bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving quality of care by standardising patient data collection in electronic medical records in an oncology department in Spain
Authors: Alonso-Jáudenes Curbera Guillermo , Gómez-Randulfe Rodríguez Martín Igor , Alonso de Castro Beatriz , Silva Díaz Sofía , Parajó Vázquez Iria , Gratal Paula , López López Rafael , García Campelo Rosario 
Published: June 2024

BackgroundEvaluation of quality of care in oncology is key in ensuring patients receive adequate treatment. American Society of Clinical Oncology’s (ASCO) Quality Oncology Practice Initiative (QOPI) Certification Program (QCP) is an international initiative that evaluates quality of care in outpatient oncology practices.MethodsWe retrospectively reviewed free-text electronic medical records from patients with breast cancer (BR), colorectal cancer (CRC) or non-small cell lung cancer (NSCLC). In a baseline measurement, high scores were obtained for the nine disease-specific measures of QCP Track (2021 version had 26 measures); thus, they were not further analysed. We evaluated two sets of measures: the remaining 17 QCP Track measures, as well as these plus other 17 measures selected by us (combined measures). Review of data from 58 patients (26 BR; 18 CRC; 14 NSCLC) seen in June 2021 revealed low overall quality scores (OQS)—below ASCO’s 75% threshold—for QCP Track measures (46%) and combined measures (58%). We developed a plan to improve OQS and monitored the impact of the intervention by abstracting data at subsequent time points.ResultsWe evaluated potential causes for the low OQS and developed a plan to improve it over time by educating oncologists at our hospital on the importance of improving collection of measures and highlighting the goal of applying for QOPI certification. We conducted seven plan–do–study–act cycles and evaluated the scores at seven subsequent data abstraction time points from November 2021 to December 2022, reviewing 404 patients (199 BR; 114 CRC; 91 NSCLC). All measures were improved. Four months after the intervention, OQS surpassed the quality threshold and was maintained for 10 months until the end of the study (range, 78–87% for QCP Track measures; 78–86% for combined measures).ConclusionsWe developed an easy-to-implement intervention that achieved a fast improvement in OQS, enabling our Medical Oncology Department to aim for QOPI certification.
Factors associated with proximal femoral fractures in older adults during hospital stay: a cross-sectional study
Authors: Moriwaki Mutsuko , Takae Asuka , Toba Mikayo , Sasaki Miki , Ogata Yasuko , Obayashi Satoshi , Kakehashi Masayuki , Fushimi Kiyohide 
Published: June 2024

BackgroundProximal femoral fractures in older adults affect prognosis, quality of life and medical expenses. Therefore, identifying patients with an elevated risk for proximal femoral fractures and implementing preventive measures to mitigate their occurrence are crucial.ObjectiveThis study aimed to develop an accurate in-hospital fracture prediction model that considers patients’ daily conditions and medical procedure status. Additionally, it investigated the changes in their conditions associated with fractures during hospital stays.DesignA retrospective observational study.Setting(s)Acute care hospitals in Japan.ParticipantsParticipants were 8 514 551 patients from 1321 medical facilities who had been discharged between April 2018 and March 2021 with hip and proximal femoral fractures.MethodsLogistic regression analysis determined the association between patients’ changes in their ability to transfer at admission and the day before fracture, and proximal femoral fracture during hospital stays.ResultsPatients were classified into fracture and non-fracture groups. The mean ages were 77.4 (SD: 7.7) and 82.6 (SD: 7.8), and the percentages of women were 42.7% and 65.3% in the non-fracture and fracture groups (p<0.01), respectively. Model 4 showed that even if a patient required partial assistance with transfer on the day before the fracture, the fracture risk increased in each category of change in ability to transfer in the following order: ‘declined’, ‘improved’ and ‘no change’.ConclusionsPatients showing improved ability to transfer during their hospitalisation are at a higher risk for fractures. Monitoring patients’ daily conditions and tracking changes can help prevent fractures during their hospital stays.
High accuracy model for HBsAg loss based on longitudinal trajectories of serum qHBsAg throughout long-term antiviral therapy
Authors: Fan Rong , Zhao Siru , Niu Junqi , Ma Hong , Xie Qing , Yang Song , Xie Jianping , Dou Xiaoguang , Shang Jia , Rao Huiying , Xia Qi , Liu Yali , Yang Yongfeng , Gao Hongbo , Sun Aimin , Liang Xieer , Yin Xueru , Jiang Yongfang , Yu Yanyan , Sun Jian , Naoumov Nikolai V , Hou Jinlin 
Published: June 2024

ObjectiveHepatitis B surface antigen (HBsAg) loss is the optimal outcome for patients with chronic hepatitis B (CHB) but this rarely occurs with currently approved therapies. We aimed to develop and validate a prognostic model for HBsAg loss on treatment using longitudinal data from a large, prospectively followed, nationwide cohort.DesignCHB patients receiving nucleos(t)ide analogues as antiviral treatment were enrolled from 50 centres in China. Quantitative HBsAg (qHBsAg) testing was prospectively performed biannually per protocol. Longitudinal discriminant analysis algorithm was used to estimate the incidence of HBsAg loss, by integrating clinical data of each patient collected during follow-up.ResultsIn total, 6792 CHB patients who had initiated antiviral treatment 41.3 (IQR 7.6–107.6) months before enrolment and had median qHBsAg 2.9 (IQR 2.3–3.3) log10IU/mL at entry were analysed. With a median follow-up of 65.6 (IQR 51.5–84.7) months, the 5-year cumulative incidence of HBsAg loss was 2.4%. A prediction model integrating all qHBsAg values of each patient during follow-up, designated GOLDEN model, was developed and validated. The AUCs of GOLDEN model were 0.981 (95% CI 0.974 to 0.987) and 0.979 (95% CI 0.974 to 0.983) in the training and external validation sets, respectively, and were significantly better than those of a single qHBsAg measurement. GOLDEN model identified 8.5%–10.4% of patients with a high probability of HBsAg loss (5-year cumulative incidence: 17.0%–29.1%) and was able to exclude 89.6%–91.5% of patients whose incidence of HBsAg loss is 0. Moreover, the GOLDEN model consistently showed excellent performance among various subgroups.ConclusionThe novel GOLDEN model, based on longitudinal qHBsAg data, accurately predicts HBsAg clearance, provides reliable estimates of functional hepatitis B virus (HBV) cure and may have the potential to stratify different subsets of patients for novel anti-HBV therapies.
Universal Credit receipt among working-age patients who are accessing specialist mental health services: results from a novel data linkage study
Authors: Stevelink Sharon A M , Bakolis Ioannis , Dorrington Sarah , Downs Johnny , Leal Ray , Madan Ira , Phillips Ava , Geiger Ben , Hotopf Matthew , Fear Nicola T 
Published: June 2024

BackgroundIn 2013, Universal Credit (UC) was introduced by the UK Government. Understanding of how UC provision is allocated among people with mental disorders, and its intersection with protected characteristics is limited. This study aimed to explore (1) how UC receipt, including UC conditionality regime, varied among users of specialist mental health services between 2013 and 2019 and (2) associations between sociodemographic and diagnostic patient characteristics and UC receipt.MethodsWorking-age individuals who had accessed specialist mental health services were included if they had their mental health record data successfully linked with administrative benefits data. Associations between sociodemographic, diagnostic patient characteristics and UC receipt were explored using logistic regression models.ResultsOf the 143 715 patients, 26.9% had received UC between 2013 and 2019. Four in five patients were allocated to the searching for work conditionality regime during their time on UC. Females were less likely to have received UC (adjusted OR (AOR) 0.87, 95% CI 0.85 to 0.89) than males, and UC receipt decreased with age. Black patients (AOR 1.39, 95% CI 1.34 to 1.44) and patients from mixed and multiple ethnic backgrounds (AOR 1.27, 95% CI 1.18 to 1.38) had a higher likelihood of UC receipt than White patients. UC receipt was lower among patients diagnosed with severe mental illness compared with other psychiatric diagnoses (AOR 0.74, 95% CI 0.71 to 0.77).ConclusionOne in four specialist mental health service users had received UC and a large majority were subject to conditionality. The temporality of UC conditionality and mental health service presentation needs further exploration.
Kindness in healthcare leadership and management: an evaluation and analysis of the concept
Authors: Dyar Rebecca , Mattick Karen , Griffiths Andrew 
Published: June 2024

BackgroundHealthcare leadership and management impacts every patient journey and every staff experience. Good leadership results in positive outcomes. Kindness is an understudied and underused leadership strategy. The research questions addressed in this study are the following: (1) Does kindness in healthcare leadership and management currently meet the criteria of a mature concept?; (2) Using concept analysis methodology, can we develop our understanding of kindness within this context?MethodsA systematic search of the peer-reviewed literature was conducted to inform a concept evaluation, followed by a concept analysis. Search terms consisted of ‘leader*’ or ‘manage*’ and ‘kindness’; databases searched comprised MEDLINE, HMIC, SPP, APA PsycInfo and CINAHL. Data extraction and thematic analysis of the data were performed manually according to concept analysis principles.ResultsThe 10 papers included from the search suggested that within healthcare leadership and management, kindness is an ‘emerging’ rather than a ‘mature’ concept. Concept analysis demonstrated a cluster of recurring attributes, allowing a theoretical definition to be put forth.ConclusionsDespite being a commonly used lay term, kindness in the context of healthcare leadership and management is not yet a mature concept. Work developing this concept is needed to validate the proposed theoretical definition. Observational studies and systematic review of the grey literature are recommended.
Unruh effect using Doppler shift method in DSR framework
Authors: Rajagopal Vishnu 
Published: June 2024

AbstractWe study the Unruh effect in doubly special relativity (DSR) framework by generalising the Doppler-shift method to DSR. For both the scalar and Dirac particles, we observe a deviation in the power spectrum of Unruh radiation from the standard Bose–Einstein and Fermi–Dirac distributions, respectively, due to the presence of the frame independent length scale of DSR. We further show that this deviation results in the modification of Unruh temperature which then depends non-linearly on the proper acceleration in DSR.
Quasinormal modes in noncommutative Schwarzschild black holes: a spectral analysis
Authors: Batic Davide , Dutykh Denys 
Published: June 2024

AbstractWe present a comprehensive analysis of quasinormal modes (QNMs) for noncommutative geometry-inspired Schwarzschild black holes, encompassing both non-extreme and extreme cases. By employing a spectral method, we calculate the QNMs in the context of scalar, electromagnetic, and gravitational perturbations. Our findings not only challenge previous claims in the literature regarding the instability of these black holes but also reveal remarkable stability for both non-extreme and extreme Schwarzschild black holes under various perturbations.
Continuous variable entanglement between propagating optical modes using optomechanics
Authors: Gopinath Greeshma , Li Yong , Davuluri Sankar 
Published: June 2024

AbstractIn this study, a method for entangling two spatially separated output laser fields from an optomechanical cavity is proposed. In the existing standard methods, entanglement is created by driving the two-mode squeezing part of the linearized optomechanical interaction;, however our method generates entanglement using the quantum back-action nullifying meter technique. As a result, entanglement can be generated outside the blue sideband frequency in both resolved and unresolved sideband regimes. We further show that the system is stable in the entire region where the Duan criterion for inseparability is fulfilled. The effect of thermal noise on the generated entanglement is examined. Finally, we compare this technique with standard methods for entanglement generation using optomechanics.
Boosting Compiler Testing by Injecting Real-World Code
Authors: Li Shaohua , Theodoridis Theodoros , Su Zhendong 
Published: June 2024

We introduce a novel approach for testing optimizing compilers with code from real-world applications. The main idea is to construct well-formed programs by fusing multiple code snippets from various real-world projects. The key insight is backed by the fact that the large volume of real-world code exercises rich syntactical and semantic language features, which current engineering-intensive approaches like random program generators are hard to fully support.
To construct well-formed programs from real-world code, our approach works by (1) extracting real-world code at the granularity of function, (2) injecting function calls into seed programs, and (3) leveraging dynamic execution information to maintain the semantics and build complex data dependencies between injected functions and the seed program. With this idea, our approach complements the existing generators by boosting their expressiveness via fusing real-world code in a semantics-preserving way.
We implement our idea in a tool, Creal, to test C compilers. In a nine-month testing period, we have reported 132 bugs to GCC and LLVM, two of the most popular and well-tested C compilers.
At the time of writing, 121 of them have been confirmed as unknown bugs, and 101 of them have been fixed. Most of these bugs were miscompilations, and many were recognized as long-latent and critical.
Our evaluation results evidently demonstrate the significant advantage of using real-world code to stress-test compilers. We believe this idea will benefit the general compiler testing direction and will be directly applicable to other compilers.
SMT Theory Arbitrage: Approximating Unbounded Constraints using Bounded Theories
Authors: Mikek Benjamin , Zhang Qirun 
Published: June 2024

SMT solvers are foundational tools for reasoning about constraints in practical problems both within and outside program analysis. Faster SMT solving improves the performance of practical tools and expands the set of tractable problems. Existing approaches to improving solver performance either focus on general algorithms applied below the level of individual theories, or focus on optimizations within a single theory. Unbounded constraints in which the number of possible variable values is infinite, such as real numbers and integers, pose a particularly difficult challenge for solvers. Bounded constraints in which the set of possible values is finite, such as bitvectors and floating-point numbers, on the other hand, are decidable and have been the subject of extensive performance improvement efforts.
This paper introduces a theory arbitrage: we transform unbounded constraints, which are often expensive to solve, into bounded constraints, which are typically cheaper to solve. By converting unbounded problems into bounded ones, theory arbitrage takes advantage of better performance on bounded constraints and unlocks optimization techniques that only apply to bounded theories. The transformation is achieved by harnessing a novel abstract interpretation strategy to infer bounds. The bounded transformed constraint is then an underapproximation of the semantics of the unbounded original. We realize our method for the theories of integers and real numbers with a practical tool (STAUB). Our evaluation demonstrates that theory arbitrage alone can speed up individual constraints by orders of magnitude and achieve up to a 1.4× speedup on average across nonlinear integer benchmarks. Furthermore, it enables the use of the recent compiler optimization-based technique SLOT for unbounded SMT theories, unlocking a further speedup of up to 3×. Finally, we incorporate STAUB into a practical termination proving tool and observe an overall 9% improvement in performance.
Associated Effects: Flexible Abstractions for Effectful Programming
Authors: Lutze Matthew , Madsen Magnus 
Published: June 2024

We present associated effects, a programming language feature that enables type
classes to abstract over the effects of their function signatures, allowing each
type class instance to specify its concrete effects.
Associated effects significantly increase the flexibility and expressive power
of a programming language that combines a type and effect system with type
classes. In particular, associated effects allow us to
(i) abstract over total and partial functions, where partial functions may throw exceptions,
(ii) abstract over immutable data structures and mutable data structures that have heap effects, and
(iii) implement adaptors that combine type classes with algebraic effects.
We implement associated effects as an extension of the Flix programming language
and refactor the Flix Standard Library to use associated effects, significantly
increasing its flexibility and expressive power. Specifically, we add associated
effects to 11 type classes, which enables us to add
28 new type class instances.
Reducing Static Analysis Unsoundness with Approximate Interpretation
Authors: Laursen Mathias Rud , Xu Wenyuan , Møller Anders 
Published: June 2024

Static program analysis for JavaScript is more difficult than for many other programming languages. One of the main reasons is the presence of dynamic property accesses that read and write object properties via dynamically computed property names. To ensure scalability and precision, existing state-of-the-art analyses for JavaScript mostly ignore these operations although it results in missed call edges and aliasing relations.
We present a novel dynamic analysis technique named approximate interpretation that is designed to efficiently and fully automatically infer likely determinate facts about dynamic property accesses, in particular those that occur in complex library API initialization code, and how to use the produced information in static analysis to recover much of the abstract information that is otherwise missed.
Our implementation of the technique and experiments on 141 real-world Node.js-based JavaScript applications and libraries show that the approach leads to significant improvements in call graph construction. On average the use of approximate interpretation leads to 55.1% more call edges, 21.8% more reachable functions, 17.7% more resolved call sites, and only 1.5% fewer monomorphic call sites. For 36 JavaScript projects where dynamic call graphs are available, average analysis recall is improved from 75.9% to 88.1% with a negligible reduction in precision.
Maximum Consensus Floating Point Solutions for Infeasible Low-Dimensional Linear Programs with Convex Hull as the Intermediate Representation
Authors: Aanjaneya Mridul , Nagarakatte Santosh 
Published: June 2024

This paper proposes a novel method to efficiently solve infeasible low-dimensional linear programs (LDLPs) with billions of constraints and a small number of unknown variables, where all the constraints cannot be satisfied simultaneously. We focus on infeasible linear programs generated in the RLibm project for creating correctly rounded math libraries. Specifically, we are interested in generating a floating point solution that satisfies the maximum number of constraints. None of the existing methods can solve such large linear programs while producing floating point solutions.
We observe that the convex hull can serve as an intermediate representation (IR) for solving infeasible LDLPs using the geometric duality between linear programs and convex hulls. Specifically, some of the constraints that correspond to points on the convex hull are precisely those constraints that make the linear program infeasible. Our key idea is to split the entire set of constraints into two subsets using the convex hull IR: (a) a set X of feasible constraints and (b) a superset V of infeasible constraints. Using the special structure of the RLibm constraints and the presence of a method to check whether a system is feasible or not, we identify a superset of infeasible constraints by computing the convex hull in 2-dimensions. Subsequently, we identify the key constraints (i.e., basis constraints) in the set of feasible constraints X and use them to create a new linear program whose solution identifies the maximum set of constraints satisfiable in V while satisfying all the constraints in X. This new solver enabled us to improve the performance of the resulting RLibm polynomials while solving the corresponding linear programs significantly faster.
Static Posterior Inference of Bayesian Probabilistic Programming via Polynomial Solving
Authors: Wang Peixin , Yang Tengshun , Fu Hongfei , Li Guanyan , Ong C.-H. Luke 
Published: June 2024

In Bayesian probabilistic programming, a central problem is to estimate the normalised posterior distribution (NPD) of a probabilistic program with conditioning via score (a.k.a. observe) statements. Most previous approaches address this problem by Markov Chain Monte Carlo and variational inference, and therefore could not generate guaranteed outcomes within a finite time limit. Moreover, existing methods for exact inference either impose syntactic restrictions or cannot guarantee successful inference in general.In this work, we propose a novel automated approach to derive guaranteed bounds for NPD via polynomial solving. We first establish a fixed-point theorem for the wide class of score-at-end Bayesian probabilistic programs that terminate almost-surely and have a single bounded score statement at program termination. Then, we propose a multiplicative variant of Optional Stopping Theorem (OST) to addressscore-recursiveBayesian programs where score statements with weights greater than one could appear inside a loop. Bayesian nonparametric models, enjoying a renaissance in statistics and machine learning, can be represented by score-recursive Bayesian programs and are difficult to handle due to an integrability issue. Finally, we use polynomial solving to implement our fixed-point theorem and OST variant. To improve the accuracy of the polynomial solving, we further propose a truncation operation and the synthesis of multiple bounds over various program inputs. Our approach can handle Bayesian probabilistic programs with unbounded while loops and continuous distributions with infinite supports. Experiments over a wide range of benchmarks show that compared with the most relevant approach (Beutner et al., PLDI 2022) for guaranteed NPD analysis via recursion unrolling, our approach is more time efficient and derives comparable or even tighter NPD bounds. Furthermore, our approach can handle score-recursive programs which previous approaches could not.