NYCU-TWO at Memotion 3: Good Foundation, Good Teacher, then you have Good Meme Analysis

This paper presents a robust solution to the Memotion 3.0 Shared Task. The goal of this task is to classify the emotion and the corresponding intensity expressed by memes, which are usually in the form of images with short captions on social media. Understanding the multi-modal features of the given memes will be the key to solving the task. In this work, we use CLIP to extract aligned image-text features and propose a novel meme sentiment analysis framework, consisting of a Cooperative Teaching Model (CTM) for Task A and a Cascaded Emotion Classifier (CEC) for Tasks B&C. CTM is based on the idea of knowledge distillation, and can better predict the sentiment of a given meme in Task A; CEC can leverage the emotion intensity suggestion from the prediction of Task C to classify the emotion more precisely in Task B. Experiments show that we achieved the 2nd place ranking for both Task A and Task B and the 4th place ranking for Task C, with weighted F1-scores of 0.342, 0.784, and 0.535 respectively. The results show the robustness and effectiveness of our framework. Our code is released at github.Comment: De-Factify 2: Second Workshop on Multimodal Fact Checking and Hate Speech Detection, co-located with AAAI 202

TaskMatrix.AI: Completing Tasks by Connecting Foundation Models with Millions of APIs

Artificial Intelligence (AI) has made incredible progress recently. On the one hand, advanced foundation models like ChatGPT can offer powerful conversation, in-context learning and code generation abilities on a broad range of open-domain tasks. They can also generate high-level solution outlines for domain-specific tasks based on the common sense knowledge they have acquired. However, they still face difficulties with some specialized tasks because they lack enough domain-specific data during pre-training or they often have errors in their neural network computations on those tasks that need accurate executions. On the other hand, there are also many existing models and systems (symbolic-based or neural-based) that can do some domain-specific tasks very well. However, due to the different implementation or working mechanisms, they are not easily accessible or compatible with foundation models. Therefore, there is a clear and pressing need for a mechanism that can leverage foundation models to propose task solution outlines and then automatically match some of the sub-tasks in the outlines to the off-the-shelf models and systems with special functionalities to complete them. Inspired by this, we introduce TaskMatrix.AI as a new AI ecosystem that connects foundation models with millions of APIs for task completion. Unlike most previous work that aimed to improve a single AI model, TaskMatrix.AI focuses more on using existing foundation models (as a brain-like central system) and APIs of other AI models and systems (as sub-task solvers) to achieve diversified tasks in both digital and physical domains. As a position paper, we will present our vision of how to build such an ecosystem, explain each key component, and use study cases to illustrate both the feasibility of this vision and the main challenges we need to address next

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Meta-analysis of genome-wide association studies identifies eight new loci for type 2 diabetes in east Asians

We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in east Asian populations. We followed our stage 1 meta-analysis of eight T2D genome-wide association studies (6,952 cases with T2D and 11,865 controls) with a stage 2 in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, which is involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of an association with T2D for PEPD5 and HNF4A6,7 has been shown in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings, derived from an east Asian population, provide new perspectives on the etiology of T2D

Sleep Duration and Sleep Quality following Acute Mild Traumatic Brain Injury: A Propensity Score Analysis

Introduction. Mild traumatic brain injury (mTBI) has been widely studied and the effects of injury can be long term or even lifelong. This research aims to characterize the sleep problems of patients following acute mTBI. Methods. A total of 171 patients with mTBI within one month and 145 non-mTBI controls were recruited in this study. The questionnaire, Pittsburgh Sleep Quality Index (PSQI), was used to evaluate seven aspects of sleep problems. A propensity score method was used to generate a quasirandomized design to account for the background information, including gender, age, Beck’s Anxiety Index, Beck’s Depression Index, and Epworth Sleepiness Scale. The effect was evaluated via cumulative logit regression including propensity scores as a covariate. Results. Before adjustment, about 60% mTBI patients and over three quarters of control subjects had mild sleep disturbance while one third mTBI patients had moderate sleep disturbance. After adjusting by the propensity scores, the scores of sleep quality and duration were significant between mTBI and control groups. Conclusion. Our study supports that sleep problem is common in mTBI group. After adjusting the confounders by propensity score, sleep duration and subjective sleep quality are the most frequently reported problems in mTBI patients within one month after the injury

Association between Sleep Deprivation in Caregivers and Risk of Injury among Toddlers: A Propensity Score Analysis

Introduction. Unintentional injury remains the leading cause of death in children worldwide. Adequate parental supervision is a crucial strategy for preventing injury. Many factors, such as a large family size, poor socioeconomic status, and the caregiver being a single mother, contribute to unintentional injury in children. In addition, sleep deprivation in caregivers might be associated with injury in children because sleep deprivation causes impaired daytime cognitive function, wake-state instability, and negative moods, thereby impairing caregiver supervision. Therefore, this study determines the association between injury in children and the sleep quality of their primary caregivers. Method. This is a retrospective case–control study on unintentional injury in children aged 0 to 4 years who visited the emergency department (case group) and an age- and sex-matched control group. Sleep quality in caregivers was assessed using the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Logistic regression was used to evaluate the association between aspects of the PSQI and injury. A propensity score model was used to generate a quasirandomized design. Results. This case-control study recruiting 277 injured and 274 noninjured children was conducted in Taiwan. There was no statistically significant difference in child’s age and primary caregiver’s age between the injured and noninjured groups. The primary outcome, Pittsburgh sleep quality index, was not significantly different between the two groups. The average scores of sleep duration and habitual sleep efficiency in the control group were higher than those in the case group. However, there was no difference between the two groups after adjusting via a propensity score model, including the following potential confounders, child’s age, child’s sex, number of previous injury, caregiver mental status, caregiver’s sex and caregiver’s age, and the number of children living together. Conclusion. Our study was the first to examine the association between injury in children and the sleep quality of their primary caregivers. We observed that no PSQI component significantly affected the risk of injury among children

Exposing effect of comb-type cathode electrode on the performance of sediment microbial fuel cells

Sediment microbial fuel cells (SMFCs) are an innovative, green technology with great potential, and they utilize a voltage drop of redox potential between aerobes and anaerobes to produce electricity and degrade organic wastewater. However, the power performance and degradation rate in SMFCs are limited by the low concentration of dissolved oxygen on the cathode. Therefore, in this study, SMFCs with comb-type cathode electrodes with carbon cloths exposed partly to air and embedded partly in the reactor substrate were designed and operated. They were utilized for enhancing the power density and the effect of three different exposed areas of cathode electrode for improving transfer of oxygen. Results showed that the power density reached 3.77 × 10−2 mW/m2 for 75% of the (MA75) exposed area, which was 1.93 times than that of 50% of the (MA50) exposed area and 6.44 times than that of 0% (i.e., completely immersed; MA0) exposed area. These results indicated that the exposed area of the cathode electrode had a positive effect on the power performance of SMFCs and would reduce the impedance of the cathode. These findings would apparently offer useful information on the feasibility of SMFCs for wastewater treatment applications in the future

Microsurgical treatment for malignant intracranial melanomas: 2 case reports and review of the literature

Primary malignant intracranial melanomas are rare tumors of the central nervous system, while the secondary or brain metastatic melanomas are among the top three brain metastatic lesions. These tumors are highly malignant and are associated with poor prognosis. The neurosurgeons have struggled with the diagnosis and treatment of these tumors. In this report, we retrospectively analyzed the clinical features, imaging findings, pathological features and prognoses of two patients who were diagnosed as having malignant intracranial melanomas. In addition, we reviewed the literature regarding diagnostic and therapeutic strategies for treating these unusual malignant lesions. <br /