bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analyzing third-party data leaks on online pharmacy websites
Authors: Rauti Sampsa , Carlsson Robin , Mickelsson Sini , Mäkilä Tuomas , Heino Timi , Pirjatanniemi Elina , Leppänen Ville 
Published: February 2024

Abstract
Purpose
With digitalization, using essential digital services such as online services has become increasingly common. These services process sensitive health related data, such as customers’ prescription medicine orders, which makes ensuring stringent data privacy crucial. The current study examines third parties such as analytics services on Finnish pharmacy websites and investigates the nature and contents of data leaks on these websites.

Methods
We perform an extensive network traffic analysis to reveal data leaks among 163 Finnish online pharmacies. We also study a set of privacy policies of these online pharmacies, and provide a legal analysis regarding the interpretation of the concept of data concerning health in the context of online pharmacies.

Results
Our findings reveal serious data leaks among Finnish online pharmacies. We found 145 pharmacies had third-party services on their websites and only 18 did not. Out of all 163 online pharmacies, 57 (35.0 %) leaked a specific prescription medicine name connected with identifying personal data on the customer. We argue that the information concerning purchases on the prescription medicines should be interpreted as data concerning health to ensure efficient protection of customers’ right to data protection and privacy.

Conclusions
We hope that these concerning results will serve as a wake-up call for the developers and maintainers of online pharmacies and other web services processing sensitive data. Any third-party services incorporated into websites processing sensitive personal data should be closely inspected in terms of data leaks, or preferably not used at all.
Reducing echocardiographic examination time through routine use of fully automated software: a comparative study of measurement and report creation time
Authors: Hirata Yukina , Nomura Yuka , Saijo Yoshihito , Sata Masataka , Kusunose Kenya 
Published: February 2024

Abstract
Background
Manual interpretation of echocardiographic data is time-consuming and operator-dependent. With the advent of artificial intelligence (AI), there is a growing interest in its potential to streamline echocardiographic interpretation and reduce variability. This study aimed to compare the time taken for measurements by AI to that by human experts after converting the acquired dynamic images into DICOM data.

Methods
Twenty-three consecutive patients were examined by a single operator, with varying image quality and different medical conditions. Echocardiographic parameters were independently evaluated by human expert using the manual method and the fully automated US2.ai software. The automated processes facilitated by the US2.ai software encompass real-time processing of 2D and Doppler data, measurement of clinically important variables (such as LV function and geometry), automated parameter assessment, and report generation with findings and comments aligned with guidelines. We assessed the duration required for echocardiographic measurements and report creation.

Results
The AI significantly reduced the measurement time compared to the manual method (159 ± 66 vs. 325 ± 94 s, p < 0.01). In the report creation step, AI was also significantly faster compared to the manual method (71 ± 39 vs. 429 ± 128 s, p < 0.01). The incorporation of AI into echocardiographic analysis led to a 70% reduction in measurement and report creation time compared to manual methods. In cases with fair or poor image quality, AI required more corrections and extended measurement time than in cases of good image quality. Report creation time was longer in cases with increased report complexity due to human confirmation of AI-generated findings.

Conclusions
This fully automated software has the potential to serve as an efficient tool for echocardiographic analysis, offering results that enhance clinical workflow by providing rapid, zero-click reports, thereby adding significant value.
Design and Parameter Optimization of Zero Position Code Considering Diffraction Based on Deep Learning Generative Adversarial Networks
Authors: Wang Shengtong , Luo Linbin , Li Xinghui 
Published: February 2024

AbstractAbsolute measurement has consistently been the primary focus in the development of precision linear and angular displacement measurements. The scheme design of binary zero position codes is an important factor for absolute measurement. Designing and optimizing high-bit zero position codes with over 100 bits face considerable challenges. Simultaneously, the working parameters of zero position codes [unit code width (b), distance (d), and yaw angle (α)] remarkably affect their post-installation performance, particularly in absolute positioning and limit code application in multi-degree-of-freedom measurement schemes. This study addresses these challenges by proposing a design method for zero position codes that considers diffraction based on generative adversarial networks and aims to explore a design with increased efficiency and accuracy as well as optimization for high-bit zero position codes. Additionally, the tolerance range of zero positioning performance for each working parameter is examined. By leveraging the adversarial network structure, this study generates the optimization of a 150-bit code and processes the tests of the zero position code by using simulation results. The following working parameter ranges for code design are recommended on the basis of theoretical and experimental results: b greater than 10 μm, d and α within 1000 μm and 3490 μrad, and avoidance of intervals with sharp changes in the full width at half maximum. The proposed code design and parameter optimization lay a solid foundation for research and engineering applications in absolute measurement field and have considerable potential for generalization and wide applicability.
How Socio-economic Inequalities Cluster People with Diabetes in Malaysia: Geographic Evaluation of Area Disparities Using a Non-parameterized Unsupervised Learning Method
Authors: Ganasegeran Kurubaran , Abdul Manaf Mohd Rizal , Safian Nazarudin , Waller Lance A. , Mustapha Feisul Idzwan , Abdul Maulud Khairul Nizam , Mohd Rizal Muhammad Faid 
Published: February 2024

AbstractAccurate assessments of epidemiological associations between health outcomes and routinely observed proximal and distal determinants of health are fundamental for the execution of effective public health interventions and policies. Methods to couple big public health data with modern statistical techniques offer greater granularity for describing and understanding data quality, disease distributions, and potential predictive connections between population-level indicators with areal-based health outcomes. This study applied clustering techniques to explore patterns of diabetes burden correlated with local socio-economic inequalities in Malaysia, with a goal of better understanding the factors influencing the collation of these clusters. Through multi-modal secondary data sources, district-wise diabetes crude rates from 271,553 individuals with diabetes sampled from 914 primary care clinics throughout Malaysia were computed. Unsupervised machine learning methods using hierarchical clustering to a set of 144 administrative districts was applied. Differences in characteristics of the areas were evaluated using multivariate non-parametric test statistics. Five statistically significant clusters were identified, each reflecting different levels of diabetes burden at the local level, each with contrasting patterns observed under the influence of population-level characteristics. The hierarchical clustering analysis that grouped local diabetes areas with varying socio-economic, demographic, and geographic characteristics offer opportunities to local public health to implement targeted interventions in an attempt to control the local diabetes burden.
Assessment on natural ventilation and pollutant dispersion around sunken squares by transient simulation
Authors: Hu Mengjuan , Zhong Jiading , Chu Yujie , Liu Jianlin 
Published: February 2024

AbstractSunken square is a semi-open public space that has been gaining popularity in urban planning and designs. Its semi-open design is beneficial to ventilation of the connected underground spaces, but it is also subject to potential exposure to ground-level traffic pollutants. To evaluate the semi-open design’s influence on the balance between underground ventilation efficiency and the pollutant exposure, this study uses large eddy simulation (LES) to simulate turbulent wind flow characteristics and pollutant dispersion in a typical sunken square. The sunken square is connected to two indoor spaces with single-sided opening, and the design features of staircase and arcade are further tested for their influences on the wind flow field. The air change rate per hour (ACH, h−1) is adopted to quantify the ventilation efficiency of the two connected indoor spaces. Results show that the staircases amplify wind velocities for the indoor spaces but also bring higher pollutant concentrations inside together. Moreover, the design of the arcade at the opening prompts the vortex to shift towards the entrance, leading to a heightened concentration of pollutants. Meanwhile, the effective ACH is mostly contributed by the turbulent diffusion (ACHt), while the mean flow (ACHm) has much less effect on the ventilation of the indoor spaces. These findings of this study provide references for sunken square design.
Virasoro Constraints for Toric Bundles
Authors: Coates Tom , Givental Alexander , Tseng Hsian-Hua 
Published: February 2024

Abstract
We show that the Virasoro conjecture in Gromov–Witten theory holds for the the total space of a toric bundle

$E \to B$

if and only if it holds for the base B. The main steps are: (i) We establish a localization formula that expresses Gromov–Witten invariants of E, equivariant with respect to the fiberwise torus action in terms of genus-zero invariants of the toric fiber and all-genus invariants of B, and (ii) we pass to the nonequivariant limit in this formula, using Brown’s mirror theorem for toric bundles.
The many swords of Shivaji: Searching for a weapon, finding a nation
Authors: Halladay Andrew 
Published: February 2024

AbstractSince at least the nineteenth century, the Maratha warrior-king Shivaji (r. 1674–80) has served as a central symbol in Indian politics. This article interrogates his legacy through the lens of his famous sword, the Bhavani Talvar. At least three swords have been identified as this weapon since the nineteenth century; by analysing each of these claims in turn, I consider how the discourse around Shivaji’s sword(s) traces the evolving legacy of Shivaji himself. Interested less in the historical merits of these claims than in the socio-political work they perform, I seek to uncover why the last of these three, now in London, has become essentially synonymous with the Bhavani Talvar in the popular sphere. Ultimately, I attribute this preference to the object’s political resonance: supposedly given to the Prince of Wales by a descendant of Shivaji in 1875, the object has been a rallying cry for Indian politicians of diverse ideological persuasions, who, in demanding its return, have sought to position themselves as the heirs to Shivaji and the healers of a nation still ailing from colonial wounds.
POVERTY, AGENCY, AND DEVELOPMENT
Authors: Rahman Tauhidur 
Published: February 2024

AbstractThis essay provides an account of four interrelated ideas. First, a person who is not poor by the standard conception of poverty can still be functionally poor. Second, poverty is a relationship between the poor and their environment (community, local markets, and local institutions). Third, poverty is a determinant of agency and impedes its exercise. Fourth, promoting agency promotes development. I conclude that agency is central to understanding both poverty and development.
USING BEHAVIORAL ECONOMICS TO REDUCE POVERTY AND OPPRESSION
Authors: Hoff Karla , Demeritt Allison 
Published: February 2024

AbstractUntil recently, economics conceived of poverty solely as a lack of material resources. This view likely captures the reality of poverty experienced by many people around the globe. However, two waves of behavioral economics demonstrate that the narrowing of people’s external environments may change people themselves: poverty lowers the quality of decision-making and poverty and oppression may depress the capacity to aspire. Poverty and a history of oppression also change how individuals are perceived. To overcome these effects may require helping people acquire new mental models. This essay discusses key findings from behavioral economics, the implications for agency, and some interventions with promising outcomes. We hope to inspire scholars and policymakers to think more deeply about the nature of poverty and oppression and to consider policies that target the psychological and sociological factors that create cycles of poverty.
The National Health Service urgent cancer referral pathway for suspected urological cancers: early economic evaluation of a risk prediction test
Authors: Cocco Paola , Smith Alison Florence , Neal Richard D. , Shinkins Bethany 
Published: February 2024

Abstract

Objectives
In the UK, the number of patients urgently referred for suspected cancer is increasing, and providers are struggling to cope with demand. We explore the potential cost-effectiveness of a new risk prediction test – the PinPoint test – to triage and prioritize patients urgently referred with suspected urological cancers.

Methods
Two simulation models were developed to reflect the diagnostic pathways for patients with (i) suspected prostate cancer, and (ii) bladder or kidney cancer, comparing the PinPoint test to current practice. An early economic analysis was conducted from a UK National Health Service (NHS) perspective. The primary outcomes were the percentage of individuals seen within 2 weeks and health care costs. An exploratory analysis was conducted to understand the potential impact of the Pinpoint test on quality-adjusted life years gained.

Results
Across both models and applications, the PinPoint test led to more individuals with urological cancer being seen within 2 weeks. Using PinPoint only to prioritize patients led to increased costs overall, whereas using PinPoint to both triage and prioritize patients led to cost savings. The estimated impact on life years gained/lost was very small and highly uncertain.

Conclusions
Using the PinPoint test to prioritize urgent referrals meant that more individuals with urological cancer were seen within 2 weeks, but at additional cost to the NHS. If used as a triage and prioritization tool, the PinPoint test shortens wait times for referred individuals and is cost saving. More data on the impact of short-term delays to diagnosis on health-related quality of life is needed.
Role of SST in Seasonal Western North Pacific Anomalous Anticyclone: Insights From AMIP Simulations in CMIP6
Authors: Wu Shuyan , Lin Wenshi , Dong Lu , Song Fengfei , Yang Song , Lu Zhiyuan , Hu Xiaoming 
Published: February 2024

AbstractThe western North Pacific anticyclone (WNPAC) significantly influences the East Asian climate and is modulated by tropical sea surface temperature (SST). This study uses 142 AMIP simulations from 33 Coupled Model Intercomparison Project (CMIP6) models to quantify the contributions of SST to the interannual variability of the WNPAC. SST forcing accounts for 66%, 77%, and 49% of the WNPAC variance in winter, spring, and summer, respectively. The persistence of the WNPAC depends on the relaying effects of SST in three tropical oceans. CMIP6 models exhibit excessive precipitation response to the Pacific SST, leading to an overestimated (underestimated) Pacific (Indian Ocean) effect in modulating the summer WNPAC. Sensitivity experiments with an atmospheric model confirm the crucial role of the Pacific in regulating the WNPAC interannual variation and the contribution from the tropical North Atlantic in spring. The tropical Indian Ocean only exerts a minor impact on the WNPAC when excluding the interactions with other oceans.
Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI
Authors: Sun Quan , Rowland Bryce T. , Chen Jiawen , Mikhaylova Anna V. , Avery Christy , Peters Ulrike , Lundin Jessica , Matise Tara , Buyske Steve , Tao Ran , Mathias Rasika A. , Reiner Alexander P. , Auer Paul L. , Cox Nancy J. , Kooperberg Charles , Thornton Timothy A. , Raffield Laura M. , Li Yun 
Published: February 2024

AbstractPolygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women’s Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.
C2-methyladenosine in tRNA promotes protein translation by facilitating the decoding of tandem m2A-tRNA-dependent codons
Authors: Duan Hong-Chao , Zhang Chi , Song Peizhe , Yang Junbo , Wang Ye , Jia Guifang 
Published: February 2024

AbstractRNA modification C2-methyladenosine (m2A) exists in both rRNA and tRNA of Escherichia coli (E. coli), installed by the methyltransferase RlmN using a radical-S-adenosylmethionine (SAM) mechanism. However, the precise function of m2A in tRNA and its ubiquity in plants have remained unclear. Here we discover the presence of m2A in chloroplast rRNA and tRNA, as well as cytosolic tRNA, in multiple plant species. We identify six m2A-modified chloroplast tRNAs and two m2A-modified cytosolic tRNAs across different plants. Furthermore, we characterize three Arabidopsis m2A methyltransferases—RLMNL1, RLMNL2, and RLMNL3—which methylate chloroplast rRNA, chloroplast tRNA, and cytosolic tRNA, respectively. Our findings demonstrate that m2A37 promotes a relaxed conformation of tRNA, enhancing translation efficiency in chloroplast and cytosol by facilitating decoding of tandem m2A-tRNA-dependent codons. This study provides insights into the molecular function and biological significance of m2A, uncovering a layer of translation regulation in plants.
The impacts of active and self-supervised learning on efficient annotation of single-cell expression data
Authors: Geuenich Michael J. , Gong Dae-won , Campbell Kieran R. 
Published: February 2024

AbstractA crucial step in the analysis of single-cell data is annotating cells to cell types and states. While a myriad of approaches has been proposed, manual labeling of cells to create training datasets remains tedious and time-consuming. In the field of machine learning, active and self-supervised learning methods have been proposed to improve the performance of a classifier while reducing both annotation time and label budget. However, the benefits of such strategies for single-cell annotation have yet to be evaluated in realistic settings. Here, we perform a comprehensive benchmarking of active and self-supervised labeling strategies across a range of single-cell technologies and cell type annotation algorithms. We quantify the benefits of active learning and self-supervised strategies in the presence of cell type imbalance and variable similarity. We introduce adaptive reweighting, a heuristic procedure tailored to single-cell data—including a marker-aware version—that shows competitive performance with existing approaches. In addition, we demonstrate that having prior knowledge of cell type markers improves annotation accuracy. Finally, we summarize our findings into a set of recommendations for those implementing cell type annotation procedures or platforms. An R package implementing the heuristic approaches introduced in this work may be found at https://github.com/camlab-bioml/leader.
Rapid synthesis of phosphor-glass composites in seconds based on particle self-stabilization
Authors: Sun Yongsheng , Wang Yuzhen , Chen Weibin , Jiang Qingquan , Chen Dongdan , Dong Guoping , Xia Zhiguo 
Published: February 2024

AbstractPhosphor-glass composites (PGC) are excellent candidates for highly efficient and stable photonic converters; however, their synthesis generally requires harsh procedures and long time, resulting in additional performance loss and energy consumption. Here we develop a rapid synthetic route to PGC within about 10 seconds, which enables uniform dispersion of Y3Al5O12:Ce3+ (YAG:Ce) phosphor particles through a particle self-stabilization model in molten tellurite glass. Thanks for good wettability between YAG:Ce micro-particles and tellurite glass melt, it creates an energy barrier of 6.94 × 105 zJ to prevent atomic-scale contact and sintering of particles in the melt. This in turn allows the generation of YAG:Ce-based PGC as attractive emitters with high quantum efficiency (98.4%) and absorption coefficient (86.8%) that can produce bright white light with luminous flux of 1227 lm and luminous efficiency of 276 lm W−1 under blue laser driving. This work shows a generalizable synthetic strategy for the development of functional glass composites.
Acoustic-driven magnetic skyrmion motion
Authors: Yang Yang , Zhao Le , Yi Di , Xu Teng , Chai Yahong , Zhang Chenye , Jiang Dingsong , Ji Yahui , Hou Dazhi , Jiang Wanjun , Tang Jianshi , Yu Pu , Wu Huaqiang , Nan Tianxiang 
Published: February 2024

AbstractMagnetic skyrmions have great potential for developing novel spintronic devices. The electrical manipulation of skyrmions has mainly relied on current-induced spin-orbit torques. Recently, it was suggested that the skyrmions could be more efficiently manipulated by surface acoustic waves (SAWs), an elastic wave that can couple with magnetic moment via the magnetoelastic effect. Here, by designing on-chip piezoelectric transducers that produce propagating SAW pulses, we experimentally demonstrate the directional motion of Néel-type skyrmions in Ta/CoFeB/MgO/Ta multilayers. We find that the shear horizontal wave effectively drives the motion of skyrmions, whereas the elastic wave with longitudinal and shear vertical displacements (Rayleigh wave) cannot produce the motion of skyrmions. A longitudinal motion along the SAW propagation direction and a transverse motion due to topological charge are simultaneously observed and further confirmed by our micromagnetic simulations. This work demonstrates that acoustic waves could be another promising approach for manipulating skyrmions, which could offer new opportunities for ultra-low power skyrmionics.