bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring factors associated with healthcare professionals’ subjective perceptions of complex issues in primary care in Japan: a self-administered survey study on confidence, satisfaction and burden levels
Authors: Haruta Junji , Goto Ryohei
Published: March 2024

Objective

The aim of this study was to explore factors associated with healthcare professionals’ subjective perceptions of complex issues in primary care settings in Japan.

Design

Cross-sectional survey conducted through a self-administered web-based questionnaire.

Setting

Japan, from June to October 2020.

Participants

Healthcare professionals recruited via an email list from the Japan Primary Care Association.

Measures

The questionnaire assessed subjective perception of satisfaction, confidence and burden regarding complex issues using a 100 mm Visual Analogue Scale (VAS). Explanatory variables included the Japanese version of the Self-assessment Scale of Interprofessional Competency (JASSIC), basic demographic information, administrative experience and an organisational climate scale. This scale comprised the ‘Plan, Do, See’ (PDS) factor for management and the ‘Do’ factor in a leader-centred direction for those working under compulsion. Factors associated with subjective perceptions were analysed using binomial logistic regression analysis and Bonferroni analysis (p<0.017).

Results

Data from 593 participants (average age of 41.2 years, including 133 nurses, 128 physicians and 120 social workers) were analysed. Median (quartile) VAS scores for satisfaction, confidence and burden were 50 (36–70), 52 (40–70) and 50 (30–66), respectively. Higher satisfaction group was significantly associated with PDS factor, Do factor and JASSIC Score. Greater confidence group associated with older age, male, Do factor, administrative experience and JASSIC Score. No factors were significantly associated with the higher perceived burden.

Conclusion

These findings reveal that interprofessional competency self-assessment influence perceptions of complex issues among healthcare professionals. Moreover, satisfaction with complex issues might be enhanced by a manageable organisational climate, while confidence might be influenced by personal attributes.
Prevalence and impact of SARS-CoV-2 infection among patients with acute ischaemic stroke: a nationwide register-based cohort study in Denmark
Authors: Mortensen Janne Kaergaard , Blauenfeldt Rolf Ankerlund , Hedegaard Jakob Nebeling , Morberg Wejse Christian , Johnsen Søren Paaske , Andersen Grethe , Simonsen Claus Ziegler
Published: March 2024

Objectives

An increased risk of stroke has been reported among patients with COVID-19 caused by SARS-CoV-2. We aimed to investigate the nationwide prevalence of SARS-CoV-2 among patients with acute ischaemic stroke and to study the impact on stroke severity, quality of care and mortality on an individual patient level.

Design

This was a nationwide register-based cohort study.

Setting

We used data from several Danish registers which were linked at an individual patient level using the unique civil registration number assigned to all Danish citizens. Patients were identified from the Danish Stroke Registry and information on SARS-CoV-2 infection status was collected from the Danish National COVID-19 Registry. Concurrent SARS-CoV-2 infection was defined as a positive PCR test within 31 days prior to, and 1 day after, stroke admission. Information on comorbidity was collected from the Danish National Patient Registry and information on vital status was collected from the Danish Civil Registration System.

Participants

A total of 11 502 patients admitted with acute ischaemic stroke from 10 March 2020 to 31 May 2021 were included in the study.

Results

Among the included patients, the majority (84.6%) were tested for SARS-CoV-2, but only 68 had a positive test. These patients were more prone to have atrial fibrillation and were more often treated with reperfusion therapy. They had a significantly increased risk of severe stroke (adjusted relative risk (aRR) 1.93, 95% CI: 1.22 to 3.04) and a significantly increased 30-day mortality risk (aRR 2.29, 95% CI: 1.19 to 4.39). There was no difference in the proportion of patients fulfilling relevant performance measures on quality of care.

Conclusion

In this nationwide study, only 0.6% of patients with acute ischaemic stroke were tested positive for a concurrent SARS-CoV-2 infection. The patients with SARS-CoV-2 presented with more severe strokes.
Constitution of Long COVID illness, patienthood and recovery: a critical synthesis of qualitative studies
Authors: Harrison Mia , Rhodes Tim , Lancaster Kari
Published: March 2024

Objectives

To investigate the lived experiences of Long COVID.

Design

Critical interpretive synthesis of qualitative research.

Data sources

PubMed and Web of Science databases were searched on 14 September 2023.

Eligibility criteria

Original peer-reviewed qualitative studies describing the experiences of Long COVID were eligible for inclusion.

Data extraction and synthesis

We used established qualitative synthesis methods to search, screen and manually code the included studies. Critical interpretation methods were used to analyse the data and develop synthetic constructs.

Results

68 articles were identified in the first phase of sampling, with 16 studies and 879 participants included in the final synthesis. The analysis of these studies was organised into three thematic constructions of Long COVID: (1) the illness, (2) the patient and (3) recovery. Long COVID was diversely characterised across study approaches, designs and findings but was underpinned by shared diagnostic logics, which shaped the identification and measurement of symptoms. The boundaries between different constitutions of Long COVID in qualitative accounts of illness experience were often imprecise. Slippages between different definitions of Long COVID had implications for patient experiences in relation to diagnosis, help-seeking and care, and expectations of recovery.

Conclusions

Long COVID is a site of multiple and diverse qualitative interpretation. Accounts of lived experience emphasise the constitutions of illness, patienthood and recovery as situated and emergent. The ongoing context-based negotiation of Long COVID is a defining qualitative feature of the condition. Approaches to researching, diagnosing and developing health interventions must be as adaptive as the varieties of Long COVID lived experience.
Extent of investigation and management of cases of ‘unexplained’ mismatch repair deficiency (u-dMMR): a UK Cancer Genetics Group consensus
Authors: McVeigh Terri Patricia , Monahan Kevin J , Christopher Joseph , West Nick , Scott Malcolm , Murray Jennie , Hanson Helen
Published: March 2024

Background

Mismatch repair deficiency (dMMR) is a characteristic feature of cancers linked to Lynch syndrome. However, in most cases, it results from sporadic somatic events rather than hereditary factors. The term ‘Lynch-like syndrome’ (LLS) has been used to guide colorectal cancer surveillance for relatives of individuals with a dMMR tumour when somatic and germline genomic testing is uninformative. As the assessment of mismatch repair through immunohistochemistry and/or microsatellite instability is increasingly applied across various tumour types for treatment planning, dMMR is increasingly detected in tumours where suspicion of hereditary aetiology is low. Our objective was to establish current practices and develop national guidance for investigating, and managing relatives of, patients with cancers demonstrating unexplained dMMR.

Methods

This was achieved through a virtual consensus meeting involving key stakeholders from the UK, through premeeting surveys, structured discussions and in-meeting polling to formulate best practice guidance.

Results

We identified variability in the availability of diagnostic technologies across specialist centres. It was agreed that equitable access to baseline testing is required, acknowledging the need for a pragmatic approach to investigating dMMR cancers not traditionally associated with Lynch syndrome. Factors such as family history, age, tumour type, protein loss pattern and extent of the investigation were deemed crucial in guiding family management. The term ‘unexplained dMMR’ was recommended over LLS.

Conclusion

Decisions regarding investigations and future cancer risk management in patients and relatives should be nuanced, considering factors like clinical suspicion of hereditary predisposition to allocate limited resources efficiently and avoid unnecessary investigations in low-suspicion families.
Evaluating nuclear charge radii based on the mean mass-density parameter using BP neural networks
Authors: Jiao Bao-Bao
Published: March 2024

In this paper, we have successfully obtained the mean mass-density parameter ([Formula: see text]) using the nuclear masses AME2020 database and nuclear charge radius (CR) CR2013 database. The empirical formula is derived based on the relationship between [Formula: see text] and [Formula: see text] (the ratio of the number of neutrons to protons). Subsequently, we obtained an empirical formula for the difference in [Formula: see text] between two neighboring isotopes. By utilizing this empirical formula along with the AME2020 and CR2013 databases, we then calculated 625 charge radii for nuclei with [Formula: see text]. The root-mean-square deviation (RMSD) between the calculated values and the experimental values in the CR2013 database is 0.0075[Formula: see text]fm. The predicted nuclear CR values are comparable to those of other researches, which some predictions closely matching the experimental values measured in recent years. Additionally, this work used the Back Propagation (BP) neural network to establish a model for describing and predicting the difference in the mean mass-density parameter between two neighboring isotopes. The RMSD between the calculated and experimental values obtained using this model is 0.0039[Formula: see text]fm. Some of our predicted values have good accuracy and compared well with experimental values. Both of the above methods indicate that the nuclear CR relationship proposed in this paper based on the difference in mean mass-density parameter has simplicity and reliability.
ANTERIOR CRUCIATE LIGAMENT STRAIN DURING STOP-JUMP LANDING: A COMPUTATIONAL STUDY
Authors: Zhu Jin , Chandrashekar Naveen
Published: March 2024

Stop-jump landing maneuvers are a particularly common source of injury to the anterior cruciate ligament (ACL). The objective of this study is to determine which kinematic and kinetic parameters contributed to greater ACL strains during stop-jump landings. A combined in vivo/computational modeling approach was used to simulate stop-jump landing activity. Motion capture data from five human participants performing a non-injurious stop-jump landing were used to compute subject- specific muscle forces and 3D kinematics of the knee. These outputs were subsequently used to simulate the activity on a validated computational model of the knee. Correlation analysis was conducted to determine which variables significantly affected the strain in the ACL. The resulting average peak ACL strain during the activity was 7.9 ± 2.4%. A bivariate correlation study found that there was a strong correlation between ACL strain and the knee range of flexion during the period from ground contact to peak ground reaction force (GRF) time ([Formula: see text] = −0.81, [Formula: see text] = 0.08). Neither the quadriceps force nor the instantaneous knee flexion angle during landing or peak GRF was strongly correlated to ACL strain. The results show that strain in the ACL during stop-jump landing could be reduced by increasing the knee range of flexion over time during the landing phase.
A Unified Thermo-Fluid–Solid Formulation for FSI and Phase Change Problems Based on the Particle Finite Element Method
Authors: Bobach Billy-Joe , Boman Romain , Carbonell Josep Maria , Papeleux Luc , Fernandez Eduardo , Ponthot Jean-Philippe
Published: March 2024

The modeling of industrial processes that involve phase change (e.g., casting, welding or additive manufacturing) is challenging due to their multiscale and multiphysics nature. The coupling of the fluid and solid mechanics is difficult due to the unknown and evolving fluid–solid interface. To deal with the difficulty of the coupling, a unified approach has been developed where fluid and solid regions are represented in the same computational domain and solved by a single solver. The interaction of fluid and solid regions is therefore automatically captured and the material can locally undergo phase transition. This allows to capture the flow in the melt and the thermal stresses in the solid. The solid material model is currently limited to linear elasticity, but it opens the path to more complex material models with plasticity modeling, which already exist in the literature. The proposed method is based on the Particle Finite Element Method (PFEM), which has been shown to accurately handle both fluid and solid mechanics. In this work, we present the key aspects of this novel unified formulation and the treatment of the fluid–solid interface in the PFEM context. The methodology is presented and verified using a set of tests. A laser spot welding example test case demonstrates the potential of combining the unified formulation with the interface treatment and the phase change capabilities and is used for the validation of the present technique.
Little rip and pseudo rip cosmological models with coupled dark energy based on a new generalized entropy
Authors: Brevik I. , Timoshkin A. V.
Published: March 2024

In this paper, we study Little Rip (LR) and Pseudo Rip (PR) cosmological models containing two coupled fluids: dark energy and dark matter. We assume a spatially flat Friedmann–Robertson–Walker (FRW) universe. The interaction between the dark energy and the dark matter fluid components is described in terms of the parameters in the generalized Equation of State (EoS) in presence of the bulk viscosity. We consider entropic cosmology and use a description based on a new generalized entropy function, which was proposed by Nojiri–Odintsov–Faraoni [From nonextensive statistics and black hole entropy to the holographic dark universe, Phys. Rev. D 105(4) (2022) 044042]. Conditions for the appearance of the (LR) and the (PR) in terms of the parameters of the (EoS) are obtained. Introducing an energy density [Formula: see text] corresponding to a specified entropy function [Formula: see text], together with an interaction term [Formula: see text] in the gravitational equations of motion, we derive modified forms of the EoS parameters. We discuss the corrections of the thermodynamic parameters associated with the generalized entropy function. Properties of the late universe as well as in the early universe in this formalism are pointed out.
Existence and classification of positive solutions for coupled purely critical Kirchhoff system
Authors: Gao Yahui , Luo Xiao , Zhen Maoding
Published: March 2024

We study the nonlinear coupled Kirchhoff system with purely Sobolev critical exponent. By using appropriate transformation, we get one equivalent system involving a critical Schrödinger system and an algebraic system. Through solving the critical Schrödinger system with a corresponding algebraic system, under suitable conditions we obtain the existence and classification of positive ground states for the Kirchhoff system in dimensions 3 and 4. Furthermore, for the degenerate case, we give a complete classification of positive ground states for the Kirchhoff system in any dimension. To the best of our knowledge, this paper is the first to give classification results for the ground states of Kirchhoff systems. The results in this paper partially extend and complement the main results established by Lü and Peng [Existence and asymptotic behavior of vector solutions for coupled nonlinear Kirchhoff-type system, J. Differ. Equ. 263 (2017) 8947–8978] considering the linearly coupled Kirchhoff system with subcritical exponent and some partial results established by Chen and Zou [Positive least energy solutions and phase separation for coupled Schrödinger equations with critical exponent, Arch. Ration. Mech. Anal. 205 (2012) 515–551; Positive least energy solutions and phase separation for coupled Schrödinger equations with critical exponent: higher dimensional case, Calc. Var. Partial Differ. Equ. 52 (2015) 423–467], where the authors considered the coupled purely critical Schrödinger system.
A paranormed fractional ordered Euler–Riesz difference sequence space
Authors: Bektaş Çiğdem A. , Bayram Erdal
Published: March 2024

In this study, we introduce a novel sequence space denoted as [Formula: see text] with a fractional order [Formula: see text]. This new space is defined by the matrix [Formula: see text], which is a composition of the Euler–Riesz matrix [Formula: see text] and the fractional ordered difference operator [Formula: see text]. We explore its topological properties along with its [Formula: see text]-, [Formula: see text]-, and [Formula: see text]-duals. Furthermore, we provide characterizations for certain matrix mappings from [Formula: see text] to the sequence spaces of Maddox.
A40 Brecon bypass landslide: investigation, remediation and asset management for climate resilience
Authors: St John Thomas W. , Oliphant Hana , Butler Matt
Published: March 2024

During February 2020, a 300 m
3
slope failure occurred within a trunk road earthwork at Brecon, Wales, leading to the initial closure of all four lanes of the dual carriageway. As part of Welsh Government's strategy for climate resilient infrastructure and in accordance with the CD622 Managing Geotechnical Risk framework, the site investigation commenced in 2020 and proceeded through various phases to the completion of remedial works in 2022. This paper discusses the approach to management of geotechnical risk for the scheme, from desk study through implementation of an on-slope ground investigation and interim risk mitigation, to design and implementation of the remedial measures. The paper describes the nature and trigger of the landslide case study, adaptations in the design phase to provide resilience to geohazards and future climatic conditions, the constraints that were overcome during the site works and measures taken to manage residual risk and ensure ease of maintenance.

Thematic collection:
This article is part of the Geo-resilience and infrastructure collection available at:
https://www.lyellcollection.org/topic/collections/geo-resilience-and-infrastructure
Robustness of Updatable Learning-based Index Advisors against Poisoning Attack
Authors: Zheng Yihang , Lin Chen , Lyu Xian , Zhou Xuanhe , Li Guoliang , Wang Tianqing
Published: March 2024

Despite the promising performance of recent learning-based Index Advisors (IAs), they exhibited the robustness issue when poisoning attacks polluted training data. This paper presents the first attempt to study the robustness of updatable learning-based IAs against poisoning attack, i.e., whether the IAs can maintain robust performance if their training/updating is disturbed by injecting an extraneous toxic workload. The goal is to provide an opaque-box stress test that is generally effective in evaluating the robustness of different learning-based IAs without using the users' private data.

There are three challenges, i.e., how to probe "index preference" from opaque-box IAs, how to design effective injecting strategies even if the IAs can be fine-tuned, and how to generate queries to meet the specific constraints for IA probing and injecting. The presented stress-test framework PIPA consists of a probing stage, an injecting stage, and a query generator. To address the first challenge, the probing stage estimates the IA's indexing preference by observing its responses to the probing workload. To address the second challenge, the injecting stage injects workloads that spoof the IA to demote the top-ranked indexes in the estimated indexing preference and promote mid-ranked indexes. The stress test is effective because the IA is trapped in a local optimum even after fine-tuning. To address the third challenge, PIPA utilizes IABART (Index Aware BART) to generate queries that can be optimized by building indexes on a given set of indexes. Extensive experiments on different benchmarks against various learning-based IAs demonstrate the effectiveness of PIPA and that existing learning-based IAs are non-robust when faced with even a subtle amount of injected extraneous toxic workloads.
FineMon: An Innovative Adaptive Network Telemetry Scheme for Fine-Grained, Multi-Metric Data Monitoring with Dynamic Frequency Adjustment and Enhanced Data Recovery
Authors: Ji Haojie , Xie Kun , Wen Jigang , Zhang Qingyi , Xie Gaogang , Liang Wei
Published: March 2024

Network telemetry, characterized by its efficient push model and high-performance communication protocol (gRPC), offers a new avenue for collecting fine-grained real-time data. Despite its advantages, existing network telemetry systems lack a theoretical basis for setting measurement frequency, struggle to capture informative samples, and face challenges in setting a uniform frequency for multi-metric monitoring. We introduce FineMon, an innovative adaptive network telemetry scheme for precise, fine-grained, multi-metric data monitoring. FineMon leverages a novel Two-sided Frequency Adjustment (TFA) to dynamically adjust the measurement frequency on the Network Management System (NMS) and infrastructure sides. On the NMS side, we provide a theoretical basis for frequency determination, drawing on changes in the rank of multi-metric data to minimize monitoring overhead. On the infrastructure side, we adjust the frequency in real-time to capture significant data fluctuations. We propose a robust Enhanced-Subspace-based Tensor Completion (ESTC) to ensure accurate recovery of fine-grained data, even with noise or outliers. Through extensive experimentation with three real datasets, we demonstrate FineMon's superiority over existing schemes in reduced measurement overhead, enhanced accuracy, and effective capture of intricate temporal features.
Efficient Algorithm for K-Multiple-Means
Authors: Fujiwara Yasuhiro , Kumagai Atsutoshi , Ida Yasutoshi , Nakano Masahiro , Nakatsuji Makoto , Kimura Akisato
Published: March 2024

K-Multiple-Means is an extension of K-means for the clustering of multiple means used in many applications, such as image segmentation, load balancing, and blind-source separation. Since K-means uses only one mean to represent each cluster, it fails to capture non-spherical cluster structures of data points. However, since K-Multiple-Means represents the cluster by computing multiple means and grouping them into specified c clusters, it can effectively capture the non-spherical clusters of the data points. To obtain the clusters, K-Multiple-Means updates a similarity matrix of a bipartite graph between the data points and the multiple means by iteratively computing the leading c singular vectors of the matrix. K-Multiple-Means, however, incurs a high computation cost for large-scale data due to the iterative SVD computations. Our proposal, F-KMM, increases the efficiency of K-Multiple-Means by computing the singular vectors from a smaller similarity matrix between the multiple means obtained from the similarity matrix of the bipartite graph. To compute the similarity matrix of the bipartite graph efficiently, we skip unnecessary distance computations and estimate lower bounding distances between the data points and the multiple means. Theoretically, the proposed approach guarantees the same clustering results as K-Multiple-Means since it can exactly compute the singular vectors from the similarity matrix between the multiple means. Experiments show that our approach is several orders of magnitude faster than previous clustering approaches that use multiple means.
Predictive and Near-Optimal Sampling for View Materialization in Video Databases
Authors: Xu Yanchao , Zhang Dongxiang , Zhang Shuhao , Wu Sai , Feng Zexu , Chen Gang
Published: March 2024

Scalable video query optimization has re-emerged as an attractive research topic in recent years. The OTIF system, a video database with cutting-edge efficiency, has introduced a new paradigm of utilizing view materialization to facilitate online query processing. Specifically, it stores the results of multi-object tracking queries to answer common video queries with sub-second latency. However, the cost associated with view materialization in OTIF is prohibitively high for supporting large-scale video streams.

In this paper, we study efficient MOT-based view materialization in video databases. We first conduct a theoretical analysis and establish two types of optimality measures that serve as lower bounds for video frame sampling. In order to minimize the number of processed video frames, we propose a novel predictive sampling framework, namely LEAP, exhibits near-optimal sampling performance. Its efficacy relies on a data-driven motion manager that enables accurate trajectory prediction, a compact object detection model via knowledge distillation, and a robust cross-frame associator to connect moving objects in two frames with a large time gap.

Extensive experiments are conducted in 7 real datasets, with 7 baselines and a comprehensive query set, including selection, aggregation and top-k queries. The results show that with comparable query accuracy to OTIF, our LEAP can reduce the number of processed video frames by up to 9× and achieve 5× speedup in query processing time. Moreover, LEAP demonstrates impressive throughput when handling large-scale video streams, as it leverages a single NVIDIA RTX 3090ti GPU to support real-time MOT-based view materialization from 160 video streams simultaneously.
LIT: Lightning-fast In-memory Temporal Indexing
Authors: Christodoulou George , Bouros Panagiotis , Mamoulis Nikos
Published: March 2024

We study the problem of temporal database indexing, i.e., indexing versions of a database table in an evolving database. With the larger and cheaper memory chips nowadays, we can afford to keep track of all versions of an evolving table in memory. This raises the question of how to index such a table effectively. We depart from the classic indexing approach, where both current (i.e., live) and past (i.e., dead) data versions are indexed in the same data structure, and propose LIT, a hybrid index, which decouples the management of the current and past states of the indexed column. LIT includes optimized indexing modules for dead and live records, which support efficient queries and updates, and gracefully combines them. We experimentally show that LIT is orders of magnitude faster than the state-of-the-art temporal indices. Furthermore, we demonstrate that LIT uses linear space to the number of record indexed versions, making it suitable for main-memory temporal data management.
HERO: A Hierarchical Set Partitioning and Join Framework for Speeding up the Set Intersection Over Graphs
Authors: Yang Boyu , Zheng Weiguo , Lian Xiang , Cai Yuzheng , Wang X. Sean
Published: March 2024

As one of the most primitive operators in graph algorithms, such as the triangle counting, maximal clique enumeration, and subgraph listing, a set intersection operator returns common vertices between any two given sets of vertices in data graphs. It is therefore very important to accelerate the set intersection, which will benefit a bunch of tasks that take it as a built-in block. Existing works on the set intersection usually followed the merge intersection or galloping-search framework, and most optimization research focused on how to leverage the SIMD hardware instructions. In this paper, we propose a novel multi-level set intersection framework, namely hierarchical set partitioning and join (HERO), by using our well-designed set intersection bitmap tree (SIB-tree) index, which is independent of SIMD instructions and completely orthogonal to the merge intersection framework. We recursively decompose the set intersection task into small-sized subtasks and solve each subtask using bitmap and boolean AND operations. To sufficiently achieve the acceleration brought by our proposed intersection approach, we formulate a graph reordering problem, prove its NP-hardness, and then develop a heuristic algorithm to tackle this problem. Extensive experiments on real-world graphs have been conducted to confirm the efficiency and effectiveness of our HERO approach. The speedup over classic merge intersection achieves up to 188x and 176x for triangle counting and maximal clique enumeration, respectively.
Zero-sided RDMA: Network-driven Data Shuffling for Disaggregated Heterogeneous Cloud DBMSs
Authors: Jasny Matthias , Thostrup Lasse , Tamimi Sajjad , Koch Andreas , István Zsolt , Binnig Carsten
Published: March 2024

In this paper, we present a novel communication scheme called zero-sided RDMA, enabling data exchange as a native network service using a programmable switch. In contrast to one- or two-sided RDMA, in zero-sided RDMA, neither the sender nor the receiver is actively involved in data exchange. Zero-sided RDMA thus enables efficient RDMA-based data shuffling between heterogeneous hardware devices in a disaggregated setup without the need to implement a complete RDMA stack on each heterogeneous device or the need for a CPU that is co-located with the accelerator to coordinate the data transfer. As such, we think that zero-sided RDMA is a major building block to make efficient use of heterogeneous accelerators in future cloud DBMSs. In our evaluation, we show that zero-sided RDMA can outperform existing one-sided RDMA-based schemes for accelerator-to-accelerator communication and thus speed up typical distributed database operations such as joins.
PreVision: An Out-of-Core Matrix Computation System with Optimal Buffer Replacement
Authors: Koo Kyoseung , Kim Sohyun , Kim Wonhyeon , Choi Yoojin , Han Juhee , Kim Bogyeong , Moon Bongki
Published: March 2024

Large-scale matrix computations have become indispensable in artificial intelligence and scientific applications. It is of paramount importance to efficiently perform out-of-core computations that often entail an excessive amount of disk I/O. Unfortunately, however, most existing systems do not focus on disk I/O aspects and are vulnerable to performance degradation when the scale of input matrices and intermediate data grows large. To address this problem, we present a new out-of-core matrix computation system called PreVision. The PreVision system can achieve optimal buffer replacement by leveraging the deterministic characteristics of data access patterns, and it can also avoid redundant I/O operations by proactively evicting the pages that are no longer referenced. Through extensive evaluations, we demonstrate that PreVision outperforms the existing out-of-core matrix computation systems and significantly reduces disk I/O operations.
Maximum k-Plex Computation: Theory and Practice
Authors: Chang Lijun , Yao Kai
Published: March 2024

The k-plex model relaxes the clique model by allowing each vertex to miss up to k neighbors, including the vertex itself. A 1-plex is a clique. Many exact algorithms have been recently designed for finding the k-plex with the largest number of vertices, known as the maximum k-plex computation problem. However, all the existing algorithms, except BS, has the trivial worst-case time complexity of O*(2n) when ignoring polynomial factors. On the other hand, although BS improves the time complexity to O*(βkn) where βk < 2 is a constant depending only on k, its practical performance is not satisfactory. In this paper, we study the maximum k-plex computation problem from both theory and practice. We first propose two new reduction rules and a new branching rule and prove that the base of the exponential time complexity is reduced to γk when the new reduction and branching rules are incorporated into a standard backtracking algorithm; here γk < βk. We then design a two-stage approach kPlexT to improve the exponent of the time complexity by separating the search of large k-plexes from the search of small ones. We prove that kPlexT runs in O*((α Δ)k+1 γ_kα) time when the maximum k-plex size Ωk(G) is at least 2k-1, and in O*((α Δ)k+1 γ_kα + min(γkn, n2k-2)) time otherwise; here, α is the degeneracy and Δ is the maximum degree of the input graph. We also prove that with slight modification, kPlexT runs in O*((αΔ)k+1 (k+1)α+k-Ωk(G)) time when ømega_k(G) ≥ 2k-1. Finally, we propose another reduction rule and a better initialization method to improve the practical performance of kPlexT. Extensive empirical studies demonstrate that kPlexT achieves state-of-the-art practical performance. We also show that our improved time complexity carries over to other related problems such as enumerating all maximal k-plexes, quasi-cliques, and k-biplexes.
DoppelGanger++: Towards Fast Dependency Graph Generation for Database Replay
Authors: Lee Wonseok , Ha Jaehyun , Han Wook-Shin , Park Changgyoo , Park Myunggon , Han Juhyeng , Lee Juchang
Published: March 2024

A database replay system (DRS) captures workloads on a production system and then replays them in a test system to test various system changes, avoiding any risk before realizing them in production. The dependency graph generation in a DRS is crucial in preserving output determinism while maximizing concurrency. The state-of-the-art dependency graph generation algorithm deployed in a commercial DBMS uses a generate-and-prune strategy. It first generates a dependency graph by performing backward scans for each request in a workload. It then prunes all redundant edges using an expensive, transitive reduction algorithm. However, we notice that this generates a large dependency graph that contains many redundant edges and its worst-case time complexity is quadratic to the number of requests in a workload. In order to solve these challenging problems, we formally propose four classes of dependency graphs for DRSs. We then present a stateful single forward scan algorithm, SSFS, to generate any class of dependency graphs by performing a single scan over all requests while succinctly maintaining states. Here, states refer to information that is stored and maintained for efficient dependency graph generation. We also propose the parallel SSFS to utilize the computation power with multi-core CPUs while balancing the loads. We implemented our DRS in a leading commercial DBMS. Extensive experiments using the TPC-C, SD benchmarks, and a real-world customer workload show that our DRS significantly improves the dependency graph generation time by up to two orders of magnitude, compared to the state-of-the-art.
In-Database Data Imputation
Authors: Perini Massimo , Nikolic Milos
Published: March 2024

Missing data is a widespread problem in many domains, creating challenges in data analysis and decision making. Traditional techniques for dealing with missing data, such as excluding incomplete records or imputing simple estimates (e.g., mean), are computationally efficient but may introduce bias and disrupt variable relationships, leading to inaccurate analyses. Model-based imputation techniques offer a more robust solution that preserves the variability and relationships in the data, but they demand significantly more computation time, limiting their applicability to small datasets.

This work enables efficient, high-quality, and scalable data imputation within a database system using the widely used MICE method. We adapt this method to exploit computation sharing and a ring abstraction for faster model training. To impute both continuous and categorical values, we develop techniques for in-database learning of stochastic linear regression and Gaussian discriminant analysis models. Our MICE implementations in PostgreSQL and DuckDB outperform alternative MICE implementations and model-based imputation techniques by up to two orders of magnitude in terms of computation time, while maintaining high imputation quality.
Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents
Authors: Butcher Bradley , Zilka Miri , Hron Jiri , Cook Darren , Weller Adrian
Published: March 2024

From science to law enforcement, many research questions are answerable only by poring over a large amount of unstructured text documents. While people can extract information from such documents with high accuracy, this is often too time-consuming to be practical. On the other hand, automated approaches produce nearly-immediate results, but are not reliable enough for applications where near-perfect precision is essential. Motivated by two use cases from criminal justice, we consider the benefits and drawbacks of various human-only, human–machine, and machine-only approaches. Finding no tool well suited for our use cases, we develop a human-in-the-loop method for fast but accurate extraction of structured data from unstructured text. The tool is based on automated extraction followed by human validation, and is particularly useful in cases where purely manual extraction is not practical. Testing on three criminal justice datasets, we find that the combination of the computer speed and human understanding yields precision comparable to manual annotation while requiring only a fraction of time, and significantly outperforms the precision of all fully automated baselines.
False Positives and Deceptive Errors in SQL Assessment: A Large-Scale Analysis of Online Judge Systems
Authors: Wang Jinshui , Chen Shuguang , Tang Zhengyi , Lin Pengchen , Wang Yupeng
Published: March 2024

Online Judge Systems (OJSs) play a crucial role in evaluating SQL programming skills. However, OJSs may not accurately evaluate students’ queries as the error-detection capabilities of test sets are insufficient, resulting in false positives that can mislead students and hinder their learning. This study analyzes a large-scale OJS’s evaluation dataset and identifies more than 110,000 (1.94%) false-positive queries. It also validates existing SQL error categorization and reveals a new type of logical error called deceptive error, which occurs when students construct queries that pass specific test cases but fail to solve the actual problem. This type of error has been overlooked in previous research and can provide new insights into how to improve OJSs by enhancing test cases and feedback. This study contributes to the understanding of assessment and evaluation practices and processes in programming education, particularly the contribution that OJSs make to student learning and to course, staff, and institutional development. It also suggests error prevention and detection techniques that can improve the effectiveness and fairness of OJSs in programming education and competitions.
Sourcebook update: RBC hemolysis studies using a simple modified blood film technique
Authors: Al-Kaleel Ali , Al-Gialani Lubna
Published: March 2024

This study presents an innovative teaching approach for understanding osmosis and its effects on red blood cells. Using a simple, modified blood film technique, students can visually observe and engage with the dynamic process of osmosis. This hands-on method enhances learning, making complex physiological concepts accessible and practical. Ideal for resource-limited settings, it bridges theoretical knowledge and practical application, transforming physiology education.
Red blood cells function as reservoirs of tumor DNA
Authors: Thompson Jeffrey C. , Li Sue , Jose Joshua S. , Predina Jarrod , Gupta Aasha , Eruslanov Evgeniy , Singhal Sunil , Albelda Steven M. , Mangalmurti Nilam S.
Published: March 2024

We present a novel method for lung cancer detection by revealing RBCs as a reservoir for tumor DNA, overcoming the limitations of current circulating tumor ctDNA methodologies. By demonstrating that RBCs can capture tumor DNA, including critical mutations found in lung cancer, we provide a promising, biopsy-free avenue for early cancer diagnostics. This discovery opens up exciting possibilities for developing RBC-based diagnostic tools, significantly enhancing the sensitivity and clinical utility of noninvasive cancer detection.
Renal vascular control during normothermia and passive heat stress does not differ between healthy younger men and women
Authors: Freemas Jessica A. , Worley Morgan L. , Gabler Mikaela C. , Hess Hayden W. , Goss Curtis S. , Baker Tyler B. , Johnson Blair D. , Chapman Christopher L. , Schlader Zachary J.
Published: March 2024

The mechanisms underlying greater heat-induced acute kidney injury risk in men versus women remain unknown. This study examined renal vascular control, including both vasodilatory (oral protein load) and vasoconstrictor (cold presser test) responses, during normothermia and heat stress and compared these responses between men and women. The results indicated that in both conditions neither renal vasodilatory nor vasoconstrictor responses differ between younger men and younger women.
Cyclooxygenase products contribute to the exaggerated exercise pressor reflex evoked by static muscle contraction in male UCD-type 2 diabetes mellitus rats
Authors: Samora Milena , Huo Yu , Stanhope Kimber L. , Havel Peter J. , Kaufman Marc P. , Harrison Michelle L. , Stone Audrey J.
Published: March 2024

We compared the pressor and cardioaccelerator responses to static muscle contraction before and after inhibition of cyclooxygenase (COX) activity within the contracting hindlimb in decerebrate, unanesthetized type 2 diabetic mellitus (T2DM) and healthy rats. The pressor responses to muscle contraction were attenuated after peripheral inhibition of COX activity in T2DM but not in healthy rats. We concluded that COX products partially contribute to the exaggerated pressor reflex in those with T2DM.
A Single High-Sensitivity Cardiac Troponin T Strategy for Ruling Out Myocardial Infarction
Authors: Gilje Patrik , Mohammad Moman A. , Roos Andreas , Ekelund Ulf , Björk Jonas , Lindahl Bertil , Holzmann Martin , Mokhtari Arash
Published: March 2024

Background. Ruling out acute myocardial infarction (AMI) in the emergency department (ED) is challenging. Studies have shown that a high-sensitivity cardiac troponin T (hs-cTnT) <5 ng/L or <6 ng/L at presentation (0 h) can be used to rule out AMI. The objective of this study was to identify whether an even higher hs-cTnT threshold can be used for a safe rule out of AMI in the ED. Methods. The derivation cohort consisted of 24,973 ED patients with a primary complaint of chest pain. In this cohort, we identified the highest concentration of 0 h hs-cTnT that corresponded to a negative predictive value (NPV) of ≥99.5% for the primary endpoint of AMI/all-cause death within 30 days and the secondary endpoint of all-cause death within one year. The results were validated in two cohorts consisting of 132,021 and 1167 ED chest pain patients. Results. The 0 h hs-cTnT threshold corresponding to a NPV of ≥99.5% for the primary endpoint was <9 ng/L (NPV: 99.6% and 95% CI: 99.5–99.7). This cutoff provided a sensitivity of 96.2% (95% CI: 95.2–97.1) and identified 59.7% of the patients as low risk compared to 35.8% and 43.9% with a 0 h hs-cTnT <5 ng/L and <6 ng/L, respectively. The results were similar in the validation cohorts and seemed to perform even better in patients where the 0 h hs-cTnT was measured >3 h after symptom onset and in those with a nonischemic ECG and nonhigh risk history. Conclusions. A 0 h hs-cTnT cutoff of <9 ng/L safely rules out AMI/death within 30 days in a majority of chest pain patients and is a more effective strategy than the currently recommended <5 ng/L and <6 ng/L cutoffs. This trial is registered with NCT03421873.
The Effect of Canagliflozin on High‐Density Lipoprotein Cholesterol and Angiopoietin‐Like Protein 3 in Type 2 Diabetes Mellitus
Authors: Liu Simo , Ke Jing , Feng Xiaotong , Wang Zongwei , Wang Xin , Yang Longyan , Zhao Dong
Published: March 2024

Background. Diabetes mellitus is often accompanied by dyslipidemia. Sodium‐glucose cotransporter‐2 (SGLT2) inhibitors, as a novel therapeutic agent for the treatment of type 2 diabetes mellitus (T2DM), have been reported to exert effects on lipid, while the results remain controversial. This study is aimed at exploring the effect of SGLT2 inhibitor canagliflozin on lipid profile. Methods. This study was a single‐center, open‐label, nonrandomized, prospective study. Metformin (500 mg three times per day) or canagliflozin (100 mg, once daily) was administered for 12 weeks. Fasting blood samples were collected before and 12 weeks after treatment. Serum lipid profile levels and angiopoietin‐like protein 3 (ANGPTL3) were determined. In animal experiment, C57BL/6 J mice were divided into three groups including control, STZ + HFD, and STZ + HFD + canagliflozin. Lipid profile and plasma ANGPTL3 level were measured after 12 week’s treatment. Moreover, the expression of ANGPTL3 was detected in the liver tissues. Results. There was a decreased trend in low‐density lipoprotein cholesterol (LDL‐c) and triglycerides (TG) after canagliflozin treatment, while canagliflozin significantly increased high‐density lipoprotein cholesterol (HDL‐c) level and decreased plasma ANGPTL3 level. In addition, the expression of ANGPTL3 in liver tissues decreased obviously in diabetic mice with canagliflozin treatment. Conclusions. Canagliflozin increases HDL‐c level and suppresses ANGPTL3 expression in patients with T2DM and diabetic mice. The reduction of ANGPTL3 may contribute to the increase of HDL‐c. However, the specific mechanism needs further research. This trial is registered with ChiCTR1900021231.
The Mesolevel Economy in Nineteenth-Century England and Wales: Applying Input-Output Accounting and Spatial Interaction Modelling to the Historical Study
Authors: Solomon Guy S. , Wilson Alan G.
Published: March 2024

This paper is offered as a contribution to understanding historical trade. The method of input-output modelling is utilised to evaluate the evolution of cities (and their associated regions) in England and Wales between 1851 and 1911. The construction of input-output accounts for each city region is based on “heroic” data assumptions, which enable the construction of a demonstration model illustrating a new iterative approach to historical analysis. In its current application, the model enables estimates to be made of mesolevel trade between cities, which enhances our analysis of urban evolution in this period.
Addressing Kidney Transplant Shortage: The Potential of Kidney Paired Exchanges in Jordan
Authors: Al-Thnaibat Mohammad H. , Balaw Mohammad K. , Al-Aquily Mohammed K. , Ghannam Reem A. , Mohd Omar B. , Alabidi Firas , Alabidi Suzan , Hussein Fadi , Rawashdeh Badi
Published: March 2024

Jordan performed the Middle East’s first living-donor kidney transplant in 1972. In 1977, the country became one of the first Arab countries to regulate organ donation and transplantation. Despite these early advances in living donor transplantation, Jordan’s organ donation after brain death program remains inactive, making it challenging to meet organ demand and placing many patients on long transplant waiting lists. As of 2020, only 14.2% of the patients with end-stage kidney disease have access to a living donor. The scarcity of compatible living donors exacerbates Jordan’s organ shortage, leaving patients with extended waits and uncertain transplant prospects. Due to the lack of living donors and the inactive brain death donation program, additional options are needed to meet organ demand. Kidney paired exchange (KPE), emerges as a potential solution to the problem of donor shortage and donor-recipient incompatibility. By allowing living donors to direct their donated organs to different compatible recipients, KPE offers the promise of expanding transplant opportunities for patients without suitable living donors. However, the current Jordanian law restricting living kidney donation to fifth-degree relatives further limits the pool of potential donors, aggravating the organ shortage situation. This article explores the feasibility of implementing KPE in Jordan and proposes an approach to implementing KPE in Jordan, considering ethical and legal aspects to substantially increase kidney transplants.