bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global research priorities for intrauterine suction and sponge tools for postpartum haemorrhage management in low-income and middle-income countries: a modified Delphi approach
Authors: Walker Dilys , Shin Linda , Santos Nicole , Butrick Elizabeth , Durocher Jill , Miller Suellen , Amsalu Ribka , Wanyoro Anthony 
Published: May 2024

IntroductionPostpartum haemorrhage (PPH) remains the leading cause of maternal mortality and morbidity globally. Innovative PPH management tools have emerged using suction and sponge tamponade but currently lack substantial evidence. Broader understanding and collaborative research prioritisation are needed, especially in low-income and middle-income countries (LMICs), where the burden of PPH-related mortality is highest. We aimed to describe the current state of evidence and to solicit stakeholder input to identify research priorities related to emerging tools for PPH management.MethodsWe used a four-phase modified Delphi approach to identify research priorities for emerging suction and sponge tools. In phase 1, we conducted a literature review and key informant interviews (KIIs) with 19 stakeholders. In phase 2, we distributed an online survey, receiving 66 responses. In phase 3, we virtually convened an expert panel of stakeholders (n=24) and a separate midwife-only focus group to discuss preliminary results and draft research questions. In phase 4, we surveyed our expert panel (n=37) for prioritisation of research questions. Surveys were disseminated via Research Electronic Data Capture while KIIs and the expert convening were held virtually.ResultsParticipants included clinicians, researchers, policy-makers, funders and tool developers from high-income and LMIC settings. The prioritisation process narrowed our focus from six tools to four, all of which were top-ranked priorities in phase 4. Stakeholders emphasised efficacy research in comprehensive emergency obstetric and newborn care facilities. Stakeholders stressed the importance of understanding adverse event risks. The urgency in conducting research on cost, provider ease of use and acceptability and patient experience differed between individuals from high-income versus LMIC settings.ConclusionAll four tools prioritised in this process have the potential to improve PPH management in LMICs. A coordinated research agenda is necessary to confirm safety and efficacy and to determine which tools are most appropriate for specific LMIC settings.
ZFYVE19 deficiency: a ciliopathy involving failure of cell division, with cell death
Authors: Yang Jing , Zhang Ya-Nan , Wang Ren-Xue , Hao Chen-Zhi , Qiu Yiling , Chi Hao , Luan Wei-Sha , Tang HongYi , Zhang Xiu-Juan , Sun XuXu , Sheps Jonathan A , Ling Victor , Cao Muqing , Wang Jian-she 
Published: May 2024

Background and aimsVariants inZFYVE19underlie a disorder characterised by progressive portal fibrosis, portal hypertension and eventual liver decompensation. We aim to create an animal model to elucidate the pathogenic mechanism.MethodsZfyve19knockout (Zfyve19−/−) mice were generated and exposed to different liver toxins. Their livers were characterised at the tissue, cellular and molecular levels. Findings were compared with those in wild-type mice and in ZFYVE19-deficient patients.ZFYVE19knockout and knockdown retinal pigment epithelial-1 cells and mouse embryonic fibroblasts were generated to study cell division and cell death.ResultsTheZfyve19−/−mice were normal overall, particularly with respect to hepatobiliary features. However, when challenged with α-naphthyl isothiocyanate,Zfyve19−/−mice developed changes resembling those in ZFYVE19-deficient patients, including elevated serum liver injury markers, increased numbers of bile duct profiles with abnormal cholangiocyte polarity and biliary fibrosis. Failure of cell division, centriole and cilia abnormalities, and increased cell death were observed in knockdown/knockout cells. Increased cell death and altered mRNA expression of cell death-related signalling pathways was demonstrated in livers fromZfyve19−/−mice and patients. Transforming growth factor-β (TGF-β) and Janus kinase-Signal Transducer and Activator of Transcription 3 (JAK-STAT3) signalling pathways were upregulated in vivo, as were chemokines such as C-X-C motif ligands 1, 10 and 12.ConclusionsOur findings demonstrated that ZFYVE19 deficiency is a ciliopathy with novel histological features. Failure of cell division with ciliary abnormalities and cell death activates macrophages and may thus lead to biliary fibrosis via TGF-β pathway in the disease.
Span of control and well-being outcomes among hospital frontline managers: too much to handle?
Authors: Hansen Ane-Kathrine Lundberg , Jacobsen Christian Bøtcher , Dalgaard Vita Ligaya 
Published: May 2024

PurposeTo examine the consequences of broader spans of control for well-being outcomes among frontline managers.MethodHealthcare managers were surveyed in collaboration with the Central Denmark Region. The response rate was 74.5%. Using regression analysis, we investigate how span of control is associated with outcomes related to well-being understood as perceived stress, burnout, job satisfaction, satisfaction with the work environment, intention to quit their current job and work–life balance.FindingsSpan of control may be an important factor in establishing well-being among frontline managers in the Danish hospital sector on several parameters. Span of control is associated the strongest with work–life balance and intention to quit, least but significantly with perceived stress and not significantly with burnout.Practical implicationsWe recommend that healthcare organisations consider whether it could be more optimal to reduce the span of control for some managers. Furthermore, we recommend that future studies pay attention to span of control and provide stronger causal evidence about its impact on healthcare workers.
POST 21st CENTURY STUDIES OF PROPERTIES AND DYNAMICS OF SURFACES DEVELOPED THROUGH DIFFERENT PURE AND COMPETITIVE GROWTH MODELS IN 1+1 AND 2+1 DIMENSIONS: A REVIEW
Authors: NINORIA S. Z. , BANERJEE D. 
Published: May 2024

With the advent of the semiconductor age and later the age of nanotechnology, the thin film and coating field have established their importance and reasons for doing in-depth studies. Different sophisticated physical techniques, like chemical vapor deposition, sputtering, evaporation, molecular beam epitaxy, etc., and the conventional spin coating or dip coating, have been employed to get thin films of specific materials/compounds. Of all these, physical techniques are particularly preferred for their ability to develop good quality thin film with high uniformity. In the field of experimental material science, there are tremendous efforts in thin film development and the study of their different properties. The properties include topological, electrical, electronic, optical, or other. At the same time, though less explored, there are developments of theoretical understanding regarding the basic mechanism of thin film growth by specific growth mechanism. In doing this, the basic mechanism of thin film growth has been categorized into different broad classes with specific features. The main features include the time dependence of interface width and values of different scaling exponents. Apart from these, studies also addressed different morphological, optical, or electrical properties of the as-grown thin films of specific material. This paper gathers the existing literature that reports the simulation-based theoretical studies related to thin film growth by different algorithms like random deposition, ballistic deposition, random deposition with surface relaxation, or their different combinations. Not only that, but the paper also summarizes different reports related to the simulation-based prediction of the material properties. As the topic is relatively new, the collection of reports added in the last 20 years has been considered. The paper has different sections. Section 1 gives basic introductory ideas related to thin film development and its properties. Sections 2 and 3 , respectively, deal with the basics of different existing models and the basic steps involved in the simulation. Section 4 gathers the related results reported by various researchers, followed by a short discussion and final concluding remarks. Undoubtedly, this paper is the first review work in this field and thus will serve as an invaluable source of information for future workers.
Missing Data Imputation with Uncertainty-Driven Network
Authors: Wang Jianwei , Zhang Ying , Wang Kai , Lin Xuemin , Zhang Wenjie 
Published: May 2024

We study the problem of missing data imputation, which is a fundamental task in the area of data quality that aims to impute the missing data to achieve the completeness of datasets. Though the recent distribution-modeling-based techniques (e.g., distribution generation and distribution matching) can achieve state-of-the-art performance in terms of imputation accuracy, we notice that (1) they deploy a sophisticated deep learning model that tends to be overfitting for missing data imputation; (2) they directly rely on a global data distribution while overlooking the local information.
Driven by the inherent variability in both missing data and missing mechanisms, in this paper, we explore the uncertain nature of this task and aim to address the limitations of existing works by proposing an u<u>N</u>certainty-driven netw<u>O</u>rk for <u>M</u>issing data <u>I</u>mputation, termed NOMI. NOMI has three key components, i.e., the retrieval module, the neural network gaussian process imputator (NNGPI) and the uncertainty-based calibration module. NOMI~ runs these components sequentially and in an iterative manner to achieve a better imputation performance. Specifically, in the retrieval module, NOMI~ retrieves local neighbors of the incomplete data samples based on the pre-defined similarity metric. Subsequently, we design NNGPI~ that merges the advantages of both the Gaussian Process and the universal approximation capacity of neural networks. NNGPI~ models the uncertainty by learning the posterior distribution over the data to impute missing values while alleviating the overfitting issue. Moreover, we further propose an uncertainty-based calibration module that utilizes the uncertainty of the imputator on its prediction to help the retrieval module obtain more reliable local information, thereby further enhancing the imputation performance. We also demonstrate that our NOMI~ can be reformulated as an instance of the well-known Expectation Maximization (EM) algorithm, highlighting the strong theoretical foundation of our proposed methods. Extensive experiments are conducted over 12 real-world datasets. The results demonstrate the excellent performance of NOMI in terms of both accuracy and efficiency.
Banzhaf Values for Facts in Query Answering
Authors: Abramovich Omer , Deutch Daniel , Frost Nave , Kara Ahmet , Olteanu Dan 
Published: May 2024

Quantifying the contribution of database facts to query answers has been studied as means of explanation. The Banzhaf value, originally developed in Game Theory, is a natural measure of fact contribution, yet its efficient computation for select-project-join-union queries is challenging. In this paper, we introduce three algorithms to compute the Banzhaf value of database facts: an exact algorithm, an anytime deterministic approximation algorithm with relative error guarantees, and an algorithm for ranking and top-k. They have three key building blocks: compilation of query lineage into an equivalent function that allows efficient Banzhaf value computation; dynamic programming computation of the Banzhaf values of variables in a Boolean function using the Banzhaf values for constituent functions; and a mechanism to compute efficiently lower and upper bounds on Banzhaf values for any positive DNF function.
We complement the algorithms with a dichotomy for the Banzhaf-based ranking problem: given two facts, deciding whether the Banzhaf value of one is greater than of the other is tractable for hierarchical queries and intractable for non-hierarchical queries.
We show experimentally that our algorithms significantly outperform exact and approximate algorithms from prior work, most times up to two orders of magnitude. Our algorithms can also cover challenging problem instances that are beyond reach for prior work.
Continual Observation of Joins under Differential Privacy
Authors: Dong Wei , Chen Zijun , Luo Qiyao , Shi Elaine , Yi Ke 
Published: May 2024

The problem of continual observation under differential privacy has been studied extensively in the literature. However, all existing works, with the exception of [28,51], have only studied the simple counting query and its derivatives. Join queries, which are arguably the most important class of queries in relational databases, have only been considered in [28,51], but the solutions offered there have two limitations: First, they only support a few specific graph pattern queries, which are special cases of joins. Second, they require hard degree/frequency constraints on the graph/database instance, and the privatized query answers have errors proportional to these constraints.
In this paper, we propose a new differentially private mechanism for continual observation of joins that overcomes these two limitations. Our mechanism supports arbitrary joins and predicates, and do not require any constraints to be given in advance, even over an infinite stream. More importantly, it yields an error that is proportional to the actual maximum degree/frequencies in the graph/database instance at the current time of observation. Such an instance-specific utility guarantee is much preferred for the continual observation problem, where the database size and the query answer may change significantly over time.
FairHash: A Fair and Memory/Time-efficient Hashmap
Authors: Shahbazi Nima , Sintos Stavros , Asudeh Abolfazl 
Published: May 2024

Hashmap is a fundamental data structure in computer science. There has been extensive research on constructing hashmaps that minimize the number of collisions leading to efficient lookup query time. Recently, the data-dependant approaches, construct hashmaps tailored for a target data distribution that guarantee to uniformly distribute data across different buckets and hence minimize the collisions. Still, to the best of our knowledge, none of the existing technique guarantees group fairness among different groups of items stored in the hashmap.
Therefore, in this paper, we introduce FairHash, a data-dependant hashmap that guarantees uniform distribution at the group-level across hash buckets, and hence, satisfies the statistical parity notion of group fairness. We formally define, three notions of fairness and, unlike existing work, FairHash satisfies all three of them simultaneously. We propose three families of algorithms to design fair hashmaps, suitable for different settings. Our ranking-based algorithms reduce the unfairness of data-dependant hashmaps without any memory-overhead. The cut-based algorithms guarantee zero-unfairness in all cases, irrespective of how the data is distributed, but those introduce an extra memory-overhead. Last but not least, the discrepancy-based algorithms enable trading off between various fairness notions. In addition to the theoretical analysis, we perform extensive experiments to evaluate the efficiency and efficacy of our algorithms on real datasets. Our results verify the superiority of FairHash compared to the other baselines on fairness at almost no performance cost.
Implementation Strategies for Views over Property Graphs
Authors: Han Soonbo , Ives Zachary G. 
Published: May 2024

The need to query complex interactions and relationships has motivated interest in property graph database platforms. For some graph applications, graph views are required to abstract the data, e.g., to capture individual-level vs. organization-level relationships; or show single computational steps vs. composite workflows. Emerging efforts to standardize graph query languages have developed semantics and language constructs for graph views.
This paper considers the task of implementing such views using rewriting techniques --- both using existing property graph DBMSs and converting to relational RDBMSs. We consider both virtual and materialized views, ways of rewriting queries, and structures for indexing data. We also note a common use case of graph views, which involves preserving a graph except minor local transformations; we develop novel extensions and semantics for this. We evaluate and compare the performance of our techniques under a variety of workloads, and we compare existing graph and relational DBMS platforms.
Scalable Distributed Inverted List Indexes in Disaggregated Memory
Authors: Widmoser Manuel , Kocher Daniel , Augsten Nikolaus 
Published: May 2024

Memory disaggregation separates compute (CPU) and main memory resources into disjoint physical units to enable elastic and independent scaling. Connected via high-speed RDMA-enabled networks, compute nodes can directly access remote memory. This setting often requires complex protocols with many network roundtrips as memory nodes have near-zero compute power.
In this paper, we design a scalable distributed inverted list index for disaggregated memory architectures. An inverted list index maps a set of terms to lists of documents that contain this term. Current solutions either partition the index horizontally or vertically with severe limitations in the disaggregated memory setting due to data and access skew, high network latency, or out-of-memory errors. Our method partitions lists into fixed-size blocks and spreads them across the memory nodes to balance skewed accesses. Block-based list processing keeps the memory footprint of compute nodes low and masks latency by interleaving remote accesses with expensive list operations. In addition, we propose efficient updates with optimistic concurrency control and read-write conflict detection. Our experiments confirm the efficiency and scalability of our method.
Targeting Chemoresistance in Advanced Bladder Cancers with a Novel Adjuvant Strategy
Authors: Seremak Juliette R. , Gupta Kunj Bihari , Bonigala Sunilkanth , Liu Elise , Marshall Brendan , Zhi Wenbo , Bokhtia Riham M. , Panda Siva S. , Lokeshwar Vinata B. , Lokeshwar Bal L. 
Published: May 2024

Abstract
Advanced urinary bladder cancer is characterized by rapid progression and development of therapy resistance. About 30% of the patients are diagnosed with high-grade tumors (grade &gt; T2a). A typical nonsurgical treatment is systemic chemotherapy using cisplatin (C) and gemcitabine (G). However, treatment failure and subsequent disease progression are common in treated patients, and adjuvant therapies are not significantly effective. The therapeutic potential of a molecular hybrid of ursolic acid (UA), a pentacyclic-triterpene conjugated to N-methyl piperazine (UA4), was tested on both naïve (WT) and gemcitabine-resistant (GemR) variants of two human invasive bladder cancer cell lines, 5637 and T24. UA4 killed 5637 (4 µmol/L), T24 (4 µmol/L) WT, and GemR cells in vitro at equal potency. Pretreatment with UA4 followed by G synergistically killed WT and GemR cells by &gt;50% compared with G followed by UA4. Oral gavage of UA4 (100 mg/kg) inhibited WT and GemR tumor growth in athymic mice. UA4 + G was more effective against GemR tumors than either drug alone. Studies revealed cytotoxic autophagy as a mechanism of UA4 cytotoxicity. UA4 induced moderate apoptosis in T24 but not in 5637 cells. Mitochondrial integrity and function were most affected by UA4 because of high levels of reactive oxygen species, disruption of mitochondrial membrane, and cell cycle arrest. These effects were enhanced in the UA4 + G combination. UA4 was well-tolerated in mice, and oral gavage led to a serum level &gt;1 µmol/L with no systemic toxicity. These results show the potential of UA4 as a nontoxic alternative treatment for high-grade bladder cancer.
Cardiomyopathy in First-Degree Relatives of Patients Presenting With Acute Myocarditis: Prevalence and Prognostic Significance
Authors: Boulet Jacinthe , Lakdawala Neal K. , Christiansen Mia Nielsen , Schou Morten , Køber Lars , Gustafsson Finn , Gislason Gunnar H. , Torp-Pedersen Christian , Andersson Charlotte 
Published: May 2024

BACKGROUND:
Acute myocarditis has been genetically linked to dilated cardiomyopathy (DCM), but the clinical significance remains uncertain. We investigated the prevalence and long-term prognosis of DCM and heart failure (HF) among unselected patients hospitalized with acute myocarditis and their first-degree relatives compared with an age- and sex-matched cohort.

METHODS:
This was an observational study utilizing the Danish nationwide registries, where all patients with a first-time myocarditis diagnosis from 1995 to 2018 were identified and matched (on birth year and sex) with 10 controls from the general population.

RESULTS:

Totally 3176 patients with acute myocarditis and 31 760 controls were included (median age, 49.8 [Q1–Q3, 32.5–70.2] years; 35.6% female). At baseline, patients with myocarditis had a higher prevalence of DCM (7 [0.2%] versus 8 [0.0%]) and HF (336 [10.6%] versus 695 [2.2%]) than controls;
P
<0.0001 for both. Patients with myocarditis more often had siblings with DCM (12 [0.4%] versus 17 [0.05%]) or HF (36 [1.1%] versus 89 [0.3%]);
P
<0.0001, odds ratios 7.09 (3.38–14.85) and 2.92 (1.25–6.80), respectively, whereas parental DCM and HF did not differ among patients with myocarditis and controls. Patients with myocarditis had greater 20-year incidence of DCM, HF, and all-cause mortality (0.5% [0.3%–0.9%], 15% [13%–17%], and 47% [44%–50%]) compared with controls (0.06% [0.03%–0.11%], 6.8% [6.4%–7.3%], and 34% [33%–35%];
P
<0.0001). Having a first-degree relative with DCM or HF was associated with increased long-term mortality among the patients with myocarditis (hazard ratio, 1.40 [1.11–1.77]) but not among the controls (hazard ratio, 0.90 [0.81–1.01];
P
difference
=0.0008).

CONCLUSIONS:
Acute myocarditis aggregates with DCM within families, where it carries a worsened prognosis. A differential association between parents and siblings (with sibling preponderance) could suggest that additional environmental factors are important for myocarditis development even in predisposed individuals.