bluuebunny/crossref_metadata_2025 huggingface dataset:
Hybridization effects on the magnetic ground state of ruthenium in double perovskite La2ZnRu1−xTixO6
Authors: Halder Shuvajit , Meneghini Carlo , Ray Sugata
Published: January 2025

An exotic quantum mechanical ground state, i.e. the non-magnetic J
eff = 0 state, has been predicted for higher transition metal

t

2
g

4

systems, due to the influence of strong spin–orbit coupling (SOC) or in other words, due to unquenched orbital moment contribution. However, previous attempts to experimentally realize such a state in 5d
4 systems had mostly been clouded by solid-state effects or the reduced strength of the renormalized SOC that might allow significant triplon condensation. Interestingly, a recent study on vacancy ordered double perovskite compound K2RuCl6 by Takahashi et al (2021 Phys. Rev. Lett.
127 227201) concluded that even within LS coupling regime the Ru4+ 4d
4 ions, within isolated RuCl6 octahedra, strongly accommodate J multiplets having J
eff = 0 as the ground state with weakly interacting J
eff = 1 excitation, due to large unquenced Ru orbital angular momentum in the system. In the present report, we show results from the double perovskite La2ZnRuO6, where Ru4+ ions form isolated RuO6 octahedra but unlike K2RuCl6, they remain chemically connected via corner-sharing with nonmagnetic ZnO6 octahedra. Next, we move on to separate out the RuO6 octahedra further by doping the Ru-site with Ti4+, in order to probe the character of the Ru4+ ions within a different structural background. We find that the system stabilizes in P2

1

/
n

space group with tilted octahedra without distortion as has been confirmed by the x-ray powder diffraction and x-ray absorption spectroscopic studies. Interestingly, the x-ray photoelectron spectroscopic valance band spectra indicated certain inhomogeneity around the half-doping region, while confirming insulating ground state for all. Moreover, unlike the vacancy ordered double perovskite cases, it is observed that here the Ru orbital angular momentum gets substantially quenched and only the Ru spin magnetic moments are realized.
Separation of sun gear crack signals based on homologous response fragment mining and common component reconstruction
Authors: Zhang Zhai , Li Hongkun
Published: January 2025

The operational state of the sun gear in the planetary gearbox significantly impacts the stability and reliability of the entire transmission system. This study introduces a novel method to enhance the precision of diagnosing faults in the sun gear of a planetary gearbox. By detecting the similarity and distribution patterns of specific length segments in vibration signals, we identify homologous response segments based on the variation of fault meshing points and sensor positions. We then utilize robust principal component analysis (Robust PCA) to reduce data dimensionality and extract low-dimensional information from these segments. Adaptive resonance sparse decomposition based on the particle swarm algorithm is employed to decouple and decompose the signals thereby enabling the separation of interference components from fault characteristic signals. This study introduces a novel method to enhance the precision of diagnosing faults in the sun gear of a planetary gearbox. By detecting the similarity and distribution patterns of specific length segments in vibration signals, we identify homologous response segments based on the variation of fault meshing points and sensor positions. We then utilize Robust PCA to reduce data dimensionality and extract low-dimensional information from these segments.
Path planning algorithm for articulated loader based on bidirectional Dubins curve
Authors: Liu Jinyue , Liu Chaojie , Han Ming , Wan Zhao , Li Tiejun , Jia Xiaohui
Published: January 2025

Wheel loaders are often used for material transportation in areas such as mines and construction sites, and their articulated motion characteristics bring great challenges to their path planning and trajectory tracking. Aiming at the problems of long planning path and low tracking accuracy in the path planning of articulated loaders, this paper proposes an improved hybrid A* algorithm based on bidirectional Dubins curve to realize the path planning and trajectory tracking in the process of automatic material transportation of loaders. Firstly, the kinematics model is constructed based on the vehicle size, and the bidirectional Dubins curve combined with hybrid A* algorithm is introduced to improve the forward and backward switching mechanism of the loader, and the path is smoothed by factor graph. Then, the kinematics model is analyzed, and the mapping relationship between navigation point speed and vehicle speed and articulation angle is obtained, and the vehicle state is obtained by sensor feedback. Finally, the vehicle speed and articulation angle are solved by graph optimization. The simulation and field test verify its performance, and the path length is shortened by 17.73% compared with that before optimization. The research results show that the proposed algorithm can accurately control the wheel loader from the initial position to the target position, realize the stable work of the whole vehicle in the work area, and provide technical support for the loader’s autonomous operation.
Fourier energy spectrum centroid: a robust and efficient approach for shear wave speed estimation in ω–k space
Authors: Zhang Xi , Dong Jinping , Lee Wei-Ning
Published: January 2025

Objective. The propagation speed of a shear wave, whether externally or internally induced, in biological tissues is directly linked to the tissue’s stiffness. The group shear wave speed (SWS) can be estimated using a class of time-of-flight (TOF) methods in the time-domain or phase speed-based methods in the frequency domain. However, these methods suffer from biased estimations or time-consuming computations, and they are especially prone to wave distortions in in vivo cases. In this work, we present a parameter-free, robust, and efficient group SWS estimation method coined as Fourier energy spectrum centroid (FESC). Approach. The proposed FESC method is based on the center of mass in

ω
−
k

space. It was evaluated on data from computer simulations with additive Gaussian noise, a commercial elasticity phantom, an ex vivo pig liver, and in vivo biceps brachii muscles of three young healthy male subjects. The FESC method was compared with two 2D frequency-domain methods: Max-fre, which considers phase SWS at the peak of k-space, and Fre-regre, which applies linear regression of phase SWS within a fixed bandwidth. Two additional benchmarks included time-domain methods based on cross-correlation (X-Corr) and radon sum transformation (RD). Main results. Statistical results showed that our FESC method and the RD method had comparable accuracy and robustness, outperforming the other benchmark methods. In the simulation and phantom studies, when the signal-to-noise ratio was higher than 25 dB, our FESC showed higher accuracy than RD. In the in vivo study, our FESC method had better repeatability than RD. Furthermore, the proposed FESC method was 100 times faster than the runner-up method, X-Corr, and 3,000 times faster than the least efficient method, RD. Significance. All results indicated that our proposed Fourier-based method shows promise in reliably and efficiently providing reference values for group SWS in homogeneous bulk media.
Integrable systems on multiplicative quiver varieties from cyclic quivers
Authors: Fairon Maxime
Published: January 2025

We consider a class of complex manifolds constructed as multiplicative quiver varieties associated with a cyclic quiver extended by an arbitrary number of arrows starting at a new vertex. Such varieties admit a Poisson structure, which is obtained by quasi-Hamiltonian reduction. We construct several families of Poisson subalgebras inside the coordinate ring of these spaces, which we use to obtain degenerately integrable systems. We also extend the Poisson center of these algebras to maximal abelian Poisson algebras, hence defining Liouville integrable systems. By considering a suitable set of local coordinates on the multiplicative quiver varieties, we can derive the local Poisson structure explicitly. This allows us to interpret the integrable systems that we have constructed as new generalizations of the spin Ruijsenaars–Schneider system with several types of spin variables.
Systematic development and bioprinting of novel nanostructured multi-material bioinks for bone tissue engineering
Authors: Korkeamäki Jannika T , Rashad Ahmad , Ojansivu Miina , Karvinen Jennika , Koivisto Janne T , Syverud Kristin , Kellomäki Minna , Miettinen Susanna , Mustafa Kamal
Published: January 2025

A functional bioink with potential in bone tissue engineering must be subjected to critical investigation throughout its intended lifespan. The aim of this study was to develop alginate–gelatin-based (Alg–Gel) multicomponent bioinks systematically and to assess the short- and long-term exposure responses of human bone marrow stromal cells (hBMSCs) printed within these bioinks with and without crosslinking. The first generation of bioinks was established by incorporating a range of cellulose nanofibrils (CNFs), to evaluate their effect on viscosity, printability and cell viability. Adding CNFs to Alg–Gel solution increased viscosity and printability without compromising cell viability. In the second generation of bioinks, the influence of nano-hydroxyapatite (nHA) on the performance of the optimized Alg–Gel-CNF formulation was investigated. The addition of nHA increased the viscosity and improved printability, and an adjustment in alginate concentration improved the stability of the structures in long-term culture. The third generation bioink incorporated RGD-functionalized alginate to support cell attachment and osteogenic differentiation. The optimized bioink composition exhibited improved printability, structural integrity in long-term culture and high hBMSC viability. In addition, the final bioink composition, RGD-Alg–Gel-CNF-nHA, showed osteogenic potential: production of the osteogenic marker proteins (Runx2, OCN), enzyme (ALP), and gene expression (Runx2, OCN). A further aim of the study was to evaluate the osteogenic functionality of cells released from the structures after bioprinting. Cells were printed in two bioinks with different viscosities and incubated at 37 °C in growth medium without additional CaCl2. This caused gelatin to dissolve, releasing the cells to attach to tissue culture plates. The results demonstrated differences in hBMSC osteogenic differentiation. Moreover, the osteogenic differentiation of the released cells was different from that of the embedded cells cultured in 3D. Thus, this systematic investigation into bioink development shows improved results through the generations and sheds light on the biological effects of the bioprinting process.
Universal state transition from soliton network to soliton-free incommensurate stacking in reconstructed van der Waals bilayers
Authors: Zhang Baidu , He Linghui , Zhang Sulin , Ni Yong
Published: January 2025

The atomic reconstruction and moiré patterns within moiré superlattices resulting from twist, stretch and vertical pressure have generated significant interest in the exploration of novel physical phenomena. In this study, we reveal a universal structural transition in moiré superlattices through comprehensive numerical simulations and theoretical analyses. This transition is characterized by a shift in the moiré pattern from a strain soliton network state at large moiré periods to a soliton-free state at smaller moiré periods. This transition is marked by the convergence of two branches of total energy solutions at a critical moiré period. We propose an intuitive size rule, highlighting that one third of the moiré periods smaller than the width of strain solitons serve as a universal trigger for this transformation. Additionally, our research shows that applying external vertical pressure can enhance interlayer van der Waals interactions, resulting in a decrease in the critical moiré period. We also demonstrate that during this state transition, the maximum elastic interaction occurs in proximity to the critical moiré period. Such structural transition regulated by the adjustment of parameters such as twist angle, in-plane stretch and pressure, provides opportunities for manipulating the exotic electronic properties of van der Waals materials.
Highly sensitive, stretchable, and transparent multidirectional wearable strain sensors based on patterned vertical graphene array
Authors: Hong Tianzeng , Li Haonan , Xue Jie , Wen Yahui , Zhu Zifu , Gao Xiaobo , Shi Yunli , Liu Dan , Zheng Qingbin
Published: January 2025

Since traditional uniaxial strain sensors constructed from isotropic materials mainly focus on identifying strain amplitude without the information of strain direction, multidimensional strain sensors are critical for capturing complex movements, such as human motions. Here, we propose a highly sensitive, stretchable, and transparent multidirectional strain sensor based on patterned vertical graphene array (PVGA) synthesized by plasma-enhanced chemical vapor deposition followed by selective etching and transferring. The obtained PVGA/Polydimethylsiloxane (PDMS) strain sensor exhibits outstanding anisotropic strain sensing performance, including high gauge factor (GF = 85.8 at 10% strain), excellent linearity (R
2 = 0.99), and outstanding selectivity (|▽| = 4.17). Cross-plied PVGA/PDMS strain sensors are also fabricated to demonstrate the application of detecting joint movements of the human body, as well as monitoring wrist motion for controlling a fruit-slicer game in the virtual environment. The sensor’s remarkable multi-dimensional sensing performance confirms their significant potential for diverse applications, notably in wearable electronics, such as personal health sensing, artificial intelligence, human-computer interaction, and soft robotics.
Financing grassroots initiatives in solid waste management: benchmarking the Tanzanian experience against international practices
Authors: Ilomo Mesia , Charles Goodluck
Published: January 2025

Although financing solid waste management (SWM) is commonly reported as a critical challenge facing waste management initiatives in most developing countries, few studies have attempted to investigate the options for financing SWM initiatives and the extent to which they are accessible by grassroots actors. To address this knowledge gap, this study explored the models for financing SWM initiatives in Tanzania and benchmarked them against international practices. In addition, the study investigated the advantages and disadvantages of the financing options available for grassroots initiatives. The findings from the systematic literature review and analysis of seven waste collection initiatives indicate that, while in advanced countries SWM activities are financed through carbon financing, and loans from the capital market, financial institutions and international agencies, in Tanzania, they are mostly financed through interest-free municipal loans, user charges (service contract), commercial loans, grants and members’ subscriptions. However, the service contract was the most common financing model in Tanzania, mainly because of the limited budget the government allocated for waste management activities. The financing options identified have some advantages and disadvantages, depending on their cost, flexibility, terms and conditions, accessibility and the inclusiveness of beneficiaries. Accordingly, we propose a hybrid model for financing SWM encompassing the public and private sector, especially in a context where government budgets allocated for SMW are limited.
Application of correlation-based recurrent neural network in porosity prediction for petroleum exploration
Authors: Mansoor Mustafa Ibrahim , Tuama Hadeel Mohammed , Humaidi Amjad Jaleel
Published: January 2025

Porosity prediction serves as a key metric to determine the characteristics of reservoirs and to reduce the exploration efforts, which in turn lead to enhancing the production planning and making economic vital decisions. In this sense, one can use low costly and low time-consumptive method by conducting experimental tests on various soil samples. Predicting porosity can be effectively utilized for identifying suitable drilling locations for petroleum exploration, thus reducing the need for extensive laboratory experiments beforehand. The seismic behavior has a direct impact on porosity features. This study works to find a mapping relationship between well-log porosity and seismic attributes. A Pearson Correlation Coefficient (PCC) method has been proposed based on diverse scales to determine the most significant seismic attributes and to reduce data dimensionality. The recurrent prediction neural network models have been proposed for learning and prediction. Three neural network models are introduced, represented by Nonlinear Autoregressive (NARX) network, the Long Short-Term Memory (LSTM) network, and the Gated Recurrent Unit (GRU) network. All these proposed models are trained to associate the nonlinear relationship between the selected attributes and porosity. The seismic attributes are assigned as the inputs to the neural models, while the porosity represents the target of neural structure. Moreover, the correlated and uncorrelated strategies are involved to test the effective attributes based on seven scenarios with the proposed neural structures. The results showed that the correlated NARX network consistently delivers better prediction accuracy and minimum errors as compared to other models for different correlation scales. Consequently, correlated NARX network is the best choice for porosity prediction.
A new approach utilizing DTCWT for feature extraction and ANN for classification to improve fingerprint recognition
Authors: N R Pradeep , D V Manjunatha , A Napolean , Rao Arjun Sunil
Published: January 2025

The authentication of biometric data using fingerprints is increasingly crucial in today’s security landscape. Despite advancements in fingerprint identification algorithms, challenges remain in matching incomplete prints. Fingerprints, known for their uniqueness and long-term durability, are widely used in biometric research, including this study. While existing literature presents successful strategies, there is still room for integrating these methods into more advanced algorithms. As technology and security demands evolve, the need for efficient, cost-effective, and reliable systems has driven researchers to develop robust algorithms. This study demonstrates a direct correlation between test and database images, with a particular focus on forensic fingerprint evidence submitted in the court of law, which must be supported by scientifically validated methods. Dual-Tree Complex Wavelet Transforms (DTCWT) is effective in capturing intricate fingerprint details by decomposing images into multiple levels while preserving directional information, making it highly suitable for fingerprint feature extraction. When combined with Artificial Neural Networks (ANNs), which excel in learning complex patterns and classifying data based on feature vectors, The identification process utilizes a combination of DTCWT for feature extraction and ANNs for classification, constructing a feature vector that forms the basis of a multiclass classifier. Using the National Institute of Standards and Technology, Special Database-4 (NIST SD-4) for evaluation, the proposed approach surpasses notable machine learning algorithms, such as K-Nearest Neighbor, Decision Tree, Random Forest, and Support Vector Machine, based on performance metrics. This approach has proven particularly effective in handling incomplete or low-quality fingerprints, addressing a major challenge in biometric authentication systems, Utilizing DTCWT and ANN in fingerprint recognition is considered a significant advancement, offering a more scalable and accurate solution for security applications, including forensic analysis and biometric identification systems. Impact Statement. The surge in information technology and the demand for heightened security have compelled researchers and scholars to seek efficient, cost-effective, accessible, and reliable methods for individual identification. Conventional fingerprint matching algorithms struggle to preserve feature information, hindering their ability to handle partial input data and perform multiple computational functions simultaneously. The adoption of Man and Machine Intelligent systems emerges as a potential solution, warranting further in-depth research. This investigation centers on deploying ANN and gauging its effectiveness using assessment metrics like F_Score, Specificity, Precision, Accuracy, and Sensitivity. It aims to compare these results with the currently prevailing machine learning algorithms and classifiers.
A comprehensive experimental investigation of different nanofluids effective thermal conductivity
Authors: Theegala Purushotham , Rachamalla Shyam Sunder
Published: January 2025

Nanofluids, renowned for their superior thermal conductivity relative to traditional fluids, have attracted considerable interest for their prospective applications in heat exchangers, cooling systems, and renewable energy technologies. Effective thermal conductivity has been determined for four distinct nanofluids such as silicon dioxide, cerium oxide, magnesium oxide and copper oxide at four different temperatures between 30 and 60 °C with intervals of 10 °C. Furthermore, four different volume percentages of nanoparticles have been chosen in the water-based base fluid, ranging from 0.5 to 2 percentages with increment of 0.5 percentages. There are various techniques to prepare the nanofluids and in the present study the ultrasonication technique has been adopted in the preparation of nanofluids. The aim of this study is to determine how the temperature and the volume percent variations of nanoparticles in the bass fluid influence the effective thermal conductivity. The effective thermal conductivity has been found to be increase with increase in the temperature and volume percentage of nanoparticles in the base fluid. The highest effective thermal conductivity at 60 °C was discovered when 0.2% volume percentage of nanoparticles have been added. The thermal conductivity of nanofluids increases with rising temperature (30 °C–60 °C) and nanoparticle volume fraction (0.5%–2%), as shown for CuO (13.1%–15.1%), MgO (18.2%–20.9%), SiO2 (5.2%–6.6%), and CeO2 (10%–12.9%) nanofluids. Numerous correlations have been adopted to compare with experimental effective thermal conductivity, such as Maxwell, Chandrasekar, and Corcine correlations. The Chandrasekar correlation consistently showed better agreement than the Maxwell and Corcine correlations when comparing the measured effective thermal conductivity to the effective thermal conductivity predicted by correlations at various temperatures and volume percentages. This present study is important as it offers insights into the optimization of nanofluids for improved thermal conductivity, which is advantageous for energy systems, cooling technologies, and industrial operations.
A simulation analysis of reactive power compensation with hybrid compensator in shunt compensated system
Authors: Joshi Minesh K , Patel R R
Published: January 2025

Distributed Flexible Alternating Current Transmission System (D-FACTS) devices are widely utilized in distribution networks to afford reactive power compensation and enhance voltage stability. These systems often encounter a combination of linear and nonlinear loads, which give rise to common power quality challenges such as voltage sags, swells, and total harmonic distortion (THD) in grid-connected environments. Addressing these issues is a critical aspect of the proposed hybrid compensator control strategy’s initial modeling and performance evaluation. The hybrid compensator integrates a Distribution Static Synchronous Compensator (DSTATCOM) with a Thyristor Switched Capacitor-Thyristor Controlled Reactor (TSC-TCR) to efficiently manage reactive power under diverse loading scenarios. A proportional-integral (PI) controller is employed to regulate the DC link voltage, with its gains optimally tuned using the Particle Swarm Optimization (PSO) algorithm. The PSO approach optimizes controller parameters, minimizes power quality disturbances, and ensures effective reactive power compensation. MATLAB simulation results confirm the efficacy and robustness of the proposed hybrid control strategy, showcasing its ability to stabilize voltage profiles and significantly reduce THD across varying load conditions in distribution systems.
A Problem of Values
Authors: Derrig Ríán
Published: January 2025

This chapter uses archival sources to develop an intellectual biography of Myres McDougal’s life and career before he met Harold Lasswell in 1935 and began to develop their ‘policy-oriented jurisprudence’. It recounts formative experiences of McDougal’s early life in rural Mississippi, juxtaposing the cultural and political life of this context, including segregation, against the later urban progressivism that shaped McDougal’s early scholarship as a New Deal property lawyer. The chapter follows McDougal’s graduate studies at the University of Oxford and his first contact with the American legal realist movement of the 1920s. It places McDougal’s scholarship in a tradition of legal thought deeply shaped by philosophical pragmatism of which legal realism was a part. McDougal’s 1930s work in modernist urban planning is examined. The chapter argues that his New Deal property law scholarship shaped McDougal’s later international law scholarship in significant ways.
Intention and Prediction in Means–End Reasoning
Authors: White Stephen J
Published: January 2025

How, if at all, does one’s intention to realize an end bear on the justification for taking the means to that end? Theories which allow that intending an end directly provides a reason to take the means are subject to a well-known “bootstrapping” objection. On the other hand, “anti-psychologistic” accounts—which seek to derive instrumental reasons directly from the reasons that support adopting the end itself—have unacceptable implications where an agent faces multiple rationally permissible options. White considers and rejects an alternative, predictive, role for intention in means–end reasoning. He then develops a new proposal, according to which instrumental reasons are not merely reasons to perform an act necessary for a given end, but to perform the act for the sake of that end.
How Can Beliefs Wrong?—A Strawsonian Epistemology
Authors: White Stephen J
Published: January 2025

We take a tremendous interest in how other people think of us. We have certain expectations of others, concerning how we are to figure in their thought and judgment. And we often feel wronged if those are disappointed. But it is puzzling how others’ beliefs could wrong us. On the one hand, moral considerations don’t bear on the truth of a belief and so seem to be the wrong kind of reasons for belief. On the other hand, truth-directed considerations seem to render moral considerations redundant. In this paper, we argue that to understand the possibility of doxastic wronging, we need to understand beliefs, no less than actions, as ways of relating to one another. In particular, how we take account of what others think and say will depend on whether we take up what P.F. Strawson calls the participant stance toward them. We show how this helps to make sense of an example Miranda Fricker identifies as a case of epistemic injustice. We then use the example to spell out the ethical significance of Tyler Burge’s idea that we have a default entitlement to accept at face value what we receive from a rational source.
Austria
Authors: Proctor Tammy M
Published: January 2025

In the spring of 1919, out of deep concern over the possibility of revolution, U.S. Food Administrator Herbert Hoover urged multinational agreements that would feed the hungry in Europe, particularly children. He argued that involvement of the United States in the rebuilding and provisioning of Europe was vital to trade and political prestige in postwar Europe. For the United States, these schemes reached their apex between 1919 and 1924 in the American Relief Administration (ARA) and its successor, the ARA European Children’s Fund. Congress appropriated $100 million to bring aid to non-enemy European countries during the six months prior to the Armistice. Later in 1919, Hoover successfully argued that even former enemy children should be fed, but with private funds and loans. Austria, the public and international face of child hunger in Europe after the war, became a testing ground for saving children and creating standardized “best practices” in foreign aid.
Germany
Authors: Proctor Tammy M
Published: January 2025

Germany represented a pivotal point, as U.S. aid to Germany faced criticism from ordinary Americans unwilling to help their former enemy. U.S. officials saw multiple benefits in an ambitious program for alleviating German distress using the religious pacifist group, the Quakers, to dispense the food, and thought that German Americans might be mobilized to support friends and families with care packages. Also high-level political concerns about U.S. access to postwar markets, Americanization at home, and the threat of socialism competed with genuine concern about healing the wounds of war and saving a generation of children from poor health. The German relief units sponsored under American auspices found themselves straddling these potent political and ethical tensions. Yet, despite considerable public reluctance in the United States for German reconstruction and aid, the Quaker Feeding began on February 26, 1920, and it fed millions of children in Germany over nearly five years.
Intersectional Solidarity
Authors: Crowder Chaya Y
Published: January 2025

This project is concerned with the circumstances under which people come to support issues that affect Black women. In particular, Intersectional Solidarity challenges the notion that racial consciousness or gender consciousness alone shape political preferences and instead argues that when it comes to issues that affect marginalized groups at the intersection of multiple identities, intersectional group consciousness shapes political behavior. This book defines intersectional solidarity as a political disposition that is characterized by awareness and distress over the oppression of marginalized subgroups, such as Black women and LGBTQ+ people of color. The central contribution of this book is the development of original measure: the intersectional solidarity index (ISI). The ISI is a four-item scale that captures group consciousness at the intersection of race, gender, class, and sexuality. By measuring intersectional solidarity, we are better able to understand the types of people who support addressing issues that disproportionately and directly affect Black women. Finally, Intersectional Solidarity focuses on how intersectional solidarity influences support for issues that affect Black women. The book expands the types of policies examined by exploring intersectional issues, such as the circumstances under which the mass public support the Maternal CARE Act, a policy that addresses the racial disparity in maternal healthcare, as well as Equal Pay Certification, which is a policy that addresses the race/gender pay gap. Intersectional Solidarity demonstrates that to fully understand how people come to care about issues that affect Black women, scholars are required to ask new questions.
On Privacy and Technology
Authors: Solove Daniel J
Published: January 2025

How is technology changing privacy? Are we doomed? Is there anything we can do? “Privacy is dead!” This cry has rung out again and again as we have witnessed the rapid rise of new digital technologies. Are we destined to watch helplessly as technology turns our society into a terrible blend of Franz Kafka’s The Trial, George Orwell’s 1984, Aldous Huxley’s Brave New World, and Margaret Atwood’s The Handmaid’s Tale? Can anything be done to save us from a dystopian world without privacy? In this short and accessible book, internationally renowned privacy expert Professor Daniel J. Solove reflects on his examination of privacy over the past twenty-five years. On Privacy and Technology describes the profound changes technology is wreaking upon privacy, why these changes matter, and what can be done about them. Solove’s lively discussions of technology and policy, infused with the humanities, argue that the law should focus on power and structure and that it is failing because it is not holding creators and users of technology accountable for the harms they create. Solove deftly weaves together philosophical ideas with concrete practical knowledge from his many years of working with technology companies and talking with policymakers. His book is an essential primer for anyone who wants to understand the threats to privacy in today’s Digital Age and how we can face them effectively. Succinct, understandable, and engaging, On Privacy and Technology is beautifully written, passionate, and filled with surprising insights.
Transforming Learning and Transforming Society
Authors: Xiang Xin
Published: January 2025

Addressing the deep-rooted and complex educational inequalities set forth in the previous chapters will require systemic changes that are far more extensive than technical bandages like installing screens and offering broadcasting programs in struggling schools. If we are at all serious about educational equity and justice, we need to thoroughly transform not only school systems but also the political, economic, and social institutions that they are embedded in. In Chapter 7, Transforming Learning and Transforming Society, the author argues that we can start this process by wrestling with two key questions collectively: whose knowledge and contribution counts, and what good schools look like.
Imposed Secession
Authors: Kudelia Serhiy
Published: January 2025

This chapter identifies the key elements of Russia’s “secessionist template,” which was first introduced in Crimea and was later adopted in Donbas. Its objective was to organize pro-Russian mobilization among locals under separatist slogans, which could then serve as a cover for the Russian armed intervention in these two regions. The chapter traces the continuity in tactics and the actors that used them from the annexation of Crimea to the onset of the armed uprising in Donbas. It also details the exact roles played by Russian agents at the start of the armed insurgency in Donbas and reveals other forms of Russian support for the insurgency, such as covert provision of arms, military training of local militants, coordination of attacks on government buildings by its proxy forces, and administering the new separatist entities.
Prime Ministers in Central and Eastern Europe
Authors: Grotz Florian , Berz Jan , Kroeber Corinna , Kukec Marko
Published: January 2025

Prime ministers in post-communist Central and Eastern Europe (CEE) are widely believed to be weak because they lack political experience and operate under extraordinarily difficult conditions. However, the literature on the personalization of politics challenges this view on the grounds that there are some exceptionally strong leaders in the region. This introductory chapter outlines how the book examines these different claims. It does so by reviewing existing approaches to highlight the main research gaps, providing a preview of a systematic concept of prime-ministerial performance and related theoretical arguments, and introducing an original dataset covering 131 prime-ministerial cabinets in eleven CEE countries from 1990 to 2018. Moreover, the chapter provides an overview of the key findings of the book’s empirical chapters.
Contextual Conditions
Authors: Grotz Florian , Berz Jan , Kroeber Corinna , Kukec Marko
Published: January 2025

The chapter explores the context in which prime ministers (PMs) in Central and Eastern Europe exercise their office. Given that post-communist PMs have had to grapple with the historical legacies of communism and the simultaneous political and economic transformation, it is widely believed that they operate under exceptionally difficult circumstances. To examine this proposition, the chapter develops an analytical framework that captures the key contextual conditions for prime-ministerial agency in post-communist democracies in three dimensions and sixteen related factors. The empirical analysis of 131 prime-ministerial cabinets reveals that complexity in the institutional, political, and economic contexts across countries and over time is not uniformly high; instead, there are specific combinations of more favourable and less favourable conditions for prime-ministerial agency. At the same time, the findings suggest that some contextual factors may be more relevant than others in explaining PMs’ varying performance. This warrants a systematic analysis of related effects, which is carried out in Chapter 8.
Defining Prime-Ministerial Performance
Authors: Grotz Florian , Berz Jan , Kroeber Corinna , Kukec Marko
Published: January 2025

The chapter presents the concept of prime-ministerial performance used in the empirical investigation. While the extant literature has employed various criteria to assess the performance of prime ministers (PMs), the present analysis systematically subsumes them under a unified concept centring on the tasks PMs ought to perform in parliamentary democracies. As an agent of the parliamentary majority, the PM is responsible for running state affairs. PMs’ tasks include settling cabinet conflicts, shaping government policies, managing exogenous crises, and securing the national interest at international level. They are also politically accountable to the parliamentary majority and depend on their own party. They hence have to secure the support of these two principals. As this theoretically grounded concept encompasses the prime-ministerial tasks essential for any parliamentary democracy, it overcomes one of the main barriers to studying prime-ministerial performance in Central and Eastern Europe during the first three decades after democratic transition.
The GLOB-cAGE Consortium: A Global Cardiovascular Collaborative Network of Older Adults with Cardiovascular Disease
Authors: Wong Jie Jun , Tse Gary , Vu Huyen Thi Thanh , Nguyen Huong Thi Thu , Lin Shuanglan , Tu Qiang , Yanhong Dong , Garcia-Zamora Sebastian , Gómez-Mesa Juan Esteban , Banach Maciej , Sze Shirley , Tan Ru-San , Liang Zhong , Koh Angela S
Published: January 2025

Background: GLOB-cAGE is a newly established unprecedented consortium that brings together cohorts of older persons with cardiovascular disease worldwide. GLOB-cAGE aims to harmonize non-identifiable data from longitudinal cohorts examining cardiovascular health and cardiovascular disease diagnosis and management in older individuals to perform meta-regression analyses using combined repositories of standardized subject-level data points.

Methods and Design: Studies registered into GLOB-cAGE are population-based longitudinal cohort studies or clinical trials, either ongoing or completed, that involve assessing cardiovascular health as a central objective. Cross-sectional studies that significantly contribute to cardiovascular research in older individuals may also be included. The GLOB-cAGE will consist of individuals already diagnosed with cardiovascular disease and primary prevention of individuals at different risks of cardiovascular disease. The studies should have a minimum sample size of 100 participants, and the participants are either adults aged above 65 years or above 40 years with longitudinal follow-up over the next few decades. Enrollment in GLOB-cAGE may involve collaboration on non-identifiable or anonymized raw or processed data for joint analyses. Sites unable to provide raw or processed data due to institutional or other reasons may participate in alternative ways, including performing separate analyses in-house. At the time of writing, there are at least ten participating teams from nine countries and 27 studies enrolled in GLOB-cAGE.

Conclusions: The GLOB-cAGE consortium is an international effort to bring together cardiovascular disease research in older persons, focusing on providing greater representation from diverse countries battling population aging. It addresses the evidence gaps from the insufficient enrolment of older individuals in randomized controlled trials and permits investigators to conduct high-quality epidemiological studies.
GOPhage: protein function annotation for bacteriophages by integrating the genomic context
Authors: Guan Jiaojiao , Ji Yongxin , Peng Cheng , Zou Wei , Tang Xubo , Shang Jiayu , Sun Yanni
Published: January 2025

Bacteriophages are viruses that target bacteria, playing a crucial role in microbial ecology. Phage proteins are important in understanding phage biology, such as virus infection, replication, and evolution. Although a large number of new phages have been identified via metagenomic sequencing, many of them have limited protein function annotation. Accurate function annotation of phage proteins presents several challenges, including their inherent diversity and the scarcity of annotated ones. Existing tools have yet to fully leverage the unique properties of phages in annotating protein functions. In this work, we propose a new protein function annotation tool for phages by leveraging the modular genomic structure of phage genomes. By employing embeddings from the latest protein foundation models and Transformer to capture contextual information between proteins in phage genomes, GOPhage surpasses state-of-the-art methods in annotating diverged proteins and proteins with uncommon functions by 6.78% and 13.05% improvement, respectively. GOPhage can annotate proteins lacking homology search results, which is critical for characterizing the rapidly accumulating phage genomes. We demonstrate the utility of GOPhage by identifying 688 potential holins in phages, which exhibit high structural conservation with known holins. The results show the potential of GOPhage to extend our understanding of newly discovered phages.
Region-specific roles of oviductal motile cilia in oocyte/embryo transport and fertility
Authors: Scully Deirdre M , Xia Tian , Musina Guzel R , McCown Michaela A , Umezu Kohei , Kircher Bonnie K , Behringer Richard R , Larina Irina V
Published: January 2025

The physiological and clinical importance of motile cilia in reproduction is well recognized; however, the specific role they play in transport through the oviduct and how ciliopathies lead to subfertility and infertility are still unclear. The contribution of cilia beating, fluid flow, and smooth muscle contraction to overall progressive transport within the oviduct remains under debate. Therefore, we investigated the role of cilia in the oviduct transport of preimplantation eggs/embryos using a combination of genetic and advanced imaging approaches. We show that the region of the oviduct where cumulus–oocyte complex circling occurs, around the time of fertilization, is correlated with asymmetrical mucosal fold arrangement and non-radially distributed ciliated epithelium. Our results suggest that motile cilia, as well as mucosal fold asymmetry, may contribute to the local flow fields that help steer luminal contents away from the epithelial walls. We also present, in vivo, volumetric evidence of delayed egg transport in a genetic mouse model with disrupted motile cilia function in the female reproductive system. Females with Dnah5 deleted in the oviduct epithelium are subfertile and demonstrate disrupted motile cilia activity within the oviduct mucosa. Fifty percent of Dnah5 mutant females have delayed egg transport where cumulus–oocyte complexes did not progress to the ampulla at the expected time point and remained within the ovarian bursa. The integration of advanced imaging with genetic dysfunction of motile cilia provides valuable insights into oviductal transport. Potentially, these data could be valuable for better understanding and management of tubal pathologies and human infertility.
Effects of vent position and numbers on hydrogen explosion dynamic characteristics
Authors: Sun Han , Yang Guogang , Sheng Zhonghua , Xu Zhuangzhuang , Yang Xiaoxing , Ji Shengzheng
Published: January 2025

Hydrogen energy has been widely used in various industrial processes. However, hydrogen explosion can cause significant loss of personnel and property, and explosion venting is an effective method to reduce the explosion damage. The mechanism of hydrogen explosion venting has become an important research topic in hydrogen energy safety engineering. This study employs numerical simulation to explore the impact of vent parameters on the hydrogen-air explosion dynamics. A geometric model considering internal and external explosion is established. Results show that venting efficiency improves as the vent is positioned closer to the ignition or the number of vents increases. The peak internal overpressure increases by 1.2 times as the single vent moves from the ignition to near the end. The external explosion overpressure and dynamic pressure grows with the decrease of internal explosion venting efficiency. The flame front deflects toward the vent and ejects from the duct under the suction effect of the vent. The vortex flow characteristics near the vent cause the flame to deform as it propagates downstream. Vents located closer to the ignition induce the formation of a reverse flow field and lead to reverse propagation of the flame. The formation of symmetrical vortex regions within the flame causes it to compress, resulting in a longer external flame length as the vent is located farther from the ignition. The maximum flame speed increases by 1.1 times as the single vent moves from the ignition to near the end. Multiple flame propagation speed are exhibited under multiple vents conditions.
Heteroanionic synthesis of lanthanum/neodymium-based titanium oxycarbide: a novel approach with multiple objectives for clean energy and pollutant-free environment
Authors: Subramanian Yathavan , Le Minh Thang , Bahruji Hasliza , Sarifuddin Wahid Sidik , Mahadi Abdul Hanif , Gubendiran Ramesh Kumar , S. A. Muhammed Ali , Raj Veena , Yassin Hayati , Irvine John T S , Azad Abul K
Published: January 2025

In this study, a new type of oxycarbide-based compounds, namely lanthanum titanium oxycarbide and neodymium titanium oxycarbide, were synthesized through solid-state reaction to replace titanium oxycarbide due to its rapid charge carrier recombination and limited responsiveness to visible light (VL) in photocatalysis. The structural, morphological, optical absorption, and vibrational properties of the synthesized catalysts were thoroughly characterized using powder X-ray diffraction, scanning electron microscopy, ultraviolet-visible spectroscopy, and Fourier transform infrared spectroscopy to assess their suitability for catalytic applications. Subsequently, the photocatalytic behavior of the synthesized materials was evaluated for their ability to degrade the hazardous Congo red (CR) dye in various types of water, including deionized water, domestic utility water used for household purposes, and seawater, under VL illumination. Notably, lanthanum titanium oxycarbide and neodymium titanium oxycarbide exhibited superior degradation efficiencies for CR dye, achieving maximum degradation rates of 87% and 89%, respectively, in domestic water used for routine household purposes within a duration of 90 minutes, when compared to TiOC. However, the degradation efficiency was slightly lower in deionized water and seawater. Additionally, lanthanum titanium oxycarbide and neodymium titanium oxycarbide demonstrated promising hydrogen evolution activity, generating 19.7 and 21.1 µmol/g, respectively, under VL in 180 minutes. The enhanced efficiency in CR removal and hydrogen generation activity of lanthanum titanium oxycarbide and neodymium titanium oxycarbide has been attributed to the synergistic effects of improved VL absorption, higher exciton separation and a supportive pH environment due to the presence of lanthanum, neodymium, and carbon ions in a combined entity.