bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bifurcation analysis of a two-infection transmission model with explicit vector dynamics
Authors: Srivastav Akhil Kumar , Steindorf Vanessa , Guerrero Bruno V. , Stollenwerk Nico , Kooi Bob W. , Aguiar Maíra 
Published: December 2023

AbstractThe investigation of epidemiological scenarios characterized by chaotic dynamics is crucial for understanding disease spread and improving disease control strategies. Motivated by dengue fever epidemiology, in this study we introduce the SIRSIR-UV model, which accounts for differences between primary and secondary infections and explicit disease vector dynamics. Our analysis, employing nonlinear dynamics and bifurcation theory, provides key insights into how vectors contribute to the overall system dynamics. In this paper, the formalization of backward bifurcation using center manifold theory, computation of Hopf and global homoclinic bifurcation curves, and derivation of analytical expressions for transcritical and tangent bifurcations deepen the understanding. The observation of chaotic behavior with the inclusion of seasonal forcing in the vector population underscores the importance of considering external factors like climate in disease spread. Our findings align with those from previous models, emphasizing the significance of simplifying assumptions, such as implicit vector dynamics, when constructing models without vector control. This study brings significant insights to the mathematical modeling of vector-borne diseases, providing a manageable framework for exploring complex epidemiological scenarios and identifying key factors influencing disease spread. While the absence of strain structure may limit predictive power in certain scenarios, the SIRSIR-UV model serves as a starting point for understanding vector-borne infectious disease dynamics.
Nascent RNA kinetics with complex promoter architecture: Analytic results and parameter inference
Authors: Shi Changhong , Yang Xiyan , Zhou Tianshou , Zhang Jiajun 
Published: December 2023

AbstractTranscription is a stochastic process that involves several downstream operations, which make it difficult to model and infer transcription kinetics from mature RNA numbers in individual cell. However, recent advances in single-cell technologies have enabled a more precise measurement of the fluctuations of nascent RNA that closely reflect transcription kinetics. In this paper, we introduce a general stochastic model to mimic nascent RNA kinetics with complex promoter architecture. We derive the exact distribution and moments of nascent RNA using queuing theory techniques, which provide valuable insights into the effect of the molecular memory created by the multistep activation and deactivation on the stochastic kinetics of nascent RNA. Moreover, based on the analytical results, we develop a statistical method to infer the promoter memory from stationary nascent RNA distributions. Data analysis of synthetic data and a realistic example, theHIV-1gene, verifies the validity of this inference method.
Dollar or percentage? The effect of reward presentation on referral likelihood
Authors: Chen Hao , Hao Shuangkang 
Published: December 2023

PurposeAddressing the significant differences between referral programs and traditional promotional marketing, this paper aims to investigate and examine the impact of how reward-related information is presented within referral programs and how it interacts with reward size and reward allocation.Design/methodology/approachThis study adopts framing effect and equity theory to build the relationship between reward presentation, reward size and reward allocation. Then, two scenario-based experimental studies are designed and conducted on Amazon Mechanical Turk.FindingsThe results show that there is no direct impact of reward presentation on referral likelihood, while the effect relies on reward size. As the levels of reward size increase, the referral likelihood gradually shifts from percentage form to dollar form as perceived size mediates the interaction effect on referral likelihood. Further, adding information about reward allocation also indicate the different impacts of equity and inequity on influencing the above findings.Originality/valueThe study contributes to the literature by introducing reward presentation and emphasizes its impact on individual’s behavior decisions in the context of referral programs. This study extends and broadens the scope and effectiveness of the framing effect on traditional promotional marketing strategies, while also bridging the gap in the literature by examining the combined role of information about rewards.
Restaurant containment measures and perceived service quality: implications for future pandemics
Authors: Ribeiro Paulo , Ramos Ricardo F. , Moro Sérgio 
Published: December 2023

Purpose
This study aims to identify the impact of restaurant pandemic mitigation measures on perceived service quality.

Design/methodology/approach
A total of 15,251 reviews were collected from 300 TripAdvisor Lisbon restaurant Web pages between March 2020 and December 2021, when Covid-19 contingency measures were in place. Grounded on the online reviews, a word frequency matrix was created and used as input on partial least squares–structural equation modeling to test the proposed hypotheses.

Findings
The results suggest that precaution measures, such as the Vaccination Certificate, negative tests and restaurant layout configuration, positively influenced perceived service quality and consumer satisfaction, moderated by consumers’ beliefs.

Originality/value
This study provides relevant information for restaurant managers, which will help them implement strategies to guarantee service quality, consumer satisfaction and revisit intentions in future pandemic scenarios.
Optimized aspect and self-attention aware LSTM for target-based semantic analysis (OAS-LSTM-TSA)
Authors: Vasavi B. , Dileep P. , Srinivasarao Ulligaddala 
Published: December 2023

PurposeAspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use graph-based mechanisms, which reduce prediction accuracy and introduce large amounts of noise. The other problem with graph-based mechanisms is that for some context words, the feelings change depending on the aspect, and therefore it is impossible to draw conclusions on their own. ASA is challenging because a given sentence can reveal complicated feelings about multiple aspects.Design/methodology/approachThis research proposed an optimized attention-based DL model known as optimized aspect and self-attention aware long short-term memory for target-based semantic analysis (OAS-LSTM-TSA). The proposed model goes through three phases: preprocessing, aspect extraction and classification. Aspect extraction is done using a double-layered convolutional neural network (DL-CNN). The optimized aspect and self-attention embedded LSTM (OAS-LSTM) is used to classify aspect sentiment into three classes: positive, neutral and negative.FindingsTo detect and classify sentiment polarity of the aspect using the optimized aspect and self-attention embedded LSTM (OAS-LSTM) model. The results of the proposed method revealed that it achieves a high accuracy of 95.3 per cent for the restaurant dataset and 96.7 per cent for the laptop dataset.Originality/valueThe novelty of the research work is the addition of two effective attention layers in the network model, loss function reduction and accuracy enhancement, using a recent efficient optimization algorithm. The loss function in OAS-LSTM is minimized using the adaptive pelican optimization algorithm, thus increasing the accuracy rate. The performance of the proposed method is validated on four real-time datasets, Rest14, Lap14, Rest15 and Rest16, for various performance metrics.
Mapping the research productivity of Pakistan Agricultural Research Council: a scientometric study
Authors: Akbar Faheem , Arif Muhammad , Rafiq Muhammad 
Published: December 2023

Purpose
This study aims to examine the research productivity of Pakistan Agricultural Research Council’s (PARC’s) researchers published during 2001–2020 by using scientometric indicators. The study explored the growth and collaborative trends along with authorship and institutional collaborative patterns at the national and international levels.

Design/methodology/approach
The study was conducted in four phases. Firstly, a search strategy was designed to retrieve reliable data sets. During the second phase, data from PARC research was retrieved from Scopus and Web of Science (WoS). In the third phase, the data were combined, and duplications were removed. Finally, the data were analysed using RStudio and VOSviewer.

Findings
The study identified 2,868 research publications from 16 communication channels spanning over the period of 2001–2020. The growth rate varied during the study period and the year 2020 was the most productive year of the organization. Most of the research was produced in multi-authorship and five authors were dominant. Pakistan Journal of Botany was the most preferred and cited source. Moreover, PARC research collaboration with Pakistani researchers was more than their international counterparts.

Research limitations/implications
Like other research, this research has some limitations. For example, this research is based on secondary data extracted from WoS and Scopus databases, world-renowned online academic. However, researchers should keep in mind while interpreting the results of this study. Secondly, the research publications published by PARC researchers during 2001–2020 were considered. Finally, this research considered English language literature only.

Practical implications
The study’s key theoretical contribution is its strategy for merging WoS and Scopus in RStudio, while its findings could assist agriculture research stakeholders in identifying new areas of research, awards, promotions and identification of research gaps.

Originality/value
To the best of the author’s knowledge, this study is the first to use scientometric indicators to evaluate PARC’s research productivity. This detailed analysis provides a deeper understanding of PARC’s contribution to agriculture research and its potential implications.
The assessment of national conduct in realizing the right to heath: using the framework of United Nations
Authors: Kokabisaghi Fatemeh 
Published: December 2023

Purpose
Health is a human right and a fundamental building block of sustainable development, economic prosperity and poverty reduction. To realize people’s right to health, evaluating the situation of the right and its determinants is necessary. This paper aims to analyze Iran’s conduct in realizing its population’s right to health.

Design/methodology/approach
A qualitative case study design involving a structured review of relevant laws, policy documents, reports and academic literature was undertaken. The data were collected from electronic databases and the official Web pages of the United Nations (UN) and Iran’s Government and analyzed by a framework suggested by the UN.

Findings
Iran’s law and policies intend to combat health inequalities and to provide an adequate standard of living for everyone, particularly disadvantaged groups and individuals. However, not all laws and policies protecting disadvantaged groups are adequately implemented. There are disparities in health status and access to health care among different socio-economic groups. International economic sanctions and government policies decreased people’s ability to access the necessities of life including health care. Moreover, social determinants of health, such as cultural beliefs regarding women’s rights have not been addressed sufficiently in the country’s laws.

Research limitations/implications
This study includes a broad range of subjects and provides an overview of the health-care system of Iran. However, more detail is needed to describe every aspect of the right to health. It was not feasible to address them all in this paper and needs more research. In addition, as with the majority of qualitative studies, the design of the current study is subject to limitations. Firstly, the research quality of narrative reviews is dependent on the researcher’ skills and more easily can be influenced by his/her personal biases. Second, the rigor is more difficult to maintain, assess and demonstrate. Nevertheless, narrative studies often complement quantitative studies and are informative.

Originality/value
To fulfill the right to health, Iran should improve affordability and quality of care and the situation of the determinants of health. The gaps in people’s access to health care need to be identified, and all necessary means and scarce resources be allocated to remove access barriers and to improve the situation of disadvantaged people. The adoption of relatively low-cost targeted programs, the proper management of resources and the prevention of unnecessary costs are suggested.
LiDAR-based SLAM for robotic mapping: state of the art and new frontiers
Authors: Yue Xiangdi , Zhang Yihuan , Chen Jiawei , Chen Junxin , Zhou Xuanyi , He Miaolei 
Published: December 2023

Purpose
In recent decades, the field of robotic mapping has witnessed widespread research and development in light detection and ranging (LiDAR)-based simultaneous localization and mapping (SLAM) techniques. This paper aims to provide a significant reference for researchers and engineers in robotic mapping.

Design/methodology/approach
This paper focused on the research state of LiDAR-based SLAM for robotic mapping as well as a literature survey from the perspective of various LiDAR types and configurations.

Findings
This paper conducted a comprehensive literature review of the LiDAR-based SLAM system based on three distinct LiDAR forms and configurations. The authors concluded that multi-robot collaborative mapping and multi-source fusion SLAM systems based on 3D LiDAR with deep learning will be new trends in the future.

Originality/value
To the best of the authors’ knowledge, this is the first thorough survey of robotic mapping from the perspective of various LiDAR types and configurations. It can serve as a theoretical and practical guide for the advancement of academic and industrial robot mapping.
Hierarchical value mapping of diners in Macao's casino restaurants
Authors: Fan Pui Kuan Tina , Choe Ja Young (Jacey) , Na Yeseul 
Published: December 2023

PurposeThis study explores the linkages between various attributes, consequences and values of casino restaurants and the differences in the hierarchical value maps between female and male customers and between casino players and non-casino players.Design/methodology/approachThis study was conducted using the means-end chain (MEC) theory. The data were collected using the hard-laddering method. Two hundred forty-one responses were analyzed.FindingsAttributes such as “taste,” “reasonable prices,” and “discounts” were associated with the values “personal happiness,” “considered,” “life satisfaction,” and “life-quality enhancement” at casino restaurants. Males were found to hold “prompt services” as important when dining at casino restaurants, while females held a “spacious environment” to be critical. Furthermore, “use of casino complimentary credits” was important to casino players, while “free parking” and “comfortable seats” mattered for non-casino players.Practical implicationsIt is suggested that casinos add more Asian cuisines in their casino restaurants in Macao to attract customers who value culinary and cultural exploration while simultaneously satisfying tourists from neighboring regions who wish to enjoy familiar foods when they visit Macao. In addition, the authors recommend that casinos develop menu items that can be served quickly to casino players.Originality/valueThis study is based on the MEC theory and broadens the range of studies on casino restaurants. Furthermore, it provides useful information to guide casino restauranteurs in developing their marketing and operational strategies for different customer segments.
Hotel leaders' benevolent leadership, career management and employees' work engagement during COVID-19: a conservation of resources perspective
Authors: Potipiroon Wisanupong , Junthong Hataikwan 
Published: December 2023

PurposeDrawing upon conservation of resources (COR) theory, this study aims to examine whether benevolent leadership from top hotel leaders can foster employees' work engagement during COVID-19 via two valued career-related resources, namely organizational career management (OCM) and individual career management (ICM). This study also proposes that the importance of ICM as a resource diminishes when ICM plays a prominent role.Design/methodology/approachSurvey data were collected from 600 employees in 20 hotels located in a major tourist destination in Thailand during COVID-19. The data were analyzed using latent moderated mediation structural equation modeling (SEM).FindingsThis study found that the relationship between hotel leaders' benevolent leadership and employees' work engagement was mediated by both OCM and ICM. Furthermore, as expected, this study found that the indirect effect of benevolent leadership via OCM was weaker when ICM was high.Practical implicationsThis study sheds light on the importance of hotel leaders and career management activities in promoting employees' work engagement. Thus, despite concerns that investing in career management activities might lead employees to manage themselves out of the organization, the current findings indicate otherwise.Originality/valueBased on the resource-gain perspective, this study contributes to the leadership and hospitality literature by being among the first to show that the influence of benevolent leadership on work engagement occurs through the simultaneous mediating roles of OCM and ICM. Moreover, this study contributes to the current debate about the interactive effects of OCM and ICM.
Embedding anatase, rutile, and brookite TiO2 nanoparticles to cotton fabric with epoxy silane and comparison of their effects on photodegradation
Authors: Sezgin Bozok Sabiha 
Published: December 2023

Purpose
This study aims to embed anatase, rutile and brookite TiO2 nanoparticles (NPs) with different crystal phases into cotton fabrics by epoxy silane and to examine the effect of these applications on the photocatalytic and mechanical properties of the fabric.

Design/methodology/approach
Different aqueous dispersions which contain anatase, rutile and brookite were prepared at three different concentrations (5%, 10% and 15%). These NPs were embedded in cotton fabrics by using GPTS [(3-glycidyloxypropyl) trimethoxysilane]. Characterization tests were performed by scanning electron microscopy (SEM), Raman and Fourier-transform infrared spectroscopy (FT/IR). Samples were stained with methylene blue (MB) and then exposed to solar light for different periods. Color changes of the samples were examined with a spectrophotometer. Air permeability, abrasion and tear strength tests were applied to all samples.

Findings
According to SEM images, the NPs were successfully attached to the cotton fabrics, and epoxy silane coating surrounded the fiber surfaces. The presence of the coating was also confirmed by Raman spectroscopy and FT/IR. The treatments reduced the stainability of the samples. The most effective applications for ensuring photocatalytic activity in cotton fabrics were suspensions as 10% brookite, 10% anatase and 5% anatase, in descending order. The applied coating slightly reduced the samples’ air permeability, and wear and tear strength.

Originality/value
The importance of this study is to determine the optimal crystal phase and its concentration by using epoxy silane to ensure self-cleaning properties on cotton fabrics. The sample treated with 10% brookite is the most approached its original white color by 99.65% as a result of degradation of MB (after 120 min). On the other hand, using the pure rutile with epoxy silane was not suitable for removing MB from the fabric.
Machine learning for forecasting the biomechanical behavior of orthopedic bone plates fabricated by fused deposition modeling
Authors: Sharma Shrutika , Gupta Vishal , Mudgal Deepa , Srivastava Vishal 
Published: December 2023

Purpose
Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates.

Design/methodology/approach
The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R2) and mean absolute error (MAE).

Findings
Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments.

Research limitations/implications
The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study.

Originality/value
This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.