bluuebunny/crossref_metadata_2025 huggingface dataset:
GTS: GPU-based Tree Index for Fast Similarity Search
Authors: Zhu Yifan , Ma Ruiyao , Zheng Baihua , Ke Xiangyu , Chen Lu , Gao Yunjun
Published: May 2024

Similarity search, the task of identifying objects most similar to a given query object under a specific metric, has gathered significant attention due to its practical applications. However, the absence of coordinate information to accelerate similarity search and the high computational cost of measuring object similarity hinder the efficiency of existing CPU-based methods. Additionally, these methods struggle to meet the demand for high throughput data management. To address these challenges, we propose GTS, a GPU-based tree index designed for the parallel processing of similarity search in general metric spaces, where only the distance metric for measuring object similarity is known. The GTS index utilizes a pivot-based tree structure to efficiently prune objects and employs list tables to facilitate GPU computing. To efficiently manage concurrent similarity queries with limited GPU memory, we have developed a two-stage search method that combines batch processing and sequential strategies to optimize memory usage. The paper also introduces an effective update strategy for the proposed GPU-based index, encompassing streaming data updates and batch data updates. Additionally, we present a cost model to evaluate search performance. Extensive experiments on five real-life datasets demonstrate that GTS achieves efficiency gains of up to two orders of magnitude over existing CPU baselines and up to 20x efficiency improvements compared to state-of-the-art GPU-based methods.
Hyper: A High-Performance and Memory-Efficient Learned Index via Hybrid Construction
Authors: Zhang Shunkang , Qi Ji , Yao Xin , Brinkmann André
Published: May 2024

Learned indexes use machine learning techniques to improve index construction. However, they often face a fundamental trade-off between performance and memory consumption, especially in dynamic environments with frequent insert and delete operations. This trade-off stems from the construction approaches used in learned indexes: The top-down approach increases performance at the cost of significant memory overhead, while the bottom-up approach focuses on memory efficiency but introduces performance issues due to prediction errors. % A unified solution that simultaneously optimizes performance and memory consumption in dynamic data management scenarios is therefore highly desirable.

We propose Hyper, a highly efficient learned index with a novel two-phase hybrid construction approach. Our approach combines bottom-up construction for leaf nodes with top-down construction for inner nodes to achieve an optimal balance between performance and memory consumption. Hyper effectively handles concurrent writes and structure adjustments without sacrificing query performance. We evaluated Hyper on both simple and complex real-world datasets and compared it to seven state-of-the-art learned indexes and several traditional data structures for dynamic workloads. The evaluation results show that Hyper achieves a remarkable performance boost of up to 3.75× with significantly reduced index memory consumption of up to 1610× in the single-thread evaluation. In high concurrency scenarios, Hyper even achieves improvements up to 5.73×, 3.72×, and 3.99× in read-only, read-write, and write-only workloads.
MCR-Tree: An Efficient Index for Multi-dimensional Core Search
Authors: Luo Chengyang , Zhu Yifan , Liu Qing , Gao Yunjun , Chen Lu , Xu Jianliang
Published: May 2024

Core models are well-known cohesive subgraph models for graph analytics that have been extensively studied. These models, including (α, β)-core, (k, l)-core, and k -core, have multiple parameters, which are referred to as multi-dimensional cores. The goal of core search is to retrieve subgraphs from a graph that satisfy the semantics of a given core model. In the literature, various indexes have been proposed to accelerate core search for different core models. However, existing indexes suffer from several limitations, such as significant redundancy, lack of scalability with respect to the number of parameters, limited generality, and inadequate consideration of index maintenance. To address these limitations, in this paper, we thoroughly investigate the problem of multi-dimensional core search. In particular, we propose a novel index called MCR-Tree, which can be applied to different core models. The MCR-Tree projects all vertices into a multi-dimensional space by leveraging the skyline corenesses, which are indexed by an R-tree. Furthermore, the MCR-Tree integrates the connectivity information of subgraphs into the nodes of the R-tree to facilitate multi-dimensional core search. Subsequently, an efficient branch-and-bound algorithm is designed to perform multi-dimensional core search by traversing the MCR-Tree. Additionally, we discuss how to maintain the MCR-Tree for graph updates. Extensive experiments demonstrate that the MCR-Tree is up to two orders of magnitude smaller than existing indexes and the MCR-Tree-based core search method is up to an order of magnitude faster than existing algorithms.
PreLog: A Pre-trained Model for Log Analytics
Authors: Le Van-Hoang , Zhang Hongyu
Published: May 2024

Large-scale software-intensive systems often produce a large volume of logs to record runtime status and events for troubleshooting purposes. The rich information in log data enables a variety of system management and diagnosis tasks. Over the years, many approaches have been proposed for automated log analytics. However, these approaches usually design separate models for each specific task, which cannot be generalized to other tasks. They are also not robust when dealing with logs from heterogeneous sources. In this paper, we propose PreLog, a novel pre-trained model for log analytics. PreLog is pre-trained on a large amount of unlabelled log data to capture the semantic meaning of logs. We design two log-specific pre-training objectives, including entry-level and sequence-level objectives, which enable PreLog to better understand the hidden structure and semantics of logs. To perform downstream log analytics tasks, we leverage a prompt tuning paradigm to convert downstream tasks' objectives into a similar form as the pre-training stage. We have conducted extensive experiments on two main log analytics tasks (i.e., log parsing and log-based anomaly detection). Experimental results show that PreLog achieves better or comparable results in comparison with the state-of-the-art, task-specific approaches. PreLog is cost-effective and can be uniformly applied to many log analytics tasks through the prompt tuning paradigm.
Query Refinement for Diverse Top-k Selection
Authors: Campbell Felix S. , Silberstein Alon , Stoyanovich Julia , Moskovitch Yuval
Published: May 2024

Database queries are often used to select and rank items as decision support for many applications. As automated decision-making tools become more prevalent, there is a growing recognition of the need to diversify their outcomes. In this paper, we define and study the problem of modifying the selection conditions of an ORDER BY query so that the result of the modified query closely fits some user-defined notion of diversity while simultaneously maintaining the intent of the original query. We show the hardness of this problem and propose a mixed-integer linear programming (MILP) based solution. We further present optimizations designed to enhance the scalability and applicability of the solution in real-life scenarios. We investigate the performance characteristics of our algorithm and show its efficiency and the usefulness of our optimizations.
ROME: Robust Query Optimization via Parallel Multi-Plan Execution
Authors: Wei Ziyun , Trummer Immanuel
Published: May 2024

We present a non-intrusive approach to robust query processing that can be used on top of any SQL execution engine. To reduce the risk of selecting highly sub-optimal query plans, we execute multiple plans in parallel. Query processing finishes once the first of these plans finishes execution.

Plans are selected to be complementary in terms of the intermediate results they generate. This increases robustness to cardinality estimation errors, making cost prediction hard, that concern a subset of candidate results. We present multiple cost-based approaches to selecting plans for robust execution. The first approach uses a simple cost model, based on diversity of intermediate results. The second approach features a probabilistic model, approximating expected execution overheads, given uncertainty on true intermediate result sizes. We present greedy and exhaustive algorithms to select optimal plans according to those cost models. The experiments demonstrate that executing multiple plans in parallel is preferable over executing single plans that are occasionally sub-optimal, as well as over several baselines.
Towards Metric DBSCAN: Exact, Approximate, and Streaming Algorithms
Authors: Mo Guanlin , Song Shihong , Ding Hu
Published: May 2024

DBSCAN is a popular density-based clustering algorithm that has many different applications in practice. However, the running time of DBSCAN in high-dimensional space or general metric space (\em e.g., clustering a set of texts by using edit distance) can be as large as quadratic in the input size. Moreover, most of existing accelerating techniques for DBSCAN are only available for low-dimensional Euclidean space. In this paper, we study the DBSCAN problem under the assumption that the inliers (the core points and border points) have a low intrinsic dimension (which is a realistic assumption for many high-dimensional applications), where the outliers can locate anywhere in the space without any assumption. First, we propose a k-center clustering based algorithm that can reduce the time-consuming labeling and merging tasks of DBSCAN to be linear. Further, we propose a linear time approximate DBSCAN algorithm, where the key idea is building a novel small-size summary for the core points. Also, our algorithm can be efficiently implemented for streaming data and the required memory is independent of the input size. Finally, we conduct our experiments and compare our algorithms with several popular DBSCAN algorithms. The experimental results suggest that our proposed approach can significantly reduce the computational complexity in practice.
Unstructured Data Fusion for Schema and Data Extraction
Authors: Chen Kaiwen , Koudas Nick
Published: May 2024

Recently, there has been significant interest in extracting actionable insights from the abundance of unstructured textual data. In this paper, we introduce a novel problem, which we term Semistructured Schema and Data Extraction (SDE). This task aims to enhance and complete tables using information discovered from textual repositories, given partial table specifications in the form of queries. To effectively solve SDE, several challenges must be overcome, which involve transforming the partial table specifications into effective queries, retrieving relevant documents, discerning values for partially specified attributes, inferring additional attributes, and constructing an enriched output table while mitigating the influence of false positives from the retrieval.

We propose an end-to-end pipeline for SDE, which consists of a retrieval component and an augmentation component, to address each of the challenges. In the retrieval component, we serialize the partial table specifications into a query and employ a dense passage retrieval algorithm to extract the top-k relevant results from the text repository. Subsequently, the augmentation component ingests the output documents from the retrieval phase and generates an enriched table. We formulate this table enrichment task as a unique sequence-to-sequence task, distinct from traditional approaches, as it operates on multiple documents during generation. Utilizing an interpolation mechanism on the encoder output, our model maintains a nearly constant context length while automatically prioritizing the importance of documents during the generation.

Due to the novelty of SDE, we establish a validation methodology, adapting and expanding existing benchmarks with the use of powerful large language models. Our extensive experiments show that our method achieves high accuracy in enriching query tables through multi-document fusion, while also surpassing baseline methods in both accuracy and computational efficiency.
Evaluation of Parameters and Nozzle Tip Damage after Clinical Use of Three Hydrophilic Intraocular Lens Injector Models
Authors: Zhang Lu , Schickhardt Sonja , Merz Patrick , Auffarth Gerd Uwe
Published: May 2024

Purpose. To assess the nozzle tip damage and the parameters of three different hydrophilic intraocular lens (IOL) injector models. Methods. After routine cataract surgeries at the University Eye Hospital Heidelberg, all the used IOL injectors were collected from the operating room and sent to our laboratory. Nozzle tip damage was assessed under a microscope and graded as follows: no damage (grade 0), slight scratches (1), deep scratches (2), extensions (3), cracks (4), and bursts (5). Each damage grade was assigned a score from 0 to 5, and the total damage score for each injector system was calculated and compared. Nozzle tip parameters (diameters and areas), plunger tip parameters, and tip angles were also measured in each model. Results. The damage scores were (median, Q3-Q1): 1 (1-1) for Accuject, 1 (1-1) for Bluemixs, and 1 (1-1) for RayOne. There was no statistically significant difference in the damage scores between the study groups (P>0.05). The outer cross-sectional vertical and horizontal diameters were 1.69 and 1.69 mm for Accuject, 1.69 and 1.69 mm for Bluemixs, and 1.70 and 1.71 mm for RayOne. Plunger tip areas were 0.78 mm2 for Accjuect, 0.74 mm2 for Bluemixs, and 0.43 mm2 for RayOne. Plunger tip area/inner cross-sectional area of the nozzle tip (%) was 31.2% for RayOne, 66.7% for Accuject, and 63.8% for Bluemixs. The tip angles for three injector models were 56° (Accuject), 56° (Bluemixs), and 44° (RayOne). Conclusions. All the injector models showed mild to moderate damage to the nozzle tip after IOL implantation, even with smaller diameter tips. RayOne resulted in the lowest ratio between plunger tip area and inner cross-sectional area of the nozzle tip and a better distribution of damage categories than the other two groups. All three injector models had relatively small tip parameters. If smaller incisions are required in certain patients, smaller tip parameters should be considered.
Method of Selection of Rural Territory in the Development of a Territorial Diagnosis
Authors: Suárez-Roldán Carolina , Hernández-Atencia Yelena , Méndez-Giraldo Germán
Published: May 2024

Purpose. The development of general‐scale diagnoses is one of the main reasons why policies, lines of action, and strategies do not adequately respond to the dynamics and needs of rural territories. Consequently, there is a recognition of the need to select rural spaces that require a territorial diagnosis due to their particular characteristics and unfavorable conditions toward balanced development. Method. We design four phases in the rural space selection method. In the first phase, of the method’s development, we identify the formation of Technical Working Table(s) as a key factor. The second phase involves a systematic literature review from local sources, tailored to the application context. In the third phase, variables measuring rural space selection are identified and validated, determining the rural zones of interest. Finally, in the fourth phase, two mathematical techniques, the analytic hierarchy process (AHP) and weighted ratings, are proposed. These techniques enable quantification of options and provide information to facilitate the decision‐making process for selecting rural spaces. Results. The first phase involves the formation of the Technical Working Table (TWT), identified as a key factor in the design and operation of the proposed research method. The Technical Working Table (TWT) comprises nine institutional actors committed to regional development, who participated in both the design and implementation of the proposed methodology. Similarly, in the phase of systematic literature review, 43 articles are selected, identifying 21, 18, and 26 variables of major significance in the ecological, social, and economic dimensions of the study area. Subsequently, in the third phase, collaboration with the TWT is employed to validate and select the nine variables constituting the criteria for rural space selection. In the final phase, results from applying the two mathematical techniques quantifying the rural space selection are obtained.​ Conclusions. The rural space selection method enhances the development of specific territorial diagnoses, given the unique characteristics and dynamics of the study area.
Propagation‐Based Train Rescheduling under Recoverable Delay Disturbances
Authors: Zhang Jun , Wu Shuyao , Deng Shejun , Ye Yuling
Published: May 2024

Real‐time train rescheduling for high‐speed railway (HSR) is a pivotal technique in HSR transportation to efficiently recover train operation under disturbance scenarios. This paper aims to put forward an integrated resolving and rescheduling method considering network delay propagation. A tree‐based conflict resolution mechanism is first established, with delicate considerations on the strategy’s adaptability under different conflict scenarios. By inputting the scheduled arrival and departure time under different conflict resolution strategies, the timetable optimizing model aims to look for an optimal solution with minimal weighted train delay and average train adjustments under necessary technical and empirical constraints solved by a combined algorithm of Pareto optimality and Nash equilibrium, where the feasible solution space is narrowed in advance by a depth‐first pruning algorithm. The performance of this coordinated train rescheduling approach is validated by a typical section disturbance in a regional HSR network administrated by the Shanghai Bureau. The results show that the proposed method can well utilizes timetable buffers and organizes train avoidance. The delay propagation characteristics are also simultaneously estimated based on the indicators of cumulative delay and instantaneous delay, which are established considering the spatio‐temporal difference between the scheduled and planned timetables, in order to verify the coordination between resolution strategies and train running delays.
Left Ventricular Strain, Arch Angulation, and Velocity-Time Integral Ratio Improve Performance of a Clinical Pathway for Fetal Diagnosis of Neonatal Coarctation of the Aorta
Authors: Phillips Aaron Anthony , Punn Rajesh , Algaze Claudia , Blumenfeld Yair J. , Chock Valerie Y. , Kwiatkowski David M. , Quirin Amy , Tacy Theresa A. , Thorson Kelly , Maskatia Shiraz A.
Published: May 2024

Introduction: Neonatal presentation of coarctation of the aorta (CoA) is a potentially life-threatening condition that is difficult to diagnose in fetal life. We therefore sought to validate and compare novel metrics that may add diagnostic value for fetal CoA, including the diastolic to systolic aortic isthmus VTI ratio (VTId:VTIs), ascending aorta to descending aorta angle (AAo-DAo), transverse aorta to descending aorta angle (TAo-DAo), and LV longitudinal strain (LVS), then to evaluate whether these novel metrics improve specificity to identify fetuses at the highest risk for postnatal CoA without compromising sensitivity. Methods: Retrospective cohort study of fetuses followed a prospective clinical pathway and previously classified as mild, moderate, or high-risk for CoA based on standard fetal echo metrics. Novel metrics were retrospectively measured in a blinded manner. Results: Among fetuses with prenatal concern for CoA, VTId:VTIs, AAo-DAo angle, TAo-DAo angle, and LVS were significantly different between surgical and non-surgical cases (p < 0.01 for all variables). In the subgroup of moderate- and high-risk fetuses, the standard high-risk criteria (flow reversal at the foramen ovale or aortic arch) did not discriminate effectively between surgical and non-surgical cases. VTId:VTIs, AAo-Dao angle, Tao-DAo angle, and LVS all demonstrated greater discrimination than standard high-risk criteria, with specificity of 100% and PPV (positive predictive value) of 78–100%. Conclusions: The incorporation of novel metrics added diagnostic value to our clinical pathway for fetal CoA with higher specificity than the previous high-risk criteria. The incorporation of these metrics into the evaluation of fetuses at moderate- or high-risk for surgical CoA may improve prenatal counseling, allow for more consistent surgical planning, and ultimately optimize hospital resource allocation.
The Founding Pioneer Cytotechnologists: The Women Who Assisted George N. Papanicolaou, MD, PhD, Develop the Pap Test for Cervical Cancer Prevention
Authors: Elgert Paul A.
Published: May 2024

Background: The earliest cytotechnologists are largely unknown. Summary: In 1943, the book “Diagnosis of Uterine Cancer by the Vaginal Smear” by Papanicolaou and Traut recognized several women who have largely faded from memory. While Mary Papanicolaou and Charlotte Street are familiar names, others like Alberta Kuder and Huldah Boerker, who inadvertently laid the groundwork for the field of cytotechnology, remain obscure. There were also women like Christine Rassias and Adele Reboul who did not receive recognition. Notably, Mrs. Lady Mary G. Papanicolaou, despite her significant contributions both in the lab and at home since 1914, was not acknowledged in her husband’s work until the publication of his Atlas in 1954. Key Message: These women set the benchmark for future cytotechnologists, unknowingly shaping the profession as we know it today.
Das casas construídas na ficção: uma leitura do espaço em A cidade e as serras e São Bernardo
Authors: Otsuka Natasha Gonçalves
Published: May 2024

Cidade, serra e sertão compõem a geografia dos dois romances analisados: A cidade e as serras e São Bernardo, de Eça de Queirós e Graciliano Ramos, respectivamente. Em ambas as narrativas, a casa figura como elemento central do relato. Pretende-se discutir no presente trabalho as relações estabelecidas entre casa, geografia e os personagens da narrativa. Como aparato teórico, foram utilizados estudos de Gaston Bachelard, Michel Collot, Antônio Cândido e Godofredo de Oliveira Neto.
O Pensamento do Tremor
Authors: Gomes Elisângela Oliveira
Published: May 2024

Resenha da tradução  do livro  La Cohée du Lamentin de Édouard Glissant.
Therapeutic Avenues to Modulate B-Cell Function in Patients With Cardiovascular Disease
Authors: O’Brien James W. , Case Ayden , Kemper Claudia , Zhao Tian X. , Mallat Ziad
Published: May 2024

The adaptive immune system plays an important role in the development and progression of atherosclerotic cardiovascular disease. B cells can have both proatherogenic and atheroprotective roles, making treatments aimed at modulating B cells important therapeutic targets. The innate-like B-cell response is generally considered atheroprotective, while the adaptive response is associated with mixed consequences for atherosclerosis. Additionally, interactions of B cells with components of the adaptive and innate immune system, including T cells and complement, also represent key points for therapeutic regulation. In this review, we discuss therapeutic approaches based on B-cell depletion, modulation of B-cell survival, manipulation of both the antibody-dependent and antibody-independent B-cell response, and emerging immunization techniques.
T-Cell/B-Cell Interactions in Atherosclerosis
Authors: Jones Peter William , Mallat Ziad , Nus Meritxell
Published: May 2024

Atherosclerosis is a complex inflammatory disease in which the adaptive immune response plays an important role. While the overall impact of T and B cells in atherosclerosis is relatively well established, we are only beginning to understand how bidirectional T-cell/B-cell interactions can exert prominent atheroprotective and proatherogenic functions. In this review, we will focus on these T-cell/B-cell interactions and how we could use them to therapeutically target the adaptive immune response in atherosclerosis.
Love and Entwined Selves in the Medieval Tristan Tradition
Authors: Clarke Isabella
Published: May 2024

This essay examines the medieval presentation of emotions and selfhood through the lens of romantic love in Marie de France’s Chevrefoil and Thomas of Britain’s Tristran, as well as their Middle High German and Old Norse translations. The focus is on the alteration or destruction of a discrete self through the experience of romantic love. By drawing on both modern scientific understandings and medieval conceptualisations of love, the essay explores how an altered sense of self is central to experiencing and portraying the emotion. However, the exact degree and nature of this alteration varies in the different texts presented here, ranging from complete fusion in Gottfried von Strassburg’s Tristan to mutually supportive entwining in the Old Norse Geitarlauf and Tristrams saga ok Ísöndar.
CWRF Downscaling with Improved Land Surface Initialization Enhances Spring–Summer Seasonal Climate Prediction Skill in China
Authors: Zhang Han , Liang Xin-Zhong , Dai Yongjiu , Song Lianchun , Li Qingquan , Wang Fang , Zhang Shulei
Published: May 2024

This study investigates skill enhancement in operational seasonal forecasts of Beijing Climate Center’s Climate System Model through regional Climate–Weather Research and Forecasting (CWRF) downscaling and improved land initialization in China. The downscaling mitigates regional climate biases, enhancing precipitation pattern correlations by 0.29 in spring and 0.21 in summer. It also strengthens predictive capabilities for interannual anomalies, expanding skillful temperature forecast areas by 6% in spring and 12% in summer. Remarkably, during 7 of 10 years with relatively high predictability, the downscaling increases average seasonal precipitation anomaly correlations by 0.22 and 0.25. Additionally, the substitution of initial land conditions via a Common Land Model integration reduces snow cover and cold biases across the Tibetan Plateau and Mongolia–northeast China, consistently contributing to CWRF’s overall enhanced forecasting capabilities. Improved downscaling predictive skill is attributed to CWRF’s enhanced physics representation, accurately capturing intricate regional interactions and associated teleconnections across China, especially linked to the Tibetan Plateau’s blocking and thermal effects. In summer, CWRF predicts an intensified South Asian high alongside a strengthened East Asian jet compared to CSM, amplifying cold air advection and warm moisture transport over central to northeast regions. Consequently, rainfall distributions and interannual anomalies over these areas experience substantial improvements. Similar enhanced circulation processes elucidate skill improvement from land initialization, where the accurate specification of initial snow cover and soil temperature within sensitive regions persists in influencing local and remote circulations extending beyond two seasons. Our findings emphasize the potential of improving physics representation and surface initialization to markedly enhance regional climate predictions.
Impact of Assimilating Radar Solid Precipitation Data in the Canadian Precipitation Analysis System
Authors: Beaudry Florence L. , Bélair Stéphane , Thériault Julie M. , Khedhaouiria Dikra , Lespinas Franck , Michelson Daniel , Feng Pei-Ning , Aubry Catherine
Published: May 2024

The Canadian Precipitation Analysis (CaPA) system provides near-real-time precipitation analyses over Canada by combining observations with short-term numerical weather prediction forecasts. CaPA’s snowfall estimates suffer from the lack of accurate solid precipitation measurements to correct the first-guess estimate. Weather radars have the potential to add precipitation measurements to CaPA in all seasons but are not assimilated in winter due to radar snowfall estimate imprecision and lack of precipitation gauges for calibration. The main objective of this study is to assess the impact of assimilating Canadian dual-polarized radar-based snowfall data in CaPA to improve precipitation estimates. Two sets of experiments were conducted to evaluate the impact of including radar snowfall retrievals, one set using the high-resolution CaPA (HRDPA) with the currently operational quality control configuration and another increasing the number of assimilated surface observations by relaxing quality control. Experiments spanned two winter seasons (2021 and 2022) in central Canada, covering part of the entire CaPA domain. The results showed that the assimilation of radar-based snowfall data improved CaPA’s precipitation estimates 81.75% of the time for 0.5-mm precipitation thresholds. An increase in the probability of detection together with a decrease in the false alarm ratio suggested an improvement of the precipitation spatial distribution and estimation accuracy. Additionally, the results showed improvements for both precipitation mass and frequency biases for low precipitation amounts. For larger thresholds, the frequency bias was degraded. The results also indicated that the assimilation of dual-polarization radar data is beneficial for the two CaPA configurations tested in this study.
Recency of Suicide Attempt, Ideation, and Reattempt in the Emergency Department: Managing Youth With a Past Attempt
Authors: Wei August X. , Mournet Annabelle M. , Bridge Jeffrey A. , Ruch Donna A. , Pao Maryland , Horowitz Lisa M.
Published: May 2024

Objective

This study describes recency of suicide attempt (SA) and suicidal ideation (SI) at index emergency department (ED) visit and post‐ED‐discharge reattempt among pediatric patients.

Methods

Secondary analysis from the ED Screen for Teens at Risk for Suicide study included patients ages 12–17 who reported a past SA during screening and received a phone call 3‐month post‐ED‐discharge assessing reattempt. Logistic regressions tested past SA/SI recency as predictors of reattempt. Descriptive statistics on SA/SI recency and reattempt are provided.

Results

Sample included 351 patients reporting a past SA during screening (70% cisgender female, 59% White, 53% psychiatric chief complaint, mean [SD] age = 15.3 [1.5]). 17% (60/351) reattempted suicide post‐ED‐discharge. Compared to patients who attempted over a year ago, patients with recent SA within 3 months, especially 1 week before screening, had greater odds of reattempting (3 months: p < 0.05, adjusted odds ratio [adjOR] = 3.1 [1.1–10.4]; 1 week: p < 0.01, adjOR = 4.8 [1.7–16.2]). Patients with recent SI within 24 h before screening had greater odds of reattempting than those with no recent SI (adjOR = 2.8 [1.1–7.6]; p < 0.05). 94% (64/68) of patients with a SA from over a year ago and no recent SI did not reattempt at follow‐up.

Conclusions

Pediatric ED patients have greater risk of reattempting suicide post‐discharge if their last SA was within the past 3 months−especially 1 week−and when most recent SI occurred within 24 h. Conversely, patients reporting SA over a year ago with no recent SI may require less immediate intervention. Findings support universal suicide risk screening and clinical pathways that use recency of SA to inform disposition.
The Columbia Academy for Psychoanalytic Educators: A Pilot Program for Developing Analysts and Supervisors of Analytic Candidates
Authors: Graver Ruth , Glick Robert Alan , Stern Gloria , Ornstein Sharone , Cabaniss Deborah , Halperin Jane , Richardson Justin , Vaughan Susan C. , Cherry Sabrina
Published: May 2024

The Columbia Academy for Psychoanalytic Educators supports graduate analysts’ professional development at the Columbia University Center for Psychoanalytic Training and Research. In 2018, a pilot program was launched for faculty interested in analyzing and supervising candidates, whose aim is to support and educate those interested in taking on these essential training functions. The focus is on educating the educators, which is a significant departure from the historical focus on evaluation, vetting, and faculty hierarchies. In the process of developing and piloting the program, complex and long debated issues in psychoanalytic education and development were considered that are relevant to many institutes, including training of supervisors and analysts of candidates, addressing problematic faculty hierarchies, creating safety for those presenting clinical work to colleagues, building professional peer relationships, and engagement of faculty in time consuming and nonremunerative activities. The authors report on their experience developing and evaluating this pilot program.
Undergraduate Students’ Awareness of and Beliefs About Unusual End-of-Life Phenomena
Authors: Claxton-Oldfield Stephen , MacEachern Sara
Published: May 2024

One hundred and forty undergraduate students responded to an online survey investigating their awareness of and beliefs about 12 unusual end-of-life phenomena (EOLP). Three quarters or more of the students had heard about the following EOLP: deathbed visions (75%), after-death communications (84%), near-death experiences (86%), and dying people choosing their time of death (88%). Students were least aware of the phenomena of shapes leaving the body after death (30%) and clocks or watches stopping when someone dies (26%). The two most common sources of students’ knowledge about EOLP were from watching TV/movies (52–79%) and the internet (38–71%); the least common source was personal/direct experience with the EOLP (2–36%). Fifty-three percent of the students strongly agreed/agreed that EOLP are spiritual events, while 41% strongly agreed/agreed that there are medical explanations for EOLP. Suggestions for future research are offered.
Review Essay: Limits of the Numerical and the Personalized Measurement Trend in Mental Health Care
Authors: de Boer Nina S. , Runhardt Rosa W.
Published: May 2024

Limits of the Numerical calls for the (re)contextualization of the numerical in the social domain and emphasizes that using quantitative data has epistemic and practical/moral considerations that may not align. In this review essay, we evaluate these claims using a case study, viz. the personalized, clinical experience sampling method (ESM) in mental health care. This case study (1) nuances claims made in Limits of the Numerical regarding the generality and non-contextuality of numerical data, and (2) highlights two additional dimensions to the numerical that have been underexposed in the book (i.e., reactivity and Ballung concepts).
Thermal evolution of deeply buried lower Paleozoic strata and its influence on hydrocarbon accumulation in the Tarim Basin, Northwest China
Authors: Liu Yuchen , Gao Jian , Li Huili , Ma Anlai
Published: May 2024

The Ordovician carbonate reservoirs in the Tarim Basin are hotspots for oil and gas exploration in recent years. However, due to the lack of effective paleo-geothermometers in carbonate formations, thermal history studies have been greatly restricted. In this study, we reconstructed thermal history of Ordovician carbonate intervals in Tarim Basin by applying clumped isotopes, equivalent vitrinite reflectance ( Requ) and zircon (U–Th)/He ages as thermal indicators. The modeled results indicated that there are three phases of heat flow evolution in the Shuntuoguole low-uplift. (a) The gradual cooling stage during Ordovician-carboniferous. The heat flow is gradually decreasing during this period. (b) Rapidly raised stage in the early Permian period. The heat flow in Shunbei and Shuntuo area are raised rapidly during this period and the maximum is 51–65 mW/m2, but the SN3 well in Shunnan area increased slightly and the heat flow values of other single wells were still relatively stable. (c) The decline stage since Middle Permian. The tectonic activity is relatively stable and the geothermal heat flow is gradually reduced during this period, but the heat flow in Shunnan area is higher than the Shunbei and Shuntuo areas. Due to the control of thermal evolution, the dissolution of the Ordovician carbonate reservoir in Shuntuoguole area occurred earlier than the formation of large quantities of hydrocarbon materials, and the improvement of reservoir physical properties provided sufficient conditions for the late oil and gas filling, which was conducive to the preservation of large oil and gas reservoirs.
Losing Their Religion: Organizational Identity Hybridization of British Political Parties 1950–2015
Authors: Arora-Jonsson Stefan , Wezel Filippo Carlo , Karthikeyan Soorjith I , Barberio Vitaliano
Published: May 2024

Our research addresses how organizations manage a shift from a single to a hybrid identity, a question that the identity literature still is grappling with. We address this question by reflecting on how organizations develop hybrid identities in response to institutional decline. Identity hybridization, we predict, takes place in stages via strategies that gradually hybridize the identity. We study how British political parties hybridized their identities in response to the decline of social-class politics over the period 1950–2015. Quantitative and qualitative analyses of the identity projections of three political parties in their election manifestos provide support for our hypotheses.
Leveraging the Dominant Pole: How Champions of an Industry-Wide Environmental Alliance Navigate Coopetition Paradoxes
Authors: Slawinski Natalie , Smith Wendy K. , Van der Byl Connie A.
Published: May 2024

Companies increasingly collaborate with competitors to innovate, minimize risks, and address sustainability crises. However, these alliances often falter or fail due to challenges arising from coopetition paradoxes—contradictory yet interdependent tensions between competition and cooperation. Extant research predominantly focuses on addressing these paradoxes through seeking a stable balance between competition and cooperation; however, we lack in-depth processual understandings of how to navigate these paradoxes as they shift over time. To address this gap in the literature, we analyze longitudinal data over the 3 years it took to establish Canada’s Oil Sands Innovation Alliance (COSIA), the unlikely alliance across 13 competitive Canadian oil sands companies to improve their industry’s environmental performance. We noted the role of competition, which we label as the dominant pole—the more powerful of two paradoxical poles—and identify leveraging the dominant pole as a core mechanism for navigating intensifying coopetition paradoxes. Rather than diminishing the dominant competition pole, alliance champions leveraged competition to enable cooperation aided by a paradox mindset. These findings reorient coopetition scholarship away from seeking stability between the two forces, toward a processual understanding of how to navigate the shifting coopetition paradoxes in alliances over time.
Future of Global Electric Vehicle Supply Chain: Exploring the Impact of Global Trade on Electric Vehicle Production and Battery Requirements
Authors: Busch Pablo , Pares Francisco , Chandra Minal , Kendall Alissa , Tal Gil
Published: May 2024

Electric vehicle (EV) adoption is a key action toward reducing global greenhouse gas emissions from the transport sector, enabling a shift from a fossil fuel intensive on-road sector to a material intensive one, especially for critical minerals used in lithium-ion batteries: lithium, cobalt, and nickel. Recent literature has manly focused on forecasting future EV demand and subsequent global battery and critical mineral requirements without modeling which countries will produce the EVs. The Model for International Electric Vehicle Trade (MONET) is a policy-scenario model that combines up-to-date EV demand forecasts, light-duty vehicle global trade flows under different scenarios, and battery characterization to estimate future EV production and battery requirements per country. Results indicate that future EV global trade will be characterized by trade within regional blocks, with contrasting results: North America will be a big producer that will still require imports to meet their demand, Europe will be a big trade region within itself, Japan and South Korea will be big exporters of EVs, and China’s production could go almost entirely to satisfy their domestic supply. Different scenarios show variability according to changes in global trade flows, which are affected by economic and geopolitical events. A major insight reflected in MONET is that an increase in demand for EVs in one country does not translate to a proportional increase in production in the same country. MONET helps to inform which countries will be major producers of EVs by vehicle size, and the amount of battery capacity they will need to secure. Future expansion of MONET includes critical materials estimations based on future battery chemistry development.
Family–School Relationships and Exclusionary Discipline of Students With and Without Disabilities
Authors: An Zhe Gigi , Yang Hyunwoo
Published: May 2024

Using data extracted from the Parent and Family Involvement in Education Survey of the 2019 National Household Education Surveys Program, this study used a series of linear probability models to examine the association between family–school relationships and exclusionary discipline. The sample included 15,360 U.S. families of K–12 non-homeschooled and non-virtual school students. Results suggest that students with disabilities experienced significantly more expulsion and suspension and that their families were less satisfied with school and received significantly more individual contact from school for negative reasons. In addition, parent satisfaction with school and individual contacts from school to parent regarding positive behaviors or schoolwork and behavior problems were statistically significantly associated with exclusionary discipline after accounting for student characteristics, such as race, age, and gender. These associations between family–school relationships and exclusionary discipline did not differ by a student’s disability status.
A cabin assembly optimization method based on force and position coordination analysis
Authors: Wu Zhengtao , Huang Xiang , Li Shuanggao , Chu Wenmin
Published: May 2024

In existing automated docking assembly solutions for aerospace products, segmented docking surfaces suffer from machining errors and deformation, making assembly difficult. The aim of this study was to reduce the internal stresses in cabin assembly and maintain sufficient assembly accuracy. A cabin assembly optimization method was developed based on force–position coordination analysis. To address the interference problem of the cabin flange surface, a penalty-function-based reweighting iterative approximation method was constructed based on the square-hole characteristics of the docking. In the assembly verification, mechanism calibration and measurement field iterative compensation optimized the mechanism pose, and the accuracy of the pose adjustment component and the cabin assembly stress were tested. The experimental results show that the method proposed can reduce the interference problem during the assembly of a flange face and optimize the assembly stress while achieving assembly accuracy. The results for accuracy and interference force after flange face assembly were obtained; however, no feedback on the analytical method was obtained through the experimental results. Therefore, it is necessary to test further the propositions investigated. The preassembly analysis method for large cabin assemblies proposed optimizes the cabin assembly accuracy and internal stress under the deformation state of the assembly surface.
An interval programming method of earth-moon trajectory for manned lunar exploration mission under interval uncertainty
Authors: Yang Luyi , Li Haiyang , Zhang Jin
Published: May 2024

There are always uncertainties in practical engineering, and the design of the optimal Earth-Moon trajectory under uncertainties significantly reduces flight risk for the manned lunar exploration mission (MLEM). This paper proposes an interval programming method to optimize the trans-lunar trajectory under interval uncertainties. Firstly, the influence of the trans-lunar injection uncertainties (TLI) is investigated, finding that the reached orbit at the perilune is very sensitive to the impulse errors at TLI. Then, the design methods of the Earth-Moon trajectory and the trajectory correction maneuver (TCM) are presented. Based on the mathematical tool of the interval possibility degree, the interval programming model is built to transform the uncertain optimization problem into a deterministic one, and then a multi-layer optimization scheme is proposed to solve it. The uncertain objectives and constraints’ interval bounds are calculated in the inner loop, and the design variables are searched and optimized in the outer loop. The proposed method is used to design the Earth-Moon trajectories of both manned and unmanned spacecraft. The designed trajectories are insensitive to the uncertainties and are validated by the Monte Carlo simulations.
Transformational Leadership: Navigating Green Behaviour Through the Ethical Climate and Overall Justice
Authors: Yanhong Li , Rafiq Muhammad
Published: May 2024

The objective of this research is to examine the association between green transformational leadership (GTL) and employee green behaviour (EGB) in the context of the manufacturing organizations in China, with the mediating role of perceived ethical climate (PEC) and moderating role of overall justice (OJ). For this purpose, a self-administered survey of self-reporting questionnaire was distributed among employees working in different manufacturing organizations in China. This study collected 401 questionnaire responses. The collected data were analysed through structural equation modelling by utilizing Mplus software. The results depict that GTL significantly impacts EGB, and this relationship is mediated by PEC. Furthermore, the results indicate that OJ significantly moderates the relationship between PEC and EGB and the relationship becomes stronger in the presence of high OJ. The current research is highly important for the manufacturing organizations in China to adopt environmentally sustainable practices. It provides implications of fostering GTL and creating a just and ethical work setting so that employees can be motivated in arousing green behaviours. The current research is unique in a sense that it brings the concept of PEC and OJ as mediating and moderating variables between GTL and EGB and fills the research gap by explaining a more limited detailed picture of the association of leadership and organizational characteristics towards environmental sustainability in the Chinese manufacturing context.
Traumatic Bilateral Brachial Plexus Injuries in an Adult: A Conservative Approach
Authors: Jerome J. Terrence Jose
Published: May 2024

Background and Aims:

Traumatic bilateral brachial plexus injuries in adults are rare and present unique challenges in management. We report a case of a 21-year-old veterinary student who sustained bilateral brachial plexus injuries following a fall from a moving two-wheeler.

Case Presentation:

The patient suffered a C5,6 brachial plexus injury on the right side and a C5–7 injury on the left side. Remarkably, the right-sided injury showed signs of recovery after four months, while the left-sided injury took seven months to resolve completely. Despite the severity of the injuries, the patient underwent a conservative approach and did not undergo any surgical intervention.

Results:

Following months of dedicated rehabilitation, the patient achieved significant recovery and was able to return to her veterinary studies. This case highlights the potential for recovery in traumatic bilateral brachial plexus injuries with conservative management, emphasising the importance of patient-specific treatment strategies and rehabilitation protocols.

Conclusion:

Conservative management can lead to significant recovery in traumatic bilateral brachial plexus injuries. Patient-specific treatment strategies and dedicated rehabilitation are crucial components of successful outcomes in such cases.