bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ecological and metabolic implications of the nurse effect of Maihueniopsis camachoi in the Atacama Desert
Authors: Díaz Francisca P. , Dussarrat Thomas , Carrasco‐Puga Gabriela , Colombié Sophie , Prigent Sylvain , Decros Guillaume , Bernillon Stéphane , Cassan Cédric , Flandin Amélie , Guerrero Pablo C. , Gibon Yves , Rolin Dominique , Cavieres Lohengrin A. , Pétriacq Pierre , Latorre Claudio , Gutiérrez Rodrigo A. 
Published: November 2023

Summary

Plant–plant positive interactions are key drivers of community structure. Yet, the underlying molecular mechanisms of facilitation processes remain unexplored. We investigated the ‘nursing’ effect of Maihueniopsis camachoi, a cactus that thrives in the Atacama Desert between c. 2800 and 3800 m above sea level. We hypothesised that an important protective factor is thermal amelioration of less cold‐tolerant species with a corresponding impact on molecular phenotypes.

To test this hypothesis, we compared plant cover and temperatures within the cactus foliage with open areas and modelled the effect of temperatures on plant distribution. We combined eco‐metabolomics and machine learning to test the molecular consequences of this association.

Multiple species benefited from the interaction with M. camachoi. A conspicuous example was the extended distribution of Atriplex imbricata to colder elevations in association with M. camachoi (400 m higher as compared to plants in open areas). Metabolomics identified 93 biochemical markers predicting the interaction status of A. imbricata with 79% accuracy, independently of year.

These findings place M. camachoi as a key species in Atacama plant communities, driving local biodiversity with an impact on molecular phenotypes of nursed species. Our results support the stress‐gradient hypothesis and provide pioneer insights into the metabolic consequences of facilitation.
Racism in paradise: Being migrants in urban agriculture in Aotearoa New Zealand
Authors: Palomino‐Schalscha Marcela , Braga Bizarria Maria Teresa , Sánchez‐Bolívar Isabella 
Published: November 2023

AbstractResearch on urban agriculture (UA) has revealed that alongside the opportunities these spaces open for community building, UA can also (re)produce exclusionary practices, especially towards minority groups. Engaging with critical debates, we conducted a collective autoethnography project to explore the nuances of joining UA as Latin American migrant women of colour in Wellington, Aotearoa. We discuss how weaving critical race theory and collective autoethnography helped us reflect and amplify our counter‐stories of racial oppression. By pushing academic thinking, we also aim to inspire others to recognise, resist and rework racist (and sexist) structures, building solidarity towards decolonial and antiracist spaces.
Admission Inflammation Markers Influence Long‐term Mortality in Elderly Patients Undergoing Hip Fracture Surgery: A Retrospective Cohort Study
Authors: Long Anhua , Yang Dongxiang , Jin Lu , Zhao Feifei , Wang Xuefei , Zhang Yakui , Liu Liang 
Published: November 2023

ObjectivesHip fractures in elderly patients are associated with a high mortality rate. Most deaths associated with hip fracture result from complications after surgery. Recent studies suggest that some inflammation biomarkers may be useful to estimate excess mortality. This study aimed to investigate the prognostic value of admission inflammation biomarkers in elderly patients with hip fracture.MethodsWe reports on a retrospective study of elderly hip fracture patients admitted to a hospital in China between January 2015 and December 2019. A total of 1085 patients were included in the study, and their demographic and pre‐operative characteristics were analyzed. The inflammation biomarkers included monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), and C‐reactive protein (CRP) to albumin ratio (CAR). The predictive performance of NLR, MLR and CAR was assessed by receiver operating characteristics (ROC) curve analysis and the association between admission inflammation markers and mortality was evaluated by Cox proportional regression.ResultsThe 30‐day, 1‐year, 2‐year, and 4‐year mortality were 1.6%, 11.5%, 21.4% and 48.9%, respectively. The optimal cut‐off values of admission NLR, MLR and CAR for 1‐year mortality were 7.28, 0.76, and 1.36. After adjusting the covariates, preoperative NLR ≥ 7.28 (HR = 1.419, 95% CI: 1.080–1.864, p = 0.012) were found to be only independent risk factors with 4‐year all‐cause mortality, the preoperative CAR ≥ 1.36 was independently associated with 1‐year (HR = 1.700, 95% CI: 1.173–2.465, p = 0.005), 2 year (HR = 1.464, 95% CI: 1.107–1.936, p = 0.008), and 4‐year (HR = 1.341, 95% CI: 1.057–1.700, p = 0.016) all‐cause mortality, While age, CCI score, and low hemoglobin at admission were also risk factors for postoperative all‐cause mortality.ConclusionAdmission CAR and NLR may be useful indicators for predicting the long‐term mortality of elderly patients undergoing hip fracture surgery, and that more research is needed to validate these findings.
The trajectory of depressive symptoms over time and the presence of depressive symptoms at a single time point with the risk of dementia among US older adults: A national prospective cohort study
Authors: Du Min , Liu Min , Liu Jue 
Published: November 2023

AimThis study aims to assess the association between trajectories of depressive symptoms and the risk of dementia, and to compare the predictive ability of trajectories using multiple data points with depressive symptoms at a single data point.MethodsWe included 5306 older adults from the Health and Retirement Study. We assessed depressive symptoms using the Center for Epidemiology Depression Scale (CES‐D), and identified its 8‐ year trajectories (2002–2010) using latent class trajectory modeling. We calculated hazard ratios (HR) using Cox proportional hazards models. The concordance index (C‐index) was used to compare the discriminative power of the models.ResultsWe identified two trajectories of depressive symptoms, characterized by maintaining low CES‐D scores, and moderate starting scores that steadily increased throughout the follow‐up period. During 40,199 person‐years, compared to the low trajectory, the increasing trajectory of depressive symptoms was associated with a higher risk of dementia (HR = 1.35; 95% CI: 1.09–1.67) (C‐index = 0.759). For every point increase in the degree of depressive symptoms (CES‐D scores) in 2010, the risk of dementia increased by 7% (95% CI: 1.03–1.12) (C‐index = 0.760). The presence of depressive symptoms (CES‐D scores ≥3) in 2010 was not associated with an increased risk of dementia (HR = 1.18; 95% CI: 0.98–1.43) (C‐index = 0.759). The C‐index values of cox models showed similar discriminative power.ConclusionsThe increasing trajectory of depressive symptoms at multiple data points and the degree of depressive symptoms at a single data point were associated with an increased risk of subsequent dementia among older adults.
Mutation of MYB36 affects isoflavonoid metabolism, growth, and stress responses in Lotus japonicus
Authors: Monje‐Rueda María Dolores , Pal'ove‐Balang Peter , Trush Kristina , Márquez Antonio J. , Betti Marco , García‐Calderón Margarita 
Published: November 2023

AbstractIsoflavonoids are mostly produced by legumes although little is known about why and how legumes are able to regulate the biosynthesis of these particular compounds. Understanding the role of potential regulatory genes of the isoflavonoid biosynthetic pathway constitutes an important topic of research. The LORE1 mutation of the gene encoding the transcription factor MYB36 allowed the identification of this gene as a regulator of isoflavonoid biosynthesis in Lotus japonicus plants. The levels of several isoflavonoid compounds were considerably lower in two lines of Ljmyb36 mutant plants compared to the WT. In addition, we found that Ljmyb36 mutant plants were significantly smaller and showed a substantial decrease in the chlorophyll levels under normal growth conditions. The analysis of plants subjected to different types of abiotic stress conditions further revealed that mutant plants presented a higher sensitivity than WT plants, indicating that the MYB36 transcription factor is also involved in the stress response in L. japonicus plants.
Does Worker Well‐Being Adapt to a Pandemic? An Event Study Based on High‐Frequency Panel Data
Authors: Schmidtke Julia , Hetschko Clemens , Schöb Ronnie , Stephan Gesine , Eid Michael , Lawes Mario 
Published: November 2023

AbstractWe estimate the dynamic impact of two waves of the COVID‐19 pandemic on an exceptionally broad range of indicators of worker well‐being. Our analyses are based on high‐frequency panel data from an app‐based survey of German workers and employ an event‐study design with individual‐specific fixed effects. We find that workers' mental health decreased substantially during the first wave of the pandemic. To a smaller extent, this is also true for life satisfaction and momentary happiness. Most well‐being indicators converged to prepandemic levels when infection rates declined. During the second wave of the pandemic, overall worker well‐being decreased less than that during the first wave. Life satisfaction does not seem to have changed at all. We conclude that worker well‐being adapts to the pandemic. Moreover, subgroup analyses indicate that, in terms of well‐being, workers who took part in a job retention scheme fared less well during the pandemic than other employees.
Allocating Mental Effort in Cognitive Tasks: A Model of Motivation in the ACT‐R Cognitive Architecture
Authors: Yang Yuxue C. , Stocco Andrea 
Published: November 2023

AbstractMotivation is the driving force that influences people's behaviors and interacts with many cognitive functions. Computationally, motivation is represented as a cost−benefit analysis that weighs efforts and rewards in order to choose the optimal actions. Shenhav and colleagues proposed an elegant theory, the Expected Value of Control (EVC), which describes the relationship between cognitive efforts, costs, and rewards. In this paper, we propose a more fine‐grained and detailed motivation framework that incorporates the principles of EVC into the ACT‐R cognitive architecture. Specifically, motivation is represented as a specific slot in the Goal buffer with a corresponding scalar value, M, that is translated into the reward value Rt that is delivered when the goal is reached. This implementation is tested in two models. The first model is a high‐level model that reproduces the EVC predictions with abstract actions. The second model is an augmented version of an existing ACT‐R model of the Simon task. The motivation mechanism is shown to permit optimal effort allocation and reproduce known phenomena. Finally, the broader implications of our mechanism are discussed.
Uncertainty of supply chains: Risk and ambiguity
Authors: Kancs d'Artis 
Published: November 2023

AbstractMotivated by the recently experienced systemic shocks (the COVID‐19 pandemic and the full‐fledged Russia's war of aggression against Ukraine)—that have created new forms of uncertainties to our supplies—this paper explores the supply chain robustness under risk aversion and ambiguity aversion. We aim to understand the potential consequences of deeply uncertain systemic events on the supply chain resilience and how does the information precision affect individual agents' choices and the chain‐level preparedness to aggregate shocks. Augmenting a parsimonious supply chain model with uncertainty, we analyse the relationship between the upstream sourcing decisions and the supply chain survival probability. Both risk‐averse and ambiguity‐averse individually‐optimising agents' upstream sourcing paths are efficient but can become vulnerable to aggregate shocks. In contrast, a chain‐level coordination of downstream firm sourcing decisions can qualitatively improve the robustness of the entire supply chain compared to the individual decision‐making baseline. Such a robust decision making ensures that in the presence of an aggregate shock—independently of its realisation—part of upstream suppliers will survive and the final goods' supply will be ensured even under the most demanding circumstances. Our results also indicate that an input source diversification extracts a cost in foregone efficiency.
Spatio‐temporal dynamics of visceral leishmaniasis in Brazil: A nonlinear regression analysis
Authors: Bruhn Fábio Raphael Pascoti , Werneck Guilherme Loureiro , Barbosa David Soeiro , Câmara Daniel Cardoso Portela , Simões Taynãna César , Buzanovsky Lia Puppim , Duarte Anna Gabryela Sousa , de Melo Saulo Nascimento , Cardoso Diogo Tavares , Donato Lucas Edel , Maia‐Elkhoury Ana Nilce Silveira , Belo Vinícius Silva 
Published: November 2023

AbstractAimsThis study describes the spatio‐temporal dynamics of new visceral leishmaniasis (VL) cases notified in Brazil between 2001 and 2020.Methods and ResultsData on the occurrence of the disease were obtained by means of the Notifiable Diseases Information System of the Brazilian Ministry of Health. Joinpoint, temporal generalized additive models and conditional autoregressive (CAR) models were used to analyse the temporal evolution of the rates in Brazil, states and regions. Spatio‐temporal generalized additive and CAR models were used to identify the distribution of annual risks of VL occurrence in the Brazilian territory in relation to variation in the spatial average. There were 63,966 VL cases in the target period (3.198 cases/year), corresponding to a mean incidence rate of 1.68 cases/100,000 inhabitants. Of these, 4451 resulted in deaths, which gives a mean mortality rate of 0.12 deaths/100,000 inhabitants and a case fatality of 6.96%. The highest incidence rate was found in the North region, followed closely by the Northeast region, which presented the second and first highest mortality rates, respectively. For all of Brazil, and in the Northeast region, there were stability in the incidence rates, while the other regions showed an increasing trend in different time segments in the period: Central‐West up to 2011, North up to 2008, Southeast up to 2004, and South up to 2010. On the other hand, all regions experienced a reduction in incidence rate during the last years of the series. The Northeast region had the highest number of municipalities with statistically significant elevated relative risks. The spatio‐temporal analysis showed the highest risk area predominantly in the Northeast region in the beginning of the time series. From 2002 to 2018, this area expanded to the interior of the country.ConclusionsThe present study has shown that VL has expanded in Brazil. However, the North and Northeast regions continue to have the highest incidence, and the risk of infection has decreased in recent years.
High‐fat diet effects on contractile performance of isolated mouse soleus and extensor digitorum longus when supplemented with high dose vitamin D
Authors: Shelley Sharn P. , James Rob S. , Eustace Steven J. , Eyre Emma L. J. , Tallis Jason 
Published: November 2023

AbstractEvidence suggests vitamin D3 (VD) supplementation can reduce accumulation of adipose tissue and inflammation and promote myogenesis in obese individuals, and thus could mitigate obesity‐induced reductions in skeletal muscle (SkM) contractility. However, this is yet to be directly investigated. This study, using the work‐loop technique, examined effects of VD (cholecalciferol) supplementation on isolated SkM contractility. Female mice (n = 37) consumed standard low‐fat diet (SLD) or high‐fat diet (HFD), with or without VD (20,000 IU/kg−1) for 12 weeks. Soleus and EDL (n = 8–10 per muscle per group) were isolated and absolute and normalized (to muscle size and body mass) isometric force and power output (PO) were measured, and fatigue resistance determined. Absolute and normalized isometric force and PO of soleus were unaffected by diet (P > 0.087). However, PO normalized to body mass was reduced in HFD groups (P < 0.001). Isometric force of extensor digitorum longus (EDL) was unaffected by diet (P > 0.588). HFD reduced EDL isometric stress (P = 0.048) and absolute and normalized PO (P < 0.031), but there was no effect of VD (P > 0.493). Cumulative work during fatiguing contractions was lower in HFD groups (P < 0.043), but rate of fatigue was unaffected (P > 0.060). This study uniquely demonstrated that high‐dose VD had limited effects on SkM contractility and did not offset demonstrated adverse effects of HFD. However, small and moderate effect sizes suggest improvement in EDL muscle performance and animal morphology in HFD VD groups. Given effect sizes observed, coupled with proposed inverted U‐shaped dose‐effect curve, future investigations are needed to determine dose/duration specific responses to VD, which may culminate in improved function of HFD SkM.
Evaluating and Developing Human-Centered Design Workshops for Engagement of Co-Designers Living and Working in Sub-Saharan Africa
Authors: Wojciechowski Lauren , Himes Emily , Cheruiyot Nelson , Hamwada Turinayo Abigail , Niyonsaba Sheila , Kramer Julia 
Published: November 2023

Abstract
Co-design is an equity-centered method of human-centered design that offers the opportunity for diverse voices (including designers and those for whom a solution is being created) to design together. As experts in their own lived experiences, co-designers provide valuable insight to help contextualize the problem being solved, leading to more feasible, viable, and desirable solutions. In particular, co-design has the potential to aid design for global health equity as health issues have many complex social influences. However, methods for practicing co-design and for evaluating that practice, especially in the context of global health, are largely understudied. This study aims to fill this gap by conducting qualitative coding and thematic analysis of survey responses from co-designers engaged in human-centered design workshops in Kenya and Uganda. From this analysis, we have gained insights on the knowledge gained by co-designers, what they enjoyed about the co-design process, what was challenging for them, and what suggestions they had for improving the workshops themselves. The findings of this study reveal that while co-designers gained knowledge and had an enjoyable experience, barriers to successful co-design continue to persist, including time constraints and language barriers. This study highlights the need for further research to overcome these barriers, by refining co-design curriculum and evaluation tools, in order to achieve more successful and equitable design.
Multi-Modal Machine Learning for Vehicle Rating Predictions Using Image, Text, and Parametric Data
Authors: Su Hanqi , Song Binyang , Ahmed Faez 
Published: November 2023

Abstract
Accurate vehicle rating prediction can facilitate designing and configuring good vehicles. This prediction allows vehicle designers and manufacturers to optimize and improve their designs in a timely manner, enhance their product performance, and effectively attract consumers. However, most of the existing data-driven methods rely on data from a single mode, e.g., text, image, or parametric data, which results in a limited and incomplete exploration of the available information. These methods lack comprehensive analyses and exploration of data from multiple modes, which probably leads to inaccurate conclusions and hinders progress in this field. To overcome this limitation, we propose a multi-modal learning model for more comprehensive and accurate vehicle rating predictions. Specifically, the model simultaneously learns features from the parametric specifications, text descriptions, and images of vehicles to predict five vehicle rating scores, including the total score, critics score, performance score, safety score, and interior score. We compare the multi-modal learning model to the corresponding unimodal models and find that the multi-modal model’s explanatory power is 4%–12% higher than that of the unimodal models. On this basis, we conduct sensitivity analyses using SHAP to interpret our model and provide design and optimization directions to designers and manufacturers. Our study underscores the importance of the data-driven multi-modal learning approach for vehicle design, evaluation, and optimization. We have made the code publicly available at http://decode.mit.edu/projects/vehicleratings/.
Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data
Authors: Bhaduri Anindya , Ramachandra Nesar , Ravi Sandipp Krishnan , Luan Lele , Pandita Piyush , Balaprakash Prasanna , Anitescu Mihai , Sun Changjie , Wang Liping 
Published: November 2023

Abstract
Establishing fast and accurate structure-to-property relationships is an important component in the design and discovery of materials. Physics-based simulation models like the finite element method (FEM) are often used to predict deformation, stress, and strain fields as a function of material microstructure in material and structural systems. Such models may be computationally expensive and time intensive if the underlying physics of the system is complex. This limits their application to solve inverse design problems and identify structures that maximizes performance. In such scenarios, surrogate models are employed to make the forward mapping efficient. Still, the high dimensionality of the input microstructure and the output field of interest may render them inefficient, especially when dealing with sparse data. Deep convolutional neural network (CNN) based surrogate models have been typically found to be very useful in handling such high-dimensional problems. In this paper, the system under study is a single ellipsoidal void structure under a uniaxial tensile load represented by a linear elastic FEM model. We consider two deep CNN architectures, a modified Convolutional Autoencoder (CAE) framework with a fully connected bottleneck and a UNet Convolutional Neural Network (CNN), and compare their accuracy in predicting the Von Mises stress field for any given input void shape in the FEM model. A sensitivity analysis is also performed using the two methods, where the variation in the prediction accuracy on unseen test data is studied with the increasing number of training samples from 20 to 100.
Design and Tracking Control of a Large-Range Reluctance-Actuated Compliant Nano-Manipulator
Authors: Li Xuexuan , Liu Yijie , Zhang Zhen 
Published: November 2023

Abstract
A large-range and high-dynamic nano-manipulator system enables high-precision and high-throughput applications in manufacturing and measurement. Reluctance actuators, with their high force density and non-contact nature, are competitive for applications that require high precision and relatively large range. The successful application of reluctance actuators in single-axis compliant nano-manipulator and bi-axis compliant micro-manipulator motivates us to pursue a reluctance-actuated bi-axis compliant nano-manipulator. To address the nonlinearity caused primarily by varying motor constant and negative stiffness of the reluctance actuator, a lead compensation controller is employed to stabilize the closed-loop system. Additionally, a model-free adaptive iterative learning control (MFAILC) approach is adopted to reduce the tracking error along the iteration axis. The proposed reluctance-actuated bi-axis compliant nano-manipulator and MFAILC based controller are experimentally verified by the triangle and the spiral trajectories. When the reference is set as a 1 Hz triangle wave with amplitude of ±1 mm, the error is reduced to 66.1 nm. The results demonstrate that the manipulator is capable of achieving large-range and nanometric-precision trajectory tracking.