bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discrete constant mean curvature surfaces on general graphs
Authors: Hoffmann Tim , Kobayashi Shimpei , Ye Zi 
Published: September 2022

AbstractThe contribution of this paper is twofold. First, we generalize the definition of discrete isothermic surfaces. Compared with the previous ones, it covers more discrete surfaces, e.g., the associated families of discrete isothermic minimal and non-zero constant mean curvature (CMC in short) surfaces, whose counterpart in smooth case are isothermic surfaces. Second, we show that the discrete isothermic CMC surfaces can be obtained by the discrete holomorphic data (a solution of the additive rational Toda system) via the discrete generalized Weierstrass type representation.
Spirituality: A Key Component of the Salvation Army’s Bridge Programme Model of Treatment in Aotearoa New Zealand
Authors: Egan Richard , Gross Julien , Cameron Claire , Hobbs Linda , Patterson Tess 
Published: September 2022

AbstractSpirituality is vital to The Salvation Army’s Bridge model of treatment for alcohol and drug addiction. Spirituality is expressed through Recovery Church, prayer, spirituality lifters, the 12-step programme, and focuses on meaning and purpose. We recruited participants from several regional centers throughout Aotearoa New Zealand and evaluated spirituality using the WHOQol-SRPB and open-ended questions. Most participants held broad understandings of spirituality, only a minority equating it with religion. Participants who completed the Programme had statistically significant increases in spiritual wellbeing at end-of-treatment. These increases were maintained at a 3-month follow-up. Increases in spiritual wellbeing were associated with decreases in severity of alcohol and drug use.
Convergence Properties of Monotone and Nonmonotone Proximal Gradient Methods Revisited
Authors: Kanzow Christian , Mehlitz Patrick 
Published: September 2022

AbstractComposite optimization problems, where the sum of a smooth and a merely lower semicontinuous function has to be minimized, are often tackled numerically by means of proximal gradient methods as soon as the lower semicontinuous part of the objective function is of simple enough structure. The available convergence theory associated with these methods (mostly) requires the derivative of the smooth part of the objective function to be (globally) Lipschitz continuous, and this might be a restrictive assumption in some practically relevant scenarios. In this paper, we readdress this classical topic and provide convergence results for the classical (monotone) proximal gradient method and one of its nonmonotone extensions which are applicable in the absence of (strong) Lipschitz assumptions. This is possible since, for the price of forgoing convergence rates, we omit the use of descent-type lemmas in our analysis.
First- and Second-Order Analysis for Optimization Problems with Manifold-Valued Constraints
Authors: Bergmann Ronny , Herzog Roland , Ortiz López Julián , Schiela Anton 
Published: September 2022

AbstractWe consider optimization problems with manifold-valued constraints. These generalize classical equality and inequality constraints to a setting in which both the domain and the codomain of the constraint mapping are smooth manifolds. We model the feasible set as the preimage of a submanifold with corners of the codomain. The latter is a subset which corresponds to a convex cone locally in suitable charts. We study first- and second-order optimality conditions for this class of problems. We also show the invariance of the relevant quantities with respect to local representations of the problem.
Evaluating the influences of urban expansion on multiple ecosystem services in drylands
Authors: Song Shixiong , He Chunyang , Liu Zhifeng , Qi Tao 
Published: September 2022

Abstract
Context
Effectively estimating the influences of urban expansion on multiple ecosystem services (ESs) is of great importance for improving urban planning in drylands. However, there are some shortcomings in the existing urban expansion models, which lead to great uncertainties in the assessment of the influences of urban expansion on multiple ESs.

Objectives
This study sought to effectively estimate the influences of urban expansion on multiple ESs in drylands.

Methods
We combined the land use scenario dynamics-urban model and ES models to estimate the influences of urban expansion on habitat quality, food production, water retention, air quality regulation, sand fixation, and aesthetics.

Results
The results showed that (1) our method can effectively evaluate the influences of urban expansion on multiple ESs in drylands, and the accuracy increased by more than 20% on average. (2) Under the impacts of future urban expansion, the annual average loss per unit area of habitat quality, food production, water retention, air quality regulation, sand fixation, and aesthetics will increase. (3) Future urban expansion will occupy more cropland and grassland, which will be the main reason for the intensified degradation of multiple ESs.

Conclusions
We suggest that the local government should focus on protecting key ecosystems, especially grasslands, from urban expansion to mitigate the potential influences on multiple ESs in drylands.
Naive automated machine learning
Authors: Mohr Felix , Wever Marcel 
Published: September 2022

AbstractAn essential task of automated machine learning ($$\text {AutoML}$$
AutoML
) is the problem of automatically finding the pipeline with the best generalization performance on a given dataset. This problem has been addressed with sophisticated $$\text {black-box}$$
black-box
optimization techniques such as Bayesian optimization, grammar-based genetic algorithms, and tree search algorithms. Most of the current approaches are motivated by the assumption that optimizing the components of a pipeline in isolation may yield sub-optimal results. We present $$\text {Naive AutoML}$$

Naive AutoML

, an approach that precisely realizes such an in-isolation optimization of the different components of a pre-defined pipeline scheme. The returned pipeline is obtained by just taking the best algorithm of each slot. The isolated optimization leads to substantially reduced search spaces, and, surprisingly, this approach yields comparable and sometimes even better performance than current state-of-the-art optimizers.
Control and navigation problems for model bio-inspired microswimmers
Authors: Lolli Alberto , Corsi Giovanni , DeSimone Antonio 
Published: September 2022

AbstractNavigation problems for a model bio-inspired micro-swimmer, consisting of a cargo head and propelled by multiple rotating flagella or propellers and swimming at low Reynolds numbers, are formulated and solved. We consider both the direct problem, namely, predicting velocity and trajectories of the swimmer as a consequence of prescribed rotation rates of the propellers, and inverse problems, namely, find the rotation rates to best approximate desired translational and rotational velocities and, ultimately, target trajectories. The equations of motion of the swimmer express the balance of the forces and torques acting on the swimmer, and relate translational and rotational velocities of the cargo head to rotation rates of the propellers. The coefficients of these equations, representing hydrodynamic resistance coefficients, are evaluated numerically through a custom-built finite-element code to simulate the (Stokes) fluid flows generated by the movement of the swimmer and of its parts. Several designs of the propulsive rotors are considered: from helical flagella with different chirality to marine propellers, and their relative performance is assessed.
Towards achieving a high degree of situational awareness and multimodal interaction with AR and semantic AI in industrial applications
Authors: Izquierdo-Domenech Juan , Linares-Pellicer Jordi , Orta-Lopez Jorge 
Published: September 2022

AbstractWith its various available frameworks and possible devices, augmented reality is a proven useful tool in various industrial processes such as maintenance, repairing, training, reconfiguration, and even monitoring tasks of production lines in large factories. Despite its advantages, augmented reality still does not usually give meaning to the elements it complements, staying in a physical or geometric layer of its environment and without providing information that may be of great interest to industrial operators in carrying out their work. An expert’s remote human assistance is becoming an exciting complement in these environments, but this is expensive or even impossible in many cases. This paper shows how a machine learning semantic layer can complement augmented reality solutions in the industry by providing an intelligent layer, sometimes even beyond some expert’s skills. This layer, using state-of-the-art models, can provide visual validation and new inputs, natural language interaction, and automatic anomaly detection. All this new level of semantic context can be integrated into almost any current augmented reality system, improving the operator’s job with additional contextual information, new multimodal interaction and validation, increasing their work comfort, operational times, and security.
Systematic description of COVID-19 pandemic using exact SIR solutions and Gumbel distributions
Authors: Amaro J. E. 
Published: September 2022

AbstractAn epidemiological study is carried out in several countries analyzing the first wave of the COVID-19 pandemic using the SIR model and Gumbel distribution. The equations of the SIR model are solved exactly using the proper time as a parameter. The physical time is obtained by integration of the inverse of the infected function over proper time. Some properties of the solutions of the SIR model are studied such as time scaling and the asymmetry, which allows to obtain the basic reproduction number from the data. Approximations to the solutions of the SIR model are studied using Gumbel distributions by least squares fit or by adjusting the maximum of the infected function. Finally, the parameters of the SIR model and the Gumbel function are extracted from the death data and compared for the different countries. It is found that ten of the selected countries are very well described by the solutions of the SIR model, with a basic reproduction number between 3 and 8.
The quantitative importance of key root traits for radial water loss under low water potential
Authors: Song Zhiwei , Zonta Francesco , Ogorek Lucas León Peralta , Bastegaard Viggo Klint , Herzog Max , Pellegrini Elisa , Pedersen Ole 
Published: September 2022

Abstract

Aims
Root tissue water can be lost to the dry topsoil via radial water loss (RWL) resulting in root shrinking and loss of contact with the rhizosphere. The root barrier to radial oxygen loss (ROL) has been shown to restrict RWL, therefore we hypothesized that the inducible barrier can be formed as a response to low soil water potential and play a role, together with other root traits, in restricting RWL.

Methods
Rice and wheat were grown in hydroponics with contrasting water potential to diagnose ROL barrier formation and to explore how key root traits (ROL barrier, root diameter, root porosity) affect RWL. Moreover, we developed a numerical model predicting RWL as a function of root diameter, root porosity and presence of a barrier to ROL.

Results
Methylene blue staining showed that low water potential induced a ROL barrier formation in roots of rice, and also resulted in an apoplastic barrier, as identified by the apoplastic tracer periodic acid. The barrier significantly restricted RWL, but root diameter and tissue porosity also influenced RWL. Our numerical model was able to reflect the empirical data and clearly demonstrated that thick roots and a barrier to ROL restricts RWL while cortical porosity accelerates RWL.

Conclusions
Our modelling approach highlighted that increase in root tissue porosity, a common response to drought, conserves water when new roots are formed, but the higher desiccation risk related to high-porosity roots can be effectively counteracted by forming thick roots or even better, by a barrier to ROL.
“The Impact of Demographic Change on Transfers of Care and Associated Well-being”
Authors: Dukhovnov Denys , Ryan Joan M. , Zagheni Emilio 
Published: September 2022

AbstractThis study aims to evaluate the impact of demographic change on long-term, macro-level childcare and adult care transfers, accounting for the associated well-being effects of informal caregiving. We measure the impact of demographic change on non-monetary care exchanged between different groups by estimating matrices of time transfers by age and sex, and weighting the time flows by self-reported indicators of well-being, for activities related to childcare and adult care. The analysis employs cross-sectional data from the American Time Use Survey 2011–2013, and the Panel Study of Income Dynamics, Disability, and Use of Time Module 2013 to produce the estimates of well-being associated with the two forms of care and their future projections. Both men and women experience more positive feelings when caring for children than when caring for adults. As a whole, caregiving is an overwhelmingly more positive experience than it is negative across both genders and care types. Yet women often report more tiredness and stress than men when providing childcare, while also experiencing more pain while performing adult care, as compared to childcare activities. Women of reproductive ages spend double the amount of care time associated with negative feelings, relative to men, most of which is spent on early childcare. We project a progressively widening gender gap in terms of positive feelings related to care in the coming decades. Future reductions in absolute caregiver well-being influenced by demographic changes at the population level may reduce workforce participation, productivity, and adversely impact psycho-physical condition of caregivers, if not offset by targeted policies.
The developmental journey of therapies targeting purine receptors: from basic science to clinical trials
Authors: Han Seunga , Suzuki-Kerr Haruna , Vlajkovic Srdjan M. , Thorne Peter R. 
Published: September 2022

AbstractSince the discovery of ATP as an extracellular signalling molecule in 1972, purinergic signalling, mediated by extracellular purines and pyrimidines has been identified in virtually all mammalian tissues and is implicated in regulating fundamental cellular processes. In recent years, there has been an increasing focus on the pathophysiology and potential therapeutic interventions based on purinergic signalling. A vast range of compounds targeting purine receptors are in clinical development, and many more are in preclinical studies, which highlights the fast growth in this research field. As a tribute to Professor Geoffrey Burnstock’s legacy in purinergic signalling, we present here a brief review of compounds targeting purine receptors that are in different stages of clinical trials. The review highlights the 50-year journey from basic research on purinergic receptors to clinical applications of therapies targeting purine receptors.
Evidence-Based Quality Improvement: a Scoping Review of the Literature
Authors: Hempel Susanne , Bolshakova Maria , Turner Barbara J. , Dinalo Jennifer , Rose Danielle , Motala Aneesa , Fu Ning , Clemesha Chase G. , Rubenstein Lisa , Stockdale Susan 
Published: September 2022

Abstract
Background
Quality improvement (QI) initiatives often reflect approaches based on anecdotal evidence, but it is unclear how initiatives can best incorporate scientific literature and methods into the QI process. Review of studies of QI initiatives that aim to systematically incorporate evidence review (termed evidence-based quality improvement (EBQI)) may provide a basis for further methodological development.

Methods
In this scoping review (registration: https://osf.io/hr5bj) of EBQI, we searched the databases PubMed, CINAHL, and SCOPUS. The review addressed three central questions: How is EBQI defined? How is evidence used to inform evidence-informed QI initiatives? What is the effectiveness of EBQI?

Results
We identified 211 publications meeting inclusion criteria. In total, 170 publications explicitly used the term “EBQI.” Published definitions emphasized relying on evidence throughout the QI process. We reviewed a subset of 67 evaluations of QI initiatives in primary care, including both studies that used the term “EBQI” with those that described an evidence-based initiative without using EBQI terminology. The most frequently reported EBQI components included use of evidence to identify previously tested effective QI interventions; engaging stakeholders; iterative intervention development; partnering with frontline clinicians; and data-driven evaluation of the QI intervention. Effectiveness estimates were positive but varied in size in ten studies that provided data on patient health outcomes.

Conclusions
EBQI is a promising strategy for integrating relevant prior scientific findings and methods systematically in the QI process, from the initial developmental phase of the IQ initiative through to its evaluation. Future QI researchers and practitioners can use these findings as the basis for further development of QI initiatives.
On the Heat Treatment of Selective-Laser-Melted 316L
Authors: Morozova Iuliia , Kehm Christian , Obrosov Aleksei , Yang Yitong , Miah Kamal Uddin Mohammad , Uludintceva Elena , Fritzsche Sebastian , Weiß Sabine , Michailov Vesselin 
Published: September 2022

AbstractThe effect of heat treatment at various temperatures (650, 850, 1050, and 1100°C) and dwell times (10 min and 1 h) on the metallurgical and microstructural evolution as well as on the related tensile properties of stainless steel 316L processed by selective laser melting (SLM) has been systematically evaluated. The metallurgical and microstructural features such as defects, stability of the columnar–cellular structure and substructure, second phase particles, and phase transformation imparted by SLM and heat treatment have been discussed. It has been shown that the processing conditions specific to SLM significantly alter the kinetics of phase evolution compared to standard welding techniques which affects the accuracy of the prediction. The influence of these characteristics on tensile properties and hardness was elucidated. It was disclosed that with increasing heat treatment temperature there was a gradual increase in elongation but a decrease in strength related to the dislocation density and the development of the microstructure.
Temporal Pattern of Neuroinflammation Associated with a Low Glycemic Index Diet in the 5xFAD Mouse Model of Alzheimer’s Disease
Authors: Dafnis Ioannis , Mountaki Christina , Fanarioti Eleni , Mastellos Dimitrios C. , Karvelas Michalis , Karathanos Vaios T. , Tzinia Athina , Dermon Catherine R. , Chroni Angeliki 
Published: September 2022

Abstract
Alzheimer’s disease (AD) is associated with brain amyloid‐β (Aβ) peptide accumulation and neuroinflammation. Currants, a low glycemic index dried fruit, and their components display pleiotropic neuroprotective effects in AD. We examined how diet containing 5% Corinthian currant paste (CurD) administered in 1-month-old 5xFAD mice for 1, 3, and 6 months affects Aβ levels and neuroinflammation in comparison to control diet (ConD) or sugar-matched diet containing 3.5% glucose/fructose (GFD). No change in serum glucose or insulin levels was observed among the three groups. CurD administered for 3 months reduced brain Aβ42 levels in male mice as compared to ConD and GFD, but after 6 months, Aβ42 levels were increased in mice both on CurD and GFD compared to ConD. CurD for 3 months also reduced TNFα and IL-1β levels in male and female mouse cortex homogenates compared to ConD and GFD. However, after 6 months, TNFα levels were increased in cortex homogenates of mice both on CurD and GFD as compared to ConD. A similar pattern was observed for TNFα-expressing cells, mostly co-expressing the microglial marker CD11b, in mouse hippocampus. IL-1β levels were similarly increased in the brain of all groups after 6 months. Furthermore, a time dependent decrease of secreted TNFα levels was found in BV2 microglial cells treated with currant phenolic extract as compared to glucose/fructose solution. Overall, our findings suggest that a short-term currant consumption reduces neuroinflammation in 5xFAD mice as compared to sugar-matched or control diet, but longer-term intake of currant or sugar-matched diet enhances neuroinflammation.
Water Quality Monitoring Using Landsat 8 and Sentinel-2 Satellite Data (2014–2020) in Timsah Lake, Ismailia, Suez Canal Region (Egypt)
Authors: Seleem T. , Bafi D. , Karantzia M. , Parcharidis I. 
Published: September 2022

AbstractThe present study aims to monitor the water quality in Timsah Lake by satellite data, the largest water body in Ismailia district, Egypt. To achieve this, multi-temporal space-born data of both Landsat-8 OLI- (L1 and L2) and Sentinel-2 (2A and 2B) were used during 2014–2020. The methodologies of Case 2 regional coast colour algorithm and aquatic reflectance were applied for monitoring the physical properties of different water characteristics encompassing chlorophyll-a, total suspended matter (TSM), and aquatic reflectance. Satellite data from dry and wet seasons (2014–2020) were selected to examine seasonal and temporal variation. Comparing water quality through the dry and wet seasons (2014–2020) is to avoid the difference in atmospheric conditions and detect seasonal variations. The present study results have shown that the Western Lagoon and its streams are considered the primary source of pollution. Specifically, lower values are observed during August 2015 for TSM (4–17 g m−3) and chlorophyll-a (2–11 g m−3), while the highest values of TSM (23–50 g m−3) appear during August 2018 and for chlorophyll-a during August 2016–2018 (20–40 g m−3). For the wet season for TSM, the lowest values are observed during 2016 (3–10 g m−3), and the maximum is noticed during 2019 (13–29 g m−3); for the chlorophyll-a, maximum values are observed during 2017 (10–23 g m−3).
Perceived Social Support and Sustained Physical Activity During the COVID-19 Pandemic
Authors: Hailey Verity , Fisher Abi , Hamer Mark , Fancourt Daisy 
Published: September 2022

Abstract
Background

COVID-19 lockdown introduced substantial barriers to physical activity, providing a unique ‘natural experiment’ to understand the social factors associated with sustained physical activity. The objectives of this study were to identify the proportion of people who successfully sustained physical activity during lockdown and to explore whether social support, loneliness and social isolation were associated with maintenance of physical activity during COVID-19 lockdown.

Method
Longitudinal data from 16,980 participants, mean age 51.3 years (SD = 14.3) from the COVID-19 Social Study was used to identify a sample of participants who maintained their physical activity despite lockdown.

Results
Seventeen percent were consistently active whilst 42% were completely inactive. After adjustment for multiple confounders, high social support was associated with a 64% (95% CI 50–80%) increased odds of sustaining physical activity and medium social support was associated with 32% (95% CI 20–44%) increased odds. Associations between physical activity and loneliness and social isolation were not found.

Conclusion
This study supports previous research showing the importance of social support for the long-term maintenance of physical activity behaviour but shows that such effects extend to contexts of social restrictions.