bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidence, mortality, and predictors of acute kidney injury in patients with heart failure: a systematic review
Authors: Ru Song‐Chao , Lv Shu‐Bin , Li Zhi‐Juan 
Published: September 2023

AbstractAcute kidney injury (AKI) is common in patients with heart failure (HF), but studies have been inconsistent about the incidence of AKI in patients with HF. We conducted a meta‐analysis to examine the incidence of AKI and its impact on mortality in patients with HF. We also looked at inpatient variables that could predict the development of AKI to identify potential risk factors, so that these can be used as a starting point for intervention and prevention in this group. The Embase, Medline, PubMed, Cochrane libraries, and Web of Science databases were used for searching articles from the inception of the database to October 2022. The EndNote software was used for screening. Meta‐analysis was performed using Stata 16.0 software to combine effect sizes. A total of 37 studies were included. Of all the 3 533 583 patients with HF, 774 887 had AKI, with a pooled incidence of 33% [95% confidence interval (CI): 32–35%]. The incidence rate of AKI in acute HF and chronic HF was 36% (95% CI: 31–40%) and 30% (95% CI: 24–35%), respectively. Eleven studies found that AKI patients had higher in‐hospital mortality than non‐AKI patients [risk ratio (RR): 3.65; 95% CI: 3.04–4.39, P < 0.001]. Mortality was assessed in five studies, and it was found that mortality remained high at 1‐year follow‐up after onset of AKI (RR: 1.85, 95% CI: 1.54–2.22, P < 0.001). Fifteen admission variables were included and analysed in 13 studies. The combined results showed that diabetes, hypertension, history of chronic kidney disease, chronic HF systolic, age, N‐terminal pro‐B‐type natriuretic peptide, creatinine > 1.0 mg/dL, index estimated glomerular filtration rate < 60 mL/min/1.73 m2, blood urea nitrogen > 24 mg/dL, intravenous dobutamine, and serum albumin were predictor factors for HF patients with AKI (P < 0.05). In this meta‐analysis, AKI occurred in approximately 33% of HF patients during hospitalization and the risk of dying in the hospital was tripled. Even during 1‐year long‐term follow‐up, the risk of death remained high, and multiple inpatient variables showed that HF patients tended to have AKI. Early intervention and treatment are important to reduce the incidence of AKI and improve the prognosis.
Do unique names fit people for creative work? Implications for job recruitment, name change, and product evaluation
Authors: Bao Han‐Wu‐Shuang , Lu Huanhua , Luo Yu L. L. 
Published: September 2023

AbstractUnique names have commonly been viewed as undesirable. However, our studies (total N = 6049) suggest the opposite: unique names are perceived as favourable to creativity in occupational contexts. Generally, people held a perception that unique‐named individuals are more creative (albeit less likable) and therefore more suitable for jobs requiring greater creativity (Studies 1–2). Accordingly, participants tended to select candidates with more unique names for creative positions (Study 3) and recommend more unique names to workers in creative jobs for a name change (Study 4). Furthermore, real‐world archival data revealed that artists (typical creative professions) tended to adopt more unique new names, which was replicated cross‐culturally in American, British, and Chinese samples (Study 5), and that Chinese movie directors with more unique names received higher evaluations for the movies they directed (Study 6). Our findings demonstrate a novel form of name stereotype and its behavioural manifestations and real‐world consequences.
Social identity emergence in attitude interactions and the identity strengthening effects of cumulative attitude agreement
Authors: O'Reilly Caoimhe , Maher Paul J. , Smith Elaine M. , MacCarron Pádraig , Quayle Michael 
Published: September 2023

AbstractThe social identity approach asserts that self‐categorization is fluid and created anew in context. Despite this, research often conceptualizes identities as being based on static categories. In this article, we assess: how attitudes may be relevant attributes used to categorize the self and others, and therefore have the potential to foster social identification; how such categories/identities can be updated with new attitudinal information; and how attitudes have greater impact when socially expressed. Across three preregistered computer‐mediated interactive experiments (N = 3087), involving attitudes relating to the Ukraine‐Russia conflict of 2022, we find, identities can be updated with the introduction of new attitudes in interaction; cumulative attitude congruence strengthens identification; attitudinal interaction strengthens opinion‐based group identification and activism intentions, and ingroups can strategically align their attitudes. We conclude that to fully understand identity formation, we must acknowledge the fluidity of self‐categories and resultant identities, in line with the original specifications of the social identity approach.
The role of specialization in increasing farmers' income: Horizontal or vertical?
Authors: Chen Xi , Zhao Limei , Liu Kai 
Published: September 2023

AbstractBased on the theory of division of labor and specialization, this article attempts to address the problem of “splitting horizontal and vertical division of labor” by innovatively integrating horizontal specialization, vertical specialization, and farmers' income into a unified analytical framework. Using the data for 416 chicken farmers in four districts and counties of Guangdong Province as the sample, the theoretical framework proposed in this article is tested by constructing multiple linear regression models and structural equation models. The results are as follows: Both vertical and horizontal specialization can bolster the income of farmers, but they have different specific mechanisms of action. Vertical specialization promotes agricultural income through the mediating effect of horizontal specialization. It is evident that the discussion of horizontal specialization of farmers should not be separated from the conditions of vertical specialization. The policy effect of emphasizing horizontal specialization alone may be limited. Especially for those farmers who are limited by their own endowments and objective conditions to increase their horizontal specialization level and production scale in the short term, it is more important to promote their vertical specialization level.
Energy attenuation behavior on propane–air premixed combustion on account of nonmetallic spherical spacers in confined space with two perforated plates
Authors: Dai Huwei , Yao Dasuo , Yu Yangyang , Zhang Junhong , Wang Dan 
Published: September 2023

AbstractEnergy attenuation behavior on propane premixed combustion on account of nonmetallic spherical spacers (NSSs) was investigated in a constant volume combustion bomb with two accelerative perforated plates. The flame evolution process is captured by a photography device with schlieren. Energy attenuation effects of NSSs were explored on flame propagation, overpressures, and pressure oscillation. Normal combustion accomplished with flame acceleration, jet autoignition, deflagration, and weak detonation is observed, respectively. NSSs show a good energy attenuation effect on propane normal combustion, jet autoignition, and deflagration evolution behavior, however, during the evolution of weak detonation, the attenuation effect is relatively weak. The mean velocities difference, as well as explosion overpressure decay rate caused by NSSs, decreases from (45.70 m/s and 26.48%) to (2.70 m/s and 18.15%) when the initial pressure increases from 0.1 to 0.5 MPa, namely, attenuation effect of NSSs on propane explosion decreases with increasing initial pressure.
Deep learning‐based method for solving seepage equation under unsteady boundary
Authors: Li Daolun , Shen Luhang , Zha Wenshu , Lv Shuaijun 
Published: September 2023

AbstractDeep learning‐based methods for solving partial differential equations have become a research hotspot. The approach builds on the previous work of applying deep learning methods to partial differential equations, which avoid the need for meshing and linearization. However, deep learning‐based methods face difficulties in effectively solving complex turbulent systems without using labeled data. Moreover, issues such as failure to converge and unstable solution are frequently encountered. In light of this objective, this paper presents an approximation‐correction model designed for solving the seepage equation featuring unsteady boundaries. The model consists of two neural networks. The first network acts as an asymptotic block, estimating the progression of the solution based on its asymptotic form. The second network serves to fine‐tune any errors identified in the asymptotic block. The solution to the unsteady boundary problem is achieved by superimposing these progressive blocks. In numerical experiments, both a constant flow scenario and a three‐stage flow scenario in reservoir exploitation are considered. The obtained results show the method's effectiveness when compared to numerical solutions. Furthermore, the error analysis reveals that this method exhibits superior solution accuracy compared to other baseline methods.
Institutional agents’ perspectives of institutional support for undocumented and DACA community college students
Authors: Muñoz Susana M. , Almeida Joél Orozco , Fraile Brian Jimenez 
Published: September 2023

AbstractGiven that community colleges enroll most of the undocumented and Deferred Action for Childhood Arrivals (DACA) students across the nation, there is an economic and moral imperative to understand how the sociopolitical environment has shifted educational opportunities for undocumented and DACA students. This paper unveils how institutional agents use their agency to shape the college community college experiences of undocumented and DACA students. Findings include institutional agents’ perspectives on navigating challenges, resistance, and virtues in the current sociopolitical climate. Recommendations are discussed to enhance humanizing and holistic institutional support for DACA and undocumented college students, as well as a proposed undocuservingness framework.Practical Takeaways
It is important for insititutional agents to use legal and racial consciouness to better serve undocumented and DACA students.
Hispanic Serving Community Colleges need to unpack servingness within the context of supporting undocumented and DACA students
A computational model to uncover the biophysical underpinnings of neural firing heterogeneity in dissociated hippocampal cultures
Authors: Dhyani Vaibhav , George Kevin , Gare Suman , Venkatesh K. V. , Mitra Kishalay , Giri Lopamudra 
Published: September 2023

AbstractCalcium (Ca2+) imaging reveals a variety of correlated firing in cultures of dissociated hippocampal neurons, pinpointing the non‐synaptic paracrine release of glutamate as a possible mediator for such firing patterns, although the biophysical underpinnings remain unknown. An intriguing possibility is that extracellular glutamate could bind metabotropic receptors linked with inositol trisphosphate (IP3) mediated release of Ca2+ from the endoplasmic reticulum of individual neurons, thereby modulating neural activity in combination with sarco/endoplasmic reticulum Ca2+ transport ATPase (SERCA) and voltage‐gated Ca2+ channels (VGCC). However, the possibility that such release may occur in different neuronal compartments and can be inherently stochastic poses challenges in the characterization of such interplay between various Ca2+ channels. Here we deploy biophysical modeling in association with Monte Carlo parameter sampling to characterize such interplay and successfully predict experimentally observed Ca2+ patterns. The results show that the neurotransmitter level at the plasma membrane is the extrinsic source of heterogeneity in somatic Ca2+ transients. Our analysis, in particular, identifies the origin of such heterogeneity to an intrinsic differentiation of hippocampal neurons in terms of multiple cellular properties pertaining to intracellular Ca2+ signaling, such as VGCC, IP3 receptor, and SERCA expression. In the future, the biophysical model and parameter estimation approach used in this study can be upgraded to predict the response of a system of interconnected neurons.
Structural biomarker‐based Alzheimer's disease detection via ensemble learning techniques
Authors: Shukla Amar , Tiwari Rajeev , Tiwari Shamik 
Published: September 2023

AbstractAlzheimer's disease (AD) is a degenerative neurological disorder with incurable characteristics. To identify the substantial solution, we used a structural biomarker (structural magnetic resonance imaging) to see the neurostructural changes in the different regions of the brain of AD, mild cognitive impairment, and cognitive normal subjects. In this study, we detected the AD and their subtypes by using the traditional machine learning and ensemble learning models. It is also identified the relative impact score of various cortical and subcortical regions of AD and their subtypes. Experimental study contains two levels of classification: binary and multiclass. The Ensemble_LR_SVM model in binary classification has 99% accuracy in detection. Random forest model in the multiclass has 82% of accuracy. In the cortical‐subcortical analysis, the right hemisphere's parahippocampal and entorhinal regions were discovered to be the most influential. Similarly, the inferior temporal and isthmus cingulate regions had a significant influence in the left hemisphere.
Means testing and Social Security in the United States
Authors: Bagchi Shantanu 
Published: September 2023

AbstractThis paper uses a heterogeneous‐agent overlapping‐generations model to examine the fiscal and distributional consequences of introducing a means test in US Social Security. I find that a means test, that is, conditioning benefit payments on a household's earnings or assets, leads to a higher implicit tax on old‐age resources, but has desirable distributional effects. A 75% cut in the benefits to households with earnings of more than 200% of the median leads to a 2.3% reduction in the overall size of Social Security, but has almost no effect on average dollar benefits. In contrast, a fiscally comparable payroll tax cut leads to an across‐the‐board decline of 2% in the average dollar benefits, despite an increase in capital and labor. A fiscally comparable delay in the benefit eligibility age increases benefits for all, but negatively affects capital and labor. Finally, an asset‐based means test causes a decline of 1% in the average dollar benefits, but has a large negative effect on capital and the accidental bequests left behind by deceased households.
Poricoic acid A induces mitophagy to ameliorate podocyte injury in diabetic kidney disease via downregulating FUNDC1
Authors: Wu Yuwen , Deng Haohua , Sun Jiazhong , Tang Jun , Li Xin , Xu Yancheng 
Published: September 2023

AbstractDiabetic kidney disease (DKD) is a devastating complication of diabetes mellitus (DM) and is the most prevalent chronic kidney disease (CKD). Poricoic acid A (PAA), a component isolated from Traditional Chinese Medicine (TCM) Poria cocos, has hypoglycaemic and anti‐fibrosis effects. However, the role of PAA in DKD remains largely unclear. To mimics an in vitro model of DKD, the mouse podocyte MPC5 cells were treated with high glucose (25 mM; HG) for 24 h. CCK‐8 and flow cytometry assays were conducted for assessing MPC5 cell viability and apoptosis. Meanwhile, streptozotocin (STZ) was used to induce experimental DKD in mice by intraperitoneal injection. PAA notably inhibited the apoptosis and inflammation, reduced the generation of ROS, and elevated the MMP level in HG‐treated MPC5 cells. Moreover, PAA obviously reduced blood glucose and urine protein levels, inhibited renal fibrosis in DKD mice. Meanwhile, PAA markedly increased LC3 and ATG5 levels and declined p62 and FUNDC1 levels in HG‐treated MPC5 cells and in the kidney tissues of DKD mice, leading to the activation of cell mitophagy. Furthermore, the downregulation of FUNDC1 also inhibited apoptosis, inflammation, and promoted mitophagy in HG‐treated MPC5 cells. As expected, the knockdown of FUNDC1 further enhanced the protective role of PAA in MPC5 cells following HG treatment, indicating that induction of mitophagy could attenuate podocyte injury. Collectively, PAA could exert beneficial effects on podocyte injury in DKD by promoting mitophagy via downregulating FUNDC1. These findings suggested that PAA may have great potential in alleviating kidney injury in DKD.
Novel hydrazones derived from anthranilic acid as potent cholinesterases and α‐glycosidase inhibitors: Synthesis, characterization, and biological effects
Authors: Tokalı Feyzi Sinan , Taslimi Parham , Taskin‐Tok Tugba , Karakuş Ahmet , Sadeghian Nastaran , Gulçin İlhami 
Published: September 2023

AbstractN‐substitued anthranilic acid derivatives are commonly found in the structure of many biologically active molecules. In this study, new members of hydrazones derived from anthranilic acid (1−15) were synthesized and investigated their effect on some metabolic enzymes such as acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and α‐glycosidase (α‐Gly). Results indicated that all the molecules exhibited potent inhibitory effects against all targets as compared to the standard inhibitors, revealed by IC50 values. Ki values of compounds for AChE, BChE, and α‐Gly enzymes were obtained in the ranges 66.36 ± 8.30–153.82 ± 13.41, 52.68 ± 6.38–113.86, and 2.13 ± 0.25–2.84 nM, respectively. The molecular docking study was performed for the most active compounds to the determination of ligand–enzyme interactions. Binding affinities of the most active compound were found at the range of –9.70 to –9.00 kcal/mol for AChE, –11.60 to –10.60 kcal/mol for BChE, and −10.30 to −9.30 kcal/mol for α‐Gly. Molecular docking simulations showed that the novel compounds had preferential interaction with AChE, BChE, and α‐Gly. Drug‐likeness properties and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analyzes of all synthesized compounds (1−15) were estimated and their toxic properties were evaluated as well as their therapeutic properties. Moreover, molecular dynamics simulations were carried out to understand the accuracy of the most potent derivatives of docking studies.
Interorganizational collaboration in a trauma‐informed community: A network analysis of cohesion and change
Authors: LeBeau Kelsea , King Lindsey , Vacca Raffaele 
Published: September 2023

AbstractStrengthening interorganizational collaboration is critical to mitigate the impact of adverse childhood experiences (ACEs) and improve community health. We examined change in interorganizational collaboration around ACEs within Peace4Tarpon's network and investigated factors influencing collaboration. We conducted a community‐wide social network analysis among 32 trauma‐informed organizations in 2016 and 2018, using network analysis methods to examine interorganizational cohesion (density, transitivity, triad census) over time, and multiple regression quadratic assignment procedure to investigate factors influencing collaboration. Network cohesion measures indicated small increases in collaboration level and greater network cohesion over time. Conducting ACEs screenings was a significant factor (b = 0.237; p < 0.01) predicting likelihood of interorganizational collaboration in 2016. No assessed ACEs practices predicted collaboration in 2018, suggesting variables assessed predicted a small proportion of variance in collaboration change. Results provide a foundation for understanding how ACEs/trauma‐informed practices influence collaboration and highlight implications of interorganizational collaboration. Peace4Tarpon's 2‐year progress provides insights for other trauma‐informed communities.
Predicting body mass in Ruminantia using postcranial measurements
Authors: Wimberly Alexa N. 
Published: September 2023

AbstractSize plays an important role in mammalian ecology. Accurate prediction of body mass is therefore critical for inferring aspects of ecology in extinct mammals. The unique digestive physiology of extant ruminant artiodactyls, in particular, is suggested to place constraints on their body mass depending on the type of food resources available. Therefore, reliable body mass estimates could provide insight into the habitat preferences of extinct ruminants. While most regression equations proposed thus far have used craniodental predictors, which for ungulates may produce misleading estimates based on indirect relationships between tooth dimensions and size, postcranial bones support the body and may be more accurate predictors of body mass. Here, I use phylogenetically informed bivariate and multiple regression techniques to establish predictive equations for body mass in 101 species of extant ruminant artiodactyls based on 56 postcranial measurements. Within limb elements, stepwise multiple regression models were typically preferred, though bivariate models often received comparable support based on Akaike's information criterion scores. The globally preferred model for predicting mass is a model including both proximal and distal width of the humerus, though several models from the radioulna received comparable support. In general, widths of long bones were good predictors, while lengths and midshaft circumferences were not. Finally, I show that where the best elements for prediction are unavailable for fossil taxa, selection of the model with lowest percent prediction error for the lowest level clade to which the fossil can be assigned could be a productive and novel way forward for predicting mass and subsequently aspects of ecology in fossil mammals.
A geometric morphometric analysis of variation in Australian frog ilia and taxonomic interpretations
Authors: Farman Roy M. , Archer Michael , Hand Suzanne J. 
Published: September 2023

AbstractAnurans including frogs and toads exhibit an ilium that is often regarded as taxonomically diagnostic. The ilium, one of the three paired bones that make up the pelvic girdle, has been important in the fossil record for identifying anuran morphotypes. Osteological collections for Australian frogs are rare in herpetological museums, and skeletonizing whole‐bodied specimens requires destroying soft tissue morphology which is valuable to anuran specialists working on living species. Computed tomography scans provide the opportunity to study anuran osteology without the loss of soft tissues. Our study, based on microcomputed tomography scans of extant Australian frogs from the public repository Morphosource and from museum collections focuses on the morphological differences between Australian frogs at the familial and generic levels using geometric morphometrics to compare the diagnostic shape of the ilium. Principal component analysis (PCA) and canonical variate analysis (CVA) were conducted to assess differences in the ilium between supraspecific groups of Australian frogs. The canonical variates analysis accurately predicted group membership (i.e., the correct family) with up to 76.2% success for cross‐validated predictions and 100% of original group predictions. While the sample was limited to familial and generic level analyses, our research shows that ilial morphology in Australian frogs is taxonomically informative. This research provides a guide for identifying Australian anurans, including fossils, as well as new information relevant to considerations about their phylogenetic relationships, and the potential use of the fossil record to enhance efforts to conserve threatened living frog species.