bluuebunny/crossref_metadata_2025 huggingface dataset:
FerroEnrich: An Interactive web tool for computing Ferroptosis index and gene enrichment
Authors: Tirumalasetty Munichandra Babu , Choubey Mayank , Wahiduzzaman Md , Barua Rashu , Mohiuddin Mohammad Sarif , Miao Qing Robert
Published: September 2024

Ferroptosis is an iron-dependent form of controlled cell death and is characterized by the formation of lipid peroxides. Understanding gene expressions associated with ferroptosis is critical for determining its function in illnesses and potential therapeutic approaches. Despite its significance, no computational model is currently available to accurately quantify the ferroptosis incident. FerroEnrich is a sophisticated web-based tool built using R Shiny application to enumerate the occurrence of ferroptosis based on the relevant gene expressions. This tool available athttps://ferroenrich.shinyapps.io/ferroenrich/processes the input gene expression file to identify genes that are resistant or prone to ferroptosis, calculates ferroptosis index value with dynamic colored heatmap and gene network plot. This manuscript describes the design, operation and usability of FerroEnrich, including examples and a discussion of its potential impact on ferroptosis research. FerroEnrich is a vital tool for researchers, allowing them to explore and analyze complicated gene expression data related to ferroptosis.
Simulating photonic devices with noisy optical elements
Authors: Vischi Michele , Di Bartolomeo Giovanni , Proietti Massimiliano , Koudia Seid , Cerocchi Filippo , Dispenza Massimiliano , Bassi Angelo
Published: September 2024

Quantum computers are inherently affected by noise. While in the long term, error correction codes will account for noise at the cost of increasing physical qubits, in the near term, the performance of any quantum algorithm should be tested and simulated in the presence of noise. As noise acts on the hardware, the classical simulation of a quantum algorithm should not be agnostic on the platform used for the computation. In this paper, we apply the recently proposed noisy gates approach to efficiently simulate noisy optical circuits described in the dual rail framework. The evolution of the state vector is simulated directly, without requiring the mapping to the density matrix framework. Notably, we test the method on both the gate-based and measurement-based quantum computing models, showing that the approach is very versatile. We also evaluate the performance of a photonic variational quantum algorithm to solve the MAX-2-CUT problem. In particular we design and simulate an ansatz, which is resilient to photon losses up to p∼10−3 making it relevant for near-term applications.

Published by the American Physical Society
2024
Lattice symmetry relaxation as a cause for anisotropic line broadening and peak shift in powder diffraction
Authors: Gregorkiewitz Miguel , Boschetti Alice
Published: September 2024

In powder diffraction, lattice symmetry relaxation causes a peak to split into several components which are not resolved if the degree of desymmetrization is small (pseudosymmetry). Here the equations which rule peak splitting are elaborated for the six minimal symmetry transitions, showing that the resulting split peaks are generally broader and asymmetric, and suffer an hkl-dependent displacement with respect to the high-symmetry parent peak. These results will be of help in Rietveld refinement of pseudosymmetric structures where an exact interpretation of peak deformation is required.
Societal bonds in virtual spaces: exploring the sense of community in online student communities at Anadolu University’s Open Education System
Authors: Uçar Merve , Güler Emel , Koçdar Serpil
Published: September 2024

Purpose

This study aims to investigate the levels of the sense of community among students enrolled in online student communities at Anadolu University Open Education System (OES), as well as their motivations for joining these communities and their expectations.

Design/methodology/approach

An explanatory sequential design incorporating mixed research methods was employed as the research framework for this study. Quantitative data were collected from 1,065 students enrolled in online student communities during the 2021–2022 academic year, while qualitative data were obtained from 14 students after the survey using an extreme case sampling method. The quantitative data were analyzed using descriptive statistics, independent samples t-tests, one-way analysis of variance tests, correlation analysis and regression analysis. The qualitative data were analyzed using content analysis.

Findings

The study results indicate that students enrolled in online student communities generally have higher levels of a sense of community. These levels did not significantly differ based on gender, employment status, entry type to the university, program studied or membership status in more than one community. However, significant differences were observed in terms of age, time spent in communities and meeting attendance. Additionally, students' perceptions of social presence had a significant effect on their sense of community.

Originality/value

This study is the first to investigate the sense of community in online student communities at Anadolu University's OES.
From physical degradation condition ratings of building elements to lost value ratio bands
Authors: Wickramasinghe Vajira , Dias Priyan , Robert Dilan , Setunge Sujeeva
Published: September 2024

Purpose

Defining degradation in terms of physical deficiency-based condition descriptors, combined with Markov chain modelling, has been shown to provide improved predictions of degradation. However, unless these physical conditions are converted to lost value ratios (LVRs), maintenance managers would not be able to grasp the cost implications of degradation. Hence the purpose of this research is to convert the predicted deficiency-based condition ratings to lost value ratio bands.

Design/methodology/approach

Rectification costs were found using a Building Schedule of Rates to arrive at LVRs for each of the physical degradation conditions for the 12 building elements studied (ranging from concrete elements through finishes and ceilings to doors and windows). These LVRs were allocated into five bands with LVR interval limits of 0.00, 0.10, 0.25, 0.50, 0.75 and 1.00, with the five intervening ranges corresponding to LVR Bands A to E. These computations were compared with those arrived at independently by industry professionals.

Findings

Elements such as doors, widows and ceilings reached the maximum LVR Band E at the worst physical Condition 5 defined. However, Condition 5 for other elements only corresponded to LVR Bands A to D. Some 83% of the LVR bands assigned to the physical conditions were in agreement with those arrived at by the professionals, or differed by only one band.

Originality/value

The conversion of deficiency-based conditions to LVR bands yielded a completely new maintenance-oriented perspective on degradation. The banding was done using a novel ranking and clustering process that identified regions of high variation in LVRs as thresholds of the bands.
Leveraging technological readiness and knowledge sources for green innovation: a resource orchestration perspective
Authors: Khayyam Muhammad , Yushi Jiang , Liu Qiqi , Idrees Hisham , Qin Shengze , Nurlegul Alinur
Published: September 2024

Purpose

This study delves into the intricate dynamics between technological readiness, knowledge sources and their collective impact on firms' ability to achieve ambidextrous green innovation (GI). It specifically aims to dissect the moderating influence of resource orchestration capability (ROC) in this nexus, proposing a nuanced exploration into how technological preparedness and the strategic utilisation of both internal and external knowledge sources can significantly steer firms towards successful exploitative and exploratory GI endeavours.

Design/methodology/approach

The study draws upon resource orchestration theory, integrating a cross-sectional approach that incorporates primary data from Pakistani manufacturing firms. The data consisting of 452 responses was analysed employing Partial Least Squares Structural Equation Modelling (PLS-SEM).

Findings

The research verifies that technological readiness has a substantial influence on exploitative and exploratory GI. Moreover, it reveals that both internal and external knowledge resources mediate the link between technological readiness and ambidextrous GI. Notably, while ROC enhances the favourable impact of external knowledge resources on both types of GI, it does not significantly moderate the effect of internal knowledge sources.

Practical implications

Managers must prioritize enhancing technological preparedness and strategically coordinating knowledge resources to drive both exploitative and exploratory environmentally friendly innovation. Investments in technology and collaborations with external partners, guided by strong resource management capabilities, are crucial for achieving sustainable innovation.

Originality/value

This research contributes to ambidextrous GI literature by examining the roles of technological readiness, mediated by internal and external knowledge sources and moderated by ROC. It offers detailed insights into the mechanisms that promote sustainable innovation, enriching the current understanding of the subject.
Internet of things platforms adoption in agriculture: comparative theoretical models
Authors: Zamil Ahmad M.A. , Javed Hafiz Muhammad Usama , Ali Saqib
Published: September 2024

Purpose

The purpose of this study is to determine the farmers’ behavioural intention (BI) to adopt Internet of things platforms (IoT-P) in the agriculture context by comparing two well-known theories: the united theory of acceptance and use of technology (UTAUT), and the decomposed theory of planned behaviour (DTPB) with the integration of innovation resistance theory (IRT).

Design/methodology/approach

Purposive sampling was used to get responses from 267 potential farmers to examine their IoT-P adoption intention in Pakistan. The PLS-SEM, PLS model evaluation criterion and PLS model selection criterion were considered to determine the significance of path co-efficient, explanatory power, predictive power and more parsimonious model.

Findings

The findings demonstrate that DTPB is the best model with the extension of functional barriers (FBs) and psychological barriers (PBs). It has more predictive relevance and explanatory power. The results show that farmers’ attitude (ATT), based on the evaluation of three attributes (i.e. perceived usefulness (PU), perceived ease of use (PEOU) and compatibility (COMP)), is the strong predictor of farmers’ BI to adopt IoT-P. In addition, self-efficacy (SEF) and facilitating conditions (FC) peer influence (PI) and superiors’ influence (SPI) are required for adoption of IoT-P devices. Finally, FB and PB significantly and negatively influence the farmers’ BI to adopt IoT-P.

Originality/value

This research is the first to consider the two technology adoption models with the integration of IRT for explaining farmers’ BI in the context of agriculture.
The impact of Sharia compliance on attracting investments: empirical evidence from GCC
Authors: Tawfik Omar Ikbal , Elmaasrawy Hamada Elsaid , Hussainey Khaled
Published: September 2024

Purpose

This study aims to demonstrate the impact of Sharia-compliance (SC) on attracting various types of investment, including foreign, family, institutional, royal, government and large individual investments.

Design/methodology/approach

The sample comprises 168 nonfinancial companies listed in the financial markets of the Gulf Cooperation Council (GCC) countries from 2009 to 2019, totaling 1,848 observations. The researchers used the ordinary least squares panel data method, with additional tests conducted using the two-stage least squares method.

Findings

The results indicate a negative relationship between SC and both foreign and institutional investments. Conversely, there is a positive relationship between SC and both family investment and large individual investor investment. Furthermore, the study found no significant relationship between SC and both government and royal investments (RIs).

Practical implications

The study enhances understanding of the role of Sharia-compliant companies in attracting investment. For managers of such companies, there is a need to make their firms more appealing to diverse investor types. Current and potential investors in Sharia-compliant companies should be aware of the investor nature controlling these companies. This study is beneficial for policymakers and regulators to assess the impact of Islamic Sharia-imposed restrictions on financial decision-making in companies. Policymakers should develop and monitor indicators of companies’ adherence to SC law in the six GCC countries and should also issue rules to enhance Sharia-compliant companies’ commitment to governance and transparency.

Originality/value

To the best of the authors’ knowledge, this study is the first of its kind to address the impact of SC on attracting different investment types. It includes six distinct investment types, notably RI, a significant variable in GCC countries’ business environment due to the considerable wealth and influence of royal family members.
Sustainability reporting in public–private hybrid organisations: a structured literature review
Authors: Ligorio Lorenzo , Caputo Fabio , Venturelli Andrea
Published: September 2024

Purpose

The growing interest in sustainability reporting by management scholars is leading to new research fields. Among the different actors involved in non-financial disclosures, recent research is paying attention to public–private hybrid organisations. This study explores the main focus and critique of current and past literature on public–private hybrids and sustainability reporting.

Design/methodology/approach

To explore the recent field of sustainability reporting in public–private hybrids, this study adopts a structured literature review on studies collected from the scientific platforms Scopus and Web of Science.

Findings

Findings revealed a young and growing field of research. Also, it emerged how more profound attention is being paid to the features and drivers of sustainability reporting in the public–private sector, along with a stimulus for further research on new reporting frameworks.

Research limitations/implications

Considering the novelty of the research field, the collection of analysed studies was very limited. Moreover, grey literature was not incorporated into the research. In addition, only two sources of data were considered.

Practical implications

This study includes different implications regarding sustainability reporting in public–private hybrids, emphasizing transparency, accountability and the need for further research and adoption of external assurance.

Originality/value

Because of the novelty of the research field, this is the first study to focus on literature that addresses the relationship between sustainability reporting and public–private entities. Furthermore, using a structured literature review has provided a profound view of the published literature.
Term structure of interest rate and macro economy: an empirical study on selected emerging countries sovereign bond
Authors: Ariefianto Doddy , Amanda Citra , Ananto Husodo Zaafri
Published: September 2024

Purpose

To examine the relationship between the term structure of interest rates of sovereign bonds in emerging nations and their macroeconomic indicators, specifically emphasizing its persistence and interaction with inflation, foreign exchange and fiscal conditions.

Design/methodology/approach

Adopting the Mean Group Instrumental Variables (MGIV) technique, as proposed by Cui et al. (2020) and Norkute et al. (2021), this study analyzes a monthly panel dataset from nine emerging economies spanning January 2010 to October 2021, totaling 1,278 observations.

Findings

The findings reveal significant persistence in both slope and curvature, with a rising yield level linked to the term structure's flattening, while shifts in inflation and exchange rates correlate with its steepening.

Originality/value

Our study is among the few which used an empirically constructed measure of the term structure of interest instead of a theoretical construct. To best our knowledge, we are the first to employ MGIV.
The use of critical reflection in one-to-one supervision in children and families social work in England: an evidence review
Authors: Leonard Kate
Published: September 2024

Purpose

English social work policies and regulatory bodies propel critical reflection as a professional requirement and a worthwhile activity. The purpose of this paper is to report on the current international and UK evidence that informs the understanding and use of critical reflection and associated terms – reflection, reflective practice and reflective supervision – in one-to-one practitioner supervision in local authority children and families social work in England.

Design/methodology/approach

A review of the evidence was undertaken using documentary policy analysis and a scholastic literature review to examine the history and current knowledge available as of December 2022.

Findings

The historical policy and professional context of critical reflection in one-to-one supervision in England is discussed. The current evidence review identified three themes – the role of critical reflection in models of supervision, the influences of national, organisational and professional cultures and the supervisor practitioner relationship. The nuanced nature of the presence of critical reflection in supervision and a lack of clarity when theorising and describing critical reflection has implications for policy, supervisory practice and research design.

Originality/value

Critical reflection in one-to-one social work supervision is under researched. This review draws on the evidence from international research and local policy to offer an understanding of the complexity of theorising, practicing and researching critical reflection in one-to-one supervision in local authority children and families social work in England.
Impact of nations’ green behavior on green growth by considering the moderating role of environmental policy stringency
Authors: Awan Amara , Hussain Kashif , Zafar Mahwish , Butt Maryam Javed , Yaghmour Samer
Published: September 2024

Purpose

Protecting the planet from unprecedented environmental crises in the presence of economic expansion has become a critical global concern. Hence, the current study aims to analyze the impact of nations’ green behaviors that they adopt to protect the planet while promoting economic expansion. Additionally, the study explores the moderating role of ES in the nexus of GI and green growth.

Design/methodology/approach

Data were collected over a period of 1990–2019. Analysis was conducted by employing panel data analysis techniques and various robustness tests, including multicollinearity, serial correlation and spatial correlation, for a sample of 33 nations by categorizing in Organization for Economic Co-operation and Development (OECD) and Brazil, Russia, India, China, and South Africa (BRICS) economies as well as in the pre- and post-financial crisis period.

Findings

Analysis of the composite sample reveals a significant positive impact of green investments and green innovations on green growth. Further analysis reveals a significant moderating role of environmental policy stringency in OECD economies, especially in the pre-financial crisis period. The interaction slope shows that the contribution of green innovations to green growth is positive at high and medium levels of ES. However, in the case of BRICS economies, this moderating role is insignificant.

Practical implications

Study findings signify the importance of stakeholder environment and urge governments to prioritize funds for sectors practicing environmentally friendly behaviors to foster green growth and stresses for more effective infrastructure of policy implementation, monitoring and evaluation.

Originality/value

The relationship of green investments, innovations and green growth has been established largely in existing literature; however, there is a dearth of studies to analyze the moderating role of ES. Hence the current study investigates this moderating role in the nexus of nations’ green behavior and green growth in different stakeholder environments and contexts.
Study on axial and bending stiffness characteristics of reinforced S-shaped bellows
Authors: Yuan Zhe , Huo Shihui
Published: September 2024

Purpose

Reinforced S-shape bellows are novel metal bellows with high pressure resistance. Displacement compensation ability is a key index in the design of metal bellows. Axial-tension-compression deformation and bending deformation are two typical displacement compensation forms. Thus, analysis of axial and bending stiffness is important in structure design.

Design/methodology/approach

In this study, theory analytics of axial tension and compression stiffness of reinforced S-shaped bellows structure is derived, and the load-displacement relationship during axial deformation is obtained by correcting the geometric parameters of waveform during axial tension and compression deformations. On the basis of them, the relationships of bending stiffness with axial tensile and compression stiffness under the action of bending loading are constructed, and thus, the theory analytics of bending stiffness is realized for S-shaped bellows.

Findings

This theory analytics is verified by comparing the results of theory analytics with those of numerical simulation for a few typical examples. An investigation on the axial and bending non-linear mechanical behaviors of multi-layer-reinforced S-shaped bellows was also carried out by numerical simulation and experiment, and the experimental results verified the reliability of the analysis method.

Originality/value

It is found that non-linearity behavior occurs greatly during the first loading course of reinforced S-shaped bellows, and the structure is strain-strengthened due to plastic deformation; however, stable stiffness characteristic is exhibited during the succeeding cyclic-loading course.
The role of chief medical officers in the Italian context: managers or clinicians?
Authors: Pratici Lorenzo , Fanelli Simone , Francesconi Andrea , Zangrandi Antonello
Published: September 2024

Purpose

Despite the advent of New Public Management theories over three decades ago, doubts persist regarding the practical implementation of these principles in the public health-care context. Challenges arise particularly from the type of system where this phenomenon is analyzed. In the Italian context, for instance, it can be arduous to define universally applicable organizational behaviors, given the interregional disparity that characterizes such a system. Furthermore, the professional identity of clinician-managers influences the perception of what “being a manager” means. This paper, thus, using the Italian context as a reference, aims to delineate what is the perception of Italian public hospitals clinician-middle-managers in terms of their responsibilities and tasks.

Design/methodology/approach

A survey-questionnaire was distributed to 6,011 Chief Medical Officers (CMOs) in Italian public hospitals, representing 100% of such role holders in the country. With a response rate of 16.7%, 1,005 responses were obtained. The questionnaire assessed CMOs' attitudes toward specific activities relevant to clinician-management, ranked from most to least important. Activities were derived from literature and categorized to discern management styles. Subgroups based on geographical location and professional orientation were also identified to isolate regional effects and professional identity influences.

Findings

Results suggested that activities associated with a collaborative approach are perceived as most important. Furthermore, it clearly emerges the difference based on professional orientation of CMOs. However, it could not be appreciated the same level of difference basing the analysis on regional disparities.

Originality/value

The interest in the role of middle management in healthcare organizations has increased over the years. Nevertheless, currently the authors believe that not many studies are focused on defining what “being a manager” means for clinician-managers themselves, rather than explaining what clinician-managers shall do.
Scientific evidence and specific context: leveraging large language models for health fact-checking
Authors: Ni Zhenni , Qian Yuxing , Chen Shuaipu , Jaulent Marie-Christine , Bousquet Cedric
Published: September 2024

Purpose

This study aims to evaluate the performance of LLMs with various prompt engineering strategies in the context of health fact-checking.

Design/methodology/approach

Inspired by Dual Process Theory, we introduce two kinds of prompts: Conclusion-first (System 1) and Explanation-first (System 2), and their respective retrieval-augmented variations. We evaluate the performance of these prompts across accuracy, argument elements, common errors and cost-effectiveness. Our study, conducted on two public health fact-checking datasets, categorized 10,212 claims as knowledge, anecdotes and news. To further analyze the reasoning process of LLM, we delve into the argument elements of health fact-checking generated by different prompts, revealing their tendencies in using evidence and contextual qualifiers. We conducted content analysis to identify and compare the common errors across various prompts.

Findings

Results indicate that the Conclusion-first prompt performs well in knowledge (89.70%,66.09%), anecdote (79.49%,79.99%) and news (85.61%,85.95%) claims even without retrieval augmentation, proving to be cost-effective. In contrast, the Explanation-first prompt often classifies claims as unknown. However, it significantly boosts accuracy for news claims (87.53%,88.60%) and anecdote claims (87.28%,90.62%) with retrieval augmentation. The Explanation-first prompt is more focused on context specificity and user intent understanding during health fact-checking, showing high potential with retrieval augmentation. Additionally, retrieval-augmented LLMs concentrate more on evidence and context, highlighting the importance of the relevance and safety of retrieved content.

Originality/value

This study offers insights into how a balanced integration could enhance the overall performance of LLMs in critical applications, paving the way for future research on optimizing LLMs for complex cognitive tasks.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2024-0111
Numerical simulation and analytical modelling of temperature and morphology of melt pool in electron beam powder bed fusion of copper
Authors: Sharabian Elmira , Khorasani Mahyar , Gulizia Stefan , Ghasemi Amir Hossein , MacDonald Eric , Downing David , Rolfe Bernard , Brandt Milan , Leary Martin
Published: September 2024

Purpose

This study aims to comprehensively investigate the electron beam powder bed fusion (EB-PBF) process for copper, offering validated estimations of melt pool temperature and morphology through numerical and analytical approaches. This work also assesses how process parameters influence the temperature fluctuations and the morphological changes of the melt pool.

Design/methodology/approach

Two distinct methods, an analytical model and a numerical simulation, were used to assess temperature profiles, melt pool morphology and associated heat transfer mechanisms, including conduction and keyhole mode. The analytical model considers conduction as the dominant heat transfer mechanism; the numerical model also includes convection and radiation, incorporating specific parameters such as beam power, scan speed, thermophysical material properties and powder interactions.

Findings

Both the analytical model and numerical simulations are highly correlated. Results indicated that the analytical model, emphasising material conduction, exhibited exceptional precision, although at substantially reduced cost. Statistical analysis of numerical outcomes underscored the substantial impact of beam power and scan speed on melt pool morphology and temperature in EB-PBF of copper.

Originality/value

This numerical simulation of copper in EB-PBF is the first high-fidelity model to consider the interaction between powder and substrate comprehensively. It accurately captures material properties, powder size distribution, thermal dynamics (including heat transfer between powder and substrate), phase changes and fluid dynamics. The model also integrates advanced computational methods such as computational fluid dynamics and discrete element method. The proposed model and simulation offer a valuable predictive tool for melt pool temperature, heat transfer processes and morphology. These insights are critical for ensuring the bonding quality of subsequent layers and, consequently, influencing the overall quality of the printed parts.
Enhanced strength, toughness and reliability in crab exoskeleton–inspired 3D-printed porous thermoplastics
Authors: Keleş Özgür , Anderson Eric H. , Tan Timothy L. , Wu Cheng-Lun , Karakoc Alp
Published: September 2024

Purpose

Fused deposition modeling enables multiscale structure control. However, most of this structural space is unexplored. Specifically, the impact of biomimetic porous structures on the mechanical behavior and reliability of common thermoplastics are unclear. In this work, porous structures inspired by the multifunctional crab exoskeleton were 3D-printed with different raster orientations, including fully rotating rasters similar to Bouligand structures found in biological materials. Tensile tests and simulations were performed to observe the stochastic behavior of fracture properties and to reveal the underlying origins of mechanical reliability in biomimetic porous systems.

Design/methodology/approach

Tensile tests were performed on 3D-printed porous structures with four different rasters. These rasters were biomimetic Bouligand, semi-Bouligand, 00 raster and 45°/−45° raster. In addition, two different sets were manufactured to observe the impact of contours on the mechanical behavior. A total of 137 tensile tests were performed. A total of 88 finite element simulations were executed using Abaqus built-in Hashin damage initiation criterion and energy-based damage evolution law. Weibull analyses were performed to quantify the stochastic properties.

Findings

Biomimetic Bouligand structure is effective in increasing fracture strength. Average fracture strength of the Bouligand structure was 33% higher compared to the default 45°/−45° and 10% higher compared to 00 rasters. Variations in strength were lower in Bouligand structure compared to the default 45°/−45° raster. However, 00 raster had the highest Weibull modulus m = 54 compared to Bouligand m = 25 and 45°/−45° m = 17. Simulations showed that Bouligand structure is effective in increasing the mechanical reliability through local damage accumulation around the holes. The simulated Weibull modulus of the Bouligand structure was 40 compared to the moduli of other rasters that ranged from 18 to 25.

Practical implications

The mechanical reliability of porous Bouligand structures is higher compared to other rasters, which makes the biomimetic structure a better choice for industrial applications. Contours decrease the strength and strain at failure for 3D-printed porous structures. Bouligand structures with rotating raster orientations increased strength and strain at failure when contours are present in the porous structure.

Originality/value

To the best of the authors’ knowledge, this is the first study showing the effects of biomimetic raster orientations on the mechanical behavior and the effects of contours on the tensile fracture properties of 3D-printed porous acrylonitrile butadiene styrene using tensile tests and fracture simulations. This is the first study applying composite fracture model to anisotropic porous 3D-printed polymers.
Herding behaviour in the cryptocurrency market: the role of uncertainty and return of classical financial markets
Authors: Ansari Hojjat , Peymany Moslem
Published: September 2024

Purpose

The purpose of the study is to examine the impact of uncertainty and return of classical financial assets on herding behaviour in the cryptocurrency market. Also, herding in this market and the impact of the COVID-19 pandemic have been investigated.

Design/methodology/approach

The study uses quantile regression to estimate the models. Daily data from ten major cryptocurrencies, the CCI30 index and three volatility indices (VIX, EVZ and GVZ), spot gold price, the MSCI and the US dollar indices from January 2018 to December 2023 have been used.

Findings

The findings show evidence of anti-herding during periods of simultaneous high volatility in stock and currency markets, as well as in the gold and currency markets. However, the results support herding in the whole sample period, which reduces when including the COVID-19 pandemic effect. In addition, the study does not support the relationship between returns of traditional financial assets and herding in the cryptocurrency market.

Practical implications

The result of the study can be useful for investors, particularly the managers of the novel class of ETFs, to make their investment decisions more consciously, regarding uncertainty in other financial markets. Also, the findings provide some insight to regulators regarding the herding behaviour in the cryptocurrency market and its influences on the financial system’s stability.

Originality/value

To the best of the authors’ knowledge, for the first time, this study examines the impact of concurrent high uncertainty conditions in classical financial markets on herding behaviour in the cryptocurrency market.
RFID-transformer recognition system (RTRS): enhancing privacy in facial recognition with transformer models
Authors: Wang Zeyuan , Xu He , Zhang Manman , Cai Zhaorui , Chen Yongyuan
Published: September 2024

Purpose

This paper aims to present a novel approach to facial recognition that enhances privacy by using radio frequency identification (RFID) technology combined with transformer models, eliminating the need for visual data and thus reducing privacy risks associated with traditional image-based systems.

Design/methodology/approach

The proposed RFID-transformer recognition system (RTRS) uses RFID technology to capture signal features such as phase and received signal strength indicator, which are then processed by a transformer model. The model is specifically designed to handle structured RFID data, capturing subtle patterns and dependencies to achieve accurate biometric recognition. The system’s performance was validated through comprehensive experiments involving different environmental conditions and user scenarios.

Findings

The experimental results demonstrate that the RTRS system achieves a recognition accuracy of 98.91%, maintaining robust performance across various challenging conditions, including low-light environments and changes in face orientation. In addition, the system provides a high level of privacy preservation by avoiding the collection and storage of visual data.

Originality/value

To the best of the authors’ knowledge, this work introduces the first RFID-based facial recognition system that fully leverages transformer models, offering a privacy-preserving alternative to traditional image-based methods. The system’s ability to perform accurately in diverse scenarios while ensuring user privacy makes it a significant advancement in biometric technology.
Cross‐equalization for time‐lapse sparker seismic data
Authors: Lee Soojin , Won Jongpil , Jun Hyunggu
Published: September 2024

Time‐lapse seismic data processing is an important technique for observing subsurface changes over time. The conventional time‐lapse seismic exploration has been conducted using a large‐scale exploration system. However, for efficient monitoring of shallow subsurface, time‐lapse monitoring based on the small‐scale exploration system is required. Small‐scale exploration system using a sparker source offers high vertical resolution and cost efficiency, but it faces challenges, such as inconsistent waveforms of sparker sources, inaccurate positioning information and a low signal‐to‐noise ratio. Therefore, this study proposes a data processing workflow to preserve the signal and enhance the repeatability of small‐scale time‐lapse seismic data acquired using a sparker source. The proposed workflow has three stages: pre‐stack, post‐stack and machine learning–based data processing. Conventional seismic data processing methods were applied to enhance the quality of the sparker seismic data during the pre‐stack data processing stage. In the post‐stack processing stage, the positions and energy correction were performed, and the machine learning–based data processing stage attenuated random noise and applied a matched filter. The data processing was performed using only the seismic signals recorded near the seafloor, and the results confirmed the improvement in the repeatability of the entire seismic profile, including that of the target area. According to the repeatability quantification results, the predictability increased and the normalized root mean square decreased during data processing, indicating improved repeatability. In particular, the repeatability of the data was greatly improved through vertical correction, energy correction and matched filtering approaches. The processing results demonstrate that the data processing method proposed in this study can effectively enhance the repeatability of high‐resolution time‐lapse seismic data. Consequently, this approach could contribute to a more accurate understanding of temporal changes in subsurface structure and material properties.
Deep‐learning‐based Q model building for high‐resolution imaging
Authors: Ju Xin , Xu Jincheng , Zhang Jianfeng
Published: September 2024

Building a macro Q model for deabsorption migration using surface reflection data is challenging owing to interferences of the reflections resulting from stacked thin layers. The effective Q approach gives an alternative way to overcome this difficulty. However, manual processing is involved for effective Q estimation. This restricts the use of denser grids in building an inhomogeneous Q model. We therefore incorporate deep learning into the effective Q approach, thus yielding a deep learning‐based Q model building scheme. The resulting scheme improves the manual effective Q estimation by simultaneously accounting for the imaging resolution and induced noises using two networks. Moreover, most manual processing is reduced in spite of denser grids in building a 3D Q model. One of the networks used is a 1D convolutional neural network that determines the optimal upper cut‐off frequency for a selected Q with an input of multi‐channel amplitude spectra, and another is a residual neural network that determines the optimal Q for a series of Q values with an input of multi‐channel imaging sections inside the selected small window filtered under the corresponding upper cut‐off frequencies. As a result, a Q model that improves the imaging resolution in the absence of amplification of noises is gained. Transfer learning is used, thus reducing the training cost when applied to different geological targets. We test our scheme using 3D field data. Higher resolution images without induced noises are obtained by a deabsorption migration using the Q model built and compared to those obtained by the migration without absorption compensation.
Establishment of an immortalized sheep mammary epithelial cell line for studying milk fat and protein synthesis
Authors: Liu Shujuan , Wang Zhanhang , Cao Heran , Tong Jiashun , Cui Jiuzeng , Li Long , Bu Qiqi , Li Yan , Jin Tianqi , An Xiaopeng , Zhang Lei , Song Yuxuan
Published: September 2024

The mammary gland, crucial for milk production in mammals, presents challenges for in vitro study due to its complex structure and limited cell lifespan. We addressed this by introducing the SV40 large T antigen into primary mammary epithelial cells (MECs) from sheep, creating an immortalized T‐tag MEC line. This line, stable for over 50 passages, maintained typical epithelial cell morphology during long‐term culture. Through transcriptome sequencing and validation, we discovered 3833 differentially expressed genes between MECs and T‐tag MEC line, encompassing key biological processes and signaling pathways like cell cycle, p53, and cancer. The cell line, expressing MEC markers (KRT8, KRT18, proliferating cell nuclear antigen, SV40, CSN2, and acetyl‐CoA carboxylase alpha), proved capable of synthesizing milk fat and protein. Despite its infinite proliferation potential, the T‐tag MEC line showed no tumor formation in mice or cell migration in vitro, indicating stability. This development offers a valuable resource for studying MECs in dairy sheep, facilitating the advancement of long‐term culture systems and in vitro lactation bioreactors.
Estimation of the maximum potential cost saving from reducing serious adverse events in hospitalized patients
Authors: Larsen Arendse Tange , Sopina Liza , Aasvang Eske Kvanner , Meyhoff Christian Sylvest , Kristensen Søren Rud , Kjellberg Jakob
Published: September 2024

Purpose

The increasing use of advanced medical technologies to detect adverse events, for instance, artificial intelligence‐assisted technologies, has shown promise in improving various aspects within health care but may also come with substantial expenses. Therefore, understanding the potential economic benefits can guide decision‐making processes regarding implementation. We aimed to estimate the potential cost savings associated with reducing length of stay and avoiding readmissions within the framework of an artificial intelligence‐assisted vital signs monitoring system.

Methods

We used data from Danish national registries and coarsened exact matching to estimate the difference in length of stay and probability of readmission among adult in‐hospital patients exposed to and not exposed to serious adverse events. We used these estimates to calculate the maximum potential savings that could be achieved by early detection of adverse events to reduce length of stay and avoid readmissions.

Results

Patients exposed to serious adverse events during admission had 2.4 (95% CI: 2.4–2.5) additional hospital bed days and had 14% (95% CI 11%–17%) higher odds of readmissions compared with patients not exposed to such events. A base case scenario yielded maximum potential savings if one patient avoided a serious adverse event of EUR 2040 due to reduced length of stay and EUR 43 due to avoidance of readmissions caused by serious adverse events.

Conclusion

Reductions in serious adverse events are associated with decreased healthcare costs due to reduced length of stay and avoided readmissions. Artificial intelligence‐assisted vital signs monitoring systems are one potential approach to reduce serious adverse events, however, the ability of this technology to reduce adverse events remains unclear. Comprehensive prospective analyses of such systems including the intervention and implementation costs are necessary to understand their full economic impact.
Temperature‐dependent lifespan extension is achieved in miR‐80‐deleted Caenorhabditis elegans by NLP‐45 to modulate endoplasmic reticulum unfolded protein responses
Authors: Zhao Chunlin , Luo Jintao , Zhang Yuqiang , Yu Yong
Published: September 2024

MicroRNA plays a crucial role in post‐transcriptional gene regulation and has recently emerged as a factor linked to aging, but the underlying regulatory mechanisms remain incompletely understood. In this study, we observed lifespan‐extending effects in miR‐80‐deficient Caenorhabditis elegans at 20°C but not 25°C. At 20°C, miR‐80 deletion leads to NLP‐45 upregulation, which positively correlates to increased abu transcripts and extended lifespan. Supportively, we identified miR‐80 binding regions in the 5′ and 3’ UTR of nlp‐45. As the temperature rises to 25°C, wildtype increases miR‐80 levels, but removal of miR‐80 is accompanied by decreased nlp‐45 expression, suggesting intervention from other temperature‐sensitive mechanisms. These findings support the concept that microRNAs and neuropeptide‐like proteins can form molecular regulatory networks involving downstream molecules to regulate lifespan, and such regulatory effects vary on environmental conditions. This study unveils the role of an axis of miR‐80/NLP‐45/UPRER components in regulating longevity, offering new insights on strategies of aging attenuation and health span prolongation.
How type‐2 dendritic cells induce Th2 differentiation: Instruction, repression, or fostering T cell‐T cell communication?
Authors: Ronchese Franca , Webb Greta R. , Ochiai Sotaro , Lamiable Olivier , Brewerton Maia
Published: September 2024

Allergic disease is caused by the activation of allergen‐specific CD4+ type‐2 T follicular helper cells (Tfh2) and T helper 2 (Th2) effector cells that secrete the cytokines IL‐4, IL‐5, IL‐9, and IL‐13 upon allergen encounter, thereby inducing IgE production by B cells and tissue inflammation. While it is accepted that the priming and differentiation of naïve CD4+ T cells into Th2 requires allergen presentation by type 2 dendritic cells (DC2s), the underlying signals remain unidentified. In this review we focus on the interaction between allergen‐presenting DC2s and naïve CD4+ T cells in lymph node (LN), and the potential mechanisms by which DC2s might instruct Th2 differentiation. We outline recent advances in characterizing DC2 development and heterogeneity. We review mechanisms of allergen sensing and current proposed mechanisms of Th2 differentiation, with specific consideration of the role of DC2s and how they might contribute to each mechanism. Finally, we assess recent publications reporting a detailed analysis of DC‐T cell interactions in LNs and how they support Th2 differentiation. Together, these studies are starting to shape our understanding of this key initial step of the allergic immune response.
Israel's War on Gaza in a Global Frame
Authors: El‐Shewy Mohamed , Griffiths Mark , Jones Craig
Published: September 2024

The objective of this article is to set out lines of international complicity in Israel's war on Gaza towards establishing not merely a refreshed agenda for research but also strategic sites of accountability and intervention. The article surveys Israeli military activities in Gaza since the 7 October 2023 Hamas attacks, drawing focus on three key points of international military collaboration: the F‐16 fighter jet; the GBU type bomb; and the weapons manufacturer, Elbit Systems. We then turn to multiple other geographies of exchange that are visible through a global frame, including military aid, ideological support, and the deployment of military personnel from overseas. The article thus substantiates an argument that Israeli military violence in Gaza depends on a global network of supply, demand, and complicity whose extraneous relationship with the state indicates politically urgent sites of critical inquiry and intervention.