bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of performance and statistical analysis of rigid pavement incorporating recycled aggregate concrete through the BBD methodology
Authors: S Karuppasamy , Malarvizhi Ganapathi
Published: January 2025

The incorporation of recycled concrete aggregate (RCA) in the construction of rigid pavements has attracted considerable interest due to its environmental and economic benefits. A statistical method known as Response Surface Methodology (RSM) serves as an effective tool for optimizing concrete mix designs by adjusting independent variables to achieve desired characteristics. However, there is a lack of extensive research that combines modified mix designs with statistical modeling to predict the mechanical properties of concrete. Furthermore, many existing studies fail to consider the combined impacts of various factors, including cement content, water-to-cement ratio, and fine-to-coarse aggregate ratio, on the performance of concrete mixtures. This study aims to develop and optimize concrete mixtures that incorporate RCA for rigid pavements using the Box-Behnken Design method. The main goals were to forecast water absorption, compressive strength, flexural strength, split tensile strength, and slump of fiber-reinforced concrete, as well as to identify optimal mix designs that fulfill specific strength requirements. A total of 30 mixtures were tested, varying in four factors: cement content (300, 350, and 400 kg m−3), water/cementitious ratios (0.3, 0.4, and 0.5), fine/coarse aggregate ratios (0.3, 0.4, and 0.5), and silica fume content (0%, 5%, and 10% by weight of cement). RSM was employed to create predictive equations for the mechanical properties of the concrete mixtures, revealing that cement content and silica fume ratios had a significant impact on these properties, followed by the fine-to-coarse aggregate and water-to-cementitious ratios. The correlation coefficients (R2) for all predictive models exceeded 0.95, indicating a strong relationship between the independent variables and the mechanical properties. The optimal mix identified for achieving a compressive strength greater than 30 MPa and a flexural strength exceeding 4.1 MPa consisted of 365 kg m−3 of cement.
Sustainable optimization of concrete strength properties using artificial neural networks: a focus on mechanical performance
Authors: Manan Aneel , Pu Zhang , Majdi Ali , Alattyih Wael , Elagan S K , Ahmad Jawad
Published: January 2025

In this study, a comprehensive dataset containing 358 data points was collected from the literature, focusing on the compressive strength, split tensile strength, and modulus of elasticity of concrete made with recycled concrete aggregate (RCA). An Artificial Neural Network was used machine to predict mechanical properties of RCA concrete. Furthermore, K-fold cross validation was utilized to validate the model’s reliability, and sensitivity analysis was performed to identify the most influential input parameters among the independent variables. The model demonstrated strong performance during training, achieving R2 values of 0.93 for compressive strength, 0.92 for split tensile strength, and 0.99 for modulus of elasticity with corresponding RMSE of 2.55, 3.85, and 0.37, respectively. The MAE and MAPE values during training were 0.68 and 0.03 for compressive strength, 0.71 and 0.03 for split tensile strength, and 0.08 and 0.01 for modulus of elasticity, respectively. Testing results revealed R2 values of 0.75 for compressive strength, 0.78 for split tensile strength, and 0.67 for modulus of elasticity, with RMSE values of 8.57, 5.03, and 3.83, respectively. Moreover, the sensitivity analysis indicated that the cement percentage and water-to-cement ratio were the main input parameters which significantly influence RCA concrete strength.
Li+ concentration and morphological changes at the anode and cathode interphases inside solid-state lithium metal batteries
Authors: Huang Chun , Wilson Matthew D , Cline Ben , Sivarajah Abeiram , Stolp Wiebe , Boone Matthieu N , Connolley Thomas , Leung Chu Lun Alex
Published: January 2025

Irregular Li heterostructure growth at the interphase between the solid electrolyte and anode reduces solid-state Li metal battery (SSLMB) performance, but the fundamental cause is still elusive. Measuring and imaging Li+ ion diffusion in operando inside an SSLMB using a commercially standard cell configuration are extremely challenging because the ultra-light Li element exhibits a minute signal-to-noise ratio using most x-ray-related characterization methods, and the weak x-ray signals of Li+ are buried by strong signals of other heavy transition metal elements in the cathode and battery enclosure. Here, we pioneer novel operando correlative imaging of coupling x-ray Compton scattering with computed tomography (XCS-CT), which is able to quantify the interplay between spatially resolved Li+ ion diffusion kinetics and Li0 metal structure growth at the interphases of both the anode and cathode sides inside a full-cell SSLMB using a solid polymer electrolyte (SPE) and commercially standard cell configuration during (dis)charging. We show a 61% increase in the efficiency of extracting Li+ ions from the cathode LiNi0.6Mn0.2Co0.2O2 to the anode during charging at 0.1 C compared with at 1 C due to restricted Li+ ion diffusion at the higher rate inside SSLMB. However, this led to the formation of a more irregular interfacial morphology, consisting not only of Li0 dendrites, but also sub-surface pore formation at the anode/SPE interphase. We find that surprisingly, the irregular Li0 structure initiation and growth are accelerated during the first Li stripping step, not the Li plating step, and the root cause is the onset imbalance of Li+ ion diffusion and redox reactions between the anode and cathode. These insights highlight the benefits of asymmetric charging and discharging rates as a promising solution to improving SSLMB performance with SPEs. The operando correlative XCS-CT imaging technique has the potential to study the relationship between active ion concentrations and buried morphological changes for a variety of battery chemistries.
Self-powered biomedical devices: biology, materials, and their interfaces
Authors: Zhuang Yuan , Zhang Quan , Wan Zhanxun , Geng Hao , Xue Zhongying , Cao Huiliang
Published: January 2025

Integrating biomedical electronic devices holds profound promise for advancements in healthcare and enhancing individuals’ quality of life. However, the persistent challenges associated with the traditional batteries’ limited lifespan and bulkiness hinder these devices’ long-term functionality and consistent power supply. Here, we delve into the biology and material interfaces in self-powered medical devices by summarizing the intrinsic electric demands in humans, analyzing material and biological mechanisms for electricity generation and storage, and discussing the pathways toward self-chargeable powering. As a result, the current challenges in material designs and biological integrations emerged to shape the future directions in advancing self-powered medical devices. This paper calls on the community to integrate biology and material science to develop self-powering medical devices and improve their clinical prospects.
An improved golden jackal optimization-hybrid kernel extreme learning machine approach for fault diagnosis of chillers
Authors: Wang Hong , Sheng Yingjie , Guo Yang , Chu Pan , Tian Zengrui , Yuan Boyang
Published: January 2025

In the context of the dual carbon target, reducing energy consumption and carbon emissions in the building sector is crucial. Chillers, being the primary source of energy consumption in building equipment, can significantly increase energy use if they fail. To enhance the detection rate of early chiller failures, this paper proposes an improved chiller fault diagnosis model based on the golden jackal optimization algorithm (IGJO) and the hybrid kernel extremum learning machine (HKELM). To address the slow convergence speed and local optimization issues of the original golden jackal algorithm (GJO), we introduce four strategies: improved sine chaotic mapping, the simplex method, a fusion of the golden sinusoidal formula, and Cauchy’s variant. These strategies form the IGJO algorithm, which improves convergence speed and global optimization ability. Next, the IGJO algorithm is used to optimize the hyperparameters of the HKELM for fast search and efficient chiller fault detection. Finally, we simulate the performance of the proposed model using ASHRAE RP-1043. The results show that the IGJO-HKELM model achieves a chiller fault diagnosis accuracy of 99.83%, demonstrating a clear advantage over other algorithms.
A deep reinforcement learning based metro train operation control optimization considering energy conservation and passenger comfort
Authors: Tan Qinyu , He Deqiang , Sun Zheng , Yao Zuofang , Zhou Jixu , Chen Tianxi
Published: January 2025

As an efficient mode of public transportation, urban rail transit promotes sustainable development by reducing energy consumption and improving service quality. Numerous studies have been conducted on this subject. However, many existing methods struggle to adapt to environmental changes due to the complexity of actual line conditions. Therefore, based on deep deterministic policy gradient (DDPG) and genetic algorithm (GA), a new optimization algorithm GA-DDPG is proposed in this paper. This algorithm utilizes DDPG for continuous action control of trains and employs GA to optimize the noise generation hyperparameter of DDPG, thereby enhancing the learning and adaptive capabilities of the algorithm. Firstly, a reference system is established based on expert knowledge to ensure safe train operation and guide the training of the algorithm model. Then, under the intervention of reference system, the GA-DDPG is used to optimize and adjust the train operation control strategy to achieve a balance in punctuality, energy efficiency, and comfort. Finally, simulation experiment shows that GA-DDPG achieves at least 5.2% energy savings and 51.2% passenger comfort compared to DDPG. More experiments further demonstrate that GA-DDPG possesses better adaptability and robustness than DDPG when the environment changes.
Synchronization and coordination control based on enhanced deviation coupling for multi-motor rigid connection systems
Authors: Jiang Chenlong , Fan Bo , Hong Qinghao , Dong Jiahao , Sun Lifan
Published: January 2025

The operational performances of the conventional controlled multi-motor drive systems are affected by the parameters of the motor, sudden load changes, and external disturbances. These factors may cause issues such as motor speed loss and torque imbalance, with severe cases potentially resulting in motor shaft fractures. In this paper, an enhanced deviation coupling-based synchronization and coordination control method is proposed for multi-motor rigid connection systems. The monomer and gear structure of the induction motor are modeled, respectively, and the transfer functions are given to analyze the factors that affect speed unsynchrony and torque uncoordination for the multi-motor systems. The inherent shortcomings of simple deviation coupling control are clarified, which makes it difficult to achieve the speed synchronization and torque balance of the multi-motor systems. An enhanced deviation coupling control method that simultaneously compensates for speed and torque is designed, and its stability is analyzed. Compared with the deviation coupling control method, the experimental results show that the proposed control method effectively reduces the speed synchronization errors and suppresses the torque output fluctuation. The control system has better performance of real-time and robustness.
Discovering emergent connections in quantum physics research via dynamic word embeddings
Authors: Frohnert Felix , Gu Xuemei , Krenn Mario , van Nieuwenburg Evert
Published: January 2025

As the field of quantum physics evolves, researchers naturally form subgroups focusing on specialized problems. While this encourages in-depth exploration, it can limit the exchange of ideas across structurally similar problems in different subfields. To encourage cross-talk among these different specialized areas, data-driven approaches using machine learning have recently shown promise to uncover meaningful connections between research concepts, promoting cross-disciplinary innovation. Current state-of-the-art approaches represent concepts using knowledge graphs and frame the task as a link prediction problem, where connections between concepts are explicitly modeled. In this work, we introduce a novel approach based on dynamic word embeddings for concept combination prediction. Unlike knowledge graphs, our method captures implicit relationships between concepts, can be learned in a fully unsupervised manner, and encodes a broader spectrum of information. We demonstrate that this representation enables accurate predictions about the co-occurrence of concepts within research abstracts over time. To validate the effectiveness of our approach, we provide a comprehensive benchmark against existing methods and offer insights into the interpretability of these embeddings, particularly in the context of quantum physics research. Our findings suggest that this representation offers a more flexible and informative way of modeling conceptual relationships in scientific literature.
Expert perspectives on living with water (meebewegen) as climate adaptation in the Netherlands
Authors: Kraan Caroline M , Haasnoot Marjolijn , Mach Katharine J
Published: January 2025

In many places around the world, flood defenses—structures such as dams, levees, and dikes—have allowed societies to grow and thrive near bodies of water. However, adapting to intensifying climate change may require an alternative or additional flood management strategy for living with water, motivated by both long-term flood risk reduction and other societal goals. Based on 43 interviews with climate adaptation experts in the Netherlands, we evaluate perspectives on living with water—or meebewegen in Dutch—including the degree to which living-with-water measures are expected to be implemented, their likely role as part of the Netherlands’ future flood risk management, and enablers and barriers. We find widespread agreement that many living-with-water measures will be implemented at large to very large scale, but find the most disagreement about the subset of living-with-water measures focused on retreat. We develop a typology that organizes the diverse set of perspectives on the future role of living with water into four quadrants, based on whether experts expect flood risk management to depend more on engineering flood defenses or living-with-water strategies, and on whether living-with-water strategies are viewed as socio-politically favorable or unfavorable. We identify spatial constraints, political leadership, living-with-water narratives, and misaligned incentives as factors shaping the barriers to and opportunities for living with water. Our research shows that, despite wildly differing perspectives about flood adaptation through living-with-water measures, points of agreement exist about limits of current adaptation strategies and some need for living with water strategies. These could be harnessed to enhance living with water where this new paradigm of water management emerges.
Inexact Gauss-Newton methods with matrix approximation by sampling for nonlinear least-squares and systems
Authors: Bellavia Stefania , Malaspina Greta , Morini Benedetta
Published: January 2025

We develop and analyze stochastic inexact Gauss-Newton methods for nonlinear least-squares problems and for nonlinear systems of equations. Random models are formed using suitable sampling strategies for the matrices involved in the deterministic models. The analysis of the expected number of iterations needed in the worst case to achieve a desired level of accuracy in the first-order optimality condition provides guidelines for applying sampling and enforcing, with a fixed probability, a suitable accuracy in the random approximations. Results of the numerical validation of the algorithms are presented.
QQMR: A structure preserving quaternion quasi-minimal residual method
Authors: Li Tao , Wang Qing-Wen
Published: January 2025

The quaternion biconjugate gradient (QBiCG) method, as a novel variant of quaternion Lanczos-type methods for solving the non-Hermitian quaternion linear systems, does not yield a minimization property. This means that the method possesses a rather irregular convergence behavior, which leads to numerical instability. In this paper, we propose a new structure-preserving quaternion quasi-minimal residual method based on the quaternion biconjugate orthonormalization procedure with coupled two-term recurrences, which overcomes the drawback of QBiCG. The computational cost and storage required by the proposed method are much less than the traditional QMR iterations for the real representation of quaternion linear systems. The convergence properties of which are also established. Finally, we report the numerical results to show the robustness and effectiveness of the proposed method compared with QBiCG.
Limit point and limit circle trichotomy for Sturm-Liouville problems with complex potentials
Authors: Leben Florian , Leguizamón Edison , Trunk Carsten , Winklmeier Monika
Published: January 2025

The limit point and limit circle classification of real Sturm-Liouville problems by H. Weyl more than 100 years ago was extended by A.R. Sims around 60 years ago to the case when the coefficients are complex. Here, the main result is a collection of various criteria which allow us to decide to which class of Sims’ scheme a given Sturm-Liouville problem with complex coefficients belongs. This is subsequently applied to a second order differential equation defined on a ray in

C

\mathbb C

which is motivated by the recent intensive research connected with

P

T

\mathcal P \mathcal T

-symmetric Hamiltonians.
TgGloL is an atypical glyoxalase/VOC domain-containing apicoplast protein that is important for the growth of Toxoplasma
Authors: Sanchez Syrian G. , Pouzet Esther , Guimbaud Loïc , Graindorge Arnault , Berry Laurence , Besteiro Sébastien
Published: January 2025

Glycolysis is a conserved metabolic pathway that converts glucose into pyruvate in the cytosol, producing ATP and NADH. In Toxoplasma gondii and several other apicomplexan parasites, some glycolytic enzymes have isoforms located in their plastid (called the apicoplast). In this organelle, glycolytic intermediates like glyceraldehyde 3-phosphate (GAP) and dihydroxyacetone phosphate (DHAP) are imported from the cytosol and further metabolized, providing ATP, reducing power, and precursors for anabolic pathways such as isoprenoid synthesis. However, GAP and DHAP can spontaneously convert into methylglyoxal, a toxic by-product detoxified by the glyoxalase system, typically involving Glyoxalase-1 (Glo-1) and Glyoxalase-2 (Glo-2). In T. gondii, we identified an atypical protein, TgGloL, containing a Glo-1-like motif but with limited homology to typical Glo enzymes. TgGloL localizes to the apicoplast, and its conditional knockdown impairs parasite growth, indicating its importance. While a specific and direct role for TgGloL in methylglyoxal detoxification within the apicoplast remains unclear, it is crucial for maintaining organelle homeostasis and for overall parasite fitness.
The dark side of fluorescent protein tagging—the impact of protein tags on biomolecular condensation
Authors: Fatti Edoardo , Khawaja Sarah , Weis Karsten
Published: January 2025

Biomolecular condensation has emerged as an important mechanism to control various cellular processes through the formation of membraneless organelles. Fluorescent protein tags have been extensively used to study the formation and the properties of condensates in vitro and in vivo, but there is evidence that tags may perturb the condensation properties of proteins. In this study, we carefully assess the effects of protein tags on the yeast DEAD-box ATPase Dhh1, a central regulator of processing bodies (P-bodies), which are biomolecular condensates involved in mRNA metabolism. We show that fluorescent tags as well as a polyhistidine tag greatly affect Dhh1 condensation in vitro and lead to condensates with different dynamic properties. Tagging of Dhh1 with various fluorescent proteins in vivo alters the number of P-bodies upon glucose starvation and some tags even show constitutive P-bodies in nonstressed cells. These data raise concerns about the accuracy of tagged protein condensation experiments, highlighting the need for caution when interpreting the results.
Accompanying Economic Transformation
Authors: Gentilini Ugo
Published: January 2025

Over history, cash transfers emerge as an accompanying ingredient to sustain economic evolution and mitigate its negative effects. The chapter presents three different pathways for such a role. First, the analysis begins by discussing cash transfers within capitalist modes of economic organization. This includes interpreting cash transfers as maintaining labor reserves, that is, how cash helped facilitate workers’ mobility towards industrial areas, support them in those locations during economic downturns, and enhance their readiness to work when labor market conditions improved. Second, cash transfers have also played an important role in shifts in economic models. The chapter provides a brief discussion of social protection practices in feudal systems, as well as locating cash transfers with socialist and communist experiences. Finally, it examines historical examples of economic inclusion. These entail cases whereby states leveraged systems of provisions and aligned them with “productivist” principles of industrial policy. In large part, the initiatives couldn’t adapt to the sweeping forces of urbanization, economic change, and conflict, but their approach and practical insights spread in different countries.
Digitized Biographies
Authors: Albrecht Eduardo
Published: January 2025

This chapter explores the harvesting of data associated to our social interactions. The chapter starts by scrutinizing historical initiatives such as the Third Department in Imperial Russia, the Dang’an of Maoist China, and early attempts by the US government to monitor citizens following the communist Red Scares in the nation. Next, it looks at how the automation of data collection techniques allowed for building on these traditions and led to the development of numerous programs today, notably the NSA’s ThinThread, the Chinese Social Credit System, and India’s Aadhaar. The chapter concludes with a discussion of the implications of these wide-ranging social monitoring programs on civil rights, noting that through such approaches to governance, persons are reduced to a kind of prosopographic file managed by the state.
India
Authors: Albrecht Eduardo
Published: January 2025

This chapter features interviews with Anushka Jain of the Digital Futures Lab and Shweta Mohandas from the Centre for Internet and Society. Both organizations are based in India and investigate issues related to technology and society, algorithmic decision-making, digital rights, and online privacy. Jain discusses the ubiquity of facial recognition projects in India and highlights the potential of the Aadhaar digital identity system to violate the rights of citizens, particularly the most vulnerable. Mohandas points out the trade-offs between maintaining national security and protecting privacy rights, discusses the potential misuse of data by foreign and private actors, and highlights the advances and lacunae of the recently passed Personal Data Protection Act. Both Mohandas and Jain agree that the use of geolocation trackers for municipal workers is open to abuse and presents a serious violation of civil rights that is likely to expand if left unchecked.
Democracy, Laws, and Policy in Shaping Abortion Views
Authors: Adamczyk Amy
Published: January 2025

This chapter examines the government’s role in shaping abortion attitudes. To understand the abortion debate—both liberal laws that allow for abortion on demand and conservative attitudes that strongly discourage abortion—democracy and the ideas it stimulates are key. The chapter explains how generic democratic values can affect abortion views. The specific role of democracy in shaping policies is also discussed. Drawing on an analysis of over 800 newspaper articles from 41 countries, I show that news articles in more democratic nations are more likely to discuss abortion from a range of different perspectives. I unpack differences between the United States and China with regard to how democracy informs public opinion and abortion-related policies. Finally, I explain how the media both influences democratic processes and encourages the exchange of information that can further aid tolerance.
The Ethics of Agency
Authors: Smith Michael
Published: January 2025

Abstract

The chapter begins with a brief history of moral philosophy in the twentieth and twenty-first centuries. The history focuses on the methodological and substantive contributions of Moore, Ayer, Rawls, and Hare, and shows how their contributions have by and large set the agenda for present-day normative ethics. Problems with that agenda, especially with Rawls’s methods of reflective equilibrium and avoidance, are presented, and an alternative agenda is suggested. The alternative begins with a defence of moral rationalism and then proceeds, via a constitutivist theory of reasons for action, to a derivation of a novel ethics of agency that consists of two moral principles—Help, but Don’t interfere—and a non-moral principle—Do what you want—that must be weighed against each other. Some novel philosophical problems raised by the ethics of agency are identified for further consideration.
Noise
Authors: Malcolm Rosalind , Pointing John
Published: January 2025

Noise pollution became conceptualized as a problem in the 1960s and 1970s, partly in response to the growth in public awareness about environmental issues. Individuals’ expectations have been raised about what constitutes a noise nuisance and when controls are needed. Recent EU legislation is intended to raise the priority of noise in relation to other environmental issues such as air and water pollution. Noise tends to be perceived differently from other forms of pollution because it has no lasting effects on the physical environment. It may interfere with the victim’s use of his property and may even diminish its value, but noise does not result in physical damage, except in the most extreme circumstances such as when accompanied by explosions. Vibration accompanying noise is included in the statutory definition: in section 79(7) of the Environmental Protection Act 1990 (EPA 1990). Such vibration may cause physical damage, though usually the loss will be one of amenity.
Insects
Authors: Malcolm Rosalind , Pointing John
Published: January 2025

A new statutory nuisance in relation to the impact of insects came into effect in England and Wales from 2006 as a result of an amendment made by the Clean Neighbourhoods and Environment Act 2005. Under section 79(1)(fa) of the Environmental Protection Act 1990 (EPA 1990), this makes insects which emanate from industrial, trade, or business premises a statutory nuisance if they are prejudicial to health or a nuisance. In Northern Ireland, the Clean Neighbourhoods and Environment Act (Northern Ireland) 2011 received Royal Assent on 4 May 2011, though it has still to come into effect. Section 63(1)(g) of that Act will make the statutory nuisance provisions in respect of insects consistent with the position in England and Wales. In Scotland, the provisions are broader than in England and Wales and section 79(1)(faa) of the EPA 1990 extends the coverage to all premises.
Inferring the genetic relationships between unsupervised deep learning–derived imaging phenotypes and glioblastoma through multi-omics approaches
Authors: Ye Liguo , Ye Cheng , Li Pengtao , Wang Yu , Ma Wenbin
Published: January 2025

This study aimed to investigate the genetic association between glioblastoma (GBM) and unsupervised deep learning–derived imaging phenotypes (UDIPs). We employed a combination of genome-wide association study (GWAS) data, single-nucleus RNA sequencing (snRNA-seq), and scPagwas (pathway-based polygenic regression framework) methods to explore the genetic links between UDIPs and GBM. Two-sample Mendelian randomization analyses were conducted to identify causal relationships between UDIPs and GBM. Colocalization analysis was performed to validate genetic associations, while scPagwas analysis was used to evaluate the relevance of key UDIPs to GBM at the cellular level. Among 512 UDIPs tested, 23 were found to have significant causal associations with GBM. Notably, UDIPs such as T1-33 (OR = 1.007, 95% CI = 1.001 to 1.012, P = .022), T1-34 (OR = 1.012, 95% CI = 1.001–1.023, P = .028), and T1-96 (OR = 1.009, 95% CI = 1.001–1.019, P = .046) were found to have a genetic association with GBM. Furthermore, T1-34 and T1-96 were significantly associated with GBM recurrence, with P-values < .0001 and P < .001, respectively. In addition, scPagwas analysis revealed that T1-33, T1-34, and T1-96 are distinctively linked to different GBM subtypes, with T1-33 showing strong associations with the neural progenitor-like subtype (NPC2), T1-34 with mesenchymal (MES2) and neural progenitor (NPC1) cells, and T1-96 with the NPC2 subtype. T1-33, T1-34, and T1-96 hold significant potential for predicting tumor recurrence and aiding in the development of personalized GBM treatment strategies.
Large-Scale Multiple Testing of Composite Null Hypotheses Under Heteroskedasticity
Authors: Gang B , Banerjee T
Published: January 2025

Heteroskedasticity poses several methodological challenges in designing valid and powerful procedures for simultaneous testing of composite null hypotheses. In particular, the conventional practice of standardizing or re-scaling heteroskedastic test statistics in this setting may severely affect the power of the underlying multiple testing procedure. Additionally, when the inferential parameter of interest is correlated with the variance of the test statistic, methods that ignore this dependence may fail to control the Type I error at the desired level. We propose a new heteroskedasticity adjusted multiple testing procedure that avoids data reduction by standardization, and directly incorporates the side information from the variances into the testing procedure. Our approach relies on an improved nonparametric empirical Bayes deconvolution estimator that offers a practical strategy for capturing the dependence between the inferential parameter of interest and the variance of the test statistic. We develop theory to show that the proposed procedure is asymptotically valid and optimal for FDR control. Simulation results demonstrate that our method outperforms existing procedures with substantial power gain across many settings at the same FDR level. The method is illustrated on an application involving the detection of engaged users on a mobile game app.
Exploratory analysis of biological age measures in a remyelination clinical trial
Authors: McMurran Christopher E , de Meo Ermelinda , Cunniffe Nick G , Brown J William L , Prados Ferran , Kanber Baris , Cole James H , Coles Alasdair J , Hägg Sara , Chard Declan T
Published: January 2025

Enhancing CNS myelin repair (remyelination) is a promising strategy to prevent neurodegeneration and associated progressive disability in multiple sclerosis. Remyelination becomes inefficient with older chronological age, but the relationship between measures of biological age and remyelination has not been previously described in a clinical cohort. Here, we investigated two measures of biological age amongst participants of the Cambridge Centre for Myelin Repair One trial of bexarotene: MRI brain age (BAMRI) and a blood-based biological age (BABlood). In people with radiologically stable multiple sclerosis (n = 44 of 49 total participants), we found that treatment with bexarotene, along with promoting remyelination, was associated with significant decrease in MRI brain age [−1.98 years, 95% confidence interval (CI) [−3.75, −0.21 years] versus placebo over 6 months, P = 0.034]. Whilst BAMRI increased as expected during the trial in the placebo group (+0.92 years, CI [−0.41, 2.26]), the brain MRIs of participants treated with bexarotene appeared on average 11 months younger at the end compared to the start of the trial (−0.93 years, CI [−2.02, 0.17]). The effect of bexarotene on BAMRI was associated with its remyelinating activity in cortical grey matter lesions (β = 0.25% units (pu)/year, CI [0.03, 0.46], P = 0.023) and brainstem lesions (β = 0.24 pu/year, CI [0.09, 0.39], P = 0.003). We also observed some regional trends that the remyelinating response to bexarotene was linked with measures of biological age at baseline. For example, after adjustment for chronological age, remyelination of brainstem lesions assessed by magnetization transfer ratio was reduced by 0.06 pu for each year increase in BAMRI (CI [0.00, 0.13], P = 0.058) and 0.02 pu for each year increase in BABlood (CI [−0.01, 0.05], P = 0.17). This is, to the best of our knowledge, the first demonstration that MRI brain age can be therapeutically modulated by a drug in people with a neurological disorder. Overall, these findings highlight that beyond chronological age, biological age may also influence the potential for repair and should be considered when developing treatments for multiple sclerosis.
Investigation of glucose oxidation mechanism on the graphene nanosheet decorated by Pt, Au, and Cu metals: a DFT study
Authors: Wang Yingying , Li Hongxia
Published: January 2025

The investigation of glucose oxidation in alkaline solutions has been conducted using DFT computations on graphene nanosheets decorated with single metal atoms of Pt, Au, and Cu (denoted as PtG, AuG, and CuG). The study reveals that all 3 catalysts are effective in catalyzing the oxidation of glucose to gluconic acid. Among these models, PtG emerges as the most favorable catalyst with the rate-determining step energy barrier of only 0.45 eV.
Synthesis and optical properties of m-phenyl carbazole derivatives showing aggregation-induced emission and thermally activated delayed fluorescence
Authors: Nakagawa Yuta , Miki Kensyo , Yamaguchi Yoshihiro
Published: January 2025

This study reports the synthesis and optical properties of four compounds with m-phenyl carbazole derivatives at their side chains. The devised compounds exhibited both aggregation-induced emission and thermally activated delayed fluorescence. By introducing a carbazole unit at the m-position, we provide a new guideline for molecular design.
Aerobic oxidation of glucosamine-HCl over AuPd-supported catalyst in a liquid-flow system
Authors: Sotani Rin , Nishimura Shun
Published: January 2025

Both a batch and a continuous-flow reactor system were investigated in the oxidation reaction of glucosamine hydrochloride (GlcN-HCl) into glucosaminic acid. In the batch reactor system, AuPd-supported catalysts using basic supports such as MgO and hydrotalcite (HT) effectively catalyzed the target oxidation reaction. Although, in the liquid-flow reaction system, these catalysts showed a gradual decrease in their activity due to exposure to the acidic nature of the GlcN-HCl product, the addition of NaOH to maintain the basic reaction condition allowed the yield to remain stable over a longer reaction time, with approximately 80% yield for 9 h of reaction in both the AuPd/MgO and AuPd/HT cases.
Robotic acquisition of echocardiographic images, a proof of concept and safety study
Authors: Windram J , Ahmed A , Becher H , Foster B , Noega M , Almajed N , Boulanger P , Punithakumar K
Published: January 2025

Background/Introduction

Though echocardiography remains the most utilized imaging modality in daily cardiology practice, a major challenge remains the physical strain and injury that can be induced in the echocardiographer.

Purpose

We developed a prototype robotic arm assisted echocardiography system which incorporates robotics with traditional echocardiography. We assessed the safety and feasibility of the system in 31 volunteers.

Methods

An ultrasound transducer was mounted upon a robotic arm (UR10 robotic arm, Universal Robots, Odense, Denmark). The transducer was connected to a Philips EPIQ 7C system. The position of the transducer was modified by the echocardiographer who could manipulate a remote stick controller in their hand whilst orientating its position in relation to the real-time images acquired upon the monitor of the echocardiography scanner. This enabled the sonographer to optimize the images and to initiate recordings of parasternal and apical 2D and 3D images. The maximal force on the robot arm was set to 5 Newtons (N) which was deemed to be both safe and to allow for adequate image quality. The force induced by the probe upon the chest wall was measured continuously. Acquired images were assessed for quality ranging from excellent to poor.

Results

17 males and 14 females were scanned. The number of images acquired varied from a minimum of 16 and a maximum of 61. The mean time taken to scan an individual was 17.4 minutes with a standard deviation (SD) of 9.9 minutes. This equated to an average of 1.9 images per minute (SD 0.7). No statistical difference was noted between the number of images per minute obtained between male and female participants (mean (+/- SD) for males was 2.1(0.8) and for females 1.8 (0.7) P=0.27). The average force that was applied by the probe was 3.95+/-0.83 Newtons. None of the volunteers reported significant discomfort in the acquisition of the images. Of the 3D images obtained 5 of the participants had poor apical 3D datasets and 3 had poor parasternal datasets but the remaining images acquired were adequate for diagnostic quality.

Conclusion(s)

Our study demonstrates the feasibility and safety of acquiring 2D and 3D images using a prototype robotic arm assisted echocardiography system. Despite using a low force to the chest wall, the majority of images obtained were of diagnostic quality. Future studies will assess the techniques validity within a routine patient population compared to standard imaging performed by an experienced sonographer.

Set up of robot-arm echocardioghy
Do artificial intelligence methods in echocardiography know when closer human scrutiny is needed?
Authors: Ng T , Hannan S H , Julea M , Singh A , Zetani M , Vimalesvaran K , Tawil M , Rana B , Demetrescu C , Ghosh A , Sehmi J , Bhattacharyya S , Stowell C , Shun-Shin M J , Francis D P
Published: January 2025

Background

Artificial intelligence (AI) measurement has the potential to transform cardiac imaging, but what if it makes a mistake? Can AI also highlight when it is most likely to have mismeasured and can experts improve these measurements? As readers become increasingly reliant on automated measures for echocardiographic analysis, we need confidence that the software will measure accurately, and also flag where human oversight is needed.

Purpose

To develop and test an open, scientific, machine-learning method of validly judging the level of certainty in an AI measurement, to enable human oversight to focus on the measurements most likely to be incorrect.

Methods

The heatmap altitude (MHA) at the measurement point is widely used as an automatic index of predicted reliability of an AI measurement. This is derived from the raw neural network output to give a level of confidence between 0 and 1 in each measurement that the AI makes. We test this not only against the AI’s difference from the expert consensus, but also, through the use of multiple experts per case, against individual experts difference from the consensus using the Unity UK Echocardiography AI collaboratives dataset of 200 parasternal long-axis images.

Each image was labelled with key points for the aortic annulus, sinus and sinotubular junction, and proximal ascending aorta dimensions by 10 experts. The mean expert consensus measure was obtained, and then the median deviation of the AI and other experts calculated.

Results

The heatmap altitude was skewed with median 0.822, IQR 0.793 to 0.841, 10th to 90th percentile 0.734 to 0.852. Images were grouped by decile, from the 20 images with lowest confidence to the 20 with the highest (Figure 1). Both the AI and expert error (deviation from expert consensus) was greatest in the lowest confidence decile and progressively lower in each decile of greater confidence (p<0.001 for trend).

In the better 9 deciles, the AI error was smaller than the human error (p<0.001); in the worst decile it was equivalent (p =NS).

Conclusion

The fully automated and open-source MHA value usefully quantifies the reliability of an AI measurement. This could be used to target human oversight where it is most needed, but care must be taken as experts may find the images similarly difficult.
Artificial intelligence for automatic echocardiography image view detection and left ventricle segmentation and ejection fraction prediction
Authors: Morales-Galan A , Lopez-Gutierrez P , Garrido-Oliver J , Dux-Santoy L , Majul H , Rivas Catoni L , Martin Grieve S , Bragulat-Arevalo M , Ferrer-Cornet M , Catala-Santarrufina A , Teixido-Tura G , Galian-Gay L , Ferreira-Gonzalez I , Rodriguez-Palomares J , Guala A
Published: January 2025

Background

Left-ventricular (LV) border segmentation is key to assess LV size and function. Current assessment has relatively large inter-observer variability, possibly impacting patients care. Artificial intelligence (AI) may permit faster and more reproducible assessment, possibly suitable to be used by non-experts.

Purpose

To train and test AI algorithms for (i) the identification of views, (ii) the segmentation of the LV in 2, 3 and 4-chamber views, and (iii) the computation of LV ejection fraction (EF).

Methods

Fifteen thousand echocardiography studies acquired in the Vall d’Hebron University Hospital (VH) for patients care were retrieved and anonymized. LV wall was identified via commercial clinical software in 619 videos with 2-, 3- and 4-chamber views (14082 frames) and 3 masks were created: LV cavity (within endocardial border), overall LV (within epicardial border) and LV wall. Annotated frames were split into independent training (465 videos) and testing (154) sets and performances were evaluated in terms of DICE score. End-diastolic and end-systolic LV volumes of 4-chamber views were identified and used to compute LV EF, which was compared with clinical reports in 488 patients. An external validation on CAMUS dataset was performed.

Results

A total of 6831 videos from 488 VH subjects were available for this analysis (Table 1). AI model identified image views with high accuracy (93%). AI performance on the segmentation of the LV cavity, overall LV and LV wall were satisfactory in 2- (0,86[0,79;0,90], 0,91[0,86;0,93], 0,79[0,74;0,83]), 3- (0,88[0,84;0,91], 0,91[0,90;0,93], 0,81[0,77;0,83]) and 4-chamber (0,90[0,86;0,93], 0,92[0,88;0,94], 0,82[0,79;0,85]) views. Segmentation performances were similar between sexes but were lower in case of atrial fibrillation and in images with low quality. In an external validation in 500 CAMUS patients performances were satisfactory, with DICE score of 0,91[0,87;0,94] and 0,80[0,73;0,84] for whole LV and LV cavity in 2 and 4-chamber views, respectively.

In VH data EF predictions were in line with expected inter-observer reproducibility, with a good linear association (R=0.39, p<0.001) but remarkable underestimation (mean error = 12%). Models performed similarly in the external validation set, with a good linear association (R=0.31, p<0.001) and minimal underestimation (mean error = 2.2%).

Conclusions

AI models can identify echocardiography views, segment the LV in 2, 3 and 4-chamber views and use the segmentation to quantify EF. Care should be taken to avoid biases in AI performances, particularly in case of atrial fibrillation and limited image quality.

Demographic and clinical information
Effective left ventricular ejection fraction by three-dimensional echocardiography is associated with survival and hospitalizations in ventricular secondary mitral regurgitation
Authors: Delcea C , Tomaselli M , Oliverio G , Gavazzoni M , Heilbron F , Pece C , Clement A M , Buta S A , Radu N , Hadareanu D , Mihaila-Baldea S , Badila E , Dan G A , Badano L , Muraru D
Published: January 2025

Introduction

Left ventricular (LV) systolic function is crucial for determining prognosis of patients with ventricular secondary mitral regurgitation (VsMR). However, both the LV ejection fraction (LVEF) and global longitudinal strain are influenced by the volume overload associated with MR. Effective LVEF (eLVEF) is a novel parameter that accounts for mitral regurgitant volumes and overcomes the load-dependency of LVEF.

Pupose

We sought to explore the association of eLVEF measured by three-dimensional (3D) echocardiography with mortality and heart failure (HF) hospitalizations in patients with VsMR.

Methods

We enrolled 212 VsMR patients (mean age 70±13 years, 26% female) from January 2015 to March 2022. 3D-eLVEF was calculated by dividing forward LV stroke volume (SV), measured by 2D-Doppler echocardiography by the LV end-diastolic volume measured by 3DE. The primary outcomes were all-cause mortality and HF hospitalization.

Results

During a mean follow-up of 22±11 months, 22% VsMR patients died and 28% had HF hospitalizations.

In multivariable Cox regression, 3D-eLVEF was independently inversely associated with all-cause mortality (HR 0.93, 95%CI 0.89-0.97, p<0.001) and HF hospitalization (HR 0.95, 95%CI 0.92 – 0.99, p<0.001), outperforming 3D-LVEF and VsMR severity parameters.

In ROC analysis, cut-off values associated with all-cause mortality were 3D-eLVEF≤24% (77% sensitivity, 61% specificity, AUC 0.74, 95%CI 0.67-0.79, p<0.0001), 3D-LVEF≤40% (87% sensitivity, 44% specificity, AUC 0.69, 95%CI 0.62-0.75, p<0.0001).

Kaplan-Meier analysis demonstrated increasing event rate with 3D-eLVEF≤24% independent of LVEF higher or lower than 40% (log-rank, p<0.001). Patients with 3D-eLVEF≤24% and 3D-LVEF >40% had a worse prognosis than patients with 3D-LVEF≤40% and 3D-eLVEF>24% (log-rank, p<0.001). Those with 3D-eLVEF≤24% had the most HF hospitalizations, irrespective of 3D-LVEF (log-rank, p=0.002)(Figure 1).

Conclusions

In patients with VsMR, 3D-eLVEF was independently associated with all-cause mortality and HF hospitalization. 3D-eLVEF≤24% had a stronger association with both outcomes compared to 3D-LVEF≤40% and refined the risk stratification.