bluuebunny/crossref_metadata_2025_split huggingface dataset:
SARS-CoV-2 booster vaccine dose significantly extends humoral immune response half-life beyond the primary series
Authors: Korosec Chapin S. , Dick David W. , Moyles Iain R. , Watmough James 
Published: February 2024

AbstractSARS-CoV-2 lipid nanoparticle mRNA therapeutics continue to be administered as the predominant therapeutic intervention to reduce COVID-19 disease pathogenesis. Quantifying the kinetics of the secondary immune response from subsequent doses beyond the primary series, and understanding how dose-dependent immune waning kinetics vary as a function of age, sex, and various comorbidities, remains an important question. We study anti-spike IgG waning kinetics in 152 individuals who received an mRNA-based primary series and a subset of 137 individuals who then received a booster dose. We find the booster dose elicits a 71-84% increase in the median Anti-S half life over that of the primary series. We find the Anti-S half life for both primary series and booster doses drops as a function of increased year of age. However, we stress that although chronological age continues to be a good proxy for vaccine-induced humoral waning, immunosenescence is likely not the mechanism, rather, more likely the mechanism is related to the presence of noncommunicable diseases, which also accumulate with age, that affect immune regulation. We are able to independently reproduce recent observations that those with pre-existing asthma exhibit a stronger primary series humoral response to vaccination than compared to those that do not, and further find this result is sustained for the booster dose. Finally, via a single-variate KruskalWallis Test we find no difference between male and female decay kinetics, however, a multivariate approach utilizing Lasso regression for feature selection reveals a statistically significant (p-value<1×10−3), albeit small, bias in favour of longer-lasting humoral immunity amongst males.
Women’s adoption of wearable health-monitoring technology: empirical evidence from a least developed country
Authors: Rahman Md. Shahinur , Hasan Najmul , Zhang Jing , Moral Iqbal Hossain , Hossain Gazi Md. Shakhawat 
Published: February 2024

PurposeAlthough wearable health-monitoring technology (WHMT) has become a stimulus for public health, women’s acceptance rate of this technology appears to be low. Thus, this study intends to investigate the factors affecting women’s adoption of WHMT.Design/methodology/approachThe unified theory of acceptance and use of technology–2 model has been used in this study as a research framework that has been extended to include lifestyle and attitude. The proposed extended framework is validated using primary data (n = 314) collected from female respondents using a structured questionnaire; the partial least square-based structural equation modeling technique is subsequently used to test the proposed hypothesis.FindingsThe results show that effort expectancy, social influence, price value, habit, attitude and lifestyle have significant positive effects on women’s behavioral intention to use WHMT and accelerate actual usage behavior. Notably, effort expectancy and habit exhibit the largest impact on behavioral intention. However, performance expectancy, facilitating conditions and hedonic motivation are not significantly associated with behavioral intentions.Practical implicationsThe findings of this study are important for healthcare practitioners and service providers to comprehensively understand the factors that affect women’s behavioral intentions in line with their actual usage behavior. This insight will help policymakers design viable strategies regarding WHMT to promote its sustainable usage in least developed countries.Originality/valueThis study contributes novelty by using an extended model that links women’s attitudes and lifestyles to their adoption of WHMT. This study also fills the gaps in the existing literature on women’s behavioral intentions in the context of WHMT by showing novel associations in the domain of WHMT uptake.
Monetary policy and overshooting of agricultural prices in China: in a supply chain perspective
Authors: Xiao Yitian , Dai Jiawu , Nuetah J. Alexander 
Published: February 2024

PurposeThe purpose of this paper is to test the overshooting effects of monetary expansion on prices of agricultural products at farm production, processing and circulation stages in China, and to investigate the heterogeneity of the overshooting mechanisms in these three links.Design/methodology/approachEmpirical results are obtained through the vector error correction model and the overshooting framework proposed by Saghaian et al. (2002b). Specifically, we first apply the Dickey–Fuller generalized least squares (DF-GLS) method to test the stationarity of the key variables, and then use the Johansen’s (1991) method to conduct the cointegration test. Finally, the vector error correction model is employed to examine the overshooting hypotheses in the three stages of China’s agricultural sector.FindingsEmpirical results indicate that overshooting of prices relative to monetary expansion in China’s agricultural sector is a common phenomenon, but with significant heterogeneity. Firstly, at the stage of agricultural production, the overshooting degree and restoration rate of material price are greater than those of agricultural products price. Secondly, at the processing stage of agricultural products, both the purchase price of agricultural products and industrial producer price have an overshooting effect, but the overshooting effect of the former is more significant than the latter. Thirdly, at the circulation stage of agricultural products, the overshooting coefficient of the wholesale price index of agricultural products is the most significant, while that of the retail and purchase price of agricultural products is not significant.Originality/valueThe paper contributes to proposing a comprehensive framework on testing the overshooting effects for three main stages of agricultural sector in China and empirically investigating the heterogeneity of the overshooting mechanisms in different stages with time series methods.
The moderating role of duality split on the relationship between CEO narcissism and earnings management
Authors: Azevedo Yuri Gomes Paiva , Silva Mariana Câmara Gomes e , Nakao Silvio Hiroshi 
Published: February 2024

Purpose
The purpose of this study is to examine the moderating effect of an exogenous corporate governance shock that curbs Chief Executive Officers’ (CEOs) power on the relationship between CEO narcissism and earnings management practices.

Design/methodology/approach
The authors performed a quasi-experiment using a differences-in-differences approach to examine Brazil’s duality split regulatory change on 101 Brazilian public firms during the period 2010–2022.

Findings
The main findings indicate that the introduction of duality split curtails the positive influence of CEO narcissism on earnings management, suggesting that this corporate governance regulation may act as a complementary corporate governance mechanism in mitigating the negative consequences of powerful narcissistic CEOs. Further robustness checks indicate that the results remain consistent after using entropy balancing and alternative measures of CEO narcissism.

Practical implications
In emerging markets, where governance systems are frequently perceived as less than optimal, policymakers and regulatory authorities can draw insights from this enforcement to shape governance systems, reducing CEO power and, consequently, improving the quality of financial reporting.

Originality/value
To the best of the authors’ knowledge, this is the first study to examine whether a duality split mitigates the influence of CEO narcissism on earnings management. Thus, this study contributes to the corporate governance literature that calls for research on the effectiveness of external corporate governance mechanisms in emerging markets as well as the CEO narcissism literature that calls for research on moderating factors that could curtail negative consequences of narcissistic CEO behavior.
Contractors’ carbon reduction behaviour: UK construction professionals’ perspective
Authors: Arogundade Suhaib , Dulaimi Mohammed , Ajayi Saheed , Saad Ali 
Published: February 2024

Purpose
The decisions of contractors could impact the reduction of construction carbon footprint. These decisions are linked to the belief of contractors which equally affects how they behave while delivering projects. This study aims to investigate the behavioural tendencies of contractors that could lead to carbon minimisation during the execution of construction projects.

Design/methodology/approach
An industry survey was performed amongst 41 UK construction professionals. Spearman’s correlation and factor analysis were used to analyse the data.

Findings
The result of the Spearman’s correlation gave rise to 14 contractors’ carbon reduction behaviour (CCRB) variables and their factor analysis yielded two distinct factors, namely, contractors’ consummate carbon reduction behaviour and contractors’ pragmatic carbon reduction behaviour. The findings suggest that in the UK, contractors are willing to take voluntary practical steps to decrease the carbon footprint of construction projects.

Practical implications
This finding might be unexpected to construction stakeholders, especially construction clients who may believe that infusing strict carbon reduction obligations in contracts is sufficient in nudging contractors to lessen the carbon impact of projects.

Originality/value
The study attempted to quantitatively derive CCRB, thereby extending the breadth of knowledge in the construction carbon reduction domain.
Microenterprise performance amidst environmental turbulence and resource scarcity: an integrated capital approach
Authors: DelVecchio Micah , Ofori-Dankwa Joseph , Darkwah Akosua K. 
Published: February 2024

PurposeMicroenterprises in emerging economies are known to operate in turbulent and resource-scarce environments. We test our hypothesis that a more comprehensive “Integrated Capital-Based Model” (ICBM) is needed when explaining the performance of microenterprises in such an environment. The model combines traditionally researched financial, human and social capital with more recently emphasized psychological and cognitive capital, providing greater explanatory power than models using only the traditional types of capital.Design/methodology/approachWe use a pooled linear regression to analyze an existing survey of more than 900 independent business owners who were interviewed seven times between 2008 and 2012 in the Accra and Tema marketplaces in Ghana. We measure the performance of microenterprises using three dependent variables (revenue, profits, and productivity). We contrast the explanatory power of ICBM models against the more traditional models.FindingsThe ICBM has significantly higher levels of explanatory power over the traditional models in examining the performance of these microenterprises. These results highlight the importance of psychological and cognitive capital in emerging economies.Research limitations/implicationsWe advocate for a more comprehensive view of capital as shown in our ICBM. However, the data were gathered only in an urban setting, which limits the generalizability to rural parts of emerging economies.Practical implicationsThese findings suggest the utility of government and appropriate agencies finding ways to enhance the level of psychological and cognitive capital of microenterprise owners.Originality/valueThis paper's originality stems from hypothesizing and empirically confirming the higher predictive efficacy of ICBM against more traditionally researched capital sources.
Assessing supply chain management’s impact on new product performance: the mediating role of marketing innovation orientation during COVID-19
Authors: Dahan Gavriel , Levi-Bliech Michal 
Published: February 2024

PurposeThe main purpose of this study is to examine the influence of two characteristics of supply chain management (SCM) (resilience and integration) on new product performance (NPP) via the mediation of marketing innovation orientation.Design/methodology/approachThis study was designed by the quantitative method, and the research model was developed based on the resource-based view (RBV) theory of 211 managers from Israeli firms using SmartPls3 software.FindingsThe main finding that emerges from this study is that marketing innovation orientation serves as a full mediator in the relationship between supply chain resilience (SCR) and NPP as well as in the relationship between supply chain integration (SCI) and NPP. Thus, companies that wish to achieve a competitive advantage over their rivals should improve and strengthen their marketing innovation orientation. By doing so, they enhance the relationship between SCM and NPP.Practical implicationsThe findings provide an applicable guideline for marketing managers. Managers should be ready to adapt to customers’ demands, environmental changes and, most importantly, disruptive events in a dynamic environment.Originality/valueThe current study sheds light on the mechanism for NPP via integrating suppliers, customers and the organization. So, managers should adopt SCR and integration to strengthen their marketing innovation orientation in order to achieve NPP.
Enhanced Irradiance Levels using Synergistically Engineered Monochromatic Wavelength Ultraviolet-C Arrays Configuration
Authors: Sheikh Jahanzeb , Saidin Dr. Syafiqah , Ahmed Malik Sameen , Tan Tian Swee , Chua Lee Suan , Mohamed Ahmed Asim Ahmed Ibrahim , Kun Ma , Tiong Matthias Foh Thye , Leong Kah Meng 
Published: February 2024

Contamination in healthcare environment poses risk of microbial transmission to healthy people. Recently, conventional ultraviolet (UV) technologies, particularly low-pressure mercury lamps have caught researcher’s attention for disinfection. Nonetheless, drawbacks such as hazardous components, limited lifespan, warm-up time, maintenance and fragility have driven researchers to delve into light emitting diode (LED) technologies as an appealing alternative. However, due to the diminishing intensity exhibited by LEDs over extended distances, prior studies primarily focused on short-distance investigations. Consequently, the phenomenon remained insufficient owing to the limited exploration in this field. Furthermore, frequently investigated LEDs in ambient settings, potentially created a gap in completely understanding the capability for irradiance attainability. Hence, this study aimed to overcome this limitation by evaluating the effectiveness of UV-C LEDs with synergistic arrangements within an enclosed chamber, offering optimum settings for examining irradiance performance. The analyzed recorded data aimed to identify trends in emission performance over different distances (5 to 60 cm), providing insights into how the arrangement of LEDs could influence irradiance output. The study unveiled that the synergistic effects of 6, 8, and 10-LED, when strategically engineered, significantly contributed to enhanced intensity. Notably, 10-SEMW LEDs exhibited a remarkable ability to maintain significant irradiance levels across extended distances. This was evident in the range between 0.037 and 0.016 mW.cm⁻² observed at 5 and 60 cm, respectively. In conclusion, the findings stress the importance of strategically arranging LEDs in a synergistic configuration to achieve optimal irradiance levels across a diverse range of spatial parameters for effective long-range disinfection.
Prediction of State of Charge for Lead-Acid Battery Based on LSTM-Attention and LightGBM
Authors: Shen Yindong , Ge Yaru 
Published: February 2024

Abstract
Accurately estimating the state of charge (SOC) of batteries is crucial for the objective of extending battery life and enhancing power supply reliability. Currently, machine learning methods are commonly used to predict the SOC of batteries, however, their accuracy in capturing the sequential nature of battery charging and discharging is insufficient. To address the problem of the SOC prediction, a deep learning model that employs long short-term memory (LSTM) with Attention mechanism is proposed. The LSTM model is designed to connect the current SOC with historical time data and to extract multidimensional features from groups of batteries. Additionally, introducing the Attention mechanism allows for the model to prioritize key information while disregarding insignificant data. This work utilizes two different approaches to the multi-cell case and the single-cell case for several reasons. Considering that the failure of a single cell can affect the entire group of batteries, the SOC prediction models for individual batteries need not take a long training time. Thus, the LightGBM model is developed to predict the SOC of a single battery whose training speed surpasses that of the deep learning model and has superior prediction accuracy and greater speed when employed with small-scale data, error within 3%. Conversely, the LSTM-Attention model yields higher prediction accuracy when processing large-scale datasets, error within 5%. Two models are proposed: one for predicting the SOC of groups of batteries and another for a single battery.
Finite Element Method-Based Dynamic Modeling Framework for Flexible Continuum Manipulators
Authors: Modassir Firdaus Md , Dilip Paranjape Omkar , Vadali Madhu 
Published: February 2024

Abstract
Flexible continuum manipulators (FCMs) are gaining importance because of their maneuverability and pliability in confined and complex spaces, where rigid link manipulators underperform. However, the dynamic behavior and control of the FCM are quite challenging due to its complex nonlinear behavior. In this study, a finite element-based dynamic model framework is derived that accounts for the geometric nonlinearities and inertial effects. An experimental setup of tendon-driven FCM, consisting of a flexible backbone, is developed to validate the model. The modal analysis of the model is in agreement with the analytical solutions, with less than 10% error. The model is also validated for various loading conditions on the tip-actuated tendon-driven FCM. The steady-state tip position predictions are within 15% of the ground truth.
A Physics-Informed Neural Operator for the Simulation of Surface Waves
Authors: Mathias Marlon S. , Netto Caio F. D. , Moreno Felipe M. , Coelho Jefferson F. , de Freitas Lucas P. , de Barros Marcel R. , de Mello Pedro C. , Dottori Marcelo , Cozman Fábio G. , Costa Anna H. R. , Nogueira Junior Alberto C. , Gomi Edson S. , Tannuri Eduardo A. 
Published: February 2024

Abstract
We develop and implement a neural operator (NOp) to predict the evolution of waves on the surface of water. The NOp uses a graph neural network (GNN) to connect randomly sampled points on the water surface and exchange information between them to make the prediction. Our main contribution is adding physical knowledge to the implementation, which allows the model to be more general and able to be used in domains of different geometries with no retraining. Our implementation also takes advantage of the fact that the governing equations are independent of rotation and translation to make training easier. In this work, the model is trained with data from a single domain with fixed dimensions and evaluated in domains of different dimensions with little impact to performance.
Beyond schistosomiasis: unraveling co-infections and altered immunity
Authors: Perera Dilhan J. , Koger-Pease Cal , Paulini Kayla , Daoudi Mohamed , Ndao Momar 
Published: February 2024

SUMMARY

Schistosomiasis is a neglected tropical disease caused by the helminth
Schistosoma
spp. and has the second highest global impact of all parasites.
Schistosoma
are transmitted through contact with contaminated fresh water predominantly in Africa, Asia, the Middle East, and South America. Due to the widespread prevalence of
Schistosoma
, co-infection with other infectious agents is common but often poorly described. Herein, we review recent literature describing the impact of
Schistosoma
co-infection between species and
Schistosoma
co-infection with blood-borne protozoa, soil-transmitted helminths, various intestinal protozoa,
Mycobacterium
,
Salmonella
, various urinary tract infection-causing agents, and viral pathogens. In each case, disease severity and, of particular interest, the immune landscape, are altered as a consequence of co-infection. Understanding the impact of schistosomiasis co-infections will be important when considering treatment strategies and vaccine development moving forward.
A dual-plasmid CRISPR/Cas9-based method for rapid and efficient genetic disruption in
Mycobacterium abscessus
Authors: Neo Donavan Marcus , Clatworthy Anne E. , Hung Deborah T. 
Published: February 2024

ABSTRACT

Mycobacterium abscessus
is increasingly recognized for causing infections that are notoriously difficult to treat, owing to its large arsenal of intrinsic antibiotic resistance mechanisms. Tools for the genetic manipulation of the pathogen are critical for enabling a better understanding of
M. abscessus
biology, pathogenesis, and antibiotic resistance mechanisms. However, existing methods are largely recombination-based, which are relatively inefficient. Meanwhile, CRISPR/Cas9 has revolutionized the field of genome editing including its recent adaptation for use in mycobacteria. In this study, we report a streamlined and efficient method for rapid genetic disruptions in
M. abscessus
. Harnessing the CRISPR1 loci from
Streptococcus thermophilus
, we have developed a dual-plasmid workflow that introduces Cas9 and sgRNA cassettes in separate steps but requires no other additional factors to engineer mutations in single genes or multiple genes simultaneously or sequentially using multiple targeting sgRNAs. Importantly, the efficiency of mutant generation is several orders of magnitude higher than reported for homologous recombination-based methods. This work, thus, reports the first application of CRISPR/Cas9 for gene editing in
M. abscessus
and is an important tool in the arsenal for the genetic manipulation of this human pathogen.

IMPORTANCE

Mycobacterium abscessus
is an opportunistic pathogen of increasing clinical importance due to its poor clinical outcomes and limited treatment options. Drug discovery and development in this highly antibiotic-resistant species will require further understanding of
M. abscessus
biology, pathogenesis, and antibiotic resistance mechanisms. However, existing methods for facile genetic engineering are relatively inefficient. This study reports on the first application of CRISPR/Cas9 for gene editing in
M. abscessus
using a dual-plasmid workflow. We establish that our method is easily programmable, efficient, and versatile for genetic disruptions in
M. abscessus
. This is a critical advancement to facilitating targeted gene function studies in this emerging pathogen.