes. We assembled a three-species community of leaf litter-degrading bacteria isolated from a grassland site in Southern California. In the polysaccharide xylan, pairs of species stably coexisted and grew equally in coculture and in monoculture. Conversely, in the monosaccharide xylose, competitive exclusion and negative interactions prevailed. These pairwise dynamics remained consistent in a three-species community: all three species coexisted in xylan, while only two species coexisted in xylose, with one species capable of using peptone. A mathematical model showed that in xylose these dynamics could be explained by resource competition. Instead, the model could not predict the coexistence patterns in xylan, suggesting other interactions exist during biopolymer degradation. Overall, our study shows that substrate complexity influences species interactions and patterns of coexistence in a synthetic microbial community of leaf litter degraders.

Most of the available data on diffusion in natural clayey rocks consider tracer diffusion in the absence of a salinity gradient despite the fact that such gradients are frequently found in natural and engineered subsurface environments. To assess the role of such gradients on the diffusion properties of clayey materials, through-diffusion experiments were carried out in the presence and absence of a salinity gradient using salt-diffusion and radioisotope tracer techniques. The experiments were carried out with vermiculite samples that contained equal proportions of interparticle and interlayer porosities so as to assess also the role played by the two types of porosities on the diffusion of water and ions. Data were interpreted using both a classical Fickian diffusion model and with a reactive transport code, CrunchClay that can handle multi-porosity diffusion processes in the presence of charged surfaces. By combining experimental and simulated data, we demonstrated that (i) the flux of water diffusing through vermiculite interlayer porosity was minor compared to that diffusing through the interparticle porosity, and (ii) a model considering at least three types of porous volumes (interlayer, interparticle diffuse layer, and bulk interparticle) was necessary to reproduce consistently the variations of neutral and charged species diffusion as a function of salinity gradient conditions.

To understand the extent of anthropogenic noise in the ocean, it is essential to compare the differences between modern noise environments and their pre-industrial equivalents. The Santa Barbara Channel, off the coast of Southern California, is a corridor for the transportation of goods to and from the busiest shipping ports in the Western hemisphere. Commercial ships introduce high levels of underwater noise into the marine environment. To quantify the extent of noise in the region, we modeled pre-industrial ocean noise levels, driven by wind, and modern ocean noise levels, resulting from the presence of both ships and wind. By comparing pre-industrial and modern underwater noise levels, the low-frequency (50 Hz) acoustic environment was found to be degraded by more than 15 dB. These results can be used to identify regions for noise reduction efforts, as well as to model scenarios to identify those with the greatest potential to support marine conservation efforts.

Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

Sustainability outcomes are influenced by the laws and configurations of natural and engineered systems as well as activities in socio-economic systems. An important subset of human activity is the creation and implementation of institutions, formal and informal rules shaping a wide range of human behavior. Understanding these rules and codifying them in computational models can provide important missing insights into why systems function the way they do (static) as well as the pace and structure of transitions required to improve sustainability (dynamic). Here, we conduct a comparative synthesis of three modeling approaches- integrated assessment modeling, engineering-economic optimization, and agent-based modeling-with underexplored potential to represent institutions. We first perform modeling experiments on climate mitigation systems that represent specific aspects of heterogeneous institutions, including formal policies and institutional coordination, and informal attitudes and norms. We find measurable but uneven aggregate impacts, while more politically meaningful distributional impacts are large across various actors. Our results show that omitting institutions can influence the costs of climate mitigation and miss opportunities to leverage institutional forces to speed up emissions reduction. These experiments allow us to explore the capacity of each modeling approach to represent insitutions and to lay out a vision for the next frontier of endogenizing institutional change in sustainability science models. To bridge the gap between modeling, theories, and empirical evidence on social institutions, this research agenda calls for joint efforts between sustainability modelers who wish to explore and incorporate institutional detail, and social scientists studying the socio-political and economic foundations for sustainability transitions.

Future climate change can cause more days with poor air quality. This could trigger more alerts telling people to stay inside to protect themselves, with potential consequences for health and health equity. Here, we study the change in US air quality alerts over this century due to fine particulate matter (PM2.5), who they may affect, and how they may respond. We find air quality alerts increase by over 1 mo per year in the eastern United States by 2100 and quadruple on average. They predominantly affect areas with high Black populations and leakier homes, exacerbating existing inequalities and impacting those less able to adapt. Reducing emissions can offer significant annual health benefits ($5,400 per person) by mitigating the effect of climate change on air pollution and its associated risks of early death. Relying on people to adapt, instead, would require them to stay inside, with doors and windows closed, for an extra 142 d per year, at an average cost of $11,000 per person. It appears likelier, however, that people will achieve minimal protection without policy to increase adaptation rates. Boosting adaptation can offer net benefits, even alongside deep emission cuts. New adaptation policies could, for example: reduce adaptation costs; reduce infiltration and improve indoor air quality; increase awareness of alerts and adaptation; and provide measures for those working or living outdoors. Reducing emissions, conversely, lowers everyones need to adapt, and protects those who cannot adapt. Equitably protecting human health from air pollution under climate change requires both mitigation and adaptation.

IntroductionCancer combination treatments involving immunotherapies with targeted radiation therapy are at the forefront of treating cancers. However, dosing and scheduling of these therapies pose a challenge. Mathematical models provide a unique way of optimizing these therapies.MethodsUsing a preclinical model of multiple myeloma as an example, we demonstrate the capability of a mathematical model to combine these therapies to achieve maximum response, defined as delay in tumor growth. Data from mice studies with targeted radionuclide therapy (TRT) and chimeric antigen receptor (CAR)-T cell monotherapies and combinations with different intervals between them was used to calibrate mathematical model parameters. The dependence of progression-free survival (PFS), overall survival (OS), and the time to minimum tumor burden on dosing and scheduling was evaluated. Different dosing and scheduling schemes were evaluated to maximize the PFS and optimize timings of TRT and CAR-T cell therapies.ResultsTherapy intervals that were too close or too far apart are shown to be detrimental to the therapeutic efficacy, as TRT too close to CAR-T cell therapy results in radiation related CAR-T cell killing while the therapies being too far apart result in tumor regrowth, negatively impacting tumor control and survival. We show that splitting a dose of TRT or CAR-T cells when administered in combination is advantageous only if the first therapy delivered can produce a significant benefit as a monotherapy.DiscussionMathematical models are crucial tools for optimizing the delivery of cancer combination therapy regimens with application along the lines of achieving cure, maximizing survival or minimizing toxicity.

There have been major advances in the science to predict the likely environmental concentrations of nanomaterials, which is a key component of exposure and subsequent risk assessment. Considerable progress has been since the first Material Flow Analyses (MFAs) in 2008, which were based on very limited information, to more refined current tools that take into account engineered nanoparticle (ENP) size distribution, form, dynamic release, and better-informed release factors. These MFAs provide input for all environmental fate models (EFMs), that generate estimates of particle flows and concentrations in various environmental compartments. While MFA models provide valuable information on the magnitude of ENP release, they do not account for fate processes, such as homo- and heteroaggregation, transformations, dissolution, or corona formation. EFMs account for these processes in differing degrees. EFMs can be divided into multimedia compartment models (e.g., atmosphere, waterbodies and their sediments, soils in various landuses), of which there are currently a handful with varying degrees of complexity and process representation, and spatially-resolved watershed models which focus on the water and sediment compartments. Multimedia models have particular applications for considering predicted environmental concentrations (PECs) in particular regions, or for developing generic "fate factors" (i.e., overall persistence in a given compartment) for life-cycle assessment. Watershed models can track transport and eventual fate of emissions into a flowing river, from multiple sources along the waterway course, providing spatially and temporally resolved PECs. Both types of EFMs can be run with either continuous sources of emissions and environmental conditions, or with dynamic emissions (e.g., temporally varying for example as a new nanomaterial is introduced to the market, or with seasonal applications), to better understand the situations that may lead to peak PECs that are more likely to result in exceedance of a toxicological threshold. In addition, bioaccumulation models have been developed to predict the internal concentrations that may accumulate in exposed organisms, based on the PECs from EFMs. The main challenge for MFA and EFMs is a full validation against observed data. To date there have been no field studies that can provide the kind of dataset(s) needed for a true validation of the PECs. While EFMs have been evaluated against a few observations in a small number of locations, with results that indicate they are in the right order of magnitude, there is a great need for field data. Another major challenge is the input data for the MFAs, which depend on market data to estimate the production of ENPs. The current information has major gaps and large uncertainties. There is also a lack of robust analytical techniques for quantifying ENP properties in complex matrices; machine learning may be able to fill this gap. Nevertheless, there has been major progress in the tools for generating PECs. With the emergence of nano- and microplastics as a leading environmental concern, some EFMs have been adapted to these materials. However, caution is needed, since most nano- and microplastics are not engineered, therefore their characteristics are difficult to generalize, and there are new fate and transport processes to consider.

Understanding species distributions and predicting future range shifts requires considering all relevant abiotic factors and biotic interactions. Resource competition has received the most attention, but reproductive interference is another widespread biotic interaction that could influence species ranges. Rubyspot damselflies (Hetaerina spp.) exhibit a biogeographic pattern consistent with the hypothesis that reproductive interference has limited range expansion. Here, we use ecological niche models to evaluate whether this pattern could have instead been caused by niche differentiation. We found evidence for climatic niche differentiation, but the species that encounters the least reproductive interference has one of the narrowest and most peripheral niches. These findings strengthen the case that reproductive interference has limited range expansion and also provide a counterexample to the idea that release from negative species interactions triggers niche expansion. We propose that release from reproductive interference enables species to expand in range while specializing on the habitats most suitable for breeding.

AbstractThis study addresses the often-overlooked chemistry of germanium compared to the extensively researched carbon and silicon. Using advanced DFT methods, we investigated the thermal decomposition of germolane (germacyclopentane). The suggested mechanisms include a 1,2-H shift and 1,1-H2 elimination to form a pentacyclic germylene (1λ2-germolane). The other pathway involves a stepwise [3 + 2] cycloreversion to form a diradical followed by ethene and germirane. Under M062X/def2-TZVP level of theory, the activation barriers in terms of Gibbs energy (ΔG‡298) for the 1,2-H shift and 1,1-H2 elimination pathways were 240.9 and 236.3 kJ/mol, respectively. The reaction energies (ΔG°298) for the initiative steps in the 1,2-H shift and 1,1-H2 elimination mechanisms were 102.9 and 96.2 kJ/mol, indicating a thermodynamic and kinetic competition between the two routes. Temperature dependence analysis from 300 to 1200 K reveals that the 1,1-H2 elimination dominates at higher temperatures and is expected to become spontaneous above 1000 K. [ABSTRACT FROM AUTHOR]

Introduction Force readiness is a priority among senior leaders across all branches of the Department of Defense. Units that do not achieve readiness benchmarks are considered non-deployable until the unit achieves the requisite benchmarks. Because military units are made up of individuals, the unit cannot be ready if the individuals within the unit are not ready. For medical personnel, this refers to one's ability to competently provide patient care in a deployed setting or their individual clinical readiness (ICR). A review of the literature found no conceptual model of ICR. Other potential concepts, such as individual medical readiness, were identified but used inconsistently. Therefore, the purpose of this article is to define ICR and propose a conceptual model to inform future efforts to achieve ICR and facilitate future study of the concept. Materials and Methods Model development occurred using a 3-step theoretical model synthesis process. The process included specification of key concepts, identification of related factors and relationships, and organizing them into an integrated network of ideas. Results ICR is the clinically oriented service members' (COSM) ability to meet the demands of the militarily relevant, assigned clinical mission. ICR leads to one's "individual clinical performance," a key concept distinct from ICR. To understand ICR, one must account for "individual characteristics," as well as one's "education," "training," and "exposure." ICR and individual clinical performance are influenced by the "quality of exposure" and the "patient care environment." One's "individual clinical performance" also reciprocally influences the patient care environment, as well as the "team's clinical performance." These factors (individual clinical performance, team clinical performance, and the patient care environment) influence "patient outcomes." In the proposed model, patient outcomes are an indirect result of ICR and its antecedents (personal characteristics, education, training, and exposure); one's individual clinical performance may not be consistent with their ICR. Patient outcomes are also influenced by the "patient environment" (external to the health care environment) and "patient characteristics"; these elements of the model do not influence ICR or individual clinical performance. Conclusion Force readiness is a Department of Defense priority. In order for military units to be deployment ready, so too must their personnel be deployment ready. For COSMs, this includes one's ability to competently provide patient care in a deployed setting or their ICR. This article defines ICR, as well as identifies another key concept and other factors associated with ICR. The proposed model is a tool for military medical leaders to communicate with and influence non-medical military leaders in the Department of Defense. Future research is needed to further refine the proposed model, determine the strength of the proposed relationships, and identify interventions to improve ICR. [ABSTRACT FROM AUTHOR]

While there are negative stereotypes against children who have been through divorce, research indicates that there are a wide range of potential outcomes children can experience after their parents' divorce. Research indicates that there are at least four protective factors that lead to positive mental health and social outcomes for children of divorce: (a) external social support, (b) self-reliance and grit, (c) positive relationships with parents, and (d) resilience and self-compassion. These protective factors are then illustrated through a narrative therapy framework, which focuses on multiple possible realities, meaning making, perception of the client as the expert of their own experience, and the role of dominant discourses in the client's life and clinical intervention. A clinical vignette is then presented, depicting a teenage girl whose parents have divorced after an especially turbulent marriage. Narrative therapy's strength is that it helps the client develop cognitive distance between their sense of self and the problems they are experiencing. However, some limitations to this presentation are that it is highly theoretical and requires further quantitative research to explore the effects of narrative therapy on clients whose parents are divorced. Further research is required to explore the wide spectrum of outcomes children can experience after divorce and how clinicians can help children reach more positive outcomes. [ABSTRACT FROM AUTHOR]

BackgroundYemen continues to endure cholera outbreaks during ongoing conflict and destructive environmental events. Air raids have been used throughout the conflict to target military and civilian infrastructure. We aimed to assess the association between air raids and cholera incidence while taking into account geographical, environmental, economic, and demographic factors that drive outbreaks.MethodsIn this ecological modelling study, we used data from Sept 12, 2016, to Dec 29, 2019, for the number of air raids, vegetation coverage, surface water, precipitation, temperature, economic variables, and cholera case and population data to model the association between conflict and the weekly incidence of cholera (per 100 000 people) in Yemen. Data were transformed into weekly intervals and governorates were categorised according to air raid severity (the number of raids in the previous 3 months). We used a negative binomial generalised additive model that accounted for geographical location and environmental, temporal, economic, and demographic variables to estimate incidence rate ratios for the association between air raid severity and cases of cholera.FindingsDuring the study period, 2 107 912 cases of cholera were reported in Yemen, and a minimum of 11 366 air raids were recorded. After controlling for relevant factors, compared with no air raids, all other levels of air raid severity were significantly associated with cholera incidence. The largest effect was noted in governorates with severe air raid levels (ie, ≥76 during the previous 3 months), which had an incidence rate ratio of 2·06 (95% CI 1·59-2·69; p

Ignorable likelihood (IL) approaches are often used to handle missing data when estimating a multivariate model, such as a structural equation model. In this case, the likelihood is based on all available data, and no model is specified for the missing data mechanism. Inference proceeds via maximum likelihood or Bayesian methods, including multiple imputation without auxiliary variables. Such IL approaches are valid under a missing at random (MAR) assumption. Rabe-Hesketh and Skrondal (Ignoring non-ignorable missingness. Presidential Address at the International Meeting of the Psychometric Society, Beijing, China, 2015; Psychometrika, 2023) consider a violation of MAR where a variable A can affect missingness of another variable B also when A is not observed. They show that this case can be handled by discarding more data before proceeding with IL approaches. This data-deletion approach is similar to the sequential estimation of Mohan et al. (in: Advances in neural information processing systems, 2013) based on their ordered factorization theorem but is preferable for parametric models. Which kind of data-deletion or ordered factorization to employ depends on the nature of the MAR violation. In this article, we therefore propose two diagnostic tests, a likelihood-ratio test for a heteroscedastic regression model and a kernel conditional independence test. We also develop a test-based estimator that first uses diagnostic tests to determine which MAR violation appears to be present and then proceeds with the corresponding data-deletion estimator. Simulations show that the test-based estimator outperforms IL when the missing data problem is severe and performs similarly otherwise.

This text is the second and final part of the article published in the previous issue (No. 42) of Almanaque Histórico Lati-noamericano on an attempt of intellectual history on the sim-ultaneous origin between dependency theory and world-systems analysis. Both parts should be read together. The aim of this sequel is precisely to deepen the argument as to why the world-systems perspective is not a mere American -or “gringo”- derivative of dependency theory. If the first part fo-cused on the “formal” aspects in terms of the theoretical properties and focal units used by the dependency theorists in their respective theoretical/historical analyses when ana-lyzed through the methodological lenses of Hopkins and Wal-lerstein, this second part will delve into the divergent “sub-stantive” aspects between the two perspectives. The latter concerns, first, the move from the comparative study of na-tional societies to the study of global totalities along with the epistemological, methodological and empirical problems this entails. Secondly, as a metatheoretical question, to criticize to what extent dependency theory really overflows or surpasses “methodological nationalism” or whether it would only con-sist of a study of the (failed) nationalization of societies in the peripheries of the world-system together with the political significance that this entails. The text concludes with a brief review of both parts and considers an early critique of the analytical text of Hopkins and Wallerstein which marked the further development of the latter's analysis of “multinational studies” in the direction of the world-system perspective.

Childhood is a period of life unique to humans. Childhood may have evolved through the need to acquire knowledge and subsistence skills. In an effort to understand the functional significance of childhood, previous research examined increases with age in returns to foraging across food resources. Such increases could be due to changes in knowledge, or other factors such as body size or strength. Here, we attempt to unpack these age-related changes. First, we estimate age-specific foraging returns for two resources. We then develop nonlinear structural equation models to evaluate the relative importance of ecological knowledge, grip strength and height in a population of part-time children foragers on Pemba island, Tanzania. We use anthropometric measures (height, strength, n = 250), estimates of ecological knowledge (n = 93) and behavioural observations for 63 individuals across 370 foraging trips. We find slower increases in foraging returns with age for trap hunting than for shellfish collection. We do not detect any effect of individual knowledge on foraging returns, potentially linked to information sharing within foraging parties. Producing accurate estimates of the distinct contribution of specific traits to an individuals foraging performance constitutes a key step in evaluating different hypotheses for the emergence of childhood.

The relationship between brain functional connectivity and structural connectivity has caught extensive attention of the neuroscience community, commonly inferred using mathematical modeling. Among many modeling approaches, spectral graph model (SGM) is distinctive as it has a closed-form solution of the wide-band frequency spectra of brain oscillations, requiring only global biophysically interpretable parameters. While SGM is parsimonious in parameters, the determination of SGM parameters is non-trivial. Prior works on SGM determine the parameters through a computational intensive annealing algorithm, which only provides a point estimate with no confidence intervals for parameter estimates. To fill this gap, we incorporate the simulation-based inference (SBI) algorithm and develop a Bayesian procedure for inferring the posterior distribution of the SGM parameters. Furthermore, using SBI dramatically reduces the computational burden for inferring the SGM parameters. We evaluate the proposed SBI-SGM framework on the resting-state magnetoencephalography recordings from healthy subjects and show that the proposed procedure has similar performance to the annealing algorithm in recovering power spectra and the spatial distribution of the alpha frequency band. In addition, we also analyze the correlations among the parameters and their uncertainty with the posterior distribution which cannot be done with annealing inference. These analyses provide a richer understanding of the interactions among biophysical parameters of the SGM. In general, the use of simulation-based Bayesian inference enables robust and efficient computations of generative model parameter uncertainties and may pave the way for the use of generative models in clinical translation applications.

Purpose – Most papers and books on conducting literature reviews primarily emphasize achieving technical quality, ensuring reproducibility and validating results. Notwithstanding the need for technical excellence, there is also a need for relevance. The purpose of this study is to address that need and offer practical and constructive suggestions for enhancing the meaningful contribution of a literature review, thereby increasing its impact and relevance for publication. Design/methodology/approach – In this conceptual paper, the authors explore strategies to enhance the relevance and contribution of a literature review. By clarifying the needs of diverse audiences and the principles of generating new insights, the authors provide a broad range of options without being prescriptive. Recognizing that every literature review is unique, this paper contrasts various approaches to offer flexible and adaptable guidance. Findings – Literature reviews can be enjoyable to read and write, offering a wide range of substantial contributions that meet the expectations of readers and journal editors. This paper offers practical suggestions for prospective authors to make their reviews more relevant, invaluable and engaging, and summarizes these suggestions in a comprehensive checklist. Research limitations/implications – The paper is not exhaustive but rather complements prevalent literature review methodologies. Originality/value – Existing literature offers limited guidance on enhancing a review’s contribution to science, academic inquiry and society. This paper fills that gap by providing both academic considerations and practical recommendations, drawing on the author’s extensive experience in reviewing and conducting literature reviews. Claves para mejorar el impacto de las revisiones de literatura: directrices para realizar contribuciones significativas Objetivo – La mayoría de los artículos y libros sobre la realización de revisiones de literatura enfatizan principalmente la obtención de calidad técnica, asegurando la reproducibilidad y validando resultados. A pesar de la necesidad de excelencia técnica, también existe la necesidad de la relevancia. El presente artículo aborda esa necesidad y tiene como objetivo ofrecer sugerencias prácticas y constructivas para mejorar la contribución significativa de una revisión de literatura, aumentando así su impacto y relevancia para su publicación. Diseño/metodología/enfoque – En este artículo conceptual, los autores exploran estrategias para mejorar la relevancia y la contribución de una revisión de literatura. Al clarificar las necesidades de audiencias diversas y los principios para generar nuevos conocimientos, los autores proporcionan una amplia gama de opciones sin ser prescriptivos. Reconociendo que cada revisión de literatura es única, este artículo contrasta varios enfoques para ofrecer orientación flexible y adaptable. Resultados – Las revisiones de literatura pueden ser placenteras de leer y escribir, ofreciendo una amplia gama de contribuciones sustanciales que satisfacen las expectativas de los lectores y editores de revistas. Este artículo ofrece sugerencias prácticas para que los autores potenciales hagan que sus revisiones sean más relevantes, valiosas y atractivas, y resume estas sugerencias en una lista de verificación integral. Originalidad – La literatura existente ofrece una orientación limitada sobre cómo mejorar la contribución de una revisión a la ciencia, la investigación académica y la sociedad. Este artículo cubre ese vacío proporcionando consideraciones académicas y recomendaciones prácticas, basadas en la extensa experiencia de los autores en la revisión y realización de revisiones de literatura. Limitaciones/implicaciones de la investigación – El artículo no es exhaustivo, sino que complementa las metodologías prevalentes de revisión de literatura. 提升文献综述影响力：提出有意义贡献的指南 目的 – 大多数关于如何进行文献综述的文章和书籍主要强调实现技术质量、确保可重复性和验证结果。尽管技术卓越性至关重要, 但同样需要注重相关性。本文正是为了满足这一需求, 旨在提供实用且建设性的建议, 以增强文献综述的有意义贡献, 从而增加其发表的影响力和相关性。 设计/方法论/途径 – 在这篇概念性文章中, 作者探讨了增强文献综述相关性和贡献的策略。通过阐明多样化受众的需求和生成新见解的原则, 作者提供了广泛的选项, 而不是一味地指示。认识到每篇文献综述都是独一无二的, 本文对比了各种方法, 以提供灵活和适应性的指导。 研究结果 – 文献综述可以既有趣味性又富有实质性贡献, 满足读者和期刊编辑的期望。本文为潜在作者提供了实用的建议, 使他们的综述更具相关性、不可或缺且引人入胜, 并将这些建议总结在一个全面的清单中。 独创性 – 现有文献对如何增强综述对科学、学术研究和社会的贡献提供的指导有限。本文通过结合学术考虑和实际建议, 弥补了这一空白, 基于作者在审阅和进行文献综述方面的丰富经验, 提供了独特的见解。 研究限制/启示 – 该文章并非详尽无遗, 而是对现有文献综述方法的补充。

Abstract Background Neoadjuvant chemotherapy followed by interval debulking surgery is currently a common treatment option for advanced epithelial ovarian cancer (EOC). The Standardized CA-125 ELIMination rate constant K (Std KELIM) and the Platinum Resistant Recurrence (PtRR) Score have been proposed as markers of tumor chemosensitivity. The aim of our study was to validate these tools for predicting platinum sensitivity in a real-world population of patients with advanced EOC treated with neoadjuvant chemotherapy. Experimental design All patients with advanced EOC treated with neoadjuvant chemotherapy at the Institut Curie between 2000 and 2015 were included. The Std KELIM was calculated with the CA-125 concentrations during the first 100 days of chemotherapy. The predictive value of Std KELIM and PtRR scores for the risk of subsequent PtRR was assessed using receiver operating characteristic (ROC) curve analysis, logistic regression and calibration curve. Kaplan–Meier survival analysis was performed for the treatment-free interval from platinum (TFIp) therapy and overall survival (OS). Results Std KELIM data were available for 149 patients. The AUC was 0.67 for PtRR. A low Std KELIM was significantly associated with PtRR (OR = 0.19 (95% CI [0.06, 0.53], p = 0.002)) according to the univariate analysis. The calibration curve of the PtRR showed a slight but significant underestimation (p = 0.02) of the probability of platinum resistance. Favorable Std KELIM (≥ 1) alone and combined with the completeness of surgery were associated with significantly better survival in terms of TFIp and OS. Conclusions Std KELIM is an early prognostic marker of chemosensitivity in a real-life setting complementary to surgical status. It could help the clinician in the early management of patients by identifying those with a worse prognosis.

This article is an exercise in intellectual history whose objec-tive is mainly to reveal the almost simultaneous origin be-tween dependency theory in Latin America and world-systems analysis in the United States since the second half of the 1960s. Here we offer in great detail and textual evidence the reasons why the world-system perspective (before having been baptized as such) is not a mere US-American (or “grin-go”) copy of dependency theory. This will be addressed, first of all, with an analysis of the “formal” aspects in the main dependency works—Dependencia y desarrollo en América Latina (1969), by Fernando Henrique Cardoso and Enzo Fa-letto; Dialéctica de la dependencia (1973), by Ruy Mauro Ma-rini; and El capitalismo dependiente latinoamericano (1974), by Vania Bambirra—through the theoretical, methodological and epistemological lenses of the essay “The Comparative Study of National Societies” published by Terence K. Hop-kins and Immanuel Wallerstein in 1967 regarding the VI World Congress of Sociology in 1966 in Evian (France). Sec-ondly, we will delve into the “substantive” aspects—that is, the methodological as well as epistemological discrepancies—between both approaches. Although they are not completely antagonistic, we want to make it clear, on the basis of their methodological and epistemological foundations, not fully discussed until now, that the lines of research in dependency theory and in world-systems analysis have divergent implica-tions.

Misophonia is commonly classified by intense emotional reactions to common everyday sounds. The condition has an impact both on the mental health of its sufferers and societally. As yet, formal models on the basis of misophonia are in their infancy. Based on developing behavioural and neuroscientific research we are gaining a growing understanding of the phenomenology and empirical findings in misophonia, such as the importance of context, types of coping strategies used and the activation of particular brain regions. In this article, we argue for a model of misophonia that includes not only the sound but also the context within which sound is perceived and the emotional reaction triggered. We review the current behavioural and neuroimaging literature, which lends support to this idea. Based on the current evidence, we propose that misophonia should be understood within the broader context of social perception and cognition, and not restricted within the narrow domain of being a disorder of auditory processing. We discuss the evidence in support of this hypothesis, as well as the implications for potential treatment approaches. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'. [ABSTRACT FROM AUTHOR]

Neuromorphic computers optimized to utilize artificial intelligence are currently receiving much attention. In this study, neural network circuit simulations are performed by varying the nonlinearity and learning rate to understand better the characteristics of the individual and parallel-connected synaptic devices. The simulation results show that pattern recognition accuracy tends to decrease with increasing nonlinearity, while the accuracy is achieved more gradually when the learning rate is reduced. By comparing the simulation results with actual experimental results, I find an ideal learning rate and investigate how to optimize neuromorphic computers. These findings will help design new neuromorphic computers to determine the appropriate learning rate. [ABSTRACT FROM AUTHOR]

The article is devoted to a topical subject of distributed generation of electrical energy. The cage and skip mine hoists of the iron ore mining enterprise were considered as generators of electrical energy. The purpose of the study is to compare theoretical and experimental data on electricity generation by mine hoisting units of the Sukha Balka PJSK (Kryvyi Rih, Ukraine). The research methods are theoretical ones - on the transformation of the potential energy of a solid body into electrical energy during its movement through a mine shaft, and experimental ones - involving instrumental measurements of the consumption and generation of electrical energy by cage and skip hoists units during industrial operation. Research schedule: collection and processing of information on the operation of the cage and skip hoists of the mine named after Frunze and similar indicators of the cage and skip hoists units of the Yuvileyna mine for the period from September 1 to December 31, 2021. The novelty of the research lies in the instrumental measurement of the electrical parameters of mine hoists in real Ukrainian operating conditions. The most significant results: it was found that the volumes of electricity generation by mine cage hoists significantly exceed the results of skip hoists. The actual indicators of electricity generation by cage hoists units are much lower than the results of theoretical estimates. There is an imbalance between the generation and consumption of energy resources - 9% for the cage elevation of the mine Frunze; about 2% for the cage hoist of the Yuvileyna mine; less than 1% on skip units. It was found that there is a statistically significant correlative relationship between the generation and consumption of electricity by the cage hoist of the mine named after Frunze and no statistically significant relationship between the generation and consumption of electricity by the cage hoist unit of the Yuvileyna mine. The electricity obtained from the daily operation of two cage and two skip units of the Sukha Balka PJSC (approximately 400 kWh) is enough to power 58 average Ukrainian households. [ABSTRACT FROM AUTHOR]

The emergence of dry gas seals has revolutionized the form of fluid sealing. The traditional research and analysis of dry gas seals is carried out by considering the lubricating medium gas as an ideal gas, but at this stage, the sealing application environment is complicated, so it is necessary to consider the real gas effect of the lubricating medium gas to expand and break through the design system of dry gas seals. We choose seven common lubricating media in dry gas seal applications and screen the optimal density expression of the real gas using different real gas equations of state. Then, we study the extent to which the compression factors of different lubricating gases deviate from the ideal gas and analyze the errors of different real gas equations of state. These results can provide an optimal expression to clarify the mechanism by which the real gas effect affects the dry gas seal performance, which helps to grasp the nature of dry gas seals, predict the dry gas seal behavior, and guide the dry gas seal application. [ABSTRACT FROM AUTHOR]

Copyright of Biomédica: Revista del Instituto Nacional de Salud is the property of Instituto Nacional de Salud of Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BackgroundThere is strong support from studies in humans and in animal models that Parkinson's disease (PD) may begin in the gut. This brings about a unique opportunity for researchers in the field of neurogastroenterology to contribute to advancing the field and making contributions that could lead to the ability to diagnose and treat PD in the premotor stages. Lack of familiarity with some of the aspects of the experimental approaches used in these studies may present a barrier for neurogastroenterology researchers to enter the field. Much remains to be understood about intestinal-specific components of gut-first PD pathogenesis and the field would benefit from contributions of enteric and central nervous system neuroscientists.PurposeTo address these issues, we have conducted a systematic review of the two most frequently used experimental models of gut-first PD: transneuronal propagation of α-synuclein preformed fibrils and oral exposure to environmental toxins. We have reviewed the details of these studies and present methodological considerations for the use of these models. Our aim is that this review will serve as a framework and useful reference for neuroscientists, gastroenterologists, and neurologists interested in applying their expertise to advancing our understanding of gut-first PD.

In this paper, we investigate the disruption of the glucose homeostasis at the whole-body level by the presence of cancer disease. Of particular interest are the potentially different responses of patients with or without hyperglycemia (including diabetes mellitus) to the cancer challenge, and how tumor growth, in turn, responds to hyperglycemia and its medical management. We propose a mathematical model that describes the competition between cancer cells and glucose-dependent healthy cells for a shared glucose resource. We also include the metabolic reprogramming of healthy cells by cancer-cell-initiated mechanism to reflect the interplay between the two cell populations. We parametrize this model and carry out numerical simulations of various scenarios, with growth of tumor mass and loss of healthy body mass as endpoints. We report sets of cancer characteristics that show plausible disease histories. We investigate parameters that change cancer cells aggressiveness, and we exhibit differing responses in diabetic and non-diabetic, in the absence or presence of glycemic control. Our model predictions are in line with observations of weight loss in cancer patients and the increased growth (or earlier onset) of tumor in diabetic individuals. The model will also aid future studies on countermeasures such as the reduction of circulating glucose in cancer patients.

The phenomenon of acoustic wave reflection off fluid-solid surfaces is the focus of this research. This research aims to measure the effect of material physical qualities on oblique incidence acoustic attenuation across a large frequency range. To construct the extensive comparison shown in the supporting documentation, reflection coefficient curves were generated by carefully adjusting the porousness and permeability of the poroelastic solid. The next stage in determining its acoustic response is to determine the pseudo-Brewster angle shift and the reflection coefficient minimum dip for the previously indicated attenuation permutations. This circumstance is made possible by modeling and studying the reflection and absorption of acoustic plane waves encountering half-space and two-layer surfaces. For this purpose, both viscous and thermal losses are taken into account. According to the research findings, the propagation medium has a significant impact on the form of the curve that represents the reflection coefficient, whereas the effects of permeability, porosity, and driving frequency are relatively less significant to the pseudo-Brewster angle and curve minima, respectively. This research additionally found that as permeability and porosity increase, the pseudo-Brewster angle shifts to the left (proportionally to porosity increase) until it reaches a limiting value of 73.4 degrees, and that the reflection coefficient curves for each level of porosity exhibit a greater angular dependence, with an overall decrease in magnitude at all incident angles. These findings are given within the framework of the investigation (in proportion to the increase in porosity). The study concluded that when permeability declined, the angular dependence of frequency-dependent attenuation reduced, resulting in iso-porous curves. The study also discovered that the matrix porosity largely affected the angular dependency of the viscous losses in the range of 1.4 × 10-14 m2 permeability.

Predator-prey interactions are one of ecology's central research themes, but with many interdisciplinary implications across the social and natural sciences. Here we consider an often-overlooked species in these interactions, namely parasites. We first show that a simple predator-prey-parasite model, inspired by the classical Lotka-Volterra equations, fails to produce a stable coexistence of all three species, thus failing to provide a biologically realistic outcome. To improve this, we introduce free space as a relevant eco-evolutionary component in a new mathematical model that uses a game-theoretical payoff matrix to describe a more realistic setup. We then show that the consideration of free space stabilizes the dynamics by means of cyclic dominance that emerges between the three species. We determine the parameter regions of coexistence as well as the types of bifurcations leading to it by means of analytical derivations as well as by means of numerical simulations. We conclude that the consideration of free space as a finite resource reveals the limits of biodiversity in predator-prey-parasite interactions, and it may also help us in the determination of factors that promote a healthy biota.

The human gut microbiome harbors substantial ecological diversity at the species level as well as at the strain level within species. In healthy hosts, species abundance fluctuations in the microbiome are thought to be stable, and these fluctuations can be described by macroecological laws. However, it is less clear how strain abundances change over time. An open question is whether individual strains behave like species themselves, exhibiting stability and following the macroecological relationships known to hold at the species level, or whether strains have different dynamics, perhaps due to the relatively close phylogenetic relatedness of cocolonizing lineages. Here, we analyze the daily dynamics of intraspecific genetic variation in the gut microbiomes of four healthy, densely longitudinally sampled hosts. First, we find that the overall genetic diversity of a large majority of species is stationary over time despite short-term fluctuations. Next, we show that fluctuations in abundances in approximately 80% of strains analyzed can be predicted with a stochastic logistic model (SLM), an ecological model of a population experiencing environmental fluctuations around a fixed carrying capacity, which has previously been shown to capture statistical properties of species abundance fluctuations. The success of this model indicates that strain abundances typically fluctuate around a fixed carrying capacity, suggesting that most strains are dynamically stable. Finally, we find that the strain abundances follow several empirical macroecological laws known to hold at the species level. Together, our results suggest that macroecological properties of the human gut microbiome, including its stability, emerge at the level of strains. IMPORTANCE To date, there has been an intense focus on the ecological dynamics of the human gut microbiome at the species level. However, there is considerable genetic diversity within species at the strain level, and these intraspecific differences can have important phenotypic effects on the host, impacting the ability to digest certain foods and metabolize drugs. Thus, to fully understand how the gut microbiome operates in times of health and sickness, its ecological dynamics may need to be quantified at the level of strains. Here, we show that a large majority of strains maintain stable abundances for periods of months to years, exhibiting fluctuations in abundance that can be well described by macroecological laws known to hold at the species level, while a smaller percentage of strains undergo rapid, directional changes in abundance. Overall, our work indicates that strains are an important unit of ecological organization in the human gut microbiome.

Patch foraging presents a sequential decision-making problem widely studied across organisms-stay with a current option or leave it in search of a better alternative? Behavioral ecology has identified an optimal strategy for these decisions, but, across species, foragers systematically deviate from it, staying too long with an option or overharvesting relative to this optimum. Despite the ubiquity of this behavior, the mechanism underlying it remains unclear and an object of extensive investigation. Here, we address this gap by approaching foraging as both a decision-making and learning problem. Specifically, we propose a model in which foragers 1) rationally infer the structure of their environment and 2) use their uncertainty over the inferred structure representation to adaptively discount future rewards. We find that overharvesting can emerge from this rational statistical inference and uncertainty adaptation process. In a patch-leaving task, we show that human participants adapt their foraging to the richness and dynamics of the environment in ways consistent with our model. These findings suggest that definitions of optimal foraging could be extended by considering how foragers reduce and adapt to uncertainty over representations of their environment.

Mainstreaming of ecosystem service approaches has been proposed as one path toward sustainable development. Meanwhile, critics of ecosystem services question if the approach can account for the multiple values of ecosystems to diverse groups of people, or for aspects of inter- and intra-generational justice. In particular, an ecosystem service approach often overlooks power dimensions and capabilities that are core to environmental justice. This article addresses the need for greater guidance on incorporating justice into ecosystem services research and practice. We point to the importance of deep engagement with stakeholders and rights holders to disentangle contextual factors that moderate justice outcomes on ecosystem service attribution and appropriation in socio-political interventions. Such a holistic perspective enables the integration of values and knowledge plurality for enhancing justice in ecosystem services research. This broadened perspective paves a way for transformative ecosystem service assessments, management, and research, which can help inform and design governance structures that nourish human agency to sustainably identify, manage, and enjoy ecosystem services for human wellbeing.

Fast fashion clothing typically has a lower price with a shorter lifecycle, resulting in more frequent purchases than traditional fashion. Consequently, consumption of fast fashion has negative consequences for the environment and society. Consistent with the lower price for fast fashion apparel, it is often lower quality and thus has lower physical durability. However, distinct from physical durability, we introduce the concept of style durability, which refers to the timelessness of the design. We propose style durability can increase clothing lifecycle as timeless clothing can be worn for extended periods without being perceived as “out of style”. In this commentary, we identify several factors that may influence a consumer’s preference for clothing with more style durability, or more classic clothing. Specifically, product-level factors such as hedonic versus utilitarian focus and experiential versus material goods may impact preference for greater style durable clothing. Additionally, consumer characteristics including self-concept clarity, self-concept continuity, and consideration of future consequences may impact the extent to which consumers choose more classic clothing. We offer future research questions that can be studied better understand how to increase consumption of style durable clothing and extend clothing lifecycles.

To date, the radiation-adaptive response has been reported as a low-dose-related phenomenon and has been associated with radiation hormesis. Well-known cancers are caused by non-radiation active reactants, in addition to radiation. A model of suppression for radiation-specific cancers was previously reported, but the model did not target radiation-nonspecific cancers. In this paper, we describe kinetic models of radiation-induced suppressors for general radiation non-specific cancers, estimating the dose M that induces the maximum hormesis effect while satisfying the condition that the risk is approximately proportional to a dose above NOAEL (No Observed Adverse Effect Level). The radiation hormesis effect is maximal when the rate constant for generation of a risk-reducing factor is the same as the rate constant for its decomposition. When the two rate constants are different, the dose M at which the radiation hormesis effect is maximized depends on both rate constants, but the dose M increases as the two rate constants approach each other, reaching a maximum dose. The theory proposed in this paper can only explain existing experiments with extremely short error bar lengths. This theory may lead to the discovery of unknown risk-reducing factor at low doses and the development of risk-reducing methods in the future.

Measurement is fundamental to all research in psychology and should be accorded greater scrutiny than typically occurs. Among other claims, McNeish and Wolf (Thinking twice about sum scores. Behavior Research Methods, 52, 2287-2305) argued that use of sum scores (a) implies that a highly constrained latent variable model underlies items comprising a scale, and (b) may misrepresent or bias relations with other criteria. The central claim by McNeish and Wolf that use of sum scores requires the assumption that a parallel test model underlies item responses is incorrect and without psychometric merit. Instead, if a set of items is unidimensional, estimators of reliability are available even if the factor model underlying the set of items does not have a highly constrained form. Thus, dimensionality of a set of items is the key issue, and whether strict constraints on parameter estimates do or do not hold dictate the appropriate way to estimate reliability. McNeish and Wolf also claimed that more precise forms of scoring, such as estimating factor scores, would be preferable to sum scores. We provide analytic bases for reliability estimation and then provide several demonstrations of reliability estimation and the relative advantages of sum scores and factor scores. We contend that several claims by McNeish and Wolf are questionable and that, as a result, multiple recommendations they made and conclusions they drew are incorrect. The upshot is that, once the dimensional structure of a set of items is verified, sum scores often have a solid psychometric basis and therefore are frequently quite adequate for psychological research.

With the worldwide increase in life span, surgical patients are becoming older and have a greater propensity for postoperative cognitive impairment, either new onset or through deterioration of an existing condition; in both conditions, knowledge of the patient's preoperative cognitive function and postoperative cognitive trajectory is imperative. We describe the clinical utility of a tablet-based technique for rapid assessment of the memory and attentiveness domains required for executive function. The pathogenic mechanisms for perioperative neurocognitive disorders have been investigated in animal models in which excessive and/or prolonged postoperative neuroinflammation has emerged as a likely contender. The cellular and molecular species involved in postoperative neuroinflammation are the putative targets for future therapeutic interventions that are efficacious and do not interfere with the surgical patient's healing process.

As modeling tools and approaches become more advanced, ecological models are becoming more complex. Traditional sensitivity analyses can struggle to identify the nonlinearities and interactions emergent from such complexity, especially across broad swaths of parameter space. This limits understanding of the ecological mechanisms underlying model behavior. Machine learning approaches are a potential answer to this issue, given their predictive ability when applied to complex large datasets. While perceptions that machine learning is a "black box" linger, we seek to illuminate its interpretive potential in ecological modeling. To do so, we detail our process of applying random forests to complex model dynamics to produce both high predictive accuracy and elucidate the ecological mechanisms driving our predictions. Specifically, we employ an empirically rooted ontogenetically stage-structured consumer-resource simulation model. Using simulation parameters as feature inputs and simulation output as dependent variables in our random forests, we extended feature analyses into a simple graphical analysis from which we reduced model behavior to three core ecological mechanisms. These ecological mechanisms reveal the complex interactions between internal plant demography and trophic allocation driving community dynamics while preserving the predictive accuracy achieved by our random forests.

Objective: The modeled CA-125 ELIMination rate constant K (KELIM) has been validated as a marker of response to chemotherapy in >12,000 patients with advanced epithelial ovarian carcinoma (EOC) treated in first-line setting enrolled in >12 clinical trials. Patient KELIM is calculable online https://www.biomarker-kinetics.org/presentation. The objective was to investigate the prognostic value of KELIM in a large real-life national cancer registry with non-selected patients. Methods: We investigated 4,025 EOC patients from the Netherlands Cancer Registry treated with neoadjuvant chemotherapy (NACT) ± followed by interval debulking surgery (IDS). Patient KELIM values were calculated in patients with ≥ 3 CA-125 measurements during NACT. KELIM was standardized with a pre-specified cut-off and scored as unfavorable/favorable (<1.0/≥1.0). KELIM's prognostic value regarding radiological response, completeness of IDS, progression-free survival (PFS), and overall survival (OS) was assessed using univariate/multivariate analyses. Results: The data from 1,582 patients treated with heterogeneous chemotherapy regimens and sequences were assessable. KELIM was prognostic for radiological response and the likelihood of complete IDS after NACT (odds ratio=2.59; 95% confidence interval [CI]=2.04-3.29). Moreover, KELIM was independently associated with PFS (hazard ratio [HR]=0.76; 95% CI=0.66-0.87), and OS (HR=0.79; 95% CI=0.69-0.91). Combining KELIM with the completeness of the IDS resulted in 3 prognostic groups (satisfactory, intermediate, and poor) with significant OS differences, namely a good, intermediate, and poor survival respectively. Conclusion: The value of KELIM, as a pragmatic indicator of response to chemotherapy, was maintained in a large real-life population-based cohort, highlighting its applicability in routine conditions. [ABSTRACT FROM AUTHOR]

Awareness of the differences in particle motion through dipolar and quadrupolar magnetic fields is vital when understanding what may occur in and around a celestial body. Astronomers need to be able to simulate particles and know what to expect with these different fields. They cannot just look through a telescope and know precisely what is happening. This paper aims to identify and record those differences. Utilizing the Boris algorithm, I will first go through two simple test cases that test the accuracy of the code. These simple test cases include uniform electric and magnetic fields. Then, I will move on to show the dipolar field and then the quadrupolar field. After that, I will compare the two and examine their important differences. These differences show themselves when putting a particle at the same point in both fields with the same initial conditions and plotting their trajectories. Through researching these differences, I found that quadrupolar magnetic fields have a greater effect on particles within them when compared to dipolar magnetic fields. In both cases, the particles follow the magnetic field lines and gyrate around them well. However, the particles are generally confined to a smaller area for quadrupolar fields. [ABSTRACT FROM AUTHOR]

Purpose: This study was conducted to develop a conceptual framework for understanding non-adherence to self-management among patients with Chronic Obstructive Pulmonary Disease (COPD). This was accomplished through a literature review, in-depth interviews with patients, and a survey of healthcare professionals featuring semi-structured open-ended questions. Methods: First, a systematic literature review was conducted across five databases. Next, 25 patients with COPD participated in detailed interviews that included seven semi-structured questions. Subsequently, 15 healthcare professionals completed a survey about factor categories and specific factors associated with non-adherence to COPD self-management. Categories and factors identified at least once across these three methods were documented. Finally, two researchers conducted preliminary mapping of the relationships between factor categories and individual factors, which was assessed for face validity by a third researcher. All processes were conducted from March 28, 2022, and January 30, 2023. Results: The research revealed eight factor categories and 53 individual factors associated with non-adherence to COPD self-management. The categories encompassed personal, socioeconomic, disease-related, functional, treatment- related, health system-related, and environmental characteristics. The literature review, patient interviews, and survey of healthcare professionals yielded 35, 19, and 44 factors, respectively. Twelve factors were identified using all three sources. All processes were conducted from March 28, 2022, and January 30, 2023. Conclusion: In this study, quantitative and qualitative methods were employed to develop a conceptual framework for non-adherence to COPD self-management. The findings indicate that effective self-management of this condition requires not only patient effort but also adaptations to complex treatment regimens, societal perceptions, and workplace environments. [ABSTRACT FROM AUTHOR]

The structure and stability of noble gas (Ng) bound [NHCM]+ complexes (M = Cu, Ag, and Au) were investigated using Quantum chemical calculations. Dissociation energies, enthalpy, and free energy changes were computed to comprehend the stability of these Ng‐bonded complexes. The nature of interactions associated to the bonding between metal and noble gas atoms was studied through the computation of electron density‐based descriptors. Detailed electronic structure study revealed electron donation from the noble gas atoms towards the metal center, resulting in the formation of dative bonds. [ABSTRACT FROM AUTHOR]

The research aims to clarify the concept of the theoretical framework and its pivotal role in conducting field social research, in addition to clarifying how to employ theoretical categories in explaining social phenomena. The research relied on the analytical-applied approach in studying the research topic. The research also concluded that theoretical selection represents one of the most important steps in the procedures of serious social research, which should be guided by a social theory from which the research hypotheses are derived, determine its approaches and methodology, and constitute the researcher's reference in the process of analysing and interpreting the studied phenomenon. The research also recommended the need to hold academic lectures and seminars in the field of sociological theories on the importance of designing a theoretical framework in directing the steps of field research. In the end, the research recommended the need to develop students' academic and applied skills in the field of employing the appropriate theoretical framework to study the research problem by holding training seminars at the bachelor's degree to acquaint them with the importance of sociological theories and their pivotal role in field research. [ABSTRACT FROM AUTHOR]

The American Behavioral Scientist (ABS) was one of the first significant journals to publish a special issue on environmental justice (EJ). The influential volume, published in 2000, bore the title Advances in EJ: Research, Theory, and Methodology. The volume contained classic EJ theoretical essays such as Taylor's "The rise of the EJ paradigm" and Pellow's "Environmental inequality formation." ABS has published other influential EJ scholarship since then. [ABSTRACT FROM AUTHOR]

After the Ministry of Education proposed the initiative to develop the future learning center, Shandong University Library conducted in-depth practical explorations from four dimensions: new spatial view, new literature and information resource view, new service view, and new team view, based on the investigation and analysis of the practical experience of peer libraries nationwide. The aim was to promote the transformation and development of university libraries, better serve the reform of higher education and talent cultivation work. Progress has been made in several fields so as to enrich the theoretical cognition and practical experience of future learning center development. [ABSTRACT FROM AUTHOR]