catena-Poly[1,1′-dimethyl-4,4′-(ethane-1,2-di­yl)dipyridinium [lead(II)-tri-μ-iodido-lead(II)-tri-μ-iodido]]

The title compound, {(C14H18N2)[Pb2I6]}n, consists of discrete 1,1′-dimethyl-4,4′-(ethane-1,2-di­yl)dipyridinium cations and one-dimensional [Pb2I6]n anions. The organic cation has an inversion center at the mid-point of the ethane C—C bond. In the anion, the PbII atom is coordinated by six I atoms in a distorted octa­hedral geometry. The I atoms bridge the PbII atoms into a polymeric chain running along [001]. These inorganic chains are separated by the isolated organic cations

X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval

Video-text retrieval has been a crucial and fundamental task in multi-modal research. The development of video-text retrieval has been considerably promoted by large-scale multi-modal contrastive pre-training, which primarily focuses on coarse-grained or fine-grained contrast. However, cross-grained contrast, which is the contrast between coarse-grained representations and fine-grained representations, has rarely been explored in prior research. Compared with fine-grained or coarse-grained contrasts, cross-grained contrast calculate the correlation between coarse-grained features and each fine-grained feature, and is able to filter out the unnecessary fine-grained features guided by the coarse-grained feature during similarity calculation, thus improving the accuracy of retrieval. To this end, this paper presents a novel multi-grained contrastive model, namely X-CLIP, for video-text retrieval. However, another challenge lies in the similarity aggregation problem, which aims to aggregate fine-grained and cross-grained similarity matrices to instance-level similarity. To address this challenge, we propose the Attention Over Similarity Matrix (AOSM) module to make the model focus on the contrast between essential frames and words, thus lowering the impact of unnecessary frames and words on retrieval results. With multi-grained contrast and the proposed AOSM module, X-CLIP achieves outstanding performance on five widely-used video-text retrieval datasets, including MSR-VTT (49.3 R@1), MSVD (50.4 R@1), LSMDC (26.1 R@1), DiDeMo (47.8 R@1) and ActivityNet (46.2 R@1). It outperforms the previous state-of-theart by +6.3%, +6.6%, +11.1%, +6.7%, +3.8% relative improvements on these benchmarks, demonstrating the superiority of multi-grained contrast and AOSM.Comment: 13 pages, 6 figures, ACMMM2

An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation

Despite making significant progress in multi-modal tasks, current Multi-modal Large Language Models (MLLMs) encounter the significant challenge of hallucination, which may lead to harmful consequences. Therefore, evaluating MLLMs' hallucinations is becoming increasingly important in model improvement and practical application deployment. Previous works are limited in high evaluation costs (e.g., relying on humans or advanced LLMs) and insufficient evaluation dimensions (e.g., types of hallucination and task). In this paper, we propose an LLM-free multi-dimensional benchmark AMBER, which can be used to evaluate both generative task and discriminative task including object existence, object attribute and object relation hallucination. Based on AMBER, we design a low-cost and efficient evaluation pipeline. Additionally, we conduct a comprehensive evaluation and detailed analysis of mainstream MLLMs including GPT-4V(ision), and also give guideline suggestions for mitigating hallucinations. The data and code of AMBER are available at https://github.com/junyangwang0410/AMBER.Comment: 11 pages, 4 figure

Evaluation and Analysis of Hallucination in Large Vision-Language Models

Large Vision-Language Models (LVLMs) have recently achieved remarkable success. However, LVLMs are still plagued by the hallucination problem, which limits the practicality in many scenarios. Hallucination refers to the information of LVLMs' responses that does not exist in the visual input, which poses potential risks of substantial consequences. There has been limited work studying hallucination evaluation in LVLMs. In this paper, we propose Hallucination Evaluation based on Large Language Models (HaELM), an LLM-based hallucination evaluation framework. HaELM achieves an approximate 95% performance comparable to ChatGPT and has additional advantages including low cost, reproducibility, privacy preservation and local deployment. Leveraging the HaELM, we evaluate the hallucination in current LVLMs. Furthermore, we analyze the factors contributing to hallucination in LVLMs and offer helpful suggestions to mitigate the hallucination problem. Our training data and human annotation hallucination data will be made public soon.Comment: 11 pages, 5 figure

Evaluation of non-invasive continuous physiological monitoring devices for neonates in Nairobi, Kenya: a research protocol

Introduction: Continuous physiological monitoring devices are often not available for monitoring high-risk neonates in low-resource settings. Easy-to-use, non-invasive, multiparameter, continuous physiological monitoring devices could be instrumental in providing appropriate care and improving outcomes for high-risk neonates in these low-resource settings. Methods and analysis: The purpose of this prospective, observational, facility-based evaluation is to provide evidence to establish whether two existing non-invasive, multiparameter, continuous physiological monitoring devices developed by device developers, EarlySense and Sibel, can accurately and reliably measure vital signs in neonates (when compared with verified reference devices). We will also assess the feasibility, usability and acceptability of these devices for use in neonates in low-resource settings in Africa. Up to 500 neonates are enrolled in two phases: (1) a verification and accuracy evaluation phase at Aga Khan University—Nairobi and (2) a clinical feasibility evaluation phase at Pumwani Maternity Hospital in Nairobi, Kenya. Both quantitative and qualitative data are collected and analysed. Agreement between the investigational and reference devices is determined using a priori-defined accuracy thresholds. Ethics and dissemination: This trial was approved by the Aga Khan University Nairobi Research Ethics Committee and the Western Institutional Review Board. We plan to disseminate research results in peer-reviewed journals and international conferences

Evaluation of Sibel’s Advanced Neonatal Epidermal (ANNE) wireless continuous physiological monitor in Nairobi, Kenya

Background: Neonatal multiparameter continuous physiological monitoring (MCPM) technologies assist with early detection of preventable and treatable causes of neonatal mortality. Evaluating accuracy of novel MCPM technologies is critical for their appropriate use and adoption. Methods: We prospectively compared the accuracy of Sibel’s Advanced Neonatal Epidermal (ANNE) technology with Masimo’s Rad-97 pulse CO-oximeter with capnography and Spengler’s Tempo Easy reference technologies during four evaluation rounds. We compared accuracy of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and skin temperature using Bland-Altman plots and root-mean-square deviation analyses (RMSD). Sibel’s ANNE algorithms were optimized between each round. We created Clarke error grids with zones of 20% to aid with clinical interpretation of HR and RR results. Results: Between November 2019 and August 2020 we collected 320 hours of data from 84 neonates. In the final round, Sibel’s ANNE technology demonstrated a normalized bias of 0% for HR and 3.1% for RR, and a non-normalized bias of -0.3% for SpO2 and 0.2°C for temperature. The normalized spread between 95% upper and lower limits-of-agreement (LOA) was 4.7% for HR and 29.3% for RR. RMSD for SpO2 was 1.9% and 1.5°C for temperature. Agreement between Sibel’s ANNE technology and the reference technologies met the a priori-defined thresholds for 95% spread of LOA and RMSD. Clarke error grids showed that all HR and RR observations were within a 20% difference. Conclusion: Our findings suggest acceptable agreement between Sibel’s ANNE and reference technologies. Clinical effectiveness, feasibility, usability, acceptability, and cost-effectiveness investigations are necessary for large-scale implementation

Ozone and Daily Mortality in Shanghai, China

BACKGROUND: Controversy remains regarding the relationship between ambient ozone and mortality worldwide. In mainland China, the largest developing country, there has been no prior study investigating the acute effect of O(3) on death risk. Given the changes in types of air pollution from conventional coal combustion to the mixed coal combustion/motor vehicle emissions in China’s large cities, it is worthwhile to investigate the acute effect of O(3) on mortality outcomes in the country. OBJECTIVES: We conducted a time-series study to investigate the relation between O(3) and daily mortality in Shanghai using 4 years of daily data (2001–2004). METHODS: We used the generalized additive model with penalized splines to analyze mortality, O(3) pollution, and covariate data in warm and cold seasons. We considered daily counts of all-cause mortality and several cause-specific subcategories (respiratory and cardiovascular). We also examined these associations among several subpopulations based on age and sex. RESULTS: O(3) was significantly associated with total and cardiovascular mortality in the cold season but not in the warm season. In the whole-year analysis, an increase of 10 μg/m(3) of 2-day average (lag01) O(3) corresponds to 0.45% [95% confidence interval (CI), 0.16–0.73%], 0.53% (95% CI, 0.10–0.96%), and 0.35% (95% CI, −0.40 to 1.09%) increase of total nonaccidental, cardiovascular, and respiratory mortality, respectively. In the cold season, the estimates increased to 1.38% (95% CI, 0.68–2.07%), 1.53% (95% CI, 0.54–2.52%), and 0.95% (95% CI, −0.71 to 2.60%), respectively. In the warm season, we did not observe significant associations for both total and cause-specific mortality. The results were generally insensitive to model specifications such as lag structure of O(3) concentrations and degree of freedom for time trend. Multipollutant models indicate that the effect of O(3) was not confounded by particulate matter ≤ 10 μm in diameter (PM(10)) or by sulfur dioxide; however, after adding nitrogen dioxide into the model, the association of O(3) with total and cardiovascular mortality became statistically insignificant. CONCLUSIONS: O(3) pollution has stronger health effects in the cold than in the warm season in Shanghai. Our analyses also strengthen the rationale for further limiting levels of O(3) pollution in outdoor air in the city