bluuebunny/crossref_metadata_2025_split huggingface dataset:
Guselkumab provides durable improvement across psoriatic arthritis disease domains: post hoc analysis of a phase 3, randomised, double-blind, placebo-controlled study
Authors: Coates Laura C , Gossec Laure , Zimmermann Miriam , Shawi May , Rampakakis Emmanouil , Shiff Natalie J , Kollmeier Alexa P , Xu Xie L , Nash Peter , Mease Philip J , Helliwell Philip S 
Published: March 2024

ObjectiveEvaluate long-term guselkumab effectiveness across Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)-recognised domains/related conditions of psoriatic arthritis (PsA).MethodsPost hoc analyses used data from DISCOVER-2 (NCT03158285) biologic/Janus-kinase inhibitor-naïve participants with active PsA (≥5 swollen/≥5 tender joints, C-reactive protein ≥0.6 mg/dL), randomised (1:1:1) to guselkumab every 4 or 8 weeks (Q4W/Q8W) or placebo with crossover to guselkumab. Outcomes aligned with key GRAPPA-recognised domains of overall disease activity, peripheral arthritis, axial disease, enthesitis/dactylitis and skin psoriasis (nail psoriasis was not evaluated). PsA-related conditions (inflammatory bowel disease (IBD)/uveitis) were assessed via adverse events through W112. Least squares mean changes from baseline through W100 in continuous outcomes employed repeated measures mixed-effects models adjusting for baseline scores. Binary measure response rates were determined with non-responder imputation for missing data.Results442/493 (90%) of guselkumab-randomised patients completed treatment through W100. Following early reductions in disease activity with guselkumab, durable improvements were observed across key PsA domains (swollen/tender joints, psoriasis, spinal pain, enthesitis/dactylitis) through W100. Response rates of therapeutically relevant targets generally increased through W100 with guselkumab Q4W/Q8W: Disease Activity Index for PsA low disease activity (LDA) 62%/59%, enthesitis resolution 61%/70%, dactylitis resolution 72%/83%, 100% improvement in Psoriasis Area and Severity Index 59%/53%, Psoriatic Arthritis Disease Activity Score LDA 51%/49% and minimal disease activity 38%/40%. Through W112, no cases of IBD developed among guselkumab-randomised patients and one case of uveitis was reported.ConclusionIn biologic-naïve patients with active PsA, guselkumab provided early and durable improvements in key GRAPPA-recognised domains through 2 years, with substantial proportions achieving important treatment targets.
Grafite: Taming Adversarial Queries with Optimal Range Filters
Authors: Costa Marco , Ferragina Paolo , Vinciguerra Giorgio 
Published: March 2024

Range filters allow checking whether a query range intersects a given set of keys with a chance of returning a false positive answer, thus generalising the functionality of Bloom filters from point to range queries. Existing practical range filters have addressed this problem heuristically, resulting in high false positive rates and query times when dealing with adversarial inputs, such as in the common scenario where queries are correlated with the keys.
We introduce Grafite, a novel range filter that solves these issues with a simple design and clear theoretical guarantees that hold regardless of the input data and query distribution: given a fixed space budget of B bits per key, the query time is O(1), and the false positive probability is upper bounded by l/2B-2, where l is the query range size. Our experimental evaluation shows that Grafite is the only range filter to date to achieve robust and predictable false positive rates across all combinations of datasets, query workloads, and range sizes, while providing faster queries and construction times, and dominating all competitors in the case of correlated queries.
As a further contribution, we introduce a very simple heuristic range filter whose performance on uncorrelated queries is very close to or better than the one achieved by the best heuristic range filters proposed in the literature so far.
Local Differentially Private Heavy Hitter Detection in Data Streams with Bounded Memory
Authors: Li Xiaochen , Liu Weiran , Lou Jian , Hong Yuan , Zhang Lei , Qin Zhan , Ren Kui 
Published: March 2024

Top-k frequent items detection is a fundamental task in data stream mining. Many promising solutions are proposed to improve memory efficiency while still maintaining high accuracy for detecting the Top-k items. Despite the memory efficiency concern, the users could suffer from privacy loss if participating in the task without proper protection, since their contributed local data streams may continually leak sensitive individual information. However, most existing works solely focus on addressing either the memory-efficiency problem or the privacy concerns but seldom jointly, which cannot achieve a satisfactory tradeoff between memory efficiency, privacy protection, and detection accuracy.
In this paper, we present a novel framework HG-LDP to achieve accurate Top-k item detection at bounded memory expense, while providing rigorous local differential privacy (LDP) protection. Specifically, we identify two key challenges naturally arising in the task, which reveal that directly applying existing LDP techniques will lead to an inferior "accuracy-privacy-memory efficiency" tradeoff. Therefore, we instantiate three advanced schemes under the framework by designing novel LDP randomization methods, which address the hurdles caused by the large size of the item domain and by the limited space of the memory. We conduct comprehensive experiments on both synthetic and real-world datasets to show that the proposed advanced schemes achieve a superior "accuracy-privacy-memory efficiency" tradeoff, saving 2300× memory over baseline methods when the item domain size is 41,270. Our code is anonymously open-sourced via the link.
Privacy Amplification by Sampling under User-level Differential Privacy
Authors: Fang Juanru , Yi Ke 
Published: March 2024

Random sampling is an effective tool for reducing the computational costs of query processing in large databases. It has also been used frequently for private data analysis, in particular, under differential privacy (DP). An interesting phenomenon that the literature has identified, is that sampling can amplify the privacy guarantee of a mechanism, which in turn leads to reduced noise scales that have to be injected.
All existing privacy amplification results only hold in the standard, record-level DP model. Recently, user-level differential privacy (user-DP) has gained a lot of attention as it protects all data records contributed by any particular user, thus offering stronger privacy protection. Sampling-based mechanisms under user-DP have not been explored so far, except naively running the mechanism on a sample without privacy amplification, which results in large DP noises. In fact, sampling is in even more demand under user-DP, since all state-of-the-art user-DP mechanisms have high computational costs due to the complex relationships between users and records. In this paper, we take the first step towards the study of privacy amplification by sampling under user-DP, and give the amplification results for two common user-DP sampling strategies: simple sampling and sample-and-explore. The experimental results show that these sampling-based mechanisms can be a useful tool to obtain some quick and reasonably accurate estimates on large private datasets.
SWIX: A Memory-efficient Sliding Window Learned Index
Authors: Liang Liang , Yang Guang , Hadian Ali , Croquevielle Luis Alberto , Heinis Thomas 
Published: March 2024

Data stream processing systems enable querying over sliding windows of streams of data. Efficient index structures for the streaming window are a crucial building block to enable querying the sliding window for operations such as aggregation and joins. This paper proposes SWIX, a novel memory-efficient learned index for sliding windows. Unlike conventional learned indexes that rely on tree structures to achieve logarithmic query cost, SWIX has a flat structure that uses substantially less memory and enables efficient query execution while having a low cost for index maintenance when inserting (and retraining). SWIX dynamically adapts itself to the real-time distribution shifts of data streams.
SWIX outperforms existing indexes in terms of query execution time and memory footprint for workloads characterized by very frequent updates. Our results show that SWIX has a significantly smaller memory footprint than conventional, streaming, and learned indexes, using only 22% to 42% of the size compared to state-of-the-art approaches, yet outperforming them by up 1.2× to 1.6× on average (and up to 52×) in terms of query time, making it a space- and time-efficient method for indexing data streams. For concurrent learned indexes, Parallel SWIX can achieve up to 3.45× throughput with only 34% of memory consumption.
Determining the Largest Overlap between Tables
Authors: Zecchini Luca , Bleifuß Tobias , Simonini Giovanni , Bergamaschi Sonia , Naumann Felix 
Published: March 2024

Both on the Web and in data lakes, it is possible to detect much redundant data in the form of largely overlapping pairs of tables. In many cases, this overlap is not accidental and provides significant information about the relatedness of the tables. Unfortunately, efficiently quantifying the overlap between two tables is not trivial. In particular, detecting their largest overlap, i.e., their largest common subtable, is a computationally challenging problem. As the information overlap may not occur in contiguous portions of the tables, only the ability to permute columns and rows can reveal it.
The detection of the largest overlap can help us in relevant tasks such as the discovery of multiple coexisting versions of the same table, which can present differences in the completeness and correctness of the conveyed information. Automatically detecting these highly similar, matching tables would allow us to guarantee their consistency through data cleaning or change propagation, but also to eliminate redundancy to free up storage space or to save additional work for the editors.
We present the first formal definition of this problem, and with it Sloth, our solution to efficiently detect the largest overlap between two tables. We experimentally demonstrate on real-world datasets its efficacy in solving this task, analyzing its performance and showing its impact on multiple use cases.
Cabin: A Compressed Adaptive Binned Scan Index
Authors: Chen Yiyuan , Chen Shimin 
Published: March 2024

Scan is a fundamental operation widely used in main-memory analytical database systems. To accelerate scans, previous studies build either record-order or sort-order structures known as scan indices. While achieving good performance, scan indices often incur significant space overhead, limiting their use in main-memory databases. For example, the most recent and best performing scan index, BinDex, consists of a sort-order position array, which is an array of rowIDs in the value order, and a set of record-order bit vectors, representing records in pre-defined value intervals. The structures can be much larger than the base data column size.
In this paper, we propose a novel scan index, Cabin, that exploits the following three techniques for better time-space tradeoff. 1) filter sketches that represent every 2^w-2 value intervals with a w-bit sketched vector, thereby exponentially reducing the space for the bit vectors; 2) selective position array that removes the rowID array for a fraction of intervals in order to lower the space overhead for the position array; and 3) data-aware intervals that judiciously select interval boundaries based on the data characteristics to better support popular values in skewed data distributions or categorical attributes. Experimental results show that compared with state-of-the-art scan solutions, Cabin achieves better time-space tradeoff, and attains 1.70 -- 4.48x improvement for average scan performance given the same space budget.
Five Interconnections of Race and Class
Authors: Billeaux-Martinez Michael , Calnitsky David 
Published: March 2024

Abstract
This paper proposes a five-part empirical typology of interconnections of race and class. We describe the mechanisms whereby (1) race is a form of class relation; (2) race relations and class relations reciprocally affect each other; (3) race acts as a sorting mechanism into class locations; (4) race acts as a mediating linkage to class locations; and (5) race interacts with class in determining other outcomes. Rather than insisting on one or another mechanism as the overarching framework for conceptualising the interconnections between race and class, we propose a theoretical integration of all five within a functionalist model. The model reconciles the empirical effects of race variables with a class-functionalist explanation of race. Our typology of interconnections is useful for situating concrete empirical phenomena, and our theoretical integration of those interconnections offers a coherent explanatory system that captures the recursive causality of race and class.
Unpaired Downscaling of Fluid Flows with Diffusion Bridges
Authors: Bischoff Tobias , Deck Katherine 
Published: March 2024

Abstract
We present a method to downscale idealized geophysical fluid simulations using generative models based on diffusion maps. By analyzing the Fourier spectra of fields drawn from different data distributions, we show how a diffusion bridge can be used as a transformation between a low resolution and a high resolution dataset, allowing for new sample generation of high-resolution fields given specific low resolution features. The ability to generate new samples allows for the computation of any statistic of interest, without any additional calibration or training. Our unsupervised setup is also designed to downscale fields without access to paired training data; this flexibility allows for the combination of multiple source and target domains without additional training. We demonstrate that the method enhances resolution and corrects context-dependent biases in geophysical fluid simulations, including in extreme events. We anticipate that the same method can be used to downscale the output of climate simulations, including temperature and precipitation fields, without needing to train a new model for each application and providing a significant computational cost savings.
An Accurate and Automated Convective Vortex Detection Method for Long-Duration Infrasound Microbarometer Data
Authors: Berg Elizabeth M. , Urtecho Louis J. , Krishnamoorthy Siddharth , Silber Elizabeth A. , Sparks Andrew , Bowman Daniel C. 
Published: March 2024

Abstract
Heating of the surficial layer of the atmosphere often generates convective vortices, known as “dust devils” when they entrain visible debris. Convective vortices are common on both Earth and Mars, where they affect the climate via dust loading, contribute to wind erosion, impact the efficiency of photovoltaic systems, and potentially result in injury and property damage. However, long-duration terrestrial convective vortex activity records are rare. We have developed a high-precision and high-recall method to extract convective vortex signatures from infrasound microbarometer data streams. The techniques utilizes a wavelet-based detector to capture potential events and then a template matching system to extract the duration of the vortex. Since permanent and temporary infrasound sensors networks are present throughout the globe (many with open data), our method unlocks a vast new convective vortex dataset without requiring the deployment of specialized instrumentation.

Significance Statement
Convective vortices, or “dust devils,” contribute to regional dust loading in Earth’s atmosphere. However, long-duration convective vortex activity records are rare. We came up with a way to autonomously detect the pressure signatures left by convective vortices striking low-frequency sound, or “infrasound,” sensors. Since permanent infrasound stations have been active for decades, our method has the potential to add orders-of-magnitude more events than previously catalogued.
Safety and long-term outcomes of remote cardiac rehabilitation in coronary heart disease patients: A systematic review
Authors: Antoniou Varsamo , Kapreli Eleni , Davos Constantinos H , Batalik Ladislav , Pepera Garyfallia 
Published: March 2024

Objective To systematically review the safety and the long-term mortality and morbidity risk-rates of the remotely-delivered cardiac rehabilitation (RDCR) interventions in coronary heart disease (CHD) patients. Methods The protocol was registered in the International Prospective Register of Systematic Reviews (CRD42023455471). Five databases (Pubmed, Scopus, Cochrane Central Register of Controlled Trials in the Cochrane Library, Cinahl and Web of Science) were reviewed from January 2012 up to August 2023. Inclusion criteria were: (a) randomized controlled trials, (b) RDCR implementation of at least 12 weeks duration, (c) assessment of safety, rates of serious adverse events (SAEs) and re-hospitalization incidences at endpoints more than 6 months. Three reviewers independently performed data extraction and assessed the risk of bias using the Cochrane Risk of Bias tool. Results 14 studies were identified involving 2012 participants and a range of RDCR duration between 3 months to 1 year. The incidence rate of exercise-related SAEs was estimated at 1 per 53,770 patient-hours of RDCR exercise. A non-statistically significant reduction in the re-hospitalization rates and the days lost due to hospitalization was noticed in the RDCR groups. There were no exercise-related deaths. The overall study quality was of low risk. Conclusions RDCR can act as a safe alternative delivery mode of cardiac rehabilitation (CR). The low long-term rates of reported SAEs and re-hospitalization incidences of the RDCR could enhance the uptake rates of CR interventions. However, further investigation is needed in larger populations and longer assessment points.
The IMPOWR Network Divided or Single Exposure Study (DOSE) Protocol: A Randomized Controlled Comparison of Once Versus Split Dosing of Methadone for the Treatment of Comorbid Chronic Pain and Opioid Use Disorder
Authors: McKendrick Greer , Davis Will , Sklar Michael , Brown Nicole , Pattillo Emma , Finan Patrick H. , Antoine Denis , Walters Vickie , Dunn Kelly E. 
Published: March 2024

Background: The Divided or Single Exposure (DOSE) trial is a double-blind, placebo-controlled examination of once versus split dosing of methadone for comorbid pain and opioid use disorder (OUD) among persons receiving methadone for OUD treatment. Methods: This multisite trial consists of a 12-week active intervention phase and 6-month follow-up period. Persons receiving methadone who endorse clinically-significant chronic pain are randomized into once-daily dosing or split dosing that is managed remotely via an electronic pillbox. Clinical pain is assessed weekly and using ecological momentary assessments. Experimentally-evoked pain is assessed using a quantitative sensory testing battery. Additional outcomes related to OUD, including withdrawal and craving, are also collected. Results: The study hypothesizes that persons assigned to the split dosing condition will report lower pain and opioid withdrawal relative to persons assigned to the traditional once-daily dosing strategy. Conclusions: Split dosing is a relatively common technique in OUD treatments; therefore, if data support this hypothesis, there is high potential for implementation.
Yin Yang 1 regulates cohesin complex protein SMC3 in mouse hematopoietic stem cells
Authors: Lu Zhanping , Wang Yinghua , Assumpção Anna L. F. V. , Liu Peng , Kopp Audrey , Saka Sahitya , Mcilwain Sean J. , Viny Aaron D. , Brand Marjorie , Pan Xuan 
Published: March 2024

Abstract
Yin Yang 1 (YY1) and structural maintenance of chromosomes 3 (SMC3) are 2 critical chromatin structural factors that mediate long-distance enhancer-promoter interactions and promote developmentally regulated changes in chromatin architecture in hematopoietic stem/progenitor cells (HSPCs). Although YY1 has critical functions in promoting hematopoietic stem cell (HSC) self-renewal and maintaining HSC quiescence, SMC3 is required for proper myeloid lineage differentiation. However, many questions remain unanswered regarding how YY1 and SMC3 interact with each other and affect hematopoiesis. We found that YY1 physically interacts with SMC3 and cooccupies with SMC3 at a large cohort of promoters genome wide, and YY1 deficiency deregulates the genetic network governing cell metabolism. YY1 occupies the Smc3 promoter and represses SMC3 expression in HSPCs. Although deletion of 1 Smc3 allele partially restores HSC numbers and quiescence in YY1 knockout mice, Yy1−/−Smc3+/− HSCs fail to reconstitute blood after bone marrow transplant. YY1 regulates HSC metabolic pathways and maintains proper intracellular reactive oxygen species levels in HSCs, and this regulation is independent of the YY1–SMC3 axis. Our results establish a distinct YY1–SMC3 axis and its impact on HSC quiescence and metabolism.
Characterization of tropospheric ozone pollution, random forest trend prediction and analysis of influencing factors in South-western Europe
Authors: Wang Jinyang , Ju Tianzhen , Li Bingnan , Huang Cheng , Xia Xuhui , Zhang Jiaming , Li Chunxue 
Published: March 2024

AbstractNowadays, environmental problems have gradually become the focus of world attention. In recent years, heat waves in many parts of Europe have increased ozone concentrations, fuelling ozone pollution. Therefore, this paper investigates the spatial and temporal distribution of tropospheric column ozone concentrations in South-western Europe, future trend changes, influencing factors, and potential source regions based on remotely sensed monitoring data from the OMI (Ozone Monitoring Instrument) from 2011 to 2021. The results show that the areas of high tropospheric column ozone concentrations are mainly concentrated in the northwest, Poland, and southeast coastal areas. At the same time, the monthly variation curve of column ozone concentration is bimodal. Trend change analyses indicate an upward trend in future column ozone concentrations in the southeastern part of the study area. The potential for increases also exists in parts of Germany, France, and Poland, which will need to be monitored. Random forest model projections found a slight decrease in column ozone concentrations in 2022 and 2023 of about 1–4 DU compared to tropospheric column ozone concentrations in 2021. The health risk assessment found that the number of all-cause premature deaths due to exposure to ozone was the highest in Germany. During the summer, when ozone pollution is high, the potential source area in the southeastern part of the study area is located at the border of the three countries, and synergistic management is recommended. In exploring the correlation between the influencing factors and ozone, it was found that there is a significant difference between the long-time and short-time series. In addition, the pathway analysis shows that the population size, distribution density, and forested area in southwestern Europe may be more sensitive to the production of tropospheric ozone.