bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolution of SARS-CoV-2 spike trimers towards optimized heparan sulfate cross-linking and inter-chain mobility
Authors: Froese Jurij , Mandalari Marco , Civera Monica , Elli Stefano , Pagani Isabel , Vicenzi Elisa , Garcia-Monge Itzel , Iorio Daniele Di , Frank Saskia , Bisio Antonella , Lenhart Dominik , Gruber Rudolf , Yates Edwin A. , Richter Ralf P. , Guerrini Marco , Wegner Seraphine V. , Grobe Kay 
Published: July 2024

AbstractThe heparan sulfate (HS)-rich extracellular matrix (ECM) serves as an initial interaction site for the homotrimeric spike (S)-protein of SARS-CoV-2 to facilitate subsequent docking to angiotensin-converting enzyme 2 (ACE2) receptors and cellular infection. Recent variants of concern (VOCs), notably Omicron, have evolved by swapping several amino acids to positively charged residues to enhance the S-protein trimer’s interaction with the negatively charged HS polysaccharide chains in the matrix. These increased interactions, however, may reduce Omicron’s ability to move through the HS-rich ECM to effectively find ACE2 receptors and infect cells, and raise the question of how HS-associated virus movement can be mechanistically explained. In this work, we show that Omicron S-proteins have evolved to balance HS interaction stability and dynamics, resulting in enhanced mobility on an HS-functionalized artificial matrix. Both properties are achieved by the ability of Omicrons S-proteins to cross-link at least two HS chains, providing both high avidity to retain the protein inside the HS-rich matrix, and fast dynamics, thus enabling direct S-protein switching between HS chains as a prerequisite for mobility at the cell surface. Optimized HS interactions can be targeted pharmaceutically, because an HS mimetic significantly suppressed surface binding and cellular infection specifically of the Omicron VOC. These findings suggest a robust way to interfere with SARS-CoV-2 Omicron infection and, potentially, future variants.
Robust deep learning estimation of cortical bone porosity from MR T1-weighted images for individualized transcranial focused ultrasound planning
Authors: Dagommer Matthieu , Daneshzand Mohammad , Nummemnaa Aapo , Guerin Bastien 
Published: July 2024

AbstractObjectiveTranscranial focused ultrasound (tFUS) is an emerging neuromodulation approach that has been demonstrated in animals but is difficult to translate to humans because of acoustic attenuation and scattering in the skull. Optimal dose delivery requires subject-specific skull porosity estimates which has traditionally been done using CT. We propose a deep learning (DL) estimation of skull porosity from T1-weighted MRI images which removes the need for radiation-inducing CT scans.ApproachWe evaluate the impact of different DL approaches, including network architecture, input size and dimensionality, multichannel inputs, data augmentation, and loss functions. We also propose back-propagation in the mask (BIM), a method whereby only voxels inside the skull mask contribute to training. We evaluate the robustness of the best model to input image noise and MRI acquisition parameters and propagate porosity estimation errors in thousands of beam propagation scenarios.Main resultsOur best performing model is a cGAN with a ResNet-9 generator with 3D 64×64×64 inputs trained with L1 and L2 losses. The model achieved a mean absolute error of 6.9% in the test set, compared to 9.5% with the pseudo-CT of Izquierdo et al. (38% improvement) and 9.4% with the generic pixel-to-pixel image translation cGAN pix2pix (36% improvement). Acoustic dose distributions in the thalamus were more accurate with our approach than with the pseudo-CT approach of both Burgos et al. and Izquierdo et al, resulting in near-optimal treatment planning and dose estimation at all frequencies compared to CT (reference).SignificanceOur DL approach porosity estimates with ∼7% error, is robust to input image noise and MRI acquisition parameters (sequence, coils, field strength) and yields near-optimal treatment planning and dose estimates for both central (thalamus) and lateral brain targets (amygdala) in the 200-1000 kHz frequency range.
Adiabatic quantum imaginary time evolution
Authors: Hejazi Kasra , Motta Mario , Chan Garnet Kin-Lic 
Published: July 2024

We introduce an adiabatic state preparation protocol which implements quantum imaginary time evolution under the Hamiltonian of the system. Unlike the original quantum imaginary time evolution algorithm, adiabatic quantum imaginary time evolution does not require quantum state tomography during its runtime and, unlike standard adiabatic state preparation, the final Hamiltonian is not the system Hamiltonian. Instead, the algorithm obtains the adiabatic Hamiltonian by integrating a classical differential equation that ensures that one follows the imaginary time evolution state trajectory. We introduce some heuristics that allow this protocol to be implemented on quantum architectures with limited resources. We explore the performance of this algorithm via classical simulations in a one-dimensional spin model and highlight essential features that determine its cost, performance, and implementability for longer times, and compare to the original quantum imaginary time evolution for ground-state preparation. More generally, our algorithm expands the range of states accessible to adiabatic state preparation methods beyond those that are expressed as ground states of simple explicit Hamiltonians.

Published by the American Physical Society
2024
Carbon emission reduction in construction industry: qualitative insights on procurement, policies and artificial intelligence
Authors: Kumar Danish , Zhang Chengyi 
Published: July 2024

PurposeThe construction industry is a major contributor to global carbon emissions. This study investigates the role of procurement and contracting methods in carbon emission reduction (CER) in the construction industry. It also examines artificial intelligence’s (AI’s) potential to drive low-carbon practices, aiming to identify transformative policies and practices.Design/methodology/approachThis study employed a qualitative methodology, engaging in semi-structured interviews with nine industry professionals alongside an innovative engagement with Generative Pre-trained Transformer (GPT) technology to gather insights into procurement and project delivery methods (PDM) role in CER. The study involved identifying patterns, organizing themes, and analyzing data to extract meaningful insights on effective policies and strategies for CER in the construction industry.FindingsThe results underscore the importance of early contractor involvement and integrated PDM for CER in construction. Results emphasize the pivotal role of project owners in directing projects toward sustainability, highlighting the need for client demand. The research identifies cost constraints, limited material availability, and human resource capacity as key barriers in the US. The study proposes innovative materials, financial incentives, education, and regulatory standards as effective interventions. It also explores the future use of AI in enhancing CER, suggesting new avenues for technological integration.Originality/valueThe study provides empirical insights into the role of procurement and PDM in CER within the US construction industry by using qualitative approach and use of a GPT. It underscores the interplay between contracting methods, stakeholder engagement, and AI’s emerging role, for enhancing policies and practices to decarbonize the US construction industry.
Does the pandemic affect the lifestyle and dietary intake? A comparative investigation during the pandemic and new normal situation
Authors: Dogra Pallavi , Kaushal Arun 
Published: July 2024

PurposeThe study attempts to investigate the role of social media in spreading awareness regarding ayurvedic immunity boosters (AIB) and changes in diet. Further, the study examines the factors affecting the willingness to pay for ayurvedic immunity boosters (WPIB) during the pandemic and new normal situation with the moderating effect of the “fear of COVID-19 infection.”Design/methodology/approachThe data were collected from millennials in two phases, i.e. the first phase (1 July–August 2021) with 300 respondents and a second phase with (June–August 2022) 257 respondents. An online questionnaire was shared with millennials using the snowball sampling technique. Descriptive statistics with SPSS and SmartPLS 4.0 software were applied to analyze the data.FindingsThe results found a variation in AIB content sharing on social media during 2021 and 2022. Results found that respondents reported significant changes in their lifestyle and diet, like consuming honey, khada, tulsi tea, etc. In 2021, health consciousness and trust significantly affected WPIB, whereas in 2022, only health consciousness was substantially affected. Fear of COVID-19 infection moderates the relationship between health consciousness, perceived fear and willingness to pay for ayurvedic products, whereas the effect on consumer preference and trust remains insignificant.Research limitations/implicationsResults could help ayurvedic product manufacturing companies understand the consumers' mindset and the factors that stimulate consumers to buy these immunity boosters. Ayurvedic advertisers should design unambiguous messages that focus on health consciousness and have trustable components to encourage consumers to adopt a healthy lifestyle.Originality/valueThis is one of its kinds of studies that presents the contrasts of how the COVID-19 crisis has significantly changed individuals' dietary intake and affected lifestyle patterns.
A new optimal weapon target assignment method using an artificial fish swarm algorithm with survival evolution
Authors: Xu Ningjun , Sun Miaomiao , Shi Zhangsong , Zhang Jin 
Published: July 2024

PurposeFirepower conflicts usually decay the firepower plan's enforceability, thus incurring high survival risks. Previous studies have shown little attention to avoiding firepower conflicts during the weapon target assignment process. This research proposes a new constrained optimization model named Firepower Conflict Free WTA (FCFWTA) and designs a Survival Evolution (SE) strategy for Artificial Fish Swarm Algorithm (AFSA) to solve the complex constrained WTA problem. In this way, commanders can get more reliable firepower assignment decision support.Design/methodology/approachA new constrained optimization model named Firepower Conflict Free WTA (FCFWTA) is constructed. FCFWTA unifies firepower decision variables for different kinds of weapons and takes the firing time point as a clue for firepower conflict checking. The objective function of FCFWTA is the weighted sum of the minimum threat value rest rate (RRTV), maximum hit efficiency (HE) and minimum latest interception time percentage (PLT). Since previous algorithms do not check and resolve intermediate results during optimization, an adapted strategy named Survival Evolution is designed. It enables making full use of the limited firepower without adjusting the coordination scenario in execution.FindingsThe proposed method offers significant advantages in two aspects. Firstly, it effectively enhances the optimization results of WTA in the absence of firepower conflicts. Evidence from Figure. 6 confirms that without the proposed method, there is a high likelihood of generating invalid outcomes. After implementing firepower conflict check and resolution, there is a substantial degradation in the objective function value. Secondly, the method excels at equitably distributing firepower among multiple targets while also enhancing the overall interception probability, irrespective of the varying complexities presented by different scenarios. This ability to maintain balance and efficiency is crucial for tackling defense-related issues.Research limitations/implicationsSpecifically, SE is tailored for MWMT problem under time and space constraints. This approach diverges significantly from conventional MWMT research, which typically focuses solely on ammunition quantity or firing range. Consequently, the primary objective was to verify the efficacy of this method. Test results indicated that SE does not exhibit uniform performance across different algorithms; while it significantly enhances the efficacy with PSO and AFSA, its influence is considerably diminished when applied to GA. It might be attributed to the inherent randomness associated with crossover and mutation, which can increase the likelihood of firepower conflicts, coupled with SE's reorganization of the chromosome.Originality/valueThe work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part.
Do dominant groups respond negatively to diversity policies? The impact of modern racism beliefs on organizational citizenship behavior intentions
Authors: Morton John 
Published: July 2024

PurposeDiversity policies have become widespread in modern organizations. Such policies often have the goal of improving the workplace experiences of marginalized groups, and understanding dominant group reactions to such policies is vital to their effectiveness. This paper investigated the dominant group (i.e. White individuals) response to diversity policies, specifically how White individuals’ modern racism beliefs influence their organizational citizenship behavior (OCB) intentions when exposed to a diversity policy.Design/methodology/approachUsing experimental methodology and a combination of social exchange theory and literature on modern racism, the two studies explore how exposure to a diversity (versus neutral) policy influences White individuals’ OCB intentions in two different settings (lab and field).FindingsThe results of these studies make clear that certain people respond negatively to diversity policies. In Study 1, White participants with relatively high modern racism beliefs showed lower OCB intentions directed at their organization when exposed to a diversity versus neutral policy. No differences emerged for White participants with relatively low modern racism beliefs. In Study 2, the results were replicated using a field sample of working adults in which they indicated their likelihood of OCB toward their employing organization.Originality/valueThe findings suggest that diversity policies can have unintended, adverse consequences for organizations, but are dependent upon employees’ modern racism beliefs. The results of the two studies provide a richer understanding of dominant group reactions to diversity policies by examining a downstream consequence of great organizational importance, i.e. OCB.
Leader responses to a pandemic: the interaction of leader gender and country collectivism predicting pandemic deaths
Authors: Triana María del Carmen , Richard Orlando , Byun Seo-Young , Park Kendall , Delgado Dora , Delgado Jorge 
Published: July 2024

PurposeThe present study examines head of state gender and national collectivism to explain how some leaders have been able to manage a pandemic better than others.Design/methodology/approachWe measure pandemic deaths per million using objective numbers for each country. Country collectivism is measured using the GLOBE study. Qualitative analyses of world leader speeches are used to examine how health-focused leaders’ language is. Media attention with sentiment analysis about each leader’s handling of the pandemic is also used to show how others reacted to leaders.FindingsCountries with female leaders showed fewer pandemic deaths than those led by male leaders. The interaction between leader gender and country collectivism predicted death. Media sentiment was more favorable for women leaders than men leaders.Practical implicationsDuring times of crises, women’s more careful tendencies keep their constituents safer than their male counterparts. Country collectivism also aids male leaders in keeping constituents safe.Social implicationsThe present study helps unpack when women leaders thrive and outperform their male counterparts. This furthers United Nations Sustainable Development Goal 5: gender equality.Originality/valueThe study examines leader gender and national collectivism to predict pandemic deaths.
Psycho-cognitive relationship between data and knowledge discovery: a conceptual critique
Authors: Saha Mousumi , Ghosh Saptarshi 
Published: July 2024

Purpose
The extraction of relevant knowledge from data is called knowledge discovery (KD). The KD process requires a large amount of data and it must be reliable before mining. Complexity is not only in deriving knowledge from data but also in improving system performance with a psycho-cognitive approach. KD demands a high level of human cognition and mental activity to generate and retrieve knowledge. Therefore, this study aims to explain how psychological knowledge is involved in KD.

Design/methodology/approach
By understanding the cognitive processes that lead to knowledge production, KD can be improved through interventions that target psychological processes, such as attention, learning and memory. In addition, psycho-cognitive approaches can help us to better grasp the process of KD and the factors that influence its effectiveness. The study attempted to correlate interdependence by interpreting cognitive approaches to KD from a psychological perspective. The authors of this paper draw on both primary and secondary literary warrants to empirically prove psychological bending in KD.

Findings
Understanding the psychological aspects of data and KD can identify the development of tools, process and environments that support individual and teams in making sense of data and extracting valuable knowledge. The study also finds that interdisciplinary collaboration, bringing together expertise in psychology, data science and domain specific knowledge fosters effective KD processes.

Originality/value
The KD system cannot function well and will not be able to achieve its full potential without psycho-cognitive foundation. It was found that KD in the KD system is influenced by human cognition. The authors made a contribution to KD by fusing psycho-cognitive approaches with data-driven technology and machine learning.
Advancing gender inclusivity: moving entrepreneurial ecosystems onto new paths
Authors: de Bruin Anne , Swail Janine 
Published: July 2024

PurposeDrawing on a constructionist-poststructuralist feminist perspective, this paper aims to extend thinking on the evolution of entrepreneurial ecosystems by exploring how gendered entrepreneurial ecosystems can become more inclusive.Design/methodology/approachThe paper contends path dependency of entrepreneurial ecosystems, maintains embedded gender bias (and biases against disadvantaged or unconventional entrepreneur groups) and builds an argument for path creation to de-bias entrepreneurial ecosystems. A metaphorical descriptor of entrepreneurial ecosystems is probed as contributing to the gendered entrepreneurial ecosystem discourse. Three propositions, namely on path creation, transformative agency and appropriate metaphors, are derived from the extant literature and an illustrative example employed to interrogate these propositions.FindingsWe advance path creation via transformative agency as a means for moving towards inclusive entrepreneurial ecosystems. We provide an alternative metaphor to springboard change to the gendered scholarly discourse on entrepreneurial ecosystems. Our illustrative example lends support to our propositions.Originality/valueThis paper helps lay a foundation for new thinking on change towards inclusive entrepreneurial ecosystems. It provides a powerful argument for broadening the mainstream path dependence view of entrepreneurial ecosystems. It is unique in suggesting a constructionist-poststructuralist feminist standpoint to challenge the dominant discourse on entrepreneurial ecosystems.
Navigating the future of megaprojects sustainability: a comprehensive framework and research agendas
Authors: Li Yongkui , Wang Mengqi , Locatelli Giorgio , Zhang Yueran 
Published: July 2024

PurposeMegaprojects can play a crucial role in achieving Sustainable Development Goals (SDGs) and tackling Global Challenges. However, they are often criticized for their massive resource consumption, poor cost/time performance and significant social-environmental impacts, including irreversible environmental damage. This study aims to chart the evolution of research on megaprojects sustainability and to offer a roadmap for future developments.Design/methodology/approachThis study adopted a systematic literature review (SLR) to identify emerging themes and gaps. This study follows a three-step process of planning, conducting and reporting, based on the Tranfield approach. The overview of megaprojects sustainability research was captured through bibliometric analysis. In addition, content analysis was carried out to reveal the development of this field and get an insight into the future directions towards sustainability transition.FindingsThis study provides a longitudinal, in-depth analysis of megaprojects sustainability studies. Drawing on sustainability science and project management theories, we introduce a three-dimensional analytical framework consisting of sustainability, scope and stakeholder. This framework explains the evolution of megaprojects sustainability research from sustainability of megaprojects, to sustainability for megaprojects and then to sustainability by megaprojects. Three future avenues are proposed: (1) SDGs orientation at multi-level; (2) scope enlargement at temporal and spatial scales and (3) inclusive development for stakeholders.Originality/valueThis research contributes to the literature by providing a comprehensive and forward-looking analysis of megaprojects sustainability research. The framework and three research agendas provide a comprehensive picture of megaproject sustainability research; the agenda for future research is intended to inspire more studies and disruptive actions towards sustainability transition.
Examining the role of expectations in outsourcing success utilizing the hierarchy of effects model
Authors: Carraher-Wolverton Colleen 
Published: July 2024

Purpose
This paper aims to involve both the development of a quantitative measure of outsourcing success that integrates recent research findings on expectations and applying the hierarchy-of-effects (HOE) model to investigating the influence of success on client satisfaction and recommendation intention.

Design/methodology/approach
This paper conducted a global survey of information systems managers and Chief Information Officers from firms who have engaged in outsourcing and analyzed the data using partial least squares (PLS).

Findings
The study analysis demonstrates the impact of client expectations on perceived outsourcing success, client satisfaction and intention to recommend. This paper also discusses how findings of this study provide important implications for both researchers and practitioners.

Originality/value
To further investigate the theoretical trend toward examining the impact of expectations on outsourcing success, this study extends the foundational success research by quantitatively demonstrating the robustness of an outsourcing success construct that incorporates expectations. Moreover, this study extends the traditional models of success by incorporating factors from each of the stages of client behavior, including cognition, affect and conation.