bluuebunny/crossref_metadata_2025 huggingface dataset:
Improving quantification accuracy of a nuclear Overhauser enhancement signal at −1.6 ppm at 4.7 T using a machine learning approach
Authors: Yin Leqi , Viswanathan Malvika , Kurmi Yashwant , Zu Zhongliang
Published: January 2025

Objective. A new nuclear Overhauser enhancement (NOE)-mediated saturation transfer MRI signal at −1.6 ppm, potentially from choline phospholipids and termed NOE(−1.6), has been reported in biological tissues at high magnetic fields. This signal shows promise for detecting brain tumors and strokes. However, its proximity to the water peak and low signal-to-noise ratio makes accurate quantification challenging, especially at low fields, due to the difficulty in separating it from direct water saturation and other confounding signals. This study proposes using a machine learning (ML) method to address this challenge. Approach. The ML model was trained on a partially synthetic chemical exchange saturation transfer dataset with a curriculum learning denoising approach. The accuracy of our method in quantifying NOE(−1.6) was validated using tissue-mimicking data from Bloch simulations providing ground truth, with subsequent application to an animal tumor model at 4.7 T. The predictions from the proposed ML method were compared with outcomes from traditional Lorentzian fit and ML models trained on other data types, including measured and fully simulated data. Main results. Our tissue-mimicking validation suggests that our method offers superior accuracy compared to all other methods. The results from animal experiments show that our method, despite variations in training data size or simulation models, produces predictions within a narrower range than the ML method trained on other data types. Significance. The ML method proposed in this work significantly enhances the accuracy and robustness of quantifying NOE(−1.6), thereby expanding the potential for applications of this novel molecular imaging mechanism in low-field environments.
Spatio-temporal modeling and simulation of a mode-locked tapered semiconductor diode laser
Authors: Wohlfeil Shulin , Koester Jan-Philipp , Wenzel Hans , Knigge Andrea
Published: January 2025

We present a theoretical model and numerical simulation results of the dynamics of a monolithic edge-emitting mode-locked tapered quantum well laser. The comprehensive simulation employs a

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dimensional traveling wave model and incorporates models for lateral current spreading and carrier diffusion, while also addressing thermal effects in the laser cavity. Our investigation of the pulse generation by passive mode-locking demonstrates good agreement with experimental observations. Furthermore, we perform a study of the intra-cavity propagation dynamics of the laser, which provides valuable insights for a better understanding of the laser’s behavior.
Divergent impacts of soil desiccation on atmospheric water vapor–temperature responses regulated by evapotranspiration
Authors: Wang Ruonan , Fan Xingwang , Liu Yongwei , Zhao Xiaosong , Wang Rong , Liu Yuanbo
Published: January 2025

Climate warming induces temporally varying atmospheric water vapor (WV), yet the spatial distribution of opposing trends across global land remains elusive. Here, we use the monthly European Centre for Medium-range Weather Forecasts Reanalysis v5 dataset to discern the responses of WV changes to the rising air temperature from 1982 to 2020. Simultaneous increases in both the WV and air temperature are observed over approximately three-quarters of global land, with a median of 0.21 mm·K–1, particularly evident in the tropics. Strong positive responses are primarily influenced by increasing trends in evapotranspiration (ET) and low-elevation areas. About one-fifth of global land shows a decline in WV with a median of −0.62 mm·K–1, predominantly in southeastern South America and southwestern North America. Negative responses are also driven by ET trends, where strong ET enhances these effects that are less pronounced in high-altitude regions. The prevalence of a positive response is highest during September–October–November (81%), while a negative response was observed most in December–January–February (35%). The spatial distribution of negative responses generally aligns with soil desiccation patterns; soil desiccation exacerbates negative responses in humid regions due to evaporative cooling but mitigates them in arid regions due to intensified warming. This study enhances our comprehension regarding the divergent responses of atmospheric WV toward global warming.
Generalised Ornstein–Uhlenbeck process: memory effects and resetting
Authors: Trajanovski P , Jolakoski P , Kocarev L , Metzler R , Sandev T
Published: January 2025

In this work we consider a generalised Ornstein–Uhlenbeck (O–U) process for a stochastically driven particle in an harmonic potential which is governed by a Fokker–Planck equation in the presence of a memory kernel. We analyse the probability density function, the mean and the mean squared displacement (MSD) by employing the subordination approach connecting the operational time of the process with the (generalised) laboratory time. We provide analytical results for the mean and the MSD in case of a power-law memory kernel which corresponds to the fractional O–U process. The generalised O–U process in the presence of Poissonian resetting is also investigated by using the renewal equation approach, and the nonequilibrium stationary state approached in the long time limit is obtained. The analytical results are confirmed by numerical simulations based on the coupled Langevin equations.
Probability theory in ghost imaging with thermal light: progress and applications
Authors: Zhao Yi-Ning , Chen Lin-Shan , Kong Lingxin , Zhang Su-Heng , Wang Chong , Ren Cheng , Cao De-Zhong
Published: January 2025

Ghost imaging reconstructs images by using two separate, but correlated beams. One beam illuminates the object and then is collected by a bucket detector. The other beam is captured by a space-resolved (pixelated) reference detector. The object information is retrieved in the correlation measurements of the two detectors. Ghost imaging can be implemented with entangled photon pairs, or with intensity correlation of thermal light (TL). For the latter, recently, a theory of joint probability density function has been proposed to investigate the high-order correlation functions of TL. The probability theory is based on two assumptions. The intensity of the reference beam inside the image resolution is assumed to be a stochastic variable, which meets a certain probability density function. The second assumption is that the bucket signals are the sums of the stochastic variables from the object. Then the joint probability density function of the bucket and reference signals can then be established. As a result, the probability theory can predict the nonlocal behaviors of ghost imaging with TL (GITL). The progress and applications of the probability theory in the GITL experiments were reviewed in this paper.
The validity of physical optics for microwave analysis: accuracy through simplicity
Authors: Mesa Francisco , Quevedo-Teruel Oscar
Published: January 2025

Traditionally, the optics and microwave communities have been separated not only by the THz band but also by differences in technical knowledge, analytical and computational approaches, design processes, and measurement methodologies. In this contribution, we aim to bridge this divide by leveraging a computational asymptotic technique from optics, known as physical optics, which holds significant potential for the microwave/antenna community. This technique allows for precise microwave calculations for radiation patterns, reflection coefficients, material losses, and mutual coupling between antennas.
Si doping enhances the tribocorrosion resistance of DLC films in acidic, alkaline and salt solutions
Authors: Zhou Hongwei , Yao Yifan , Niu Weiming , Xiao Yuping , Shang Lunlin , Li Hao , Zhu Minhao
Published: January 2025

The a-C:H and a-C:H:Si were fabricated by plasma-enhanced chemical vapor deposition. The microstructures, surface morphologies, mechanical properties, corrosive properties and tribological properties of the a-C:H and a-C:H:Si films were systematically investigated. The findings revealed that silicon doping reduces the residual stress, hardness and modulus of as-fabricated films while increasing the sp3 content. As a result, silicon doping enhances the thickness and densification of a-C:H:Si films. This enhancement serves to prevent corrosive solutions from penetrating the film-substrate interface through cracks and averting the risk of catastrophic failure of the films due to accumulation of corrosion products at the interface. The composition of the boundary lubrication film formed in NaCl, HCl, and NaOH solutions was discussed by examining different reactions between samples and ZrO2 spheres with corrosive solutions at varying pH levels. Additionally, the a-C:H:Si films exhibited favorable tribological performances in corrosive solutions, as evidenced by low friction coefficients and low wear rates. In 96 h neutral salt spray experiments, it was noted that a-C:H:Si films exhibit limited spalling, indicating consistent protection for SUS 304 stainless steel. These findings highlight the significance of doped Si atoms in carbon films for enhancing their tribocorrosion resistance properties.
Novel approach for quality control testing of medical displays using deep learning technology
Authors: Maruyama Sho , Mizutani Fumiya , Watanabe Haruyuki
Published: January 2025

Objectives: In digital image diagnosis using medical displays, it is crucial to rigorously manage display devices to ensure appropriate image quality and diagnostic safety. The aim of this study was to develop a model for the efficient quality control (QC) of medical displays, specifically addressing the measurement items of contrast response and maximum luminance as part of constancy testing, and to evaluate its performance. In addition, the study focused on whether these tasks could be addressed using a multitasking strategy. Methods: The model used in this study was constructed by fine-tuning a pretrained model and expanding it to a multioutput configuration that could perform both contrast response classification and maximum luminance regression. QC images displayed on a medical display were captured using a smartphone, and these images served as the input for the model. The performance was evaluated using the area under the receiver operating characteristic curve (AUC) for the classification task. For the regression task, correlation coefficients and Bland–Altman analysis were applied. We investigated the impact of different architectures and verified the performance of multi-task models against single-task models as a baseline. Results: Overall, the classification task achieved a high AUC of approximately 0.9. The correlation coefficients for the regression tasks ranged between 0.6 and 0.7 on average. Although the model tended to underestimate the maximum luminance values, the error margin was consistently within 5% for all conditions. Conclusion: These results demonstrate the feasibility of implementing an efficient QC system for medical displays and the usefulness of a multitask-based method. Thus, this study provides valuable insights into the potential to reduce the workload associated with medical-device management the development of QC systems for medical devices, highlighting the importance of future efforts to improve their accuracy and applicability.
Impact of green finance on poverty reduction: evidence from China
Authors: Xu Wei , Wang Xiaoning , Zhang Yun , Wang Feng
Published: January 2025

Integrating environmental sustainability within the financial sector, known as green finance, offers a promising approach to poverty reduction in China. This study investigates the impact of green finance on poverty reduction in China. We construct a comprehensive index of green finance, which includes green credit, green insurance, and green investment, to evaluate its development across China’s provinces. We uncover the intricate relationship between green finance and poverty reduction using panel data regression analysis on a dataset spanning 30 provinces from 2010 to 2021. Our findings indicate a positive and significant association between the advancement of green finance and poverty reduction. Notably, this effect is most pronounced in Eastern China, intermediate in Central China, and the least in Western China. This regional disparity underscores the need for geographically sensitive policy interventions to harness green finance’s poverty-reducing potential effectively. Furthermore, we identify economic growth and industrial structure upgrading as primary mediators between green finance and poverty reduction. While environmental improvement plays a role, its impact as a mediator is relatively small, suggesting a more nuanced approach to integrating environmental sustainability with poverty reduction strategies. The study contributes to the literature by providing empirical evidence on the effectiveness of green finance in poverty reduction. It offers insights for policymakers to enhance green finance strategies, emphasizing economic growth, industrial advancement, and sustainable development.
Toward zero-excess lithium sulfur batteries: a systematic cell parameter study
Authors: Cruddos Joshua H , Robinson James B , Shearing Paul R , Rettie Alexander J E
Published: January 2025

Zero-excess lithium (ZEL) or ‘anode-free’ batteries aim to minimize negative electrode material and address the challenges associated with handling thin lithium metal foils during fabrication. To date, most studies in the field of ZEL cells have primarily focused on lithium-ion chemistry, with considerably fewer systematic investigations into ZEL-sulfur (ZELiS) cell fabrication and optimization. Here we develop a ZELiS battery, comprising a Li2S-based composite positive electrode on carbon paper paired with a Ni foil current collector (CC) and evaluate the effects of various CC materials, electrolyte volume to Li2S mass ratio and C-rate. The developed cells reproducibly achieve an average Coulombic efficiency of 99% from cycles 2 to 200, and a final capacity of 272 mAh g−1
Li2S at a C/10 rate. Furthermore, we employ x-ray computed tomography to elucidate the morphological changes and degradation processes occurring within the positive electrode composite, revealing the irreversible loss of Li2S/S8 during cycling, which is exacerbated at high rates. These results should be useful in the development of commercially viable ZEL energy storage devices.
ADL-Net: attention-driven densenet-LSTM network for underwater images classification
Authors: Asam Yusuf , Zhou Zhiyu
Published: January 2025

Imaging in marine environment is a challenging task due to several reasons, including light variations, color distortions, noise, and limited datasets, which causes inaccurate target classification problems. This paper presents a methodology for image classification in marine biology and environmental research. We proposed the Attention-Driven DenseNet-LSTM Network (ADL-Net), aiming to improve classification accuracy of underwater imagery. Initially, feature extraction is performed using multi-levels of DenseNet201, which excels in hierarchical feature extraction, offering stability and rapid convergence. In the next stage, two modified attention mechanisms are designed: the squeeze and excitation operations are used to refine channel-specific feature responses, while the convolutional block attention module refines attention for both channels and spatial dimensions. These attention mechanisms help the model to highlight important features and minimize distractions. Additionally, a Bi-directional Long Short-Term Memory layer is integrated to capture spatial dependencies and improve classification robustness. Various training strategies are used to find the best parameter tuning. Our method demonstrates excellent performance when tested on fish datasets: LifeCLEF 2015 and Fish4Knowledge, achieving accuracies of 98.02%, and 99.52%, respectively. These findings underscore ADL-Net’s potential for enhancing automated underwater image classification, advancing research in marine ecology.
A method to investigate the influence of temperature and working conditions on the pressure distribution of hydrodynamic bearings
Authors: Pham Van Hung , Le Duc Bao , Nguyen Thuy Duong
Published: January 2025

This paper investigates the influence of oil temperature and operating conditions on the pressure distribution in a hydrodynamic bearing using an innovative measurement method. The method employs a single pressure sensor mounted on the bearing bush, which is gradually rotated around the bearing circumference using a differential mechanism. Experiments were performed at oil inlet temperatures of 40 °C, 60 °C, and 80 °C, with rotational speeds of 1100, 1500, and 1900 rpm. The findings reveal that the maximum pressure (Pmax​) increases by approximately 48%–56% as the rotational speed rises from 1100 to 1900 rpm. Conversely, Pmax​ decreases by about 19%–22% when the oil temperature increases from 40 °C to 80 °C. The study concludes that the effect of rotational speed on Pmax​ is significantly greater than that of oil temperature.
An investigation from raw components to composite: 3D printed Voronoi lattice core structured sandwich composite with woven glass fiber-epoxy outer layer
Authors: Gür Yılmaz , Benlikaya Ruhan , Çelik Sare
Published: January 2025

A key emerging trend in mechanical engineering design involves adopting strategies that build lightweight lattice geometries, particularly for sandwich structures. These structures are characterized by low mass, a significant surface area to volume ratio, high porosity, and suitable mechanical behavior. This study focuses on the fabrication and investigation of thermoplastic polyurethane (TPU) Voronoi lattice core (V-core) structured sandwich composite with woven glass fiber (WGF)-Epoxy outer layer. The TPU V-Core structure was fabricated using the Fused Filament Fabrication (FFF) three dimensional (3D) printing method. Fourier Transform Infrared Spectroscopy (FTIR), Raman Spectroscopy, and Thermogravimetric Fourier Transform Infrared Spectroscopy (TG-FTIR) analyses were used to examine the interactions between the components within the sandwich composite structure. The experimental results demonstrated that the investigated structure has intricate interactions at the interface between the WGF-Epoxy outer layer and the V-core structure. The thermal stability and thermal degradation pathway of the composite and its components were also examined. In addition, three-point bending (TPB) tests were conducted on the sandwich composite and also on the core structures with plain rectangular prism and Voronoi lattice to assess their mechanical behavior.
Research on heating temperature control method of VOC gas sensor and development of new sensor module
Authors: Wang Bo , Ma Minghao
Published: January 2025

Sensors made of various new materials exhibit high sensitivity and accuracy in detecting volatile organic compounds (VOCs). However, they also demand higher working temperatures to unleash their outstanding performance within a certain temperature range. Furthermore, the fluctuation of ambient temperature throughout the year significantly impacts the heating temperature of the sensors. Conventional commercial sensor modules utilizing constant voltage heating are no longer able to meet the precise temperature control requirements. Therefore, our research team conducted a heat transfer analysis to establish the mathematical relationship between heating temperature and voltage. This was subsequently validated through finite element analysis, leading to the development of a multivariate linear regression model for predicting voltage based on the desired target temperature and ambient temperature. To address this, we proposed an approach to automatically adjust the heating temperature by controlling the heating voltage duty cycle using a microcontroller based on the ambient temperature. As a result, a novel adaptive temperature-controlled sensor module was developed. Experimental tests demonstrated that within the heating temperature range of 263 °C–464 °C, the substrate temperature could be controlled with an average error of 4.36%, meeting the precision requirements for sensor heating temperature control. In comparison with the commercial module, the temperature-controlled module exhibited a notable improvement in sensitivity when responding to different ambient temperatures. At 0 °C, the average sensitivity enhancement for the MQ3 and MQ7 sensors compared to the commercial module was 12.77% and 31.5%, respectively, and at 40 °C, the average enhancements were 5.94% and 19.8%. This sensor module and temperature control method provide theoretical and technical references for the accurate measurement of VOC parameters.
Dynamic configuration optimization of FPGA accelerators through reinforcement learning for enhanced performance and resource utilization
Authors: Pal Sandipan , Upadhyaya Bijoy Kumar , Majumder Tanmoy , Dasgupta Sudeb , Das Narottam , Bhattacharjee Abhishek
Published: January 2025

Deploying Sparse Ternary Neural Networks on edge devices is in the areas of computational efficiency and energy optimization is a challenging task. This work presents a new FPGA-based accelerator integrating reinforcement learning and neural architecture search to dynamically optimize Sparse Ternary Neural Networks (Sparse TNN) for real-time applications. The design adopts adaptive pruning and quantization techniques for computational complexity and power consumption with the desired accuracy. Experimental evaluation on the Xilinx ZCU102 platform achieves up to 16.46 × speedup compared to dense models at less than 1% accuracy loss and achieves state-of-the-art performance on benchmarks such as Google Net and MobileNetV2. This work holds promise for resource-constrained high-throughput applications, bringing FPGA-based deep learning closer to efficiency and scalability.
Synthesis of biomass-derived carbon quantum dots/polyaniline nanocomposite for photocatalytic degradation of brilliant green dye and bioimaging applications
Authors: Qurtulen Qurtulen , Mujahid Mohammad , Al-Hartomy Omar A , Alzahrani Ahmed Obaid M , Ahmad Asrar
Published: January 2025

Currently, highly efficient nano photocatalysts driven by visible light are being developed for organic pollutant removal and bioimaging applications. Carbon quantum dots (CQDs) have been shown to enhance the photocatalytic activity of nanocomposites. In this work, we report the surface modification of a polyaniline (PANI) photocatalyst using hydrothermally produced CQDs. The synthesized nanocomposite (CQDs/PANI) was characterized using advanced analytical techniques. These studies confirmed the presence of PANI and CQDs and demonstrated their roles in improving electron-hole pair separation and reducing the band gap of PANI. The photocatalytic activity of the CQDs/PANI (5 wt%) nanocomposite was evaluated under visible light irradiation for the degradation of Brilliant Green dye in aqueous solution. The synthesized photocatalyst achieved nearly 100% dye removal after 35 min of irradiation. The kinetics of the dye degradation was predicted using the Langmuir–Hinshelwood model, with a rate constant (kapp) of 0.0351. The study also investigated the effects of initial dye concentration, pH, and photocatalyst dosage on the photocatalytic activity of CQDs/PANI (5 wt%). The optimal conditions were 15 mg of photocatalyst per 50 ml of a 10-ppm dye solution, with a neutral pH of 7. The photocatalyst demonstrated excellent stability and reusability over four reaction cycles. The exact cell line of human breast cells used in this work is MCF-7. Additionally, the nanocomposite was evaluated for cell imaging in human breast cancer cells (MFC-7), showing excellent biocompatibility and low cytotoxicity.
Archaeological Overview of Child Burials in the Bronze and Iron Ages
Authors: Garroway Kristine Henriksen
Published: January 2025

This chapter presents an overview of infant and child burials from the Early Bronze I–Iron Age II to demonstrate that sites throughout the land of Israel show a propensity to bury infants, and at times young children, differently than the adults in their community. In doing so, it provides a broad overview of the methods—tombs, caves, jars, pits—used for burying children, as well as the grave goods found with them. The relationship between (potential) personhood and differentiated burials is explored as a reason for why children and infants are not always found alongside other members of their community. A case study of the intramural burials in Megiddo Area K concludes the chapter as a means of thinking about ways in which personhood intersected with burials.
The Unity Argument
Authors: Asarnow Samuel
Published: January 2025

This chapter provides the central argument for Reasons Last and the Reasoning View. This Unity Argument begins with the observation that there appears to be a deep conceptual unity between normative reasons and motivating reasons. How can this unity be explained? The chapter argues that attempts to understand normative reasons in terms of motivating reasons, or vice versa, lead to implausible consequences in either the philosophy of mind or moral philosophy. The way to avoid those consequences is to adopt Reasons Last, the idea that we should understand both kinds of reasons in terms of some other phenomenon. It then argues that the Reasoning View is the most plausible way to implement the Reasons Last program. We should understand both kinds of reasons in terms of the idea of the norms of good practical reasoning.
New Ethnic Communal Property Regimes
Authors: Altamirano Rayo Giorleny
Published: January 2025

This chapter articulates how the logic of state interests in Indigenous land titling extends beyond Latin America into other regions of the Global South, such as Africa and Southeast Asia. Based on secondary evidence, the chapter shows how state officials use Indigenous land titling to preserve and reproduce the state’s territorial power in Kenya and Indonesia. The chapter articulates the book’s broader theoretical contribution to literature on multiculturalism, the limitations of a rights-based framework to further Indigenous self-determination, the power of the modern state in a globalized era, the politics of implementation of formal institutions, and contemporary strategies of state building. Finally, the chapter describes how state elites use Indigenous land titling as a state building tool by erecting ethnic communal property regimes—differentiated institutional frameworks at the local level, which serve them to effectively control people in remote, resource-rich territories.
EU Law and Economics
Authors: Steinbach Armin
Published: January 2025

This book examines the design and evolution of European law from the perspective of economics. It draws on various branches of the economic sciences—including rational choice and game theory, and institutional and behavioural economics—to expand our understanding of EU law and its effects. It seeks to complement doctrinal research on EU law by generating insights that are typically ignored in discussions of legal doctrine—including why the EU Treaties are designed as they are, how the Treaties and secondary EU law should be crafted, and how EU rules should be interpreted. While legal scholars draw on a range of interpretive methods, economics furnishes an alternative set of tools for explaining core legal principles such as conferral, subsidiarity, and mutual recognition. The law considers the actions of EU institutions in terms of their competences and instruments; economics, by contrast, can shed light on underlying motive dynamics—that is, on why Union institutions behave as they do within existing legal frameworks. This book devotes attention to EU Treaties and secondary law, as well as their adjudicative interpretation. The aim of the book is not to correct or revise existing legal perspectives, but rather to offer additional descriptive and normative metrics that expand our understanding of various issues, including in particular the decision-making behaviour of EU institutions and Member States. The book vividly demonstrates the immense value of harnessing the multifarious tools and methods of economics to analyse various issues in EU law, not least in relation to current reform debates.
Centralization
Authors: Steinbach Armin
Published: January 2025

Centralization, revolving around intrajurisdictional efficiency, addresses whether public activities should be pursued at the EU level or at Member State level. The intrajurisdictional question of whether and how to centralize within the EU revolves around two core legal provisions in the EU Treaty—the principle of conferral and the principle of subsidiarity. Conferral raises the question of whether the EU allocation of competences is efficient or inefficient from an intrajurisdictional perspective. Federalism theory and the theory of system competition anchored in institutional economics offer economic answers as to whether centralization or decentralization is the optimal solution. In this regard, ‘homogeneity’ has been a term widely used by lawyers, political scientists, and economists in order to make inferences on the optimal distribution of competences between the central authority and Member States. Another question concerns whether the principle of conferral is effectively applied and respected within the existing allocation of competences in the EU, which leads to the discussion of judicial innovations such as ‘implied powers’ or effet utile. Similarly, the principle of subsidiarity can be challenged from an economic perspective using economies of scale and scope as well as cost-benefit analysis as benchmarks for the exercise of EU competences.
Non-consensual EU law
Authors: Steinbach Armin
Published: January 2025

This chapter inquires into how and why we see uneven or non-multilateral integration within the EU. The incentive structure guides EU members to engage in differentiated integration (as opposed to a unified integration speed), while the economic perspective depends on the economic method used. While rational choice focuses on cost-benefit considerations and game-theoretic considerations as the main drivers of non-consensualism, drawing from behavioural economics reveals heuristics at work when states determine their policy course that is relevant for differentiated integration. The reciprocity-based matching-reservation mechanism underpinning EU Treaty reservations does not work when states face asymmetric incentives, with asymmetry defined by diverse preferences, different implementation costs, and significant power imbalances. Yet fewer reservations and less differentiation exist under EU law compared to international law, which indicates greater homogeneity and less asymmetry among European states.
Enforcement
Authors: Steinbach Armin
Published: January 2025

Game theory is a suitable tool for studying how Member States comply with EU law as it examines the incentives for states to either cooperate or defect. The incentive structure varies depending on whether the situation involves a coordination problem without distributional conflicts or whether a prisoner’s dilemma is at stake. The Union institutional enforcement architecture generally increases members’ contributions to cooperation, which not only increases compliance ex post but also ensures an ex-ante chilling effect on defecting behaviour. Unlike international law, the enforcement structure, consisting of the EU Commission as the administrative and detective agency as well as the ECJ as the adjudicating body, is designed to overcome the second order collective action dilemma prevalent under international law.
The European Parliament
Authors: Steinbach Armin
Published: January 2025

European Parliament decisions tend to have higher agency costs compared to the national setting, due to greater limitations on the expression of public preferences. Legally, the chain of legitimacy that runs from voters through political parties to the parliament is significantly diluted. In addition, economically, parties in the European Parliament only partially fulfil their intermediate function of aggregating public preferences. The widely observed absence of a ‘European demos’ increases citizens’ agency costs, because European parliamentary decisions are not subjected to the same scrutiny as decisions at national levels. The German Constitutional Court views this as limiting the transfer of sovereign rights to the EU level, an argument that can be drawn also from the theory of fiscal federalism: in the absence of a sufficient degree of preference homogeneity, public goods should be provided at local rather than at federal level.
The European Court of Justice
Authors: Steinbach Armin
Published: January 2025

Intended to minimize agency costs through controlling EU institutions such as the Council and the Commission, the ECJ itself has furthered the ‘constitutionalization’ process through ‘innovative’ legal interpretations, driving up agency costs. This creates the risk that the bundle of collective goods offered on the supply side by EU institutions will diverge from the demand-side preferences of citizens. ‘Negative integration’ has further increased agency costs, while ‘positive integration’ entails significant transaction costs. The principal–agent perspective also invites exploration of the Court’s discretionary space, which varies depending on whether the Council makes decisions by unanimity or qualified majority.
The European Central Bank
Authors: Steinbach Armin
Published: January 2025

Economics offers a rationale for certain features of delegation to non-majoritarian institutions such as the ECB. But principal–agent theory also sheds light on the problems associated with the expansion of ECB powers in recent years without effective oversight and accountability, thus creating significant agency costs through possible misalignment with the preferences of Member States or citizens as principals. Central bank officials should seek to minimize monetary policy spillovers to policy domains over which they have no authority, while federalism theory suggests that economic policy should remain in the hands of Member States, in order to allow public policies to reflect regionally heterogeneous preferences.
European Public Goods
Authors: Steinbach Armin
Published: January 2025

This chapter explores the provision of European public goods and offers a framework for their identification and governance. While identification of European public goods draws from the insight of fiscal federalism, institutional and legal instruments exist to manage economic trade-offs and to find institutional arrangements for public-good provision, to maximize the benefits of public goods for EU members. The institutional and legal framework offers instruments and principles to effectively address this trade-off. This paper considers five levers that allow for the customization of public goods at either EU or Member States level (or both), taking into account the specific characteristics of each. These include the allocation of competences within the margins of the Treaty; the decision-making rules in the Council; the provision of public goods at the level of ‘clubs’ of member states with similar preferences organized within or outside the Treaty; a variable combination of centralization/decentralization of rule-making, financing, and delivery of public goods; and compensation or redistributive mechanisms to achieve greater alignment of preferences. One of the principal implications of the legal contribution to the discourse on European public goods is that the question of whether public goods should be provided at the national or European level may be a misguided one. The pertinent question, therefore, is how to establish institutional frameworks for the provision of public goods, with a view to optimizing the benefits of such goods for EU members. While the EU remains severely constrained in ensuring funding of European public goods, the theory of institutional and fiscal congruence offers normative guidance on optimal EU public finance.
Internal market: economic integration
Authors: Steinbach Armin
Published: January 2025

This chapter discusses how market freedoms should ensure an optimal allocation of economic resources. An efficient market is fully integrated, and the rationale of European integration then lies in efficient factor allocation and the existence of economies of scale. In line with the Court’s jurisprudence, economic inefficiencies may result from discriminatory and non-discriminatory measures that potentially restrict trade. However, the relationship between individual freedom and public policy intervention is one where efficiency concerns militate against preference heterogeneity. The Court’s wide interpretation of all potentially trade-restrictive measures to be in violation of basic freedoms must be narrowed by acknowledging leeway to account for heterogenous preferences.
Economic and monetary union
Authors: Steinbach Armin
Published: January 2025

This chapter discusses how the institutional design and legal framework of EMU can be approached through federalism theory and institutional economics. EMU raises the question of how state organization principles interact with debt dynamics and instruments to contain debt, in particular how the treatment of debt varies between federal states and union states and how this impacts budget consolidation. The analysis explores how core legal norms such as the no-bailout clause and the ban on monetary state financing can reconcile legal and economic rationales.
Helium Plasma-Driven Radiofrequency for Skin Contraction: Clinical Use, Safety Recommendations, and Results in High-Definition Body Contouring Surgery
Authors: Hoyos Alfredo E , Perez Mauricio E , Cala Laura C , Dominguez Rodrigo , Vranis Neil M , Dayan Erez
Published: January 2025

Background

For many years, liposuction has remained one of the most-performed cosmetic procedures by plastic surgeons around the world. However, determining the degree of residual skin laxity after evacuation of fat remains a challenge. Renuvion (J-Plasma, Apyx Medical, Clearwater, FL) is a radiofrequency device propelled by helium plasma that generates rapid heating at the subcutaneous layer leading to controlled skin retraction.

Objectives

The authors present the clinical results of their experience with the J-Plasma device in combination with high-definition liposculpture (HDL), while providing some safety recommendations for its use.

Methods

The authors retrospectively collected data from a cohort of patients who underwent HDL in combination with J-Plasma therapy in at least 1 body segment between January 2018 and June 2019 at Dhara Clinic (Bogota, Colombia). Also, 100 patients were randomly selected to complete a satisfaction survey of their results.

Results

The authors evaluated 174 consecutive cases: 149 females (85.6%) and 25 males (14.4%). J-Plasma was performed in addition to HDL alone in 96 cases (55.2%), whereas other aesthetic procedures were performed in addition to J-Plasma and HDL in 78 cases (44.8%). They reported 44% of patients as being “very satisfied” and 41% “partially satisfied.”

Conclusions

The helium plasma-based device, J-Plasma, has several unique features that enable surgeons to achieve adequate levels of soft-tissue contraction when used in conjunction with liposuction during High-Def body contouring surgery.

Level of Evidence: 4 (Therapeutic)
STMGraph: spatial-context-aware of transcriptomes via a dual-remasked dynamic graph attention model
Authors: Lin Lixian , Wang Haoyu , Chen Yuxiao , Wang Yuanyuan , Xu Yujie , Chen Zhenglin , Yang Yuemin , Liu Kunpeng , Ma Xiaokai
Published: January 2025

Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction. Here, we developed an STMGraph, a universal dual-view dynamic deep learning framework that combines dual-remask (MASK-REMASK) with dynamic graph attention model (DGAT) to exploit ST data outperforming pre-existing tools. The dual-remask mechanism masks the embeddings before encoding and decoding, establishing dual-decoding-view to share features mutually. DGAT leverages self-supervision to update graph linkage relationships from two distinct perspectives, thereby generating a comprehensive representation for each node. Systematic benchmarking against 10 state-of-the-art tools revealed that the STMGraph has the optimal performance with high accuracy and robustness on spatial domain clustering for the datasets of diverse ST platforms from multi- to sub-cellular resolutions. Furthermore, STMGraph aggregates ST information cross regions by dual-remask to realize the batch-effects correction implicitly, allowing for spatial domain clustering of ST multi-slices. STMGraph is platform independent and superior in spatial-context-aware to achieve microenvironmental heterogeneity detection, spatial domain clustering, batch-effects correction, and new biological discovery, and is therefore a desirable novel tool for diverse ST studies
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL
Authors: Shi Mingguang , Li Xuefeng
Published: January 2025

Despite significant advancements in single-cell representation learning, scalability and managing sparsity and dropout events continue to challenge the field as scRNA-seq datasets expand. While current computational tools struggle to maintain both efficiency and accuracy, the accurate connection of these dropout events to specific biological functions usually requires additional, complex experiments, often hampered by potential inaccuracies in cell-type annotation. To tackle these challenges, the Zero-Inflated Graph Attention Collaborative Learning (ZIGACL) method has been developed. This innovative approach combines a Zero-Inflated Negative Binomial model with a Graph Attention Network, leveraging mutual information from neighboring cells to enhance dimensionality reduction and apply dynamic adjustments to the learning process through a co-supervised deep graph clustering model. ZIGACL’s integration of denoising and topological embedding significantly improves clustering accuracy and ensures similar cells are grouped closely in the latent space. Comparative analyses across nine real scRNA-seq datasets have shown that ZIGACL significantly enhances single-cell data analysis by offering superior clustering performance and improved stability in cell representations, effectively addressing scalability and managing sparsity and dropout events, thereby advancing our understanding of cellular heterogeneity.
Integrative co-registration of elemental imaging and histopathology for enhanced spatial multimodal analysis of tissue sections through TRACE
Authors: Lu Yunrui , Han Serin , Srivastava Aruesha , Shaik Neha , Chan Matthew , Diallo Alos , Kumar Naina , Paruchuri Nishita , Deosthali Hrishikesh , Ravikumar Vismay , Cornell Kevin , Stommel Elijah , Punshon Tracy , Jackson Brian , Kolling Fred , Vahdat Linda , Vaickus Louis , Marotti Jonathan , Ho Sunita , Levy Joshua
Published: January 2025

Elemental imaging provides detailed profiling of metal bioaccumulation, offering more precision than bulk analysis by targeting specific tissue areas. However, accurately identifying comparable tissue regions from elemental maps is challenging, requiring the integration of hematoxylin and eosin (H&E) slides for effective comparison. Facilitating the streamlined co-registration of whole slide images (WSI) and elemental maps, TRACE enhances the analysis of tissue regions and elemental abundance in various pathological conditions. Through an interactive containerized web application, TRACE features real-time annotation editing, advanced statistical tools, and data export, supporting comprehensive spatial analysis. Notably, it allows for comparison of elemental abundances across annotated tissue structures and enables integration with other spatial data types through WSI co-registration.

Availability and implementation

Available on the following platforms—GitHub: jlevy44/trace_app, PyPI: trace_app, Docker: joshualevy44/trace_app, Singularity: docker://joshualevy44/trace_app.
Unraveling the elongating bovine conceptus microenvironment: identification of gene transcripts and proteins along the conceptus-maternal interface in cattle
Authors: Peterson Katheryn D , Freeman Trevor F , Poudel Shankar P , Behura Susanta K , Kakhniashvili D , Johnson Daniel L , Prado Tulio M , Strickland Lew G , Beever Jonathan E , Spencer Thomas E , Mathew Daniel J
Published: January 2025

The bovine conceptus elongates near Day 16 of development and releases interferon-tau, disrupting the endometrial luteolytic mechanism to sustain luteal P4 and pregnancy. Conceptus factors other than interferon tau modify local endometrial activities to support pregnancy; however, the microenvironment is largely uncharacterized. We utilized a bovine conceptus-endometrial culture system to elucidate the microenvironment in the form of gene transcripts and protein. Estrus synchronized heifers remained cyclic (13) or were inseminated (9) to produce Day 16 cyclic endometrium and elongating conceptuses, respectively. Conceptus sections and endometrium were then used to generate tissue cultures in 1 ml of medium: (i) no tissue (control med; n = 7), (ii) mono-cultured conceptus (conceptus; n = 9) (iii) mono-cultured endometrium (endo; n = 13), or (iv) endo-conceptus co-culture (n = 15). After 12 h, tissue gene transcripts were sequenced (RNA-Seq) and media underwent proteomic analysis (LC–MS/MS). Compared to conceptus and endo, co-cultured conceptus and endometrial tissue contained 3400 and 4575 differentially expressed genes, respectively (P ≤ 0.01). More abundantly expressed endometrial differentially expressed genes were associated with interferon signaling whereas more abundantly expressed conceptus differentially expressed genes were associated with protein homeostasis and metabolism (FDR < 0.001). When co-culture media where compared to endo media, 288 more abundant proteins were identified (P < 0.05). Biological processes related to these proteins included antigen presentation via MHC Class Ib and keratinization (FDR < 0.001). Within the mono-cultured conceptus and endometrial media, folate receptor alpha (FOLR1; P < 0.001) was identified as the most abundant secreted protein suggesting the reproductive tissues elicit a microenvironment supportive of conceptus growth involving folate metabolism.