bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Readily Achieved Potentiostatic Method in Density Functional Theory Calculation for Improved Prediction of the Performance for Electrocatalytic Nitrogen Reduction Reaction
Authors: Hai Guangtong , Wang Haihui 
Published: September 2023

AbstractAccurate prediction of the catalytic performance of nitrogen reduction reaction catalysts based on density functional theory (DFT) calculation is of great significance for developing catalytic materials for nitrogen fixation. However, the applied electrode potential induced the fixation of Fermi level and solvation effect are commonly ignored in the current computational hydrogen electrode method, which leads to the large deviation between the calculation predicted limit potential and the experimentally measured limit potential. In this work, the simple external iteration method is proposed to simulate the Fermi level of the catalysts that are fixed by the applied electrode potential, along with the hybrid solvent model to describe the strong interaction, such as hydrogen bond, between the solvent molecules and the intermediates. This method allowed the theoretical and experimental limit potentials to be in good agreement, indicating the significant effect of the electrode potential and solvation in the DFT calculation. These results will guide the calculation‐based prediction of other reaction systems in the field of electrocatalysis.
FIDEL: Fog integrated federated learning framework to train neural networks
Authors: Kumar Aditya , Srirama Satish Narayana 
Published: September 2023

AbstractTechnological advancement in the digital era has continued to produce voluminous amounts of data through various devices. Even though data is produced distributively, it needs to be accumulated centrally for processing, analysis, and knowledge extraction that faces several challenges such as bandwidth, latency, congestion, privacy, and security. Fog computing paradigm addresses some of these issues, and can be used as a distributed data processing unit. Federated learning trains a shared model over distributed nodes. However, a fog node can not process continuously growing data due to computational limitations. In this paper, we propose FIDEL: a fog integrated federated learning framework for neural network training using resource‐constrained devices. The federation of resource‐constrained Internet of Things (IoT) devices creates a shared global model trained on local data, which is generalized on the unseen dataset for prediction/inferences. We have also designed an online training scheme to process continuous data with limited compute resources. The FIDEL supports both synchronous and asynchronous federate learning that empowers resource‐constrained devices to train machine learning models. To test the learning capabilities of the FIDEL, we have trained three neural networks (i) Shallow network; (ii) Deep Network; (iii) Convolutional Neural Network (CNN) models for human position detection in industrial IoT setup on rapidly changing datasets. The experimental results show that the framework can learn input–output relationships with significantly high accuracy. The overall system efficiency of the framework is reasonable in terms of latency and memory usage for resource‐constrained devices.
Defense program quality‐cost‐delay optimization: architecture framework, a bridge between program management and system engineering
Authors: Brisacier‐Porchon Lorraine , Hammami Omar 
Published: September 2023

AbstractMilitary program management and system engineering re quire the expression of costs and delay trade‐off with respect to system architecture. If architecture frameworks (AF) such as NATO (NAF) were designed to fill this common need, their current state is essentially descriptive. As it turns out, building defense systems architectures using those frameworks in a properly anticipated cost/delay budget envelope would require to have all system engineering already solved, because the architecture frameworks are designed to provide an explicit representation of the operational domain that can be used in analysis, for articulation of issues and requirements, as support to planning, and as a means of solution design and validation, among other things. Thus Quality‐Resource‐Time <Q,R,T> optimality in a regularly evolving environment cannot be represented in acceptable delay without automated optimization assistance. Our contribution in this article explores coupling architecture framework with operation research (OR) models to enable computer assisted design and evaluation of heterogeneous views in NATO Architecture Framework (NAF). Our illustrative example is a Linear Programming based bridge between program management and system engineering to anticipate <Q,R,T> optimal trade‐offs. This article presents promising results, with which we hope to show how OR and AF will be indivisible in architecture evaluation process.
Integral nonlocal stress gradient elasticity of functionally graded porous Timoshenko nanobeam with symmetrical or anti‐symmetrical condition
Authors: Li Chang , Qing Hai 
Published: September 2023

AbstractUtilization of symmetrical or anti‐symmetrical condition could improve the calculation efficiency. In this paper, a mathematical formulation is proposed to deal with the symmetrical or anti‐symmetrical condition in an integral nonlocal stress gradient model (INSGM), which is transformed equivalently into differential form with constitutive boundary condition as well as constitutive symmetrical or anti‐symmetrical condition. Unlike general constitutive boundary conditions, an integral item is introduced to constitutive symmetrical and anti‐symmetrical conditions, and they are opposite to each other. Based on INSGM with symmetrical or anti‐symmetrical conditions, static bending of simply‐supported (SS) and clamped‐clamped (CC) functionally graded porous Timoshenko nanobeams is investigated for symmetrical loads, including uniformly distributed load (UDL) and middle point force, as well as anti‐symmetrical loads, including anti‐symmetrical UDL and middle point moment. The exact solutions are deduced and expressed in explicit form for different boundary and loading conditions. Calculation shows that, under UDL, bending deflections of half Timoshenko nanobeams based on current model agree well with those for whole Timoshenko nanobeams based on general INSGM for both SS and CC boundary conditions. Numerical study is performed to show the effectiveness of current model.
Seismic Full Waveform Inversion Accelerated by Overlapping Data Input and Computation
Authors: Zhang Junqiu , Rao Ying 
Published: September 2023

AbstractSeismic full waveform inversion (FWI) is a powerful technology to obtain high-precision and high-resolution images of subsurface structures. However, FWI is a data-intensive algorithm that needs to read extensive seismic data from disks, which significantly affects its performance. We proposed a portable parallel framework to improve FWI by overlapping data input and computation (ODIC). The framework is based on POSIX threads (Pthreads), which is a standard thread API library and can create a parent thread and a child thread in the FWI process. The former is used to perform computation and the latter to read data from disks, both running simultaneously. This framework has two attractive features. First, it is broadly applicable; it can run on almost any computer from a laptop to a supercomputer. Second, it is easy to implement; it can be readily applied to existing FWI programs. A 3D FWI example shows that the framework speeds up FWI considerably.
“There is No Reliable Evidence to Pass Moral Judgment on Frauwallner.”
Authors: Franco Eli 
Published: September 2023

AbstractThis paper engages with a little-known controversy between Jakob Stuchlik and Walter Slaje on the involvement of Erich Frauwallner, the renowned scholar of Indian philosophy (1898–1974), with NS institutions. It sheds new light on this controversy and highlights the Aryan-supremacist ideology that is reflected in Frauwallner’s division of the history of Indian philosophy into an Aryan and non-Aryan period. On the whole, the paper sides with Stuchlik and exposes Slaje’s attempt to whitewash Frauwallner and certain aspects of his work, despite his adoption of NS ideology and involvement with NS institutions such as the Gestapo and SA. Moreover, the paper dwells on Frauwallner’s adherence to antisemitism and Aryan-supremacist ideology even after the WWII and as late as the 1960s.
Mathematical modeling for further improving task scheduling on Big Data systems
Authors: Souravlas Stavros , Anastasiadou Sofia , Sifaleras Angelo 
Published: September 2023

AbstractIn the big data era which we have entered, the development of smart scheduler has become a necessity. A Distributed Stream Processing System (DSPS) has the role of assigning processing tasks to the available resources (dynamically or not) and route streaming data between them. Smart and efficient task scheduling can reduce latencies and eliminate network congestions. The most commonly used scheduler is the default Storm scheduler, which has proven to have certain disadvantages, like the inability to handle system changes in a dynamic environment. In such cases, rescheduling is necessary. This paper is an extension of a previous work on dynamic task scheduling. In such a scenario, some type of rescheduling is necessary to have the system working in the most efficient way. In this paper, we extend our previous works Souravlas and Anastasiadou (Appl Sci 10(14):4796, 2020); Souravlas et al. (Appl Sci 11(1):61, 2021) and present a mathematical model that offers better balance and produces fewer communication steps. The scheduler is based on the idea of generating larger sets of communication steps among the system nodes, which we call superclasses. Our experiments have shown that this scheme achieves better balancing and reduces the overall latency.
Augmenting Stationary Covariance Functions with a Smoothness Hyperparameter and Improving Gaussian Process Regression Using a Structural Similarity Index
Authors: Chlingaryan Anna , Leung Raymond , Melkumyan Arman 
Published: September 2023

Abstract
Gaussian process (GP) regression provides a probabilistic framework for modeling geochemistry in mineral resource estimation and environmental monitoring applications. An issue with this approach is that the kernel hyperparameters obtained by maximizing the log-marginal likelihood (LML) often produce GP posterior mean estimates that are overly smooth. This motivates the development of augmented kernels that are more capable of capturing the variability inherent in geological/geochemical processes than the existing stationary covariance functions like the Matérn kernels. This paper makes two contributions. First, it describes an extended class of stationary kernels that contain an extra smoothness hyperparameter ($$\alpha $$
α
) which can be learned from the input data. Valid intervals for $$\alpha $$
α
that lead to positive semi-definiteness are determined. Second, it uses a statistical measure called the structural similarity index (SSIM) to quantify smoothness and the spatial fidelity of GP solutions with respect to the input samples. This provides a new way for validating and optimizing GP models. Statistical and spectral analyses provide insights into the behavior of $$\alpha $$
α
in the augmented kernels which retain useful properties such as sparsity. Results on the Northern Great Basin geochemical dataset demonstrate that, all things being equal, (1) adjusting $$\alpha $$
α
increases spatial fidelity in GP regression; (2) SSIM is a more reliable spatial quality measure than LML; and (3) the optimal $$\alpha $$
α
value obtained is correlated with the Wiener entropy of the random process, which indicates the spectral flatness of the chemical signal in the Fourier domain. For GP regression, function smoothness may be defined using Sobolev space. The results show that $$\alpha $$
α
regulates over-smoothing by moderating the rate of decay in the power spectrum of the equivalent kernel.

Graphic abstract
The Role of Narratives for Gaining Domestic Political Legitimacy: China’s Image Management during COVID-19
Authors: Klenk Elias , Gurol Julia 
Published: September 2023

AbstractCrises constitute ideal opportunities for authoritarian leaders to promote certain narratives, shaping reality in their favor and crafting their own preferred storylines about current events. In other words: they serve authoritarian leaders on a silver platter the opportunity to instrumentalize these unforeseen circumstances to gain domestic political legitimacy by promoting strategic narratives. The COVID-19 pandemic was no exception in this regard. Ever since its onset in early 2020, the Chinese Communist Party (CCP) was among the most active actors worldwide seeking to capitalize on the global crisis for legitimation purposes. Whether applying narratives of governance supremacy, portraying the People’s Republic of China as a “global savior,” or promoting emotionally appealing nationalistic narratives, the regime used the pandemic as a window of opportunity to rebrand its international role and enhance its domestic legitimacy. When observing the CCP’s communication style over the course of 24 pandemic months (2020–2022), however, major shifts become apparent regarding the main narratives crafted in communication with national audiences. Based on this, the paper focuses on the role of such narratives for legitimation claims. Using exemplary media articles collected between the outbreak of the pandemic in China in late 2019 until the harsh Shanghai lockdown in spring 2022, it thus traces the narratives employed by Chinese state elites and explores how they are intertwined with nationalism and broader power claims.
Second order linear differential equations with a basis of solutions having only real zeros
Authors: Bergweiler Walter , Eremenko Alexandre , Rempe Lasse 
Published: September 2023

AbstractLet A be a transcendental entire function of finite order. We show that, if the differential equation w″ + Aw = 0 has two linearly independent solutions with only real zeros, then the order of A must be an odd integer or one half of an odd integer. Moreover, A has completely regular growth in the sense of Levin and Pfluger. These results follow from a more general geometric theorem, which classifies symmetric local homeomorphisms from the plane to the sphere for which all zeros and poles lie on the real axis, and which have only finitely many singularities over finite non-zero values.
Disgust Processing and Potential Relationships with Behaviors in Autism
Authors: Jayashankar Aditya , Aziz-Zadeh Lisa 
Published: September 2023

Abstract
Purpose of Review
While there are reports of differences in emotion processing in autism, it is less understood whether the emotion of disgust, in particular, plays a significant role in these effects. Here, we review literature on potential disgust processing differences in autism and its possible associations with autistic traits.

Recent Findings
In autism, there is evidence for differences in physical disgust processing, pica behaviors, attention away from other’s disgust facial expressions, and differences in neural activity related to disgust processing. In typically developing individuals, disgust processing is related to moral processing, but modulated by individual differences in interoception and alexithymia.

Summary
Autistic individuals may experience atypical disgust, which may lead to difficulty avoiding contaminants and affect socio-emotional processing. In autism, such outcomes may lead to increased occurrences of illness, contribute to gastrointestinal issues, diminish vicarious learning of disgust expression and behaviors, and potentially contribute to differences in processes related to moral reasoning, though further research is needed.
Genetically Engineered Foods and Moral Absolutism: A Representative Study from Germany
Authors: Jauernig Johanna , Uhl Matthias , Waldhof Gabi 
Published: September 2023

AbstractThere is an ongoing debate about genetic engineering (GE) in food production. Supporters argue that it makes crops more resilient to stresses, such as drought or pests, and should be considered by researchers as a technology to address issues of global food security, whereas opponents put forward that GE crops serve only the economic interests of transnational agrifood-firms and have not yet delivered on their promises to address food shortage and nutrient supply. To address discourse failure regarding the GE debate, research needs to understand better what drives the divergent positions and which moral attitudes fuel the mental models of GE supporters and opponents. Hence, this study investigates moral attitudes regarding GE opposition and support in Germany. Results show that GE opponents are significantly more absolutist than supporters and significantly less likely to hold outcome-based views. Furthermore, GE opponents are more willing to donate for preventing GE admission than supporters are willing to donate for promoting GE admission. Our results shed light on why the divide between opponents and supporters in the German GE debate could remain stark and stable for so long.
What about young adults’ photo manipulation activity? The predictive role of body shame and the mediating effect of body esteem
Authors: Gioia Francesca , McLean Siân A. , Rega Valeria , Boursier Valentina 
Published: September 2023

AbstractIn recent years, the centrality of photos on Social Networking Sites (SNSs) dramatically increased among young adults. The particular attention addressed to visual self-presentation might lead to body shame, influencing individuals’ body esteem and, likely, promoting photo manipulation (PM). Indeed, manipulating photos to alter how the body appears might be driven by the need to improve self-esteem and reduce body shame, albeit by digitally modified body image. Consequently, two studies were conducted. Study1 psychometrically evaluated the PM scale in a sample of Italian young adults (N = 922). Study2 verified the direct and indirect effect of body shame on PM, testing the mediating effect of body esteem and the moderating effect of gender (N = 595). The PM scale for young adults showed good psychometric properties. The tested mediation model revealed that body shame was both directly and indirectly associated with PM, via body esteemappearancein both male and female participants and via body esteem attribution among young men (R2 = 0.204;p < .001). Implications for young adults’ appearance-related issues are discussed.
Data-Driven Revolution: Advancing Scientific and Technological Innovation in Chinese A-Share Listed Companies
Authors: Wei Xing 
Published: September 2023

AbstractThe transformative role of big data technology in fostering scientific and technological innovation, leading to sustainable development and economic growth, has become increasingly crucial in modern business environments. This study utilizes text analysis of annual financial reports from Chinese A-share listed companies to assess the frequency of keywords related to big data application technology. Through panel data regression, the research investigates the significant impact of big data technology on scientific and technological innovation across diverse industries while controlling for relevant financial and corporate governance variables. The findings reveal a positive correlation between big data application technology and scientific and technological innovation, even after accounting for control factors. Moreover, private enterprises emerge as influential contributors to scientific and technological advancement. The study highlights the theoretical implications of integrating big data technology with the real economy to optimize resources effectively, and the policy implications call for targeted strategies to nurture innovation in established and growing enterprises. As future research prospects, this study lays the groundwork for exploring additional dimensions of big data technology’s impact on innovation and its implications for sustainable development in the ever-evolving business landscape.
The Right to be an Exception to Predictions: a Moral Defense of Diversity in Recommendation Systems
Authors: Viganò Eleonora 
Published: September 2023

AbstractRecommendation systems (RSs) predict what the user likes and recommend it to them. While at the onset of RSs, the latter was designed to maximize the recommendation accuracy (i.e., accuracy was their only goal), nowadays many RSs models include diversity in recommendations (which thus is a further goal of RSs). In the computer science community, the introduction of diversity in RSs is justified mainly through economic reasons: diversity increases user satisfaction and, in niche markets, profits.I contend that, first, the economic justification of diversity in RSs risks reducing it to an empirical matter of preference; second, diversity is ethically relevant as it supports two autonomy rights of the user: the right to an open present and the right to be treated as an individual. So far, diversity in RSs has been morally defended only in the case of RSs of news and scholarly content: diversity is held to have a depolarizing effect in a democratic society and the scientific community and make the users more autonomous in their news choices. I provide a justification of diversity in RSs that embraces all kinds of RSs (i.e., a holistic moral defense) and is based on a normative principle founded on the agency of the user, which I call the right to be an exception to predictions. Such a right holds that the proper treatment of a RS user qua agent forbids providing them with recommendations based only on their past or similar users’ choices.
Construction of ternary PEG200-based DESs lubrication systems via tailoring tribo-chemistry
Authors: Li Yuting , Lan Songyu , Liu Yazhou , Cao Cheng , Tang Zicheng , Deng Deyin , Liu Fuyuan , Li Hao , Fan Xiaoqiang , Zhu Minhao 
Published: September 2023

AbstractDesigning novel lubricants with easily customized structures, devisable compositions, and simple and economic synthesis over traditional lubricants is critical to fulfilling complex applications, prolonging machine lifetime, and saving energy. Deep eutectic solvents (DESs), which show tunable composition, adjustable structure, easy fabrication, and environmental friendliness, are promising candidates for variable and complicated lubricants applications. To promote the use of DESs as lubricants, a series of PEG200-based DESs with active heteroatoms were fabricated to tailor the tribological performance via tribo-chemistry. Thereinto, PEG200/boric acid (BA) DES shows optimal lubrication performance by forming tribo-chemical reaction film composited of B2O3, iron oxides, and FeOOH, and PEG200/thiourea (TU) DES displays abrasive wear-reducing property by producing FeS tribo-chemical film. Given the excellent abrasive wear-resistance of PEG200/TU DES and friction reduction of PEG200/BA DES, ternary PEG200/BA/TU DESs, composited of PEG200/TU DES and PEG200/BA DES, are first exploited. The ternary DESs possess superior wettability and thermal stability, which render them potential lubricants. Tribological tests of the ternary DESs demonstrate that synergistic lubrication is achieved by forming a transfer film consisting of FexBy, BN, B2O3, and FeS. Wherein FexBy, BN, and B2O3 increase load bearing of the film, and FeS mitigates severe abrasive wear. The proposed design philosophy of novel DESs as lubricants opens up a unique realm that is unattainable by traditional DESs lubrication mechanisms and provides a platform to design next-generation DESs lubrication systems.