Bis(4-ammonio-4-methyl­pentan-2-one-κO)dioxalato-κ4 O 1,O 2-copper(II)

The title compound, [Cu(C2O4)2(C6H14NO)2], was synthesized by mixing diacetonamine hydrogen oxalate and copper sulfate in ethanol/water. The mol­ecule is centrosymmetric, so two pairs of equivalent ligands lie trans to each other. The CuII center, located on a position with 2/m site symmetry, is six-coordinated by four O atoms from two oxalate ligands at short distances and the carbonyl O atoms from the 4-amino-4-methyl­pentan-2-one ligands at longer distances. Mol­ecules are linked through inter­molecular N—H⋯O hydrogen bonds between the amino groups and carbonyl O atoms; no intra­molecular hydrogen bonds are formed

Comprehensive operating efficiency measurement of 28 Chinese airports using a two-stage DEA-Tobit method

This paper presents a two-stage method combining data envelopment analysis (DEA) and a Tobit model to analyze the comprehensive operating efficiency of 28 airports in China in 2016. At the first stage, the DEA-BCC (Banker-Charnes-Cooper) model was employed to obtain the comprehensive operating efficiency of the combination of flight departure punctuality, non-cancellations, landing bridge rates from the perspective of airport infrastructure, surrounding airspace, route layouts, flight volume and weather. At the second stage, a Tobit model was used to analyze the influence of nine input variables from four aspects on obtained comprehensive operating efficiency, ultimately providing a clear and straightforward basis for formulating and testing policies. The comprehensive operating efficiency with this combination was further compared with each of the three efficiencies respectively. The important findings included the following: (1) The comprehensive operation efficiencies of most airports were greater than the individual efficiency; (2) These four types of operation efficiencies for most airports did not achieved DEA validity (100% efficiency), except for six airports (i.e., Haikou, Dalian, Jinan, Fuzhou, Nanning and Lanzhou); (3) These factors affecting each of the four types of operation efficiencies were different in that the number of terminals, duration of impact and average daily inbound and outbound flights had a negative impact on airport operational efficiency, while the average number of overnight aircraft per day and peak hour sorties had positive effects

Graph Learning and Its Applications: A Holistic Survey

Graph learning is a prevalent domain that endeavors to learn the intricate relationships among nodes and the topological structure of graphs. These relationships endow graphs with uniqueness compared to conventional tabular data, as nodes rely on non-Euclidean space and encompass rich information to exploit. Over the years, graph learning has transcended from graph theory to graph data mining. With the advent of representation learning, it has attained remarkable performance in diverse scenarios, including text, image, chemistry, and biology. Owing to its extensive application prospects, graph learning attracts copious attention from the academic community. Despite numerous works proposed to tackle different problems in graph learning, there is a demand to survey previous valuable works. While some researchers have perceived this phenomenon and accomplished impressive surveys on graph learning, they failed to connect related objectives, methods, and applications in a more coherent way. As a result, they did not encompass current ample scenarios and challenging problems due to the rapid expansion of graph learning. Different from previous surveys on graph learning, we provide a holistic review that analyzes current works from the perspective of graph structure, and discusses the latest applications, trends, and challenges in graph learning. Specifically, we commence by proposing a taxonomy from the perspective of the composition of graph data and then summarize the methods employed in graph learning. We then provide a detailed elucidation of mainstream applications. Finally, based on the current trend of techniques, we propose future directions.Comment: 20 pages, 7 figures, 3 table

Improving Retrieval-Augmented Large Language Models via Data Importance Learning

Retrieval augmentation enables large language models to take advantage of external knowledge, for example on tasks like question answering and data imputation. However, the performance of such retrieval-augmented models is limited by the data quality of their underlying retrieval corpus. In this paper, we propose an algorithm based on multilinear extension for evaluating the data importance of retrieved data points. There are exponentially many terms in the multilinear extension, and one key contribution of this paper is a polynomial time algorithm that computes exactly, given a retrieval-augmented model with an additive utility function and a validation set, the data importance of data points in the retrieval corpus using the multilinear extension of the model's utility function. We further proposed an even more efficient ({\epsilon}, {\delta})-approximation algorithm. Our experimental results illustrate that we can enhance the performance of large language models by only pruning or reweighting the retrieval corpus, without requiring further training. For some tasks, this even allows a small model (e.g., GPT-JT), augmented with a search engine API, to outperform GPT-3.5 (without retrieval augmentation). Moreover, we show that weights based on multilinear extension can be computed efficiently in practice (e.g., in less than ten minutes for a corpus with 100 million elements)

14-Year Outcome of Angle-Closure Prevention with Laser Iridotomy in the Zhongshan Angle Closure Prevention Study: Extended Follow-Up of a Randomized Controlled Trial

Purpose: This study aimed to evaluate the efficacy of laser peripheral iridotomy (LPI) prophylaxis for primary angle closure suspects (PACS) after 14 years and to identify risk factors for the conversion from PACS to primary angle closure (PAC)./ Design: An extended follow-up of Zhongshan Angle Closure Prevention (ZAP) study./ Participants: A total of 889 Chinese patients aged 50 to 70 years with bilateral PACS./ Methods: Each patient received LPI in one randomly selected eye, with the fellow untreated eye serving as a control. Since the risk of glaucoma was low and acute angle closure (AAC) only occurred in rare cases, the follow-up was extended to 14 years despite substantial benefits of LPI reported after the 6-year visit./ Main Outcome Measures: The primary outcome was incidence of PAC, a composite endpoint including peripheral anterior synechiae (PAS), intraocular pressure (IOP) > 24 mmHg, or AAC. Results During the 14 years, 390 LPI-treated eyes and 388 control eyes were lost to the follow-up. A total of 33 LPI-treated eyes and 105 control eyes reached primary endpoints (P <0.01). Within them, twelve eyes developed AAC or primary angle closure glaucoma (AAC: five control eyes and one LPI-treated eye; PACG: four control eyes and two LPI-treated eyes). The hazard ratio for progression to PAC was 0.31 (95% confidence interval, 0.21–0.46) in LPI-treated eyes compared with control eyes. At the 14-year visit, LPI-treated eyes had severer nuclear cataract, higher IOP, larger angle width and limbal anterior chamber depth (LACD) than control eyes. Higher IOP, shallower LACD, and central anterior chamber depth (CACD) were associated with an increased risk of developing endpoints in control eyes. In the treated group, eyes with higher IOP, shallower LACD, or less IOP elevation after dark room–prone provocative tests (DRPPT) were more likely to develop PAC after LPI./ Conclusions: Despite a two-third decrease in PAC incidence after LPI, the cumulative risk of PAC was relatively low in the community-based PACS population over 14 years. Apart from IOP, IOP elevation after DRPPT, CACD, and LACD, more risk factors are needed to achieve precise prediction of PAC occurrence and guide clinical practice

Identifying and analyzing novel epilepsy-related genes using random walk with restart algorithm.

As a pathological condition, epilepsy is caused by abnormal neuronal discharge in brain which will temporarily disrupt the cerebral functions. Epilepsy is a chronic disease which occurs in all ages and would seriously affect patients' personal lives. Thus, it is highly required to develop effective medicines or instruments to treat the disease. Identifying epilepsy-related genes is essential in order to understand and treat the disease because the corresponding proteins encoded by the epilepsy-related genes are candidates of the potential drug targets. In this study, a pioneering computational workflow was proposed to predict novel epilepsy-related genes using the random walk with restart (RWR) algorithm. As reported in the literature RWR algorithm often produces a number of false positive genes, and in this study a permutation test and functional association tests were implemented to filter the genes identified by RWR algorithm, which greatly reduce the number of suspected genes and result in only thirty-three novel epilepsy genes. Finally, these novel genes were analyzed based upon some recently published literatures. Our findings implicate that all novel genes were closely related to epilepsy. It is believed that the proposed workflow can also be applied to identify genes related to other diseases and deepen our understanding of the mechanisms of these diseases

Literature Explorer: effective retrieval of scientific documents through nonparametric thematic topic detection

© 2020 The Authors. Published by Springer. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1007/s00371-019-01721-7Scientific researchers are facing a rapidly growing volume of literatures nowadays. While these publications offer rich and valuable information, the scale of the datasets makes it difficult for the researchers to manage and search for desired information efficiently. Literature Explorer is a new interactive visual analytics suite that facilitates the access to desired scientific literatures through mining and interactive visualisation. We propose a novel topic mining method that is able to uncover “thematic topics” from a scientific corpus. These thematic topics have an explicit semantic association to the research themes that are commonly used by human researchers in scientific fields, and hence are human interpretable. They also contribute to effective document retrieval. The visual analytics suite consists of a set of visual components that are closely coupled with the underlying thematic topic detection to support interactive document retrieval. The visual components are adequately integrated under the design rationale and goals. Evaluation results are given in both objective measurements and subjective terms through expert assessments. Comparisons are also made against the outcomes from the traditional topic modelling methods.This research is supported by the European Commission with project Dr Inventor (No 611383), MyHealthAvatar (No 60929), and by the UK Engineering and Physical Sciences Research Council with project MyLifeHub (EP/L023830/1).Published onlin

Long-term gastrointestinal symptoms and sleep quality sequelae in adolescents after COVID-19: a retrospective study

ObjectiveTo evaluate the long-term gastrointestinal (GI) symptoms and sleep quality sequelae in adolescents with COVID-19.MethodsBetween June and July 2023, an online survey was done in Xiaoshan District, Hangzhou City, Zhejiang Province, China, using the GI Symptom Rating Scale (GSRS) and the Pittsburgh Sleep Quality Inventory (PSQI).ResultsGI symptoms in COVID-19 patients increased by 11.86% compared to before infection, while sleep quality decreased by 10.9%. Over time, there was a significant increase in the cumulative incidence rate of GI symptoms and sleep disorders (p &lt; 0.001). Follow-up of COVID-19 positive patients within 6 months of infection showed that GI symptoms and sleep quality began to ease starting from the first month after infection. Further analysis indicated a significant linear relationship between the severity of GI symptoms and sleep quality (R &gt; 0.5, p &lt; 0.001). Moreover, females, older age, and higher education were identified as risk factors influencing the long-term effects of COVID-19.ConclusionSARS-CoV-2 affects GI symptoms and sleep quality in adolescents during both the acute phase and post-infection periods. Over time, these symptoms gradually alleviate. A significant correlation exists between GI symptoms and sleep quality

Long-Term Risk and Prediction of Progression in Primary Angle Closure Suspect

IMPORTANCE: Identifying primary angle closure suspect (PACS) eyes at risk of angle closure is crucial for its management. However, the risk of progression and its prediction are still understudied in long-term longitudinal studies about PACS. OBJECTIVE: To explore baseline predictors and develop prediction models for the 14-year risk of progression from PACS to primary angle closure (PAC). DESIGN, SETTING, AND PARTICIPANTS: This cohort study involved participants from the Zhongshan Angle Closure Prevention trial who had untreated eyes with PACS. Baseline examinations included tonometry, ultrasound A-scan biometry, and anterior segment optical coherence tomography (AS-OCT) under both light and dark conditions. Primary angle closure was defined as peripheral anterior synechiae in 1 or more clock hours, intraocular pressure (IOP) greater than 24 mm Hg, or acute angle closure. Based on baseline covariates, logistic regression models were built to predict the risk of progression from PACS to PAC during 14 years of follow-up. RESULTS: The analysis included 377 eyes from 377 patients (mean [SD] patient age at baseline, 58.28 [4.71] years; 317 females [84%]). By the 14-year follow-up visit, 93 eyes (25%) had progressed from PACS to PAC. In multivariable models, higher IOP (odds ratio [OR], 1.14 [95% CI, 1.04-1.25] per 1-mm Hg increase), shallower central anterior chamber depth (ACD; OR, 0.81 [95% CI, 0.67-0.97] per 0.1-mm increase), and shallower limbal ACD (OR, 0.96 [95% CI, 0.93-0.99] per 0.01 increase in peripheral corneal thickness) at baseline were associated with an increased 14-year risk of progression from PACS to PAC. As for AS-OCT measurements, smaller light-room trabecular-iris space area (TISA) at 500 μm from the scleral spur (OR, 0.86 [95% CI, 0.77-0.96] per 0.01-mm2 increase), smaller light-room angle recess area (ARA) at 750 μm from the scleral spur (OR, 0.93 [95% CI, 0.88-0.98] per 0.01-mm2 increase), and smaller dark-room TISA at 500 μm (OR, 0.89 [95% CI, 0.80-0.98] per 0.01-mm2 increase) at baseline were identified as predictors for the 14-year risk of progression. The prediction models based on IOP and central and limbal ACDs showed moderate performance (area under the receiver operating characteristic curve, 0.69; 95% CI, 0.63-0.75) in predicting progression from PACS to PAC, and inclusion of AS-OCT metrics did not improve the model's performance. CONCLUSIONS AND RELEVANCE: This cohort study suggests that higher IOP, shallower central and limbal ACDs, and smaller TISA at 500 μm and light-room ARA at 750 μm may serve as baseline predictors for progression to PAC in PACS eyes. Evaluating these factors can aid in customizing PACS management