bluuebunny/crossref_metadata_2025_split huggingface dataset:
Causes and predictors of mortality in South Africans with systemic sclerosis
Authors: Dire Zodwa , Ickinger Claudia , Tikly Mohammed 
Published: June 2023

AbstractBackgroundThere is a dearth of mortality data on systemic sclerosis (SSc) in sub‐Saharan Africa. We undertook a retrospective study of causes and predictors of death in low‐income indigent South Africans with SSc.MethodsA retrospective records review of clinicodemographic, laboratory, and outcome data of SSc patients attending a state‐funded tertiary Rheumatology service in South Africa.ResultsMost of the 164 patients were Black (92.7%) and female (87.8%). The mean (SD) age at diagnosis and follow‐up duration were 42.6 (12.9) and 5.5 (5.6) years, respectively. The majority (75.6%) had diffuse cutaneous SSc (dcSSc); and digital pits/ulcers, interstitial lung disease (ILD), and pulmonary hypertension (PH) were documented in 73.6%, 55.0%, and 38.3%, respectively. There were 56 known deaths and an equal number of patients were lost to follow‐up. Deaths resulted from ILD complicated by PH (42.9%), infections (8.9%), cardiac disease (7.1%), and malignancies (3.6%). Estimated 5‐ and 10‐year survival rates for patients with known outcomes were 58% and 42%, respectively. Independent predictors of death were renal dysfunction and cor pulmonale.ConclusionMost patients in this study of South Africans had dcSSc and poor outcomes. Known deaths resulted from cardiorespiratory complications of ILD complicated by PH. Cor pulmonale and renal dysfunction were independent predictors of death.
A deep learning factor analysis model based on importance‐weighted variational inference and normalizing flow priors: Evaluation within a set of multidimensional performance assessments in youth elite soccer players
Authors: Kilian Pascal , Leyhr Daniel , Urban Christopher J. , Höner Oliver , Kelava Augustin 
Published: June 2023

AbstractExploratory factor analysis is a widely used framework in the social and behavioral sciences. Since measurement errors are always present in human behavior data, latent factors, generating the observed data, are important to identify. While most factor analysis methods rely on linear relationships in the data‐generating process, deep learning models can provide more flexible modeling approaches. However, two problems need to be addressed. First, for interpretation, scaling assumptions are required, which can be (at least) cumbersome for deep generative models. Second, deep generative models are typically not identifiable, which is required in order to identify the underlying latent constructs. We developed a model that uses a variational autoencoder as an estimator for a complex factor analysis model based on importance‐weighted variational inference. In order to receive interpretable results and an identified model, we use a linear factor model with identification constraints in the measurement model. To maintain the flexibility of the model, we use normalizing flow latent priors. Within the evaluation of performance measures in a talent development program in soccer, we found more clarity in the separation of the identified underlying latent dimensions with our models compared to traditional PCA analyses.
Valorization of Mango By‐Products: Extraction and Characterization of Starch from Seed Kernels
Authors: Choudhary Poonam , Devi Thingujam Bidyalakshmi , Dawange Sandeep Popatrao , Narsaiah Kairam 
Published: June 2023

AbstractThis study optimizes the starch extraction process from mango seed kernels using a combined Plackett–Burman and Box–Behnken design. Further, the morphological and functional properties of extracted starch are analyzed. The particle size, temperature, time, and mixing solid–liquid ratio significantly affect the starch yield (p ≤ 0.05). The optimized conditions (0.58 mm of particle size, 39.29 min duration, temperature of 49.29 °C, and mixing solid–liquid ratio of 1:5.02 g mL−1) yield 50.34% starch with 94.95% purity. In addition, the extracted starch shows excellent lightness value with a greenish and yellowish hue. The swelling power and water solubility index are improved by increasing the temperature. The granules are round to oval and of 19.4 µm particle size and exhibit 40.08% crystallinity and an A‐type pattern under X‐ray diffraction study. In addition, the extracted starch shows more elastic behavior during rheological analysis. Results suggest that the developed process would help industries to isolate high‐quality starch at a large scale, and starch extracted in this study has the potential for various applications.
Influence of habitat and other factors on Largemouth Bass abundance in Lake Okeechobee, Florida
Authors: Hanlon Charles G. , Jordan Alyssa 
Published: June 2023

Abstract

Objective
Submerged aquatic vegetation (SAV) is an important part of shallow lake ecosystems. It provides protective cover and foraging habitat for age-0 and juvenile Largemouth Bass Micropterus salmoides and other small fish, creates structure and habitat for macroinvertebrates and other fauna, and can influence the physical environment by stabilizing sediments and reducing water column turbidity.

Methods
For this study, we reviewed annual abundance data for Largemouth Bass collected via electrofishing from 2002 to 2019, along with environmental covariates that included SAV cover (habitat) and turbidity.

Result
All age-groups of Largemouth Bass were positively correlated with vascular SAV cover. Age-0 Largemouth Bass were most abundant when SAV cover exceeded approximately 24% (9400 ha) of the littoral and nearshore area, while the juvenile and all-ages groups were most abundant when SAV cover exceeded 20% and 12% of the area, respectively. Following major storm events, water depth and turbidity increased, SAV cover was reduced to &lt;5% of the littoral and nearshore area, and the abundance of age-0 Largemouth Bass was reduced more than 90%.

Conclusion
Once removed from the landscape and exposed to turbid conditions, vascular SAV will reestablish only if water clarity increases and light is sufficient to support plant growth. Lowering water levels for an extended period has been shown to reduce nearshore turbidity and jumpstart the recovery of SAV in Lake Okeechobee and other shallow lakes globally. Without adequate SAV habitat, recruitment of age-0 and juvenile Largemouth Bass will likely be suppressed. Maintaining a minimum coverage of vascular SAV (20–35%) in the littoral and nearshore area should increase the abundance of age-0 and juvenile Largemouth Bass and provide beneficial habitat for adult Largemouth Bass and other lake fauna.
Using the diagnostic assessment and achievement of college success (DAACS) to promote SRL skills among entry‐level college students: Challenges and recommendations
Authors: Cleary Timothy J. , Bryer Jason M. , Andrade Heidi L. 
Published: June 2023

AbstractThis chapter provides an overview of a novel computer‐based learning environment, the Diagnostic Assessment and Achievement of College Success (DAACS), designed to generate and leverage diagnostic assessment data about college students’ academic and self‐regulated learning (SRL) skills to create effective success pathways for students as they transition to college life. As implemented across multiple large‐scale research projects conducted in online, hybrid, and traditional brick and mortar college contexts, DAACS integrates diagnostic assessments with automated and actionable feedback, social supports (i.e., advisors), and various open educational resources (OERs), such as an SRL Lab and writing support. In this paper, we reveal two key challenges when implementing DAACS technology, specifically in relation to student SRL functioning and skills: (1) quality and level of participation among stakeholders, and (2) uptake of diagnostic data and feedback. Through illustrative examples and recommended solutions to these challenges, readers will gain insights about a few important yet thorny issues related to implementing and using SRL‐enhanced technological supports in college contexts.
Insects of Reproductive Structures
Authors: Strong Ward B. , Mangini Alex C. , Candau Jean-Noel 
Published: June 2023

AbstractThe insects that feed on reproductive structures of forest trees are not only economically important, they are fascinating examples of the ability of insects to adapt to and exploit the many niches available in forest ecosystems. Cones, fruits, seeds, nuts, catkins and pollen are rich food sources available to insect herbivores. These reproductive structures are qualitatively and quantitatively different from vegetative parts of the tree, in terms of food quality, spatial and temporal distribution, and plant protective strategies. In this chapter we will explore types of reproductive structure herbivory, nutritive value and host defenses, insect strategies and community structure, evolutionary consequences for the host, and implications for management.
IPM: The Forest Context
Authors: Sweeney Jon , Dodds Kevin J. , Fettig Christopher J. , Carnegie Angus J. 
Published: June 2023

AbstractIntegrated pest management (IPM) is perhaps best described as “…the maintenance of destructive agents, including insects, at tolerable levels by the planned use of a variety of preventative, suppressive or regulatory tactics that are ecologically and economically efficient and socially acceptable.
Spatial Tools and ppWebGIS Platforms for Sustainable Urban Development and Climate Change Adaptation
Authors: Mougiakou Eleni , Parskevopoulos Yannis , Tsadari Sofia 
Published: June 2023

AbstractIn the last decades, a shift towards more democratic, participatory processes has occurred, rooted in the need to address environmental problems and climate change threats. Moreover, these participatory processes have been increasingly required in today’s spatial plans, strategies, and studies, for example, in Sustainable Urban Mobility Plans, Urban Climate Change Adaptation and Resilience Plans, and Sustainable Development Plans. In this context, academia and industry have built various public participation web-based solutions (ppWebGIS) and other geospatial participation tools to facilitate participatory procedures and support and inform the participants (planners, policymakers, citizens, etc.) towards spatial decision-making.However, despite the recent advancements in methodological and technological participatory geospatial tools, they are weak in addressing the complex issues found in “outlier” urban areas, i.e., areas with challenging conditions and characteristics. This paper introduces a comprehensive methodological framework for participatory spatial planning that conceptualizes and utilizes geospatial tools and platforms to address the challenges and opportunities in areas with special conditions. As part of an ongoing research program, the paper’s main contribution is to provide methodological innovation for participatory spatial planning in areas with special conditions through conceptualizing and implementing participatory geospatial tools to solve complex and multifactorial spatial problems.
Prozess- und Kostenanalyse an der Universitätsmedizin Greifswald
Authors: Krohn Markus 
Published: June 2023

ZusammenfassungIm Abschnitt 2.2.3 wurde aufgezeigt, dass die Zusatzentgelte für extrakorporale Dialyseverfahren nach Verfahrensart, Dauer und Patientenalter differenzieren. Weiterhin kann durch die OPS-Kodes eine Differenzierung nach der Antikoagulation vorgenommen werden. Eine Kostenanalyse der deutschen Arbeitsgemeinschaft für Klinische Nephrologie (DAGKN) zeigt zusätzlich, dass auch die Art des Gefäßzuganges einen Einfluss auf die Kosten haben kann.
The Sustainable Housing Challenge
Authors: Moore Trivess , Doyon Andréanne 
Published: June 2023

AbstractThis chapter explores historic, current, and future challenges that are contributing to holding back a sustainable housing transition. In doing this, we highlight a range of challenges across different domains (e.g., technical, financial, knowledge, practice). The intent of this chapter is to present some of the common challenges to help us develop an understanding of the types of things we need to address in order to scale up the provision of sustainable housing. Some of these challenges are deeply complex and play out differently at different scales. We discuss the various challenges around the scales where decisions are typically made: the dwelling scale, the neighbourhood and city scale, and the state, national and international scale. We follow this with a discussion of the wider residential market and the unwillingness to change and the complexity of housing.
Socio-Technical Dimensions for a Sustainable Housing Transition
Authors: Moore Trivess , Doyon Andréanne 
Published: June 2023

AbstractIn this chapter, we explore key socio-technical dimensions that we have identified through the wider literature and our own sustainable housing research which we feel are important to address if a transition to sustainable housing is to be achieved. The ten socio-technical dimensions we cover in this chapter are:

guiding principles,

physical attributes,

knowledge,

geography,

industrial structures and organizations,

markets, users, and power,

policy, regulations, and governance,

everyday life and practices,

culture, civil society, and social movements,

ethical aspects.

This chapter explores each dimension in turn by providing a definition, overview of how the current housing regime engages with the dimension and how sustainable housing offers a different approach. We also provide a short example of how this is being provided or considered in practice.
Facilitating the Sustainable Housing Transition
Authors: Moore Trivess , Doyon Andréanne 
Published: June 2023

AbstractIn this chapter, we reflect on the preceding chapters of the book to discuss implications of the evidence and current context for facilitating the sustainable housing transition. We do this across three core sections. (1) We discuss the importance of drawing upon sustainability transitions theory to inform the sustainable housing transitions. This includes reflections on how we need to extend the theory to align with the unique challenges of the housing sector. (2) We discuss the sustainable housing transition, including where we are placed in that transition, potential pathways forward, and challenges that still need to be addressed. (3) We reflect on the types of innovations that are required across policy, practice, and research to help facilitate the sustainable housing transition.
Relevant dilaton stabilization
Authors: Csáki Csaba , Geller Michael , Heller-Algazi Zamir , Ismail Ameen 
Published: June 2023

Abstract
We propose a simple modification of the Goldberger-Wise mechanism for stabilizing the scale of spontaneously broken conformal theories. The source of explicit conformal symmetry breaking is a relevant operator with a small coefficient, as opposed to the usual mechanism of an almost marginal operator with an order-one coefficient. In the warped 5D picture this relevant stabilization corresponds to a small tadpole for the bulk scalar on the UV brane, which can be technically natural if it is the only source for the breaking of a symmetry (for example, a discrete Z2). This modification of the stabilization mechanism has significant consequences for the nature of the conformal phase transition, since the radion/dilaton potential is no longer shallow. The bounce action is significantly reduced, leading to a weaker first-order phase transition instead of the supercooled and strongly first-order transition seen in Goldberger-Wise stabilization. This also leads to reduction of gravitational wave signals which, however, may still be observable at future detectors. We present numerical and analytical studies of the phase transition and the resulting gravitational wave signal strength, assuming that the effective dilaton potential provides a good leading approximation. While the dilaton is not expected to be generically light in this setup, in order to keep perturbative control over the effective theory one needs to mildly tune the dilaton quartic to be somewhat small.
Regularity properties of k-Brjuno and Wilton functions
Authors: Lee Seul Bee , Marmi Stefano , Petrykiewicz Izabela , Schindler Tanja I. 
Published: June 2023

AbstractWe study functions related to the classical Brjuno function, namelyk-Brjuno functions and the Wilton function. Both appear in the study of boundary regularity properties of (quasi) modular forms and their integrals. We consider various possible versions of them, based on the$$\alpha $$α-continued fraction developments. We study their BMO regularity properties and their behaviour near rational numbers of their finite truncations. We then complexify the functional equations which they fulfill and we construct analytic extensions of thek-Brjuno and Wilton functions to the upper half-plane. We study their boundary behaviour using an extension of the continued fraction algorithm to the complex plane. We also prove that the harmonic conjugate of the realk-Brjuno function is continuous at all irrational numbers and has a decreasing jump of$$\pi /q^k$$π/qkat rational pointsp/q.
Assessment of Machine Learning Methods to Predict Massive Blood Transfusion in Trauma
Authors: Strickland Matt , Nguyen Anthony , Wu Shinyi , Suen Sze‐Chuan , Mu Yanda , Del Rio Cuervo Juan , Shin Brandon J. , Kalakuntla Tej , Ghafil Cameron , Matsushima Kazuhide 
Published: June 2023

AbstractBackgroundAccurately predicting which patients are most likely to benefit from massive transfusion protocol (MTP) activation may help patients while saving blood products and limiting cost. The purpose of this study is to explore the use of modern machine learning (ML) methods to develop and validate a model that can accurately predict the need for massive blood transfusion (MBT).MethodsThe institutional trauma registry was used to identify all trauma team activation cases between June 2015 and August 2019. We used an ML framework to explore multiple ML methods including logistic regression with forward and backward selection, logistic regression with lasso and ridge regularization, support vector machines (SVM), decision tree, random forest, naive Bayes, XGBoost, AdaBoost, and neural networks. Each model was then assessed using sensitivity, specificity, positive predictive value, and negative predictive value. Model performance was compared to that of existing scores including the Assessment of Blood Consumption (ABC) and the Revised Assessment of Bleeding and Transfusion (RABT).ResultsA total of 2438 patients were included in the study, with 4.9% receiving MBT. All models besides decision tree and SVM attained an area under the curve (AUC) of above 0.75 (range: 0.75–0.83). Most of the ML models have higher sensitivity (0.55–0.83) than the ABC and RABT score (0.36 and 0.55, respectively) while maintaining comparable specificity (0.75–0.81; ABC 0.80 and RABT 0.83).ConclusionsOur ML models performed better than existing scores. Implementing an ML model in mobile computing devices or electronic health record has the potential to improve the usability.
Long-term outcomes following transcatheter aortic valve implantation with the Portico self-expanding valve
Authors: Giordano Arturo , Mas-Peiro Silvia , Fichtlscherer Stephan , Schaefer Andreas , Beyer Martin , Maisano Francesco , Ascione Guido , Buzzatti Nicola , Teles Rui , Brito João , Albuquerque Francisco , Sondergaard Lars , Vanhaverbeke Maarten , Quagliana Angelo , Costa Giuliano , Barbanti Marco , Ferraro Paolo , Morello Alberto , Cimmino Michele , Albanese Michele , Pepe Martino , Bardi Luca , Giordano Salvatore , Cittadini Antonio , Corcione Nicola , Biondi-Zoccai Giuseppe 
Published: June 2023

Abstract
Aim
Transcatheter aortic valve implantation (TAVI) is a mainstay in the management of severe aortic valve stenosis in elderly patients, but there is uncertainty on their long-term effectiveness. We aimed to assess the long-term outcome of patients undergoing TAVI with the Portico valve.

Methods
We retrospectively collected the data on patients in whom TAVI with Portico was attempted from 7 high-volume centres. Only patients theoretically eligible for 3 or more years of follow-up were included. Clinical outcomes, including death, stroke, myocardial infarction, reintervention for valve degeneration and hemodynamic valve performance were systematically assessed.

Results
A total of 803 patients were included, with 504 (62.8%) women, mean age of 82 years, median EuroSCORE II of 3.1%, and 386 (48.1%) subjects at low/moderate risk. The median follow-up was 3.0 years (3.0; 4.0). The composite of death, stroke, myocardial infarction, and reintervention for valve degeneration occurred in 37.5% (95% confidence interval: 34.1–40.9%), with all-cause death in 35.1% (31.8–38.4%), stroke in 3.4% (1.3–3.4%), myocardial infarction in 1.0% (0.3–1.5%), and reintervention for valve degeneration in 1.1% (0.6–2.1%). The mean aortic valve gradient at follow-up was 8.1 ± 4.6 mmHg, and at least moderate aortic regurgitation was present in 9.1% (6.7–12.3%). Independent predictors of major adverse events or death were: peripheral artery disease, chronic obstructive pulmonary disease, estimated glomerular filtration rate, atrial fibrillation, prior pacemaker implantation, EuroSCORE II, and reduced left ventricular ejection fraction (all p < 0.05).

Conclusions
Portico use is associated with favorable long-term clinical outcomes. Clinical outcomes were largely impacted by baseline risk factors and surgical risk.
Role of dietary sodium restriction in chronic heart failure: systematic review and meta-analysis
Authors: Urban Szymon , Fułek Michał , Błaziak Mikołaj , Fułek Katarzyna , Iwanek Gracjan , Jura Maksym , Grzesiak Magdalena , Szymański Oskar , Stańczykiewicz Bartłomiej , Ptaszkowski Kuba , Zymlinski Robert , Ponikowski Piotr , Biegus Jan 
Published: June 2023

Abstract
Background
Dietary sodium restriction remains a guidelines-approved lifestyle recommendation for chronic heart failure (CHF) patients. However, its efficacy in clinical outcome improvement is dubious.

Objective
The study evaluated whether dietary sodium restriction in CHF reduces clinical events.

Methods
We performed a systematic review of the following databases: Academic Search Ultimate, ERIC, Health Source Nursing/Academic Edition, MEDLINE, Embase, Clinicaltrials.gov and Cochrane Library (trials) to find studies analysing the impact of sodium restriction in the adult CHF population. Both observational and interventional studies were included. Exclusion criteria included i.e.: sodium consumption assessment based only on natriuresis, in-hospital interventions or mixed interventions—e.g. sodium and fluid restriction in one arm only. The review was conducted following PRISMA guidelines. Meta-analysis was performed for the endpoints reported in at least 3 papers. Analyses were conducted in Review Manager (RevMan) Version 5.4.1.

Results
Initially, we screened 9175 articles. Backward snowballing revealed 1050 additional articles. Eventually, 9 papers were evaluated in the meta-analysis. All-cause mortality, HF-related hospitalizations and the composite of mortality and hospitalisation were reported in 8, 6 and 3 articles, respectively. Sodium restriction was associated with a higher risk of the composite endpoint (OR 4.12 [95% CI 1.23–13.82]) and did not significantly affect the all-cause mortality (OR 1.38 [95% CI 0.76–2.49]) or HF hospitalisation (OR 1.63 [95% CI 0.69–3.88]).

Conclusions
In a meta-analysis, sodium restriction in CHF patients worsened the prognosis in terms of a composite of mortality and hospitalizations and did not influence all-cause mortality and HF hospitalisation rate.

Graphical abstract