bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systemic Treatment Followed by Radical Resection Combined with Intestinal Autotransplantation (RRCIA) for Locally Advanced Pancreatic Cancer
Authors: Qiao Guoliang , Bai Xueli , Li Xiang , Zhang Qi , Chen Yiwen , Ma Tao , Wu Guosheng , Xiao Wenbo , Sun Ke , Jiang Tian’an , Su Xinhui , Morse Michael A. , Liang Tingbo 
Published: December 2024

Objective:
The present study aimed to assess the efficacy of this approach and establish the criteria that identify LAPC patients who may achieve survival benefits from RRCIA.

Summary Background Data:
Surgical resection for locally advanced pancreatic cancer (LAPC) remains challenging and associated with high morbidity and mortality, especially for surgery with major arterial reconstruction. We previously showed the feasibility and safety of Radical Resection Combined with Intestinal Autotransplantation (RRCIA) after systemic treatment.

Methods:
A retrospectively observational and prospectively validated study with three cohorts was conducted using multiple treatments. Overall survival (OS) and progression-free survival (PFS) were compared for both analyses. Propensity-score matching (PSM) and stabilized inverse probability of treatment weighting (IPTW) were performed to adjust for potential confounders.

Results:
Among 208 patients with LAPC we identified 48 who underwent systemic treatment followed by RRCIA. Using Propensity-score matching (PSM) and stabilized inverse probability of treatment weighting (IPTW) analyses, we observed that patients who underwent RRCIA had better overall and progression free survival compared with patients who did not have surgery (PSM cohort: median OS: 25.8 mo vs. 14.2 mo, P=0.0031, and IPTW cohort: median OS: 23.2 mo vs. 15.4 mo, P=0.0069) and PFS (PSM cohort: median PFS: 13.3 mo vs. 7.0 mo, P=0.0246, and IPTW cohort: median OS: 13.3 mo vs. 8.8 mo, P=0.002). Further prospective analysis showed that patients who received systemic treatment followed by RRCIA were associated with improved OS and PFS compared with patients who were eligible but did not receive RRCIA (median OS: 22.6 mo vs. 18.2 mo, P=0.035; median PFS: 13.2 mo vs. 10.3 mo, P=0.0412). Moreover, stratified and multivariable analysis demonstrated that preoperative CA19-9 normalization and duration of initial treatment over 8 cycles were predictors for precise selection of patients who would benefit from RRCIA. Meanwhile, adjuvant therapy after RRCIA was a significant factor for improving survival.

Conclusion:
This study suggests that RRCIA appears to be effective and associated with improved outcomes for LAPC patients with favorable response to systemic treatment. LAPC patients Should have at least 8 cycles of systemic treatment and CA19-9 normalization to be considered for RRCIA.
3-Year Survival Outcomes of Patients with Enhanced Recovery After Surgery vs. Conventional Care in Laparoscopic Distal Gastrectomy
Authors: Tian Yulong , Cao Shougen , Li Leping , Yu Wenbin , Ding Yinlu , Zhang Guangyong , Jiang Lixin , Qu Jianjun , Wang Hao , Wang Xinjian , Mao Weizheng , Zhang Huanhu , Chu Xianqun , Hui Xizeng , Zhang Dongfeng , Niu Zhaojian , Jing Changqing , Jiang Haitao , Liu Xiaodong , Li Zequn , Kehlet Henrik , Zhou Yanbing ,   on behalf of the Shandong Gastrointestinal Surgery Study Group (GISSG)
Published: December 2024

Objectives:
The efficacy of enhanced recovery after surgery (ERAS) to improve the prognosis of patients who undergo laparoscopic distal gastrectomy (LDG) for gastric cancer is uncertain. This randomized study compared oncological outcomes in LDG after ERAS or conventional care.

Background:
At present, randomized controlled trials have confirmed that ERAS can improve the short-term clinical outcomes of patients undergoing LDG, but whether it improves survival has not been reported yet.

Methods:
A multicenter, randomized, controlled trial was performed to compare oncological outcomes of ERAS versus conventional care in LDG. Between April 4, 2019, and March 18, 2020, 527 patients with locally advanced lower gastric adenocarcinoma were recruited from 13 centers in China. The primary endpoints were 3-year overall survival (OS) and disease-free survival (DFS). The secondary endpoints were complications, mortality, recovery, time of receiving adjuvant chemotherapy and medical expenses.

Results:
The full analysis set included 186 cases in the ERAS group and 184 in conventional group, well balanced with respect to patient demographics and baseline characteristics (published before). Postoperative hospital stay and the interval before adjuvant chemotherapy were obviously shorter in the ERAS group compared to conventional group as reported previously and with lower medical expenses. Compared with the conventional group, ERAS group had fewer overall complications (21.0% vs. 30.4%, respectively; P=0.037). The median (IQR) follow-up for all cases was 42.17 (range, 3.12-48.50) months. The 3-year OS and DFS in the ERAS group and conventional group were 86.56% and 80.11% (log-rank P=0.025), 79.57% and 69.57% (log-rank P=0.027), respectively. In a subgroup analysis of stage I and II disease patients, 3-year OS and DFS were similar between the groups (P=0.901; P=0.859 for stage I and P=0.421; P=0.459 for stage II). However, in the stage III disease, the ERAS group exhibited longer 3-year OS and DFS than the conventional group (79.41% vs. 64.47% for OS, log-rank P=0.046; 70.59% vs. 53.95% for DFS, log-rank P=0.046).

Conclusions:
Patients undergoing ERAS LDG had fewer overall complications, shorter hospital stay, decreased medical expenses, and improved 3-year OS and DFS rates, particularly in cases with stage III gastric cancer.
Replicating the ‘seductive allure of neuroscience explanations’ effect in a classroom experiment and an online study
Authors: Väth Pearl Amber , von Petersdorff Jakob , Neumann Christof , Mundry Roger , Fischer Julia 
Published: December 2024

The ‘seductive allure of neuroscience explanations’ effect refers to the observation that superfluous neuroscience information (SNI) added to an explanation can bias judgements of information quality. We report the results of a classroom experiment to sensitize undergraduate students to that issue. In contrast to previous studies, students rated good explanations without SNI the highest. Inspired by these observations, we set out to conceptually replicate the original study using an online experiment that allowed us to directly assess the statistical interactions between explanation quality, the presence of SNI and expertise levels. In this preregistered study, participants (
n
= 430) with varying levels of expertise rated the quality of good and bad explanations, with or without SNI. Irrespective of the presence of SNI, participants across all expertise levels rated good explanations more favourably than bad ones. Still, the differences were surprisingly small, and the variation in rating was high. We also found a statistically significant interaction between the impact of SNI and expertise, with SNI boosting ratings mostly in participants with less expertise (
p
< 0.001), corroborating previous findings. Developing a curriculum that trains students to distinguish between actual explanations and ‘crap’ would ultimately also sensitize teachers and experts that produce and review scientific information.
A novel HLA Class II presentation prediction algorithm deciphers immunogenic CD4 epitopes specific to KRAS G12C
Authors: Sprague Daniel , Hart Meghan G. , Klein Joshua , Kounlavouth Sonia , Vegesna Rahulsimham , Rotunno Melissa , Kraemer-Tardif Lauren D. , Zhou Rita , Kemp Lindsey , Greene Adrienne C. , Araya Joshua , Mantilla Alexis , Adeoye Bukola , Dominguez Calixto , Ferguson Andrew R. , Johnson Melissa L. , Davis Matthew J. , Lane Monica , Palmer Christine D. , Jooss Karin , Dhanik Ankur 
Published: December 2024

AbstractAccurate prediction of peptide presentation by HLA molecules is important for generation of effective individualized cancer vaccines and immunotherapies. While presentation prediction algorithms for HLA class I have been successfully applied in the context of such therapies, improved prediction algorithms for class II are needed. EDGE-II is a novel algorithm based on a protein large language model that has a learned allele deconvolution network trained on existing and new immunopeptidomics data. It delivers state-of-the-art performance on prediction of peptide presentation by HLA class II and immunogenicity elicited by CD4+ T-cell epitopes. In a patient with a KRAS G12C positive tumor treated with a KRAS G12C targeting immunotherapy, EDGE-II identified KRAS G12C class II neoantigens that elicited clonally expanded CD4+T cells with cytotoxic transcriptional profiles post-vaccination. EDGE-II could play an important role in the development of effective cancer immunotherapies by elucidating an enriched understanding of the immunopeptidome.
Density correlations under global and local charge conservation
Authors: Vovchenko Volodymyr 
Published: December 2024

This work presents a formalism to compute spatial n-point correlations of a conserved charge density in a large thermal system in the canonical ensemble, with explicit results presented up to fourth order. The resulting correlators contain local and balancing terms expressed through the grand-canonical susceptibilities for any equation of state. The new formalism is used to introduce a Gaussian local baryon number conservation in (spatial) rapidity in heavy-ion collisions at CERN Large Hadron Collider conditions through a modulation of the balancing term. Connection to the conservation volume Vc approach is established, indicating that the latter is appropriate for observables within a limited range around midrapidity. Quantitative analysis of the experimental data of the ALICE Collaboration on net proton cumulants in central Pb-Pb collisions at sNN=5.02 TeV shows significant evidence for local baryon conservation.

Published by the American Physical Society
2024
Analysing the factors of bus transport operations influencing the energy consumption of electric buses in real world for sustainable transport strategies
Authors: Bendigiri Priyanka , Rao Prakash 
Published: December 2024

Purpose
In any public transit system composed of electric buses, the bus transport operating parameters tend to influence their energy consumption. However, it is essential to know which parameters are the influential ones and how they are influencing the energy consumption of the electric buses. Therefore, this study aims to investigate the transport-related operational aspects of the electric bus transit system.

Design/methodology/approach
This study presents the actual world data of the energy consumption of electric buses and analyses the influences of the bus transport operations on the same using panel regression analysis. The data collected from six bus depots in a city are analysed depot-wise. Furthermore, a comprehensive analysis of the complete electric urban transit system is presented, followed by a framework to examine the parameters that influence the energy consumption of electric buses. A further framework is proposed to show how the electricity consumption of electric buses can be optimised.

Findings
The panel regression analysis, conducted for the real-world data collected over six depots of the public transit system composed of electric buses, indicates that the number of passengers have a positive impact on their energy consumption as compared to their mileage. With increased energy consumption, the earnings of the transit system are seen reducing. Therefore, the authors propose recommendations to increase the earnings to make the system financially more viable.

Originality/value
The study is one of its kind in the Indian context. It is based on real-world data collected over a period of 12 months from the six depots of the public transit system of a city composed of electric buses. The model is easily replicable and deployable to big bus networks if longitudinal data are obtained from the bus transit operators.
Maintenance in aviation enabled by Industry 4.0 technologies: exploring the current research trends using a topic modeling approach
Authors: Rath Bikash , Jha Kaushal Kumar , Padhy Ramakrushna , Jena Debashish 
Published: December 2024

PurposeSince passenger safety is critical, aviation maintenance is essential. Aviation maintenance management is changing due to Industry 4.0 (I4.0). According to earlier research, I4.0 technologies improve aircraft manufacturing efficiency and responsiveness through automation, predictive maintenance and process self-optimization. Thus, this study examines I4.0 research and aircraft maintenance's potential interaction.Design/methodology/approachUsing a text-mining methodology, this paper looks at the state of the art in aviation maintenance research in the I4.0 era. We used the topic modeling approach and Latent Dirichlet Allocation (LDA) technique to analyze the abstracts and indexed keywords of 929 research articles on the intersection of aviation maintenance and I4.0, subsequently clustering them into eight topics.FindingsWe have mapped out the emerging research trends at the intersection of “aviation maintenance” and “I4.0 technologies”, and presented suggestions for theoretical frameworks, applied frameworks and future lines of inquiry. This paper makes a theoretical contribution to the systematization of literature on I4.0 technologies in aviation maintenance. It provides valuable insight for managers by exploring the implications and opportunities that arise in light of recent innovations brought by I4.0 in aviation maintenance.Originality/valueThis study focuses on the use of Industry 4.0 technologies in aircraft maintenance processes, contributing to the growing research on digital technology in maintenance and maintenance, repair and overhaul (MRO). Furthermore, the study's analysis of the LDA topic model provides valuable insights for future research on using I4.0 technologies to investigate specific areas of application in the context of digital maintenance.
The influence of marine ecological compensation policy on enterprises’ environmental investment
Authors: Pan Xiongfeng , Feng Shenghan 
Published: December 2024

PurposeThis article investigates the influence of marine ecological compensation policy on enterprises’ environmental investment and explores whether enterprise ownership could impact the said influence.Design/methodology/approachUsing the data of China's A-share listed enterprises for the period 2007–2020, the paper develops a difference-in-differences model and a moderating effect model.FindingsThe outcomes corroborate that the marine ecological compensation policy positively influences enterprises' environmental investment, and the effect is nonlinear. Specifically, the marine ecological compensation policy significantly impacts enterprises with lower and higher environmental investment. The empirical evidence from the moderation model shows that the effect of the policy is more significant on the non-state-owned enterprises’ environmental investment.Research limitations/implicationsThe findings are based on a sample of 559 listed A-share enterprises in China. Additional studies could focus on data from other countries.Practical implicationsBased on the present scenario of Chinese enterprises' environmental investment, the results report that the marine compensation policy needs to be differentiated for firms having different ownership and different levels of environmental investment. The study provides valuable insights for the government to formulate marine ecological compensation policies.Originality/valueMarine ecology increasingly affects the economic development of countries, and the study on the influence of relevant environmental policies is of practical significance. However, most scholars concentrate on the research of environmental regulation, and have little focus on the policy effect of marine environmental compensation. This paper studies how marine ecological compensation policy influences the environmental investment behavior of enterprises, and further analyzes the difference in the policy effect caused by the nature of enterprises’ ownership, which not only fills the gap in this field, but also provides a scientific basis for the formulation and adjustment of marine ecological compensation policy.
Mindful consumption: cultivating sustainable consumption behavior for food and clothing through mindfulness among Generation Z
Authors: Kumar Sachin , Panda Tapan K. 
Published: December 2024

Purpose
Generation Z (GenZers) significantly influences sustainability-related issues in emerging economies like India. Literature on sustainability suggests exploring ways to enhance their sustainable behavior, especially for food and clothing products, which have detrimental consequences despite being essential. Mindfulness is often proposed as a factor that could potentially influence sustainability. However, the empirical association between mindfulness and sustainable consumption behavior (SCB) and the underlying pathways remain underexplored. Therefore, this study aims to advance the empirical understanding of how GenZers’ trait mindfulness affects their SCB for food and clothing.

Design/methodology/approach
Based on a time-lagged study involving responses from 519 Indian GenZers (college students aged 18–24 years) the authors examined two models (one for SCB related to food and one for clothing) to explore the direct relationships and mediating factors between trait mindfulness and SCB.

Findings
GenZers with higher levels of trait mindfulness are more likely to influence their SCB for food and clothing. Besides, in both models, self-regulation, self-compassion and prosocialness mediate the association between trait mindfulness and SCB.

Research limitations/implications
Mindfulness and its intervening variables are promising for positively driving SCB for food and clothing. Marketers and policymakers can consider these findings to strategize and encourage sustainable consumption, particularly among GenZers.

Originality/value
This seminal study uses the reperceiving theory to empirically validate the relationship between GenZers’ trait mindfulness and SCB for food and clothing.
Effects of sponsorship disclosures on social media influencer–user psychological contract violation: moderated mediation effects through the expectancy violations lens
Authors: Jhawar Anand , Varshney Sanjeev , Kumar Prashant 
Published: December 2024

Purpose
The purpose of this study is to deploy the psychological lens of “expectancy violation” to examine the effects of social media influencers’ (SMIs) sponsorship disclosure on social media users’ (SMUs) behavioral outcomes (i.e. influencer avoidance, influencer switching and brand avoidance) and whether these relationships are moderated by SMIs’ honesty declaration and SMU cynicism.

Design/methodology/approach
A 2x2 between-subjects experimental design was used across four studies. Data collected across four online experiments were analyzed.

Findings
Study 1 found that sponsorship disclosures increased influencer avoidance, influencer switching and brand avoidance. Study 2 found that SMUs’ psychological contract violation with SMIs mediated these relationships. However, SMIs’ effective honesty declaration statements (vs no declaration) subdued SMUs’ negative behavioral outcomes. Study 3 elucidated that SMUs’ cynicism (vs no cynicism) accentuated the effects of sponsorship disclosures on influencer avoidance, influencer switching and brand avoidance. Studies 2 and 3 supported moderated mediation effect through SMUs’ psychological contract violation for honesty declaration but not SMU cynicism.

Practical implications
This study elucidates SMUs’ evaluation of brand-sponsored SMI posts and provides managers with tools such as honesty declaration statements and tags to offset the negative effects on consumer behavioral outcomes.

Originality/value
This is one of the initial studies investigating SMUs’ psychological contract violation and the effects of SMUs’ cynicism in SMIs’ sponsorship disclosure context. Also, this study conceptualizes a novel construct, influencer switching, as one of the consequences of sponsorship disclosure.
Roots of resilience: a qualitative exploration of youth driven community food gardens in Cape Town, South Africa
Authors: Kanosvamhira Tinashe P. 
Published: December 2024

PurposeThe purpose of this study is to investigate the dynamics of youth engagement in urban agriculture, particularly through youth gardens in distressed neighbourhoods of Cape Town. This examination is crucial due to the limited involvement of youth in urban agriculture, which poses a threat to the sustainability of these practices despite their recognised contributions to urban development.Design/methodology/approachThe research employs a qualitative methodology to explore the motivations, challenges and experiences of young urban farmers. Semi-structured interviews with youth participants from selected urban community gardens, complemented by virtual ethnography, form the core of the data collection process. This approach provides an in-depth understanding of the factors influencing youth participation in urban farming.FindingsThe study reveals that youth engagement in urban agriculture is motivated by various factors, including entrepreneurial aspirations, environmental justice activism, and a dedication to food justice. These findings suggest that for urban agriculture initiatives to be effective in such settings, they must acknowledge and address the specific motivations and contextual challenges faced by young people.Research limitations/implicationsThe study’s findings are context-specific to the distressed neighbourhoods of Cape Town, which may limit their generalisability to other urban settings. Future research could expand the scope to include a comparative analysis with other cities.Practical implicationsThe insights gained from this study can inform the design of urban agriculture initiatives that better engage youth, thereby fostering community development and sustainable urban practices.Originality/valueThis research offers novel insights into the underexplored area of youth engagement in urban agriculture within distressed urban environments. By focusing on the voices and experiences of young urban farmers in Cape Town, the study contributes to the development of targeted policies and programmes that aim to promote inclusive and sustainable urban agriculture practices, particularly by enhancing youth involvement.
Accelerating target‐oriented multi‐parameter elastic full‐waveform uncertainty estimation by reciprocity
Authors: Mulder W. A. , Kuvshinov B. N. 
Published: December 2024

AbstractThe accuracy of a model obtained by multi‐parameter full‐waveform inversion can be estimated by analysing the sensitivity of the data to perturbations of the model parameters in selected subsurface points. Each perturbation requires the computation of the seismic response in the form of Born scattering data for a typically very large number of shots, making the method time consuming. The computational cost can be significantly reduced by placing sources of different types at the Born scatterer, the point where the subsurface parameters are perturbed. Instead of modelling each shot separately, reciprocity relations provide the wavefields from the shot positions to the scatter point in terms of wavefields from the scatterer to the shot positions. In this way, the Born scattering data from a single point in the isotropic elastic case for a marine acquisition with pressure sources and receivers can be expressed in terms of the wavefields for force and moment tensor sources located at the scatterer and only a small number of forward runs are required. A two‐dimensional example illustrates how the result can be used to determine the Hessian and local relative covariance matrix for the model parameters at the scatterer at the cost of five forward simulations. In three dimensions, that would be nine.