bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gradually increasing context‐sensitivity shapes the development of children's verb marking: A corpus study
Authors: Sawyer Hannah , Bannard Colin , Pine Julian 
Published: July 2024

AbstractThere is substantial evidence that children's apparent omission of grammatical morphemes in utterances such as “She play tennis” and “Mummy eating” is in fact errors of commission in which contextually licensed unmarked forms encountered in the input are reproduced in a context‐blind fashion. So how do children stop making such errors? In this study, we test the assumption that children's ability to recover from error is related to their developing sensitivity to longer‐range dependencies. We use a pre‐registered corpus analysis to explore the predictive value of different cues with regards to children's verb‐marking errors and observe a developmental pattern consistent with this account. We look at context‐independent cues (the identity of the specific verb being used) and at the relative value of context‐dependent cues (the identity of the specific subject+verb sequence being used). We find that the only consistent effect across a group of 2‐ to 3‐year‐olds and a group of 3‐ to 4‐year‐olds is the relative frequency of unmarked forms of specific subject+verb sequences being used. The relative frequency of unmarked forms of the verb alone is predictive only in the younger age group. This is consistent with an account in which children recover from making errors by becoming progressively more sensitive to context, at first the immediately preceding lexical contexts (e.g., the subject that precedes the verb) and eventually more distant grammatical markers (e.g., the fronted auxiliary that precedes the subject in questions).Research Highlights
We provide a corpus analysis investigating input effects on young children's verb‐marking errors (e.g., Mummy go) across development (between 2 and 4 years of age).
We find evidence that these apparent errors of omission are in fact input‐driven errors of commission that persist into the third year of life.
We compare the relative effect on error rates of context‐independent (e.g., verb) and context‐dependent (e.g., subject+verb sequence) cues across developmental time.
Our findings support the proposal that children recover from making verb‐marking errors by becoming progressively more sensitive to preceding context.
The peer mental health stigmatization scale‐revised (PMHSS‐R): Psychometric properties and cross‐cultural factorial invariance in university students in Ireland and Argentina
Authors: Tisocco Franco , Nearchou Finiki , Hennessy Eilis , Fernández Liporace Mercedes 
Published: July 2024

AbstractIntroductionThe study aimed to assess the psychometric quality of the Peer Mental Health Stigmatization Scale – Revised (PMHSS‐R), by examining its factorial structure among young adults in Ireland and Argentina.MethodA total of 429 participants aged between 18 and 25 years old were recruited (n = 187 Ireland, n = 242 Argentina). The PMHSS‐R was completed by Irish participants and was translated, pilot‐studied, and subsequently completed by Argentinian participants.ResultsA Confirmatory Factor Analysis demonstrated optimal factor loadings for an eight‐item solution and acceptable internal consistency for both scale dimensions in the Argentinian sample. Satisfactory levels of partial scalar invariance were achieved between countries, indicating that the scale measures mental health stigma consistently across cultures.Discussion and ConclusionsOur findings highlight the PMHSS‐R as a cross‐culturally valid and reliable psychometric instrument to evaluate interventions targeting stigma. In conclusion, the PMHSS‐R can be used in cross‐cultural research to compare levels of mental health stigma and investigate the interplay between stigma and other psychologically relevant constructs between different countries and cultural contexts.
Deep abdominal breathing reduces heart rate and symptoms during orthostatic challenge in patients with postural orthostatic tachycardia syndrome
Authors: Stick Moritz , Leone Ariane , Fischer Fiona , Schulz Jörg B. , Maier Andrea 
Published: July 2024

AbstractBackground and purposeThis study investigated the effects of deep abdominal breathing on cardiovascular parameters and symptoms in patients with postural orthostatic tachycardia syndrome (POTS) during head‐up tilt‐table (HUT) challenge.MethodsThirty POTS patients completed two consecutive rounds of 10‐min HUT in a crossover design. One round was HUT without intervention, and one round combined the HUT with deep breathing at a rate of 6 breaths/min. Cardiovascular parameters, including mean blood pressure and maximum and mean heart rate (HR), were measured supine and standing. Symptoms were assessed using the Vanderbilt Orthostatic Symptom Score (VOSS).ResultsDuring the breathing technique, the mean HR increase was −7.35 bpm (95% confidence interval [CI] = −11.71 to −2.98), and the maximum HR increase was −6.27 bpm (95% CI = −11.85 to −0.68, p = 0.041), significantly lower compared to normal breathing. Additionally, improvements were observed in all absolute cardiovascular parameters during standing, with VOSS symptoms simultaneously and significantly decreasing by −5.38 (95% CI = −10.43 to −0.36).ConclusionsSlow deep abdominal breathing can act as a simple technique to reduce the standing HR increase upon HUT in patients with POTS. This suggests that modulation of the cardiopulmonary neurocircuits and the respiratory pump may reduce HR increase and symptoms in patients with POTS. The findings of this study highlight the use of a safe, zero‐cost, and simple behavioral tool to suggest to POTS patients for symptom relief apart from standard treatment. The observed improvements in cardiovascular parameters and symptoms offer a promising therapeutic approach for patients in times of inadequate treatment options.
Drivers of sustainability reporting by local governments over time: A structured literature review
Authors: Mol André , van Schie Vera , Budding Tjerk 
Published: July 2024

AbstractThis paper provides an overview of the current state of the literature on sustainability reporting by local governments. It focuses on the reasons why municipalities use sustainability reporting and what contingency factors incentivize or disincentivize its implementation. The study is based on a structured literature review of 190 papers, published in journals on business, environment, and accountancy, covering a 35‐year period (1987–2021). We find that sustainability reporting by local governments can be explained from interrelated theoretical perspectives, mainly legitimacy, stakeholder, institutional, and accountability theory. The implementation of sustainability reporting is influenced by contextual factors; the main determinants are organizational and political variables. Based on the papers we reviewed, we provide policy recommendations to improve sustainability reporting in practice and make suggestions for future research.
Predictive model of the efficiency of hematopoietic stem cell collection in patients with multiple myeloma and lymphoma based on multiple peripheral blood markers
Authors: Ran Longrong , Peng Yu , Zhao Mingyu , Luo Xin , Chen Shuang , Tang Xinyi , Zhang Yakun , Li Lian , Li Liangmei , Zhang Wei , Jiang Tingting , Wu Xuelian , Hu Renzhi , Liu Yao , Yang Zailin 
Published: July 2024

AbstractIntroductionAutologous hematopoietic stem cell transplantation (ASCT) has gained extensive application in the treatment of lymphoma and multiple myeloma (MM). Plenty of studies demonstrate that peripheral blood indicators could be considered potential predictive biomarkers for hematopoietic stem cells (HSCs) collection efficiency, including white blood cell count (WBC), monocyte count (Mono), platelet count (PLT), hematocrit, and hemoglobin levels. Currently, clinically practical predictive models based on these peripheral detection indicators to quickly, conveniently, and accurately predict collection efficiency are lacking.MethodsIn total, 139 patients with MM and lymphoma undergoing mobilization and collection of ASCT were retrospectively studied. The study endpoint was successful collection of autologous HSCs. We analyzed the effects of clinical characteristics and peripheral blood markers on collection success, and screened variables to establish a prediction model. We determined the optimal cutoff value of peripheral blood markers for predicting successful stem cell collection and the clinical value of a multi‐marker prediction approach. We also established a prediction model for collection efficacy.ResultsUnivariate and multivariate logistic regression analyses showed that the mobilization regimen, Mono, PLT, mononuclear cell count (MNC), and peripheral blood CD34+ cell count (PB CD34+ counts) were significant predictors of successful collection of peripheral blood stem cells (PBSC). Two predictive models were constructed based on the results of multivariate logistic analyses. Model 1 included the mobilization regimen, Mono, PLT, and MNC, whereas Model 2 included the mobilization regimen, Mono, PLT, MNC, and PB CD34+ counts. Receiver operating characteristic (ROC) curve analysis showed that the PB CD34+ counts, Model 1, and Model 2 could predict successful HSCs collection, with cutoff values of 26.92 × 106/L, 0.548, and 0.355, respectively. Model 1 could predict successful HSCs collection with a sensitivity of 84.62%, specificity of 75.73%, and area under the curve (AUC) of 0.863. Model 2 could predict successful HSCs collection with a sensitivity of 83.52%, specificity of 94.17%, and AUC of 0.946; thus, it was superior to the PB CD34+ counts alone.ConclusionOur findings suggest that the combination of the mobilization regimen, Mono, PLT, MNC, and PB CD34+ counts before collection has predictive value for the efficacy of autologous HSCs collection in patients with MM and lymphoma. Using models based on these predictive markers may help to avoid over‐collection and improve patient outcomes.
“Knowledge is confused”: Rethinking pull factors in light of asylum and refugee integration policies
Authors: Boland Colleen , Morente Daniel , Sanchez‐Montijano Elena 
Published: July 2024

AbstractThe degree to which asylum or refugee integration policy influences a forcibly displaced individual's decision to settle in one European country versus another remains understudied, yet highly visible in policy and public debate. This work asks what explains this decision‐making via Spanish case study. The authors analyse 30 in‐depth interviews with persons seeking international protection from Spain combined with surveys among Spanish NGOs conducted in 2021. Main results firstly demonstrate that few individuals were previously aware of their intended destination's integration policies. Second, decision‐making affected by policies differs between individuals, related to socio‐demographic characteristics (origin country, age, gender). Third, EU policies serve as an auxiliary consideration. Finally, individual personal networks serve as the recurrent, principal pull factor. This paper contributes by highlighting that Spanish integration policies do not serve as a primary influence on decision‐making; instead, they serve as secondary or mediating factors, alongside the main factor of personal networks.
Using Human Resources Data to Predict Turnover of Community Mental Health Employees: Prediction and Interpretation of Machine Learning Methods
Authors: Wu Wei , Fukui Sadaaki 
Published: July 2024

ABSTRACTThis study used machine learning (ML) to predict mental health employees' turnover in the following 12 months using human resources data in a community mental health centre. The data contain 621 employees' information (e.g., demographics, job information and client information served by employees) hired between 2011 and 2021 (56.5% turned over during the study period). Six ML methods (i.e., logistic regression, elastic net, random forest [RF], gradient boosting machine [GBM], neural network and support vector machine) were used to predict turnover, along with graphical and statistical tools to interpret predictive relationship patterns and potential interactions. The result suggests that RF and GBM led to better prediction according to specificity, sensitivity and area under the curve (>0.8). The turnover predictors (e.g., past work years, work hours, wage, age, exempt status, educational degree, marital status and employee type) were identified, including those that may be unique to the mental health employee population (e.g., training hours and the proportion of clients with schizophrenia diagnosis). It also revealed nonlinear and nonmonotonic predictive relationships (e.g., wage and employee age), as well as interaction effects, such that past work years interact with other variables in turnover prediction. The study indicates that ML methods showed the predictability of mental health employee turnover using human resources data. The identified predictors and the nonlinear and interactive relationships shed light on developing new predictive models for turnover that warrant further investigations.
Fast firing of 3 mol% yttria‐stabilized zirconia: On the effect of heating rate on sintering
Authors: Biesuz Mattia , De Bona Emanuele , Manière Charles 
Published: July 2024

AbstractThe impact of rapid heating on sintering is currently getting a growing scientific interest. Previous results have shown that when considering 90 nm‐sized 3 mol% yttria‐stabilized zirconia (3YSZ) powder the heating rate effect on densification is not detectable, whereas it is huge when using finer powder (≈20 nm, specific surface area, SSA = 30–60 m2 g−1). Herein, we investigate the fast firing of ≈40 nm 3YSZ powder (SSA = 16 m2 g−1) and compare it with conventional sintering. The results show that the heating rate has a modest effect on the final density with improvements always below 2%–3% in terms of relative density. The relatively good match between fast firing and the densification behavior predicted by the master sintering curves agrees with the observed microstructural evolution, where fast‐firing provides only a modest effect on the pore size. Finally, it is shown that the heating rate does not impact the dynamics of closed pore formation.
Rheumatoid arthritis reduces the risk of colorectal cancer through immune inflammation mediation
Authors: Li Qifan , Zhou Liang , Xia Dan , Wang Jiaqian 
Published: July 2024

AbstractThere is a close relationship between immune‐mediated inflammation and cancer, and there is still controversy over whether rheumatoid arthritis (RA) increases the risk of malignancy. We first used Mendelian randomization (MR) analysis to explore the potential causal relationship between RA and pan‐cancer. And verify the effect of immune‐mediated inflammation on cancer through intermediate MR analysis. Then we extracted the standardized incidence rate of malignancy in RA patients relative to the general population through large‐scale meta‐analysis. Finally, we performed pan‐cancer analysis on the RA related genes obtained from MR analysis. And perform immune related analysis on key genes to reveal the association between RA and malignancy. The MR analysis demonstrated a negative correlation between RA and pan‐cancer (p = 0.008). Autoimmune traits were the main mediating variable for the causal relationship between RA and pan‐cancer. Based on the results of the meta‐analysis, we validated that RA reduces the risk of developing colorectal cancer (SIR = 0.69, 95% CI 0.53–0.85). Pan‐cancer analysis also showed that high expression of RA related genes was negatively correlated with colon adenocarcinoma. IL6R was the gene with the highest correlation among them, and its correlation with immune cells was higher in colorectal cancer than in other malignancy. Our MR study provides evidence that RA was associated with reduced risk of colorectal cancer. This effect is caused by immune‐mediated inflammation, with IL6R being a key regulatory gene.
A transcriptional cascade involving BBX22 and HY5 finely regulates both plant height and fruit pigmentation in citrus
Authors: Fu Jialing , Liao Li , Jin Jiajing , Lu Zhihao , Sun Juan , Song Lizhi , Huang Yue , Liu Shengjun , Huang Ding , Xu Yuantao , He Jiaxian , Hu Bin , Zhu Yiqun , Wu Fangfang , Wang Xia , Deng Xiuxin , Xu Qiang 
Published: July 2024

ABSTRACTDwarfing is a pivotal agronomic trait affecting both yield and quality. Citrus species exhibit substantial variation in plant height, among which internode length is a core element. However, the molecular mechanism governing internode elongation remains unclear. Here, we unveiled that the transcriptional cascade consisting of B‐BOX DOMAIN PROTEIN 22 (BBX22) and ELONGATED HYPOCOTYL 5 (HY5) finely tunes plant height and internode elongation in citrus. Loss‐of‐function mutations of BBX22 in an early‐flowering citrus (Citrus hindsii “SJG”) promoted internode elongation and reduced pigment accumulation, whereas ectopic expression of BBX22 in SJG, sweet orange (C. sinensis), pomelo (C. maxima) or heterologous expression of BBX22 in tomato (Solanum lycopersicum) significantly decreased internode length. Furthermore, exogenous application of gibberellin A3 (GA3) rescued the shortened internode and dwarf phenotype caused by BBX22 overexpression. Additional experiments revealed that BBX22 played a dual role in regulation internode elongation and pigmentation in citrus. On the one hand, it directly bound to and activated the expression of HY5, GA metabolism gene (GA2 OXIDASE 8, GA2ox8), carotenoid biosynthesis gene (PHYTOENE SYNTHASE 1, PSY1) and anthocyanin regulatory gene (Ruby1, a MYB DOMAIN PROTEIN). On the other hand, it acted as a cofactor of HY5, enhancing the ability of HY5 to regulate target genes expression. Together, our results reveal the critical role of the transcriptional cascade consisting of BBX22 and HY5 in controlling internode elongation and pigment accumulation in citrus. Unraveling the crosstalk regulatory mechanism between internode elongation and fruit pigmentation provides key genes for breeding of novel types with both dwarf and health‐beneficial fortification in citrus.
Does synthetic data augmentation improve the performances of machine learning classifiers for identifying health problems in patient–nurse verbal communications in home healthcare settings?
Authors: Scroggins Jihye Kim , Topaz Maxim , Song Jiyoun , Zolnoori Maryam 
Published: July 2024

AbstractBackgroundIdentifying health problems in audio‐recorded patient–nurse communication is important to improve outcomes in home healthcare patients who have complex conditions with increased risks of hospital utilization. Training machine learning classifiers for identifying problems requires resource‐intensive human annotation.ObjectiveTo generate synthetic patient–nurse communication and to automatically annotate for common health problems encountered in home healthcare settings using GPT‐4. We also examined whether augmenting real‐world patient–nurse communication with synthetic data can improve the performance of machine learning to identify health problems.DesignSecondary data analysis of patient–nurse verbal communication data in home healthcare settings.MethodsThe data were collected from one of the largest home healthcare organizations in the United States. We used 23 audio recordings of patient–nurse communications from 15 patients. The audio recordings were transcribed verbatim and manually annotated for health problems (e.g., circulation, skin, pain) indicated in the Omaha System Classification scheme. Synthetic data of patient–nurse communication were generated using the in‐context learning prompting method, enhanced by chain‐of‐thought prompting to improve the automatic annotation performance. Machine learning classifiers were applied to three training datasets: real‐world communication, synthetic communication, and real‐world communication augmented by synthetic communication.ResultsAverage F1 scores improved from 0.62 to 0.63 after training data were augmented with synthetic communication. The largest increase was observed using the XGBoost classifier where F1 scores improved from 0.61 to 0.64 (about 5% improvement). When trained solely on either real‐world communication or synthetic communication, the classifiers showed comparable F1 scores of 0.62–0.61, respectively.ConclusionIntegrating synthetic data improves machine learning classifiers' ability to identify health problems in home healthcare, with performance comparable to training on real‐world data alone, highlighting the potential of synthetic data in healthcare analytics.Clinical RelevanceThis study demonstrates the clinical relevance of leveraging synthetic patient–nurse communication data to enhance machine learning classifier performances to identify health problems in home healthcare settings, which will contribute to more accurate and efficient problem identification and detection of home healthcare patients with complex health conditions.
The Role of Informative Names in Niche Dynamics and Product Survival in a High‐Velocity Industry
Authors: Khessina Olga M. , Reis Samira 
Published: July 2024

AbstractHow do customers discover new products? Recent research has found that a firm can facilitate the discovery and subsequent purchase of its product by giving it an advantageous name. However, no product exists in isolation, rather it competes for customer attention with other products both within and across product niches. We theorize that a product may benefit from the names of competitors’ products within its niche because certain product names can trigger a positive spillover effect. Specifically, product viability should increase with the proliferation of products with informative names in a focal niche because informative names attract attention to the niche, and consequently benefit all its products, regardless of whether they have informative names or not. This beneficial influence should be especially strong when a niche is new. Additionally, a product's market fate may depend not only on the prevalent naming practices in its niche, but also on naming practices in competing niches. We find support for our theorizing in event‐history analyses of all CD‐drive products shipped in the worldwide optical disk drive industry, 1983–1999. Ultimately, our findings suggest that in high‐velocity markets, to facilitate product discovery by customers, firms should enter niches populated by products with informative names.
Shifting systems of racial inequity: Applying critical race psychology to advance racial justice
Authors: Brenick Alaina , Miller Andrea L. , Moadel‐Attie Roxanne , Salter Phia S. , Bonam Courtney M. 
Published: July 2024

AbstractSince the murder of George Floyd in 2020, a renewed and more mainstream attention to systemic racism emerged. Critical Race Theory (CRT) has permeated the larger public discourse around race more than ever before. Yet, social, scientific, and political backlash intended to silence conversations about the systemic and power‐driven nature of racism have also characterized these years. 30+ years have passed since CRT's introduction as a critical analysis of how the legal system fails minoritized groups; 20+ years have passed since CRT's introduction into the social psychological field. Although psychology provides a strong foundation for the CRT tenets, incorporating CRT into the field of psychology has lagged behind many other fields (e.g., sociology, education). In two installments, this special issue (re)introduces psychological researchers to CRT and Psychological Critical Race Theory (PCRT), underscores CRT's importance and limitations in the context of psychological research, features novel applications and directions in CRT, and addresses the current political climate of opposition to discussions of CRT. This second installment looks outward highlighting psychological research applying (P)CRT frameworks to advance racial justice. We conclude with reflections on the history of CRT and PCRT and the shifts necessary in our scholarship‐activism to dismantle systems of racial oppression.