bluuebunny/crossref_metadata_2025_split huggingface dataset:
Darker side of industry 4.0 and its impact on triple‐bottom‐line sustainability
Authors: Narkhede Ganesh , Dohale Vishwas , Mahajan Yash 
Published: April 2024

AbstractWhile the literature commonly prevails a positive outlook on how Industry 4.0 (I4.0) enhances sustainability, there exists an understudied aspect—the darker side of I4.0—that has negative implications and has not yet been systematically addressed. This research aims to challenge the assumption of a sustainable I4.0 by highlighting the potential negative implications of I4.0 technologies on sustainability, emphasising potential measures to mitigate such effects, and presenting a framework for a sustainable future. A dual research methodology was used to conduct this research work. The systematic literature review (SLR) method was used to synthesise the literature. Additionally, a questionnaire was sent to 34 manufacturing Small and Medium‐Sized Enterprises (SMEs) to measure their current progress towards triple‐bottom‐line (TBL) sustainability. This SLR navigates through the complex multifaceted nature of the dark side of I4.0, including job displacement, wage disparity, cybersecurity risks, socio‐economic disparities, and environmental effects. This study presents a structured five‐step approach that emphasises the integration of cutting‐edge I4.0 technologies with a focus on sustainable development practices to address economic, environmental, and social issues for a sustainable I4.0 future. This article aimed to understand I4.0 as a whole phenomenon from the perspective of TBL sustainability. The originality of this research article lies in uncovering the hitherto less‐understudied negative aspects of I4.0 and presenting a complex interpretation of I4.0 and its impact on TBL sustainability.
The moderating role of catastrophizing in day‐to‐day dynamic stress and depressive symptoms
Authors: Zhan Lei , Lin Li , Wang Xiaoyu , Sun Xianghong , Huang Zheng , Zhang Liang 
Published: April 2024

AbstractThe way individuals handle daily stressors can significantly influence their mental health. Those who struggle with emotion regulation are especially vulnerable to the negative effects of stress. This study explored the role of catastrophizing, a maladaptive emotion regulation strategy, in shaping the relationships between daily stress responses and depressive symptoms. A total of 75 healthy college students participated in the study. We adopted an Ecological Momentary Assessment protocol over 14 consecutive days to capture the day‐to‐day dynamics of stress reactivity and recovery. Our findings indicate that individuals with higher levels of catastrophizing exhibited increased daily stress reactivity and delayed daily stress recovery, consequently raising their likelihood of experiencing amplified depressive symptoms. In contrast, those with lower levels of catastrophizing did not experience the same negative effects of increased daily stress reactivity on their mental health. These results enhance understanding of how real‐life stressors contribute to the development of mental health issues and underscore the importance of adaptive emotion regulation for improved overall health and well‐being.
Systematic review: Comparing zk‐SNARK, zk‐STARK, and bulletproof protocols for privacy‐preserving authentication
Authors: Oude Roelink Bjorn , El‐Hajj Mohammed , Sarmah Dipti 
Published: April 2024

AbstractThis systematic literature review examines the implementation and analysis of zk‐SNARK, zk‐STARK, and bulletproof non‐interactive zero‐knowledge proof (NIZKP) protocols in privacy‐preserving applications across diverse sectors. Examining 41 research works obtained through the systematic search queries and filtering criteria published from 2015 to April 2023, we categorized findings into financial, medical, business, general, and other domains. Our analysis highlights significant variations of up to several orders of magnitude in real‐world performance across implementations utilizing NIZKP protocols. However, divergent methodologies in security analyses hindered conclusive comparisons. Addressing research gaps, our future endeavors aim to establish a real‐world benchmark for these protocols.
Flexural fatigue performance and damage evolution analysis of multiscale polypropylene fiber‐reinforced concrete
Authors: Liang Ninghui , You Xiufei , Zhou Kan , Liu Xinrong , Mao Jinwang 
Published: April 2024

AbstractAs an excellent concrete reinforcement material, polypropylene fiber has a high potential for bulk‐scale applications. In this study, a comprehensive experimental campaign was carried out to assess the flexural fatigue performance of multiscale polypropylene fiber‐reinforced concrete (MPFRC). Two types of fine polypropylene fiber (FPF) and one type of coarse polypropylene fiber (CPF) were selected for single doping or hybridization into concrete. The fatigue deformation damage mechanism of polypropylene fiber reinforced concrete (PFRC) was analyzed through acoustic emission (AE) and scanning electron microscopy. Results indicated that the incorporation of polypropylene fibers could significantly improve the strength of concrete, with the best results for MPFRC, where the compressive, tensile, and flexural strength were increased by 13.12%, 20.59%, and 25.49%, respectively, compared to the plain concrete. The fatigue life of PFRC obeyed the Weibull distribution at different stress levels, with the mean fatigue life of MPFRC increasing by up to 6.37 times. The fatigue strain‐to‐cycle ratio curves coincided with the cumulative AE ringing count‐to‐cycle ratio curves, both showed that the fatigue damage process of MPFRC underwent three distinct stages, accounting for 5%, 85%, and 10% of the total fatigue life, respectively. By forming a three‐dimensional mesh structure inside the concrete, polypropylene fibers effectively mitigated internal damage and improved the fatigue performance of the concrete.
Factors influencing water strategy objectives fulfillment: A survey findings from Sudan
Authors: Abdelgalil Eltigani , Mohamed Mohamed , Musa Manahil , Barakat Nagla , Abdelrahman Fathelrahman 
Published: April 2024

AbstractChallenges faced by countries in their struggle for economic and social development are increasingly related to water. Developing and managing water resources requires an appropriate water strategy. However, many factors influence the achievement of desired goals of water strategies. This qualitative study analyzes factors influencing water strategies to promote appropriate water management. Data was collected during 2019 from 10 states of North Kurdufan, White Nile, Gezira, Sennar, Gedarif, Khartoum, Kassala, Red Sea, River Nile, and Northern state in Sudan. A total of 300 people including water officials, water supply engineers, and community leaders were interviewed. Water availability, community participation, coordination between water institutions, integrated water resources management (IWRM), and finance were identified as factors influencing water strategy objectives fulfillment. Out of 300 respondents in all states, a group of 149 (49.7%), mentioned that water strategy objectives were fulfilled and more than half of the respondents 151 (50.3%) evaluated that water strategy objectives were not fulfilled. A multiple regression statistically significantly predicted water strategy objective achievement, F (5, 295) = 57.6314 p < .005, R = .704. R2 = .485, from water availability, coordination between water‐related institutions, IRWM, and availability of finance. Results show that community participation, water availability, coordination between water‐related institutions, and availability of finance are insignificantly (p > .005) influenced water strategy objective fulfillment. The findings will contribute to the social dimension of water resources management and development.
Visualization
Authors: Münster Sander , Apollonio Fabrizio Ivan , Bluemel Ina , Fallavollita Federico , Foschi Riccardo , Grellert Marc , Ioannides Marinos , Jahn Peter Heinrich , Kurdiovsky Richard , Kuroczyński Piotr , Lutteroth Jan-Eric , Messemer Heike , Schelbert Georg 
Published: April 2024

Abstract3D computer-based visualization refers to all those methodologies adopted to produce, represent, describe, transmit, and present graphically/visually digital 3D models in a way that is perceivable by the human eye. Visualization is one of the core aspects of 3D reconstruction because it is the most effective medium to synthesize complex data in a visual way and makes the results more accessible and comprehensible not only to professionals but also to laypersons.
Methods
Authors: Barrientos Armando 
Published: April 2024

AbstractThis chapter discusses methods appropriate to the study of social protection in Latin America. It reviews and assesses the main methodological approaches employed by researchers in the past. Building on these, it identifies methods appropriate to developing a theoretical perspective capable of explaining the evolution and current configuration of social protection institutions in the region. Recent trends in social research methods reveal a renewed emphasis on causal inference. The application of quasi-experimental methods in the study of the outcomes of social protection interventions, initially in the context of conditional income transfers, has focused attention on the causal effects of social protection interventions. The chapter assesses the challenges associated with the application of causal inference models in the context of research on institutions relying on observational data. It argues the potential outcomes approach offers a systematic framework for incorporating attention to counterfactuals. It makes a case for the use of graphical casual models to help discriminate causal versus non-causal association between variables, thus refining researchers’ hypotheses and linking the model to potential empirical counterparts.
A study of the SYK2 model with twisted boundary conditions
Authors: Murugan Jeff , Slayen Ruach Pillay , Van Zyl Hendrik J. R. 
Published: April 2024

Abstract
We study a version of the 2-body Sachdev-Ye-Kitaev (SYK2) model whose complex fermions exhibit twisted boundary conditions on the thermal circle. As we show, this is physically equivalent to coupling the fermions to a 1-dimensional external gauge field A(t). In the latter formulation, the gauge field itself can be thought of as arising from a radial symmetry reduction of a (2 + 1)-dimensional Chern-Simons gauge field Aμ(t,x). Using the diagnostic tools of the out-of-time-order correlator (OTOC) and spectral form factor (SFF), which probe the sensitivity to initial conditions and the spectral statistics respectively, we give a detailed and pedagogical study of the integrable/chaotic properties of the model. We find that the twisting has no effect on the OTOCs and, by extension, the early-time chaos properties of the model. It does, however, have two notable effects on the spectral form factor; an enhancement of the early-time slope and the emergence of an explicit twisting-dependent timescale needed for the manifestation of zero modes. These zero modes are responsible for the late-time exponential ramp in the quadratic SYK model.
No U(1) ‘electric-magnetic’ duality in Einstein gravity
Authors: Monteiro Ricardo 
Published: April 2024

Abstract
We revisit the question of whether classical general relativity obeys, beyond the linearised order, an analogue of the global U(1) electric-magnetic duality of Maxwell theory, with the Riemann tensor playing the role analogous to the field strength. Following contradictory claims in the literature, we present a simple gauge-invariant argument that the duality does not hold. The duality condition is the conservation of the helicity charge. Scattering amplitudes of gravitons in general relativity, and of gluons in Yang-Mills theory, violate this selection rule already at tree level. Indeed, the maximally-helicity-violating (MHV) amplitudes are famous for their simplicity. The duality in the linearised theories is, therefore, broken by the interactions. In contrast, the tree-level scattering amplitudes in duality-invariant theories of non-linear electromagnetism are known to obey helicity conservation. While the duality is not a symmetry of the full theory of general relativity, it does hold within a sector of the solution space, including vacuum type D solutions, where the duality is known to rotate between mass and NUT charge.
Bedeutung von künstlicher Intelligenz für die Risikoerkennung vor chirurgischen Eingriffen
Authors: Sanchez Rosenberg Guillermo , Egloff Christian 
Published: April 2024

ZusammenfassungNach Herzerkrankungen und Schlaganfall ist die postoperative Sterblichkeit innerhalb von 30 Tagen nach dem Indexeingriff die dritthäufigste Todesursache weltweit [24]. In der elektiven Orthopädie liegt die 30-Tage-Mortalitätsrate unter 1 % [4], dennoch können postoperative Komplikationen oft verheerend sein. In der Ära der „qualitativen Gesundheitsversorgung“ ist die Umsetzung von Strategien zur Risikostratifizierung und zur Optimierung der Zuweisung von Gesundheitsressourcen zur Verbesserung der postoperativen Ergebnisse von entscheidender wirtschaftlicher Bedeutung. Dieser Beitrag untersucht die transformative Rolle der künstlichen Intelligenz (KI) bei der Risikobewertung in der Orthopädie als Teil des ganzheitlichen Entscheidungsprozesses zur Verbesserung der Ergebnisse im Gesundheitswesen.
Mathematical analysis of modified level-set equations
Authors: Bothe Dieter , Fricke Mathis , Soga Kohei 
Published: April 2024

AbstractThe linear transport equation allows to advect level-set functions to represent moving sharp interfaces in multiphase flows as zero level-sets. A recent development in computational fluid dynamics is to modify the linear transport equation by introducing a nonlinear term to preserve certain geometrical features of the level-set function, where the zero level-set must stay invariant under the modification. The present work establishes mathematical justification for a specific class of modified level-set equations on a bounded domain, generated by a given smooth velocity field in the framework of the initial/boundary value problem of Hamilton–Jacobi equations. The first main result is the existence of smooth solutions defined in a time-global tubular neighborhood of the zero level-set, where an infinite iteration of the method of characteristics within a fixed small time interval is demonstrated; the smooth solution is shown to possess the desired geometrical feature. The second main result is the existence of time-global viscosity solutions defined in the whole domain, where standard Perron’s method and the comparison principle are exploited. In the first and second main results, the zero level-set is shown to be identical with the original one. The third main result is that the viscosity solution coincides with the local-in-space smooth solution in a time-global tubular neighborhood of the zero level-set, where a new aspect of localized doubling the number of variables is utilized.
Fisheye freshness detection using common deep learning algorithms and machine learning methods with a developed mobile application
Authors: Yildiz Muslume Beyza , Yasin Elham Tahsin , Koklu Murat 
Published: April 2024

Abstract
Fish is commonly ingested as a source of protein and essential nutrients for humans. To fully benefit from the proteins and substances in fish it is crucial to ensure its freshness. If fish is stored for an extended period, its freshness deteriorates. Determining the freshness of fish can be done by examining its eyes, smell, skin, and gills. In this study, artificial intelligence techniques are employed to assess fish freshness. The author’s objective is to evaluate the freshness of fish by analyzing its eye characteristics. To achieve this, we have developed a combination of deep and machine learning models that accurately classify the freshness of fish. Furthermore, an application that utilizes both deep learning and machine learning, to instantly detect the freshness of any given fish sample was created. Two deep learning algorithms (SqueezeNet, and VGG19) were implemented to extract features from image data. Additionally, five machine learning models to classify the freshness levels of fish samples were applied. Machine learning models include (k-NN, RF, SVM, LR, and ANN). Based on the results, it can be inferred that employing the VGG19 model for feature selection in conjunction with an Artificial Neural Network (ANN) for classification yields the most favorable success rate of 77.3% for the FFE dataset.

Graphical Abstract
Transcriptome response of diatom Skeletonema marinoi to lower temperature
Authors: Jing Xiaoli , Zhen Yu , Mi Tiezhu , Yu Zhigang , Wang Yucheng , Wang Xiaohong 
Published: April 2024

AbstractTemperature is an important environmental factor for phytoplankton. Phytoplankton growth, metabolism, biodiversity, productivity, and distribution are influenced by temperature-driven nutrient stratification and mixing, as well as species’ optimal growth temperatures. There have been a number of studies focused on physiological and biochemical mechanisms of environmental–biological interactions in diatoms, yet the underlying transcriptional regulators remain limited. Here, we performed an RNA-seq-based gene expression analysis to explore the Skeletonema marinoi (isolated from Jiaozhou Bay of Qingdao, 36.13°N, 120.16°E on July 5th, 2013) cellular responses induced by low temperature (12 °C). Digital gene expression profiling of S. marinoi generated 20,319 unigenes, of which 573 differentially expressed genes appeared in the low-temperature treatment group. According to GO and KEGG enrichment analysis, different genes were involved in ten metabolic and biosynthesis pathways: ribosome, lipid, porphyrin, and chlorophyll metabolism showed strong transcriptional cold tolerances. The regulation of genes related to translation processes (e.g., pentatricopeptide repeat), fatty acid metabolism (e.g., acyl-CoA synthetase), and photosynthesis (e.g., porphyrin enzymes) provides new molecular-level insight into cold stress responses in eukaryotic marine phytoplankton. Our study suggests that this Skeletonema species could be a potential candidate for understanding the fate of thermo-sensitive diatom communities and oceanic ecosystems facing climate change.
Insights into plant regeneration: cellular pathways and DNA methylation dynamics
Authors: Lee Seunga , Park Young Seo , Rhee Ji Hoon , Chu Hyojeong , Frost Jennifer M. , Choi Yeonhee 
Published: April 2024

AbstractPlants, known for their immobility, employ various mechanisms against stress and damage. A prominent feature is the formation of callus tissue—a cellular growth phenomenon that remains insufficiently explored, despite its distinctive cellular plasticity compared to vertebrates. Callus formation involves dedifferentiated cells, with a subset attaining pluripotency. Calluses exhibit an extraordinary capacity to reinitiate cellular division and undergo structural transformations, generating de novo shoots and roots, thereby developing into regenerated plants—a testament to the heightened developmental plasticity inherent in plants. In this way, plant regeneration through clonal propagation is a widely employed technique for vegetative reproduction. Thus, exploration of the biological components involved in regaining pluripotency contributes to the foundation upon which methods of somatic plant propagation can be advanced. This review provides an overview of the cellular pathway involved in callus and subsequent de novo shoot formation from already differentiated plant tissue, highlighting key genes critical to this process. In addition, it explores the intricate realm of epigenetic regulatory processes, emphasizing the nuanced dynamics of DNA methylation that contribute to plant regeneration. Finally, we briefly discuss somaclonal variation, examining its relation to DNA methylation, and investigating the heritability of epigenomic changes in crops.
Artificial intelligence for automated detection and measurements of carpal instability signs on conventional radiographs
Authors: Hendrix Nils , Hendrix Ward , Maresch Bas , van Amersfoort Job , Oosterveld-Bonsma Tineke , Kolderman Stephanie , Vestering Myrthe , Zielinski Stephanie , Rutten Karlijn , Dammeier Jan , Ong Lee-Ling Sharon , van Ginneken Bram , Rutten Matthieu 
Published: April 2024

Abstract
Objectives
To develop and validate an artificial intelligence (AI) system for measuring and detecting signs of carpal instability on conventional radiographs.

Materials and methods
Two case-control datasets of hand and wrist radiographs were retrospectively acquired at three hospitals (hospitals A, B, and C). Dataset 1 (2178 radiographs from 1993 patients, hospitals A and B, 2018–2019) was used for developing an AI system for measuring scapholunate (SL) joint distances, SL and capitolunate (CL) angles, and carpal arc interruptions. Dataset 2 (481 radiographs from 217 patients, hospital C, 2017–2021) was used for testing, and with a subsample (174 radiographs from 87 patients), an observer study was conducted to compare its performance to five clinicians. Evaluation metrics included mean absolute error (MAE), sensitivity, and specificity.

Results
Dataset 2 included 258 SL distances, 189 SL angles, 191 CL angles, and 217 carpal arc labels obtained from 217 patients (mean age, 51 years ± 23 [standard deviation]; 133 women). The MAE in measuring SL distances, SL angles, and CL angles was respectively 0.65 mm (95%CI: 0.59, 0.72), 7.9 degrees (95%CI: 7.0, 8.9), and 5.9 degrees (95%CI: 5.2, 6.6). The sensitivity and specificity for detecting arc interruptions were 83% (95%CI: 74, 91) and 64% (95%CI: 56, 71). The measurements were largely comparable to those of the clinicians, while arc interruption detections were more accurate than those of most clinicians.

Conclusion
This study demonstrates that a newly developed automated AI system accurately measures and detects signs of carpal instability on conventional radiographs.

Clinical relevance statement
This system has the potential to improve detections of carpal arc interruptions and could be a promising tool for supporting clinicians in detecting carpal instability.
Influence of fabrication deviations on the polarization-maintaining behavior of inhibited-coupling guiding hollow-core fibers
Authors: Chen Bowen , Kühlthau Tim , Röhrer Christian , Graf Thomas , Abdou Ahmed Marwan 
Published: April 2024

AbstractNumerical simulations were conducted to analyze the influence of the design parameters of tubular inhibited-coupling guiding hollow-core photonic crystal fibers (IC-HCPCFs) on the bending-induced phase shift. The possibility to implement polarization-maintaining (PM) tubular IC-HCPCFs using a low-birefringence approach (with a modal birefringence parameter $$B<$$

B
<

$$7\times {10}^{-9}$$

7
×

10

-
9

) is discussed. Two different tubular IC-HCPCF designs with 7 and 8 glass capillaries are proposed for operation at a wavelength of 1030 nm. The numerical simulation predicts low guiding losses and a PM behavior sustaining a degree of linear polarization (DOLP) larger than 90% after 10 m of fiber with a bend radius larger than 0.2 m. This shows great potential for high-power beam delivery in an industrial environment. The influence that fabrication deviations have on the polarization-maintaining behavior was also investigated and indicates tight fabrication tolerances for both proposed fiber designs. Small deviations from the ideal symmetrical structure can lead to an enhancement of undesired modal birefringence. To ensure a DOLP larger than 90% at the exit of a 10 m-long fiber and for a bending radius > 0.2 m precise control of the drawing parameters during the fiber production is required, which is challenging but is considered to be technically feasible.