bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of altruism on COVID-19 vaccination rates
Authors: Hierro Luis Á. , Patiño David , Atienza Pedro , Garzón Antonio J. , Cantarero David 
Published: January 2023

Abstract
Background
After the emergence of the first vaccines against the COVID-19, public health authorities have promoted mass vaccination in order to achieve herd immunity and reduce the effects of the disease. Vaccination rates have differed between countries, depending on supply (availability of resources) and demand (altruism and resistance to vaccination) factors.

Methods
This work considers the hypothesis that individuals’ health altruism has been an important factor to explain the different levels of vaccination between countries, using the number of transplants as a proxy for altruism. Taking European Union’s countries to remove, as far as possible, supply factors that might affect vaccination, we carry out cross-sectional regressions for the most favorable date of the vaccination process (maximum vaccination speed) and for each month during the vaccination campaign.

Results
Our findings confirm that altruism has affected vaccination rates against the COVID-19. We find a direct relationship between transplants rates (proxy variable) and vaccination rates during periods in which the decision to be vaccinated depended on the individual’s choice, without supply restrictions. The results show that other demand factors have worked against vaccination: political polarization and belonging to the group of countries of the former Eastern bloc.

Conclusions
Altruism is a useful tool to define future vaccination strategies, since it favors the individuals’ awareness for vaccination.
Neocosmopolitan distributions of invertebrate aquatic invasive species due to euryhaline geographic history and human-mediated dispersal: Ponto-Caspian versus other geographic origins
Authors: Dobrzycka-Krahel Aldona , Stepien Carol A. , Nuc Zofia 
Published: January 2023

Abstract
Background
Aquatic invertebrate species that have broad salinity tolerances may be pre-adapted for invasion success and biogeographic distributional range expansions, facilitated by human-mediated dispersal (HMD), leading to a trend to become neocosmopolitan across many regions of the world. This pattern appears to characterize many Ponto-Caspian (P-C) aquatic invertebrates, which have a > 100-year history as aquatic invasive species (AIS), spreading throughout much of Eurasia and for some, in North America and beyond. Our study compiles comparative salinity conditions and distributional data for AIS invertebrate species globally versus those originating from the P-C region, to test whether they statistically differ.

Results
Our investigation discerns that a total of 1861 invertebrate AIS taxa have been recorded worldwide, with (A) 70.5% exclusively living in the saline adaptive zone of brackish (0.5–30 ppt; A1) and/or marine waters (> 30 ppt; A2), (B) 20% in the freshwater adaptive zone alone (0–0.5 ppt), (C) 7.5% being euryhaline (across both A and B), and (D) 2% being semi-aquatic in either (D1) freshwater/terrestrial or (D2) saline/terrestrial environments. In contrast, our results indicate the following proportions for AIS invertebrates of P-C origins: (A) 27% exclusively inhabit the saline adaptive zone, (B) 25% are entirely freshwater, (C) 45% are euryhaline, and (D) 3% are semi-aquatic, significantly differing from the global pattern. Euryhaline AIS native to the P-C region thus markedly outnumber (45%) those originating from other regions (7.5%), likely pre-adapting them for widespread establishment in harbors, estuaries, and coastal areas. Moreover, most P-C invertebrate AIS (70%) contain freshwater-tolerant populations (B + C), rendering them very successful invaders of inland water bodies. These broad salinity tolerances of P-C AIS underlie their tremendous invasion successes and growing neocosmopolitan distributions with HMD.

Conclusions
An evolutionary and recent history of broad salinity tolerances of a large proportion of P-C invertebrates appears to enhance their ability to invade, establish, and spread in new regions, especially harbors, estuaries, and freshwaters, leading to their increasing neocosmopolitan distributions. This trend likely will continue—accelerating with climate change and increased global transportation—meriting worldwide conservation agency focus and cooperation, along with public education programs aimed to rapidly identify and circumvent new introductions and spread.
The impact of genotyping strategies and statistical models on accuracy of genomic prediction for survival in pigs
Authors: Liu Tianfei , Nielsen Bjarne , Christensen Ole F. , Lund Mogens Sandø , Su Guosheng 
Published: January 2023

AbstractBackgroundSurvival from birth to slaughter is an important economic trait in commercial pig productions. Increasing survival can improve both economic efficiency and animal welfare. The aim of this study is to explore the impact of genotyping strategies and statistical models on the accuracy of genomic prediction for survival in pigs during the total growing period from birth to slaughter. ResultsWe simulated pig populations with different direct and maternal heritabilities and used a linear mixed model, a logit model, and a probit model to predict genomic breeding values of pig survival based on data of individual survival records with binary outcomes (0, 1). The results show that in the case of only alive animals having genotype data, unbiased genomic predictions can be achieved when using variances estimated from pedigree-based model. Models using genomic information achieved up to 59.2% higher accuracy of estimated breeding value compared to pedigree-based model, dependent on genotyping scenarios. The scenario of genotyping all individuals, both dead and alive individuals, obtained the highest accuracy. When an equal number of individuals (80%) were genotyped, random sample of individuals with genotypes achieved higher accuracy than only alive individuals with genotypes. The linear model, logit model and probit model achieved similar accuracy.ConclusionsOur conclusion is that genomic prediction of pig survival is feasible in the situation that only alive pigs have genotypes, but genomic information of dead individuals can increase accuracy of genomic prediction by 2.06% to 6.04%.
Stage-specific nutritional management and developmental programming to optimize meat production
Authors: Zhao Liang , Liu Xiangdong , Gomez Noe A , Gao Yao , Son Jun Seok , Chae Song Ah , Zhu Mei-Jun , Du Min 
Published: January 2023

AbstractOver the past few decades, genetic selection and refined nutritional management have extensively been used to increase the growth rate and lean meat production of livestock. However, the rapid growth rates of modern breeds are often accompanied by a reduction in intramuscular fat deposition and increased occurrences of muscle abnormalities, impairing meat quality and processing functionality. Early stages of animal development set the long-term growth trajectory of offspring. However, due to the seasonal reproductive cycles of ruminant livestock, gestational nutrient deficiencies caused by seasonal variations, frequent droughts, and unfavorable geological locations negatively affect fetal development and their subsequent production efficiency and meat quality. Therefore, enrolling livestock in nutritional intervention strategies during gestation is effective for improving the body composition and meat quality of the offspring at harvest. These crucial early developmental stages include embryonic, fetal, and postnatal stages, which have stage-specific effects on subsequent offspring development, body composition, and meat quality. This review summarizes contemporary research in the embryonic, fetal, and neonatal development, and the impacts of maternal nutrition on the early development and programming effects on the long-term growth performance of livestock. Understanding the developmental and metabolic characteristics of skeletal muscle, adipose, and fibrotic tissues will facilitate the development of stage-specific nutritional management strategies to optimize production efficiency and meat quality.
The development progress of multi-array colourimetric sensors based on the M13 bacteriophage
Authors: Kim Sung-Jo , Lee Yujin , Choi Eun Jung , Lee Jong-Min , Kim Kwang Ho , Oh Jin-Woo 
Published: January 2023

AbstractTechniques for detecting chemicals dispersed at low concentrations in air continue to evolve. These techniques can be applied not only to manage the quality of agricultural products using a post-ripening process but also to establish a safety prevention system by detecting harmful gases and diagnosing diseases. Recently, techniques for rapid response to various chemicals and detection in complex and noisy environments have been developed using M13 bacteriophage-based sensors. In this review, M13 bacteriophage-based multi-array colourimetric sensors for the development of an electronic nose is discussed. The self-templating process was adapted to fabricate a colour band structure consisting of an M13 bacteriophage. To detect diverse target chemicals, the colour band was utilised with wild and genetically engineered M13 bacteriophages to enhance their sensing abilities. Multi-array colourimetric sensors were optimised for application in complex and noisy environments based on simulation and deep learning analysis. The development of a multi-array colourimetric sensor platform based on the M13 bacteriophage is likely to result in significant advances in the detection of various harmful gases and the diagnosis of various diseases based on exhaled gas in the future.
Adipose tissue macrophages: implications for obesity-associated cancer
Authors: Li Bei , Sun Si , Li Juan-Juan , Yuan Jing-Ping , Sun Sheng-Rong , Wu Qi 
Published: January 2023

AbstractObesity is one of the most serious global health problems, with an incidence that increases yearly and coincides with the development of cancer. Adipose tissue macrophages (ATMs) are particularly important in this context and contribute to linking obesity-related inflammation and tumor progression. However, the functions of ATMs on the progression of obesity-associated cancer remain unclear. In this review, we describe the origins, phenotypes, and functions of ATMs. Subsequently, we summarize the potential mechanisms on the reprogramming of ATMs in the obesity-associated microenvironment, including the direct exchange of dysfunctional metabolites, inordinate cytokines and other signaling mediators, transfer of extracellular vesicle cargo, and variations in the gut microbiota and its metabolites. A better understanding of the properties and functions of ATMs under conditions of obesity will lead to the development of new therapeutic interventions for obesity-related cancer.
Exploring the growth value equity valuation model with data visualization
Authors: Yeh I-Cheng , Liu Yi-Cheng 
Published: January 2023

AbstractThe Growth Value Model (GVM) proposed theoretical closed form formulas consisting of Return on Equity (ROE) and the Price-to-Book value ratio (P/B) for fair stock prices and expected rates of return. Although regression analysis can be employed to verify these theoretical closed form formulas, they cannot be explored by classical quintile or decile sorting approaches with intuition due to the essence of multi-factors and dynamical processes. This article uses visualization techniques to help intuitively explore GVM. The discerning findings and contributions of this paper is that we put forward the concept of the smart frontier, which can be regarded as the reasonable lower limit of P/B at a specific ROE by exploring fair P/B with ROE-P/B 2D dynamical process visualization. The coefficients in the formula can be determined by the quantile regression analysis with market data. The moving paths of the ROE and P/B in the current quarter and the subsequent quarters show that the portfolios at the lower right of the curve approaches this curve and stagnates here after the portfolios are formed. Furthermore, exploring expected rates of return with ROE-P/B-Return 3D dynamical process visualization, the results show that the data outside of the lower right edge of the “smart frontier” has positive quarterly return rates not only in the t + 1 quarter but also in the t + 2 quarter. The farther away the data in the t quarter is from the “smart frontier”, the larger the return rates in the t + 1 and t + 2 quarter.
Predicting abnormal trading behavior from internet rumor propagation: a machine learning approach
Authors: Cheng Li-Chen , Lu Wei-Ting , Yeo Benjamin 
Published: January 2023

AbstractIn 2021, the abnormal short-term price fluctuations of GameStop, which were triggered by internet stock discussions, drew the attention of academics, financial analysts, and stock trading commissions alike, prompting calls to address such events and maintain market stability. However, the impact of stock discussions on volatile trading behavior has received comparatively less attention than traditional fundamentals. Furthermore, data mining methods are less often used to predict stock trading despite their higher accuracy. This study adopts an innovative approach using social media data to obtain stock rumors, and then trains three decision trees to demonstrate the impact of rumor propagation on stock trading behavior. Our findings show that rumor propagation outperforms traditional fundamentals in predicting abnormal trading behavior. The study serves as an impetus for further research using data mining as a method of inquiry.
Evaluating the impact of factors in vehicle based pavement sensing implementation: sensor placement, pavement temperature, speed, and threshold
Authors: Zhang Dada , Ho Chun-Hsing , Zhang Fangfang 
Published: January 2023

AbstractThe purpose of the paper is to improve the efficiency of vehicle based sensing technology in highway pavement condition assessment by evaluating the effect of four factors (sensor placement, pavement temperature, drive speed, and threshold for pavement distress classification) and providing suggestions to better improve the accuracy of pavement condition detection and minimize the interruption of pavement sensing operation. Two I-10 corridors in the Phoenix region were selected for vibration data collection and data analysis. A series of statistical analyses were performed to determine if each one of the factors has a significant impact on the pavement distress detection. The results of Analysis of Variance (ANOVA) tests and Analysis of Covariance (ANCOVA) tests show that the placement of sensors have a significant effect in the pavement condition assessments. The significant differences occurred in the group of sensors that were placed on the same side of the vehicle, as well as, in either front wheels or rear wheels of the vehicle. The effect of pavement temperature on the vehicle based sensing implementation is significant while the mean drive speed is not seen as a significant factor in the pavement condition survey. The two thresholds were determined to select points of interest (POI; cracks, potholes) for the pavement distress classification and these POIs are in good agreement with international roughness index (IRI) data in an ArcGIS map. The findings of the paper can be used to better improve the computing algorithms of vehicle based sensing techniques.
Efficacy of psychosocial interventions for survivors of intimate partner violence: protocol for a systematic review and meta-analysis
Authors: Micklitz Hannah M. , Glass Carla M. , Bengel Jürgen , Sander Lasse B. 
Published: January 2023

Summary
Survivors of intimate partner violence (IPV) are at risk for serious health consequences, and providing effective psychosocial interventions to support these individuals is a major global health challenge. Previous systematic reviews and meta-analyses in this field do not allow for clear conclusions about the efficacy of these interventions, owing to a narrow focus on specific subpopulations or intervention formats. This protocol presents a systematic review and meta-analysis, which will provide a comprehensive overview of the empirical evidence of various psychosocial interventions for survivors of IPV and investigate their efficacy in improving safety-related, mental health and psychosocial outcomes both overall and within homogeneous subgroups (trial registration: https://osf.io/4gp95). We will systematically search the literature databases PsycInfo, MEDLINE, Embase and CENTRAL. Randomised controlled trials evaluating the efficacy of psychosocial interventions in increasing the safety or mental health of IPV survivors compared with a control group will be eligible. We will extract relevant data from eligible studies and assess study quality using the Cochrane Risk of Bias 2 (RoB 2) tool. We will qualitatively summarise the results and we will calculate weighted effect sizes under random effect model assumption for the primary outcomes IPV, depression and post-traumatic stress disorder. We will perform subgroup analyses to investigate the moderating effects of theoretical basis, delivery mode, intensity and setting of psychosocial interventions. The resultant overview of the current body of evidence for psychosocial interventions for IPV survivors is intended to inform future research and practice.
Machine Learning and Nomogram Prognostic Modeling for 2-Year Head and Neck Cancer–Specific Survival Using Electronic Health Record Data: A Multisite Study
Authors: Kotevski Damian P. , Smee Robert I. , Vajdic Claire M. , Field Matthew 
Published: January 2023

PURPOSE There is limited knowledge of the prediction of 2-year cancer-specific survival (CSS) in the head and neck cancer (HNC) population. The aim of this study is to develop and validate machine learning models and a nomogram for the prediction of 2-year CSS in patients with HNC using real-world data collected by major teaching and tertiary referral hospitals in New South Wales (NSW), Australia. MATERIALS AND METHODS Data collected in oncology information systems at multiple NSW Cancer Centres were extracted for 2,953 eligible adults diagnosed between 2000 and 2017 with squamous cell carcinoma of the head and neck. Death data were sourced from the National Death Index using record linkage. Machine learning and Cox regression/nomogram models were developed and internally validated in Python and R, respectively. RESULTS Machine learning models demonstrated highest performance (C-index) in the larynx and nasopharynx cohorts (0.82), followed by the oropharynx (0.79) and the hypopharynx and oral cavity cohorts (0.73). In the whole HNC population, C-indexes of 0.79 and 0.70 and Brier scores of 0.10 and 0.27 were reported for the machine learning and nomogram model, respectively. Cox regression analysis identified age, T and N classification, and time-corrected biologic equivalent dose in two gray fractions as independent prognostic factors for 2-year CSS. N classification was the most important feature used for prediction in the machine learning model followed by age. CONCLUSION Machine learning and nomogram analysis predicted 2-year CSS with high performance using routinely collected and complete clinical information extracted from oncology information systems. These models function as visual decision-making tools to guide radiotherapy treatment decisions and provide insight into the prediction of survival outcomes in patients with HNC.
On the Hermitian momentum of Wigner-Dunkl quantum mechanics
Authors: Chung Won Sang , Junker Georg , Dong Shi-Hai , Hassanabadi Hassan 
Published: January 2023

Abstract
In this paper the Hermitian momentum operator on the usual Hilbert space is constructed for the Wigner-Dunkl quantum mechanics utilizing a symmetric Dunkl derivative. The inverse of the derivative is shown to exhibit different realization on the subspaces of even and odd functions. The continuity conditions at finite discontinuities of symmetric potential is investigated. As an example, the finite symmetric square well is discussed in detail.
Model studies on motion of respiratory droplets driven through a face mask
Authors: Karmakar Rahul , Ghosal Aishani , Chakrabarti J. 
Published: January 2023

Abstract
Face masks are used to intercept respiratory droplets to prevent spreading of air-borne diseases. Designing face masks with better efficiency needs microscopic understanding on how respiratory droplets move through a mask. Here we study a simple model on the interception of droplets by a face mask. The mask is treated as a polymeric network in an asymmetric confinement, while the droplet is taken as a micrometer-sized tracer colloidal particle, subject to driving force that mimics the breathing. We study numerically, using the Langevin dynamics, the tracer particle permeation through the polymeric network. We show that the permeation is an activated process following an Arrhenius dependence on temperature. The potential energy profile responsible for the activation process increases with tracer size, tracer bead interaction, network rigidity and decreases with the driving force and confinement length. A deeper energy barrier led to better efficiency to intercept the tracer particles of a given size in the presence of driving force at room temperature. Our studies may help to design masks with better efficiency.
Mechanisms of eukaryotic transcription termination at a glance
Authors: Xie Juanjuan , Libri Domenico , Porrua Odil 
Published: January 2023

ABSTRACT
Transcription termination is the final step of a transcription cycle, which induces the release of the transcript at the termination site and allows the recycling of the polymerase for the next round of transcription. Timely transcription termination is critical for avoiding interferences between neighbouring transcription units as well as conflicts between transcribing RNA polymerases (RNAPs) and other DNA-associated processes, such as replication or DNA repair. Understanding the mechanisms by which the very stable transcription elongation complex is dismantled is essential for appreciating how physiological gene expression is maintained and also how concurrent processes that occur synchronously on the DNA are coordinated. Although the strategies employed by the different classes of eukaryotic RNAPs are traditionally considered to be different, novel findings point to interesting commonalities. In this Cell Science at a Glance and the accompanying poster, we review the current understanding about the mechanisms of transcription termination by the three eukaryotic RNAPs.