Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Supervised Multimodal Opinion Summarization

Recently, opinion summarization, which is the generation of a summary from multiple reviews, has been conducted in a self-supervised manner by considering a sampled review as a pseudo summary. However, non-text data such as image and metadata related to reviews have been considered less often. To use the abundant information contained in non-text data, we propose a self-supervised multimodal opinion summarization framework called MultimodalSum. Our framework obtains a representation of each modality using a separate encoder for each modality, and the text decoder generates a summary. To resolve the inherent heterogeneity of multimodal data, we propose a multimodal training pipeline. We first pretrain the text encoder–decoder based solely on text modality data. Subsequently, we pretrain the non-text modality encoders by considering the pretrained text decoder as a pivot for the homogeneous representation of multimodal data. Finally, to fuse multimodal representations, we train the entire framework in an end-to-end manner. We demonstrate the superiority of MultimodalSum by conducting experiments on Yelp and Amazon datasets.
Search Spaces for Neural Model Training

While larger neural models are pushing the boundaries of what deep learning can do, often more weights are needed to train models rather than to run inference for tasks. This paper seeks to understand this behavior using search spaces -- adding weights creates extra degrees of freedom that form new paths for optimization (or wider search spaces) rendering neural model training more effective. We then show how we can augment search spaces to train sparse models attaining competitive scores across dozens of deep learning workloads. They are also are tolerant of structures targeting current hardware, opening avenues for training and inference acceleration. Our work encourages research to explore beyond massive neural models being used today.
Quantum mean-value approximator for hard integer-value problems

Evaluating the expectation of a quantum circuit is a classically difficult problem known as the quantum mean value problem (QMV). It is used to optimize the quantum approximate optimization algorithm and other variational quantum eigensolvers. We show that such an optimization can be improved substantially by using an approximation rather than the exact expectation. Together with efficient classical sampling algorithms, a quantum algorithm with minimal gate count can thus improve the efficiency of general integer-value problems, such as the shortest vector problem (SVP) investigated in this work.
Deconditional Downscaling with Gaussian Processes

Refining low-resolution (LR) spatial fields with high-resolution (HR) information, often known as statistical downscaling, is challenging as the diversity of spatial datasets often prevents direct matching of observations. Yet, when LR samples are modeled as aggregate conditional means of HR samples with respect to a mediating variable that is globally observed, the recovery of the underlying fine-grained field can be framed as taking an"inverse"of the conditional expectation, namely a deconditioning problem. In this work, we propose a Bayesian formulation of deconditioning which naturally recovers the initial reproducing kernel Hilbert space formulation from Hsu and Ramos (2019). We extend deconditioning to a downscaling setup and devise efficient conditional mean embedding estimator for multiresolution data. By treating conditional expectations as inter-domain features of the underlying field, a posterior for the latent field can be established as a solution to the deconditioning problem. Furthermore, we show that this solution can be viewed as a two-staged vector-valued kernel ridge regressor and show that it has a minimax optimal convergence rate under mild assumptions. Lastly, we demonstrate its proficiency in a synthetic and a real-world atmospheric field downscaling problem, showing substantial improvements over existing methods.
Linearized propagation equations for metric fluctuations in a general (non-vacuum) background geometry

The linearized dynamical equation for metric perturbations in a fully general, non-vacuum, background geometry is obtained from the Hamilton variational principle applied to the action up to second order. We specialize our results to the case of traceless and transverse metric fluctuations, and we discuss how the intrinsic properties of the matter stress tensor can affect (and modify) the process of gravity wave propagation even in most conventional geometric scenarios, like (for instance) those described by a FLRW metric background. We provide explicit examples for fluid, scalar field and electromagnetic field sources.
Towards Minimax Optimal Best Arm Identification in Linear Bandits

We study the problem of best arm identiﬁcation in linear bandits in the ﬁxed-budget setting. By leveraging properties of the G-optimal design and incorporating it into the arm allocation rule, we design a parameter-free algorithm, Optimal Design-based Linear Best Arm Identiﬁcation (OD-LinBAI). We provide a theoretical analysis of the failure probability of OD-LinBAI. While the performances of existing methods (e.g., BayesGap) depend on all the optimality gaps, OD-LinBAI depends on the gaps of the top d arms, where d is the effective dimension of the linear bandit instance. Furthermore, we present a minimax lower bound for this problem. The upper and lower bounds show that OD-LinBAI is minimax optimal up to multiplicative factors in the exponent. Finally, numerical experiments corroborate our theoretical ﬁndings.
Do the Periodic Activities of Repeating Fast Radio Bursts Represent the Spins of Neutron Stars?

Fast radio bursts (FRBs) are mysterious radio transients with millisecond durations. Recently, ∼16 days of periodic activity and ∼159 days of possible periodicity were detected to arise from FRB 180916.J0158+65 and FRB 121102, respectively, and the spin period of a slow-rotation magnetar was further considered to be one of the possible explanations of the periodic activities of repeating FRBs. For isolated neutron stars, the spin evolution suggests that it has difficulty reaching several hours. In this work, we mainly focus on the possible maximum spin period of isolated NSs/magnetars dominated by an interaction between a star’s magnetic field and the disk. We find that the disk wind plays an important role in spin evolution, whose influence varies the power-law index in the evolution equation of mass flow rate. For a magnetar without disk wind, the longest spin period is tens of hours. When the disk wind with a classical parameter is involved, the maximum spin period can reach hundreds of hours. But for an extremely large index of mass flow rate due to disk wind or other angular momentum extraction processes, a spin period of ∼(16–160) days is still possible.
Astragaloside IV Suppresses Hepatic Proliferation in Regenerating Rat Liver after 70% Partial Hepatectomy via Down-Regulation of Cell Cycle Pathway and DNA Replication

Astragaloside IV (AS-IV) is one of the major bio-active ingredients of huang qi which is the dried root of Astragalus membranaceus (a traditional Chinese medicinal plant). The pharmacological effects of AS-IV, including anti-oxidative, anti-cancer, and anti-diabetic effects have been actively studied, however, the effects of AS-IV on liver regeneration have not yet been fully described. Thus, the aim of this study was to explore the effects of AS-IV on regenerating liver after 70% partial hepatectomy (PHx) in rats. Differentially expressed mRNAs, proliferative marker and growth factors were analyzed. AS-IV (10 mg/kg) was administrated orally 2 h before surgery. We found 20 core genes showed effects of AS-IV, many of which were involved with functions related to DNA replication during cell division. AS-IV down-regulates MAPK signaling, PI3/Akt signaling, and cell cycle pathway. Hepatocyte growth factor (HGF) and cyclin D1 expression were also decreased by AS-IV administration. Transforming growth factor β1 (TGFβ1, growth regulation signal) was slightly increased. In short, AS-IV down-regulated proliferative signals and genes related to DNA replication. In conclusion, AS-IV showed anti-proliferative activity in regenerating liver tissue after 70% PHx.
Endothelial Dysfunction and SARS-CoV-2 Infection: Association and Therapeutic Strategies

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), has been recently considered a systemic disorder leading to the procoagulant state. Preliminary studies have shown that SARS-CoV-2 can infect endothelial cells, and extensive evidence of inflammation and endothelial dysfunction has been found in advanced COVID-19. Endothelial cells play a critical role in many physiological processes, such as controlling blood fluidity, leukocyte activation, adhesion, platelet adhesion and aggregation, and transmigration. Therefore, it is reasonable to think that endothelial dysfunction leads to vascular dysfunction, immune thrombosis, and inflammation associated with COVID-19. This article summarizes the association of endothelial dysfunction and SARS-CoV-2 infection and its therapeutic strategies.
Revisiting Platinum-Based Anticancer Drugs to Overcome Gliomas

Although there are many patients with brain tumors worldwide, there are numerous difficulties in overcoming brain tumors. Among brain tumors, glioblastoma, with a 5-year survival rate of 5.1%, is the most malignant. In addition to surgical operations, chemotherapy and radiotherapy are generally performed, but the patients have very limited options. Temozolomide is the most commonly prescribed drug for patients with glioblastoma. However, it is difficult to completely remove the tumor with this drug alone. Therefore, it is necessary to discuss the potential of anticancer drugs, other than temozolomide, against glioblastomas. Since the discovery of cisplatin, platinum-based drugs have become one of the leading chemotherapeutic drugs. Although many studies have reported the efficacy of platinum-based anticancer drugs against various carcinomas, studies on their effectiveness against brain tumors are insufficient. In this review, we elucidated the anticancer effects and advantages of platinum-based drugs used in brain tumors. In addition, the cases and limitations of the clinical application of platinum-based drugs are summarized. As a solution to overcome these obstacles, we emphasized the potential of a novel approach to increase the effectiveness of platinum-based drugs.
Synthesis and Characterization of Electrospun Composite Scaffolds Based on Chitosan-Carboxylated Graphene Oxide with Potential Biomedical Applications

This research study reports the development of chitosan/carboxylated graphene oxide (CS/GO-COOH) composite scaffolds with nanofibrous architecture using the electrospinning method. The concept of designed composite fibrous material is based on bringing together the biological properties of CS, mechanical, electrical, and biological characteristics of GO-COOH with the versatility and efficiency of ultra-modern electrospinning techniques. Three different concentrations of GO-COOH were added into a chitosan (CS)-poly(ethylene oxide) (PEO) solution (the ratio between CS/PEO was 3/7 (w/w)) and were used in the synthesis process of composite scaffolds. The effect of GO-COOH concentration on the spinnability, morphological and mechanical features, wettability, and biological properties of engineered fibrous scaffolds was thoroughly investigated. FTIR results revealed the non-covalent and covalent interactions that could take place between the system’s components. The SEM micrographs highlighted the nanofibrous architecture of scaffolds, and the presence of GO-COOH sheets along the composite CS/GO-COOH nanofibers. The size distribution graphs showed a decreasing trend in the mean diameter of composite nanofibers with the increase in GO-COOH content, from 141.40 nm for CS/PG 0.1% to 119.88 nm for CS/PG 0.5%. The dispersion of GO-COOH led to composite scaffolds with increased elasticity; the Young’s modulus of CS/PG 0.5% (84 ± 4.71 MPa) was 7.5-fold lower as compared to CS/PEO (662 ± 15.18 MPa, p < 0.0001). Contact angle measurements showed that both GO-COOH content and crosslinking step influenced the surface wettability of scaffolds, leading to materials with ~1.25-fold higher hydrophobicity. The in vitro cytocompatibility assessment showed that the designed nanofibrous scaffolds showed a reasonable cellular proliferation level after 72 h of contact with the fibroblast cells.
Eggmanone Effectively Overcomes Prostate Cancer Cell Chemoresistance

Prostate cancer chemoresistance is a major therapeutic problem, and the underlying mechanism is not well understood and effective therapies to overcome this problem are not available. Phosphodiesterase-4 (PDE4), a main intracellular enzyme for cAMP hydrolysis, has been previously shown to involve in the early chemo-sensitive prostate cancer cell proliferation and progression, but its role in the more-advanced chemo-resistant prostate cancer is completely unknown. Here we found that the expression of PDE4 subtype, PDE4D, is highly elevated in the chemo-resistant prostate cancer cells (DU145-TxR and PC3-TxR) in comparison to the chemo-sensitive prostate cancer cells (DU145 and PC3). Inhibition of PDE4D with a potent and selective PDED4 inhibitor, Eggmanone, effectively decreases the invasion and proliferation as well as induces cell death of the chemo-resistant prostate cancer cells (DU145-TxR and PC3-TxR). These results were confirmed by siRNA knockdown of PDE4D. We and colleagues previously reported that Eggmanone can effectively blocked sonic Hedgehog signaling via PDE4D inhibition, and here our study suggests that that Eggmanone downregulated proliferation of the chemo-resistant prostate cancer cells via sonic Hedgehog signaling. In addition, Eggmanone treatment dose-dependently increases docetaxel cytotoxicity to DU145-TxR and PC3-TxR. As cancer stem cells (CSCs) are known to be implicated in cancer chemoresistance, we further examined Eggmanone impacts on CSC-like properties in the chemo-resistant prostate cancer cells. Our study shows that Eggmanone effectively down-regulates the expression of CSCs’ marker genes Nanog and ABC sub-family G member 2 (ABCG2) and attenuates sphere formation in DU145-TxR and PC3-TxR cells. In summary, our work shows that Eggmanone effectively overcomes the chemoresistance of prostate cancer cells presumably through sonic Hedgehog signaling and targeting CSCs, suggesting that Eggmanone may serve as a novel agent for chemo-resistant prostate cancer.
Epigenetic Alterations of Maternal Tobacco Smoking during Pregnancy: A Narrative Review

In utero exposure to maternal tobacco smoking is the leading cause of birth complications in addition to being associated with later impairment in child’s development. Epigenetic alterations, such as DNA methylation (DNAm), miRNAs expression, and histone modifications, belong to possible underlying mechanisms linking maternal tobacco smoking during pregnancy and adverse birth outcomes and later child’s development. The aims of this review were to provide an update on (1) the main results of epidemiological studies on the impact of in utero exposure to maternal tobacco smoking on epigenetic mechanisms, and (2) the technical issues and methods used in such studies. In contrast with miRNA and histone modifications, DNAm has been the most extensively studied epigenetic mechanism with regard to in utero exposure to maternal tobacco smoking. Most studies relied on cord blood and children’s blood, but placenta is increasingly recognized as a powerful tool, especially for markers of pregnancy exposures. Some recent studies suggest reversibility in DNAm in certain genomic regions as well as memory of smoking exposure in DNAm in other regions, upon smoking cessation before or during pregnancy. Furthermore, reversibility could be more pronounced in miRNA expression compared to DNAm. Increasing evidence based on longitudinal data shows that maternal smoking-associated DNAm changes persist during childhood. In this review, we also discuss some issues related to cell heterogeneity as well as downstream statistical analyses used to relate maternal tobacco smoking during pregnancy and epigenetics. The epigenetic effects of maternal smoking during pregnancy have been among the most widely investigated in the epigenetic epidemiology field. However, there are still huge gaps to fill in, including on the impact on miRNA expression and histone modifications to get a better view of the whole epigenetic machinery. The consistency of maternal tobacco smoking effects across epigenetic marks and across tissues will also provide crucial information for future studies. Advancement in bioinformatic and biostatistics approaches is key to develop a comprehensive analysis of these biological systems.
Malnutrition Risk among Older Mexican Adults in the Mexican Health and Aging Study

Few studies assess the malnutrition risk of older Mexican adults because most studies do not assess nutritional status. This study proposes a modified version of the Mini Nutritional Assessment (MNA) to assess the risk of malnutrition among older Mexicans adults in the Mexican Health and Aging Study (MHAS). Data comes from the 2012, 2015, and 2018 waves of the MHAS, a nationally representative study of Mexicans aged 50 and older. The sample included 13,338 participants and a subsample of 1911 with biomarker values. ROC analysis was used to calculate the cut point for malnutrition risk. This cut point was compared to the definition of malnutrition from the ESPEN criteria, BMI, low hemoglobin, or low cholesterol. Logistic regression was used to assess predictors of malnutrition risk. A score of 10 was the optimal cut point for malnutrition risk in the modified MNA. This cut point had high concordance to identify malnutrition risk compared to the ESPEN criteria (97.7%) and had moderate concordance compared to BMI only (78.6%), and the biomarkers of low hemoglobin (56.1%) and low cholesterol (54.1%). Women, those older than 70, those with Seguro Popular health insurance, and those with fair/poor health were more likely to be malnourished. The modified MNA is an important tool to assess malnutrition risk in future studies using MHAS data.
Multi-Functional MPT Protein as a Therapeutic Agent against Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis (TB), avoids the host immune system through its virulence factors. MPT63 and MPT64 are the virulence factors secreted by MTB which regulate host proteins for the survival and proliferation of MTB in the host. Here, we found that MPT63 bound directly with TBK1 and p47phox, whereas MPT64 interacted with TBK1 and HK2. We constructed a MPT63/64-derived multifunctional recombinant protein (rMPT) that was able to interact with TBK1, p47phox, or HK2. rMPT was shown to regulate IFN-β levels and increase inflammation and concentration of reactive oxygen species (ROS), while targeting macrophages and killing MTB, both in vitro and in vivo. Furthermore, the identification of the role of rMPT against MTB was achieved via vaccination in a mouse model. Taken together, we here present rMPT, which, by regulating important immune signaling systems, can be considered an effective vaccine or therapeutic agent against MTB.
Association Between Constipation and Frailty Components in Patients Undergoing Late Phase II Cardiac Rehabilitation

Background The Japanese Ministry of Health, Labour and Welfare reported that the overall constipation complaint rates among men and women are 2.5% and 4.6%, respectively. To evaluate the impact of constipation on patients with cardiovascular diseases, we investigated the association between constipation and frailty components in patients undergoing cardiac rehabilitation (CR). Methods We enrolled 102 consecutive patients undergoing late phase II CR (mean age: 62.7 ± 13.4 years; 68 (67%) were men). We investigated clinical characteristics, observed defecation status and evaluated frailty components assessed by the Kihon checklist. According to the Clinical Guidelines for Chronic Constipation, the subjects were divided into constipation and non-constipation groups. Results Constipation was noted in 33 patients (32%). Interestingly, the constipation complaint rate was only 15%. Age was significantly higher in the constipation group than in the non-constipation group; however, no differences in sex, underlying diseases and prevalence rates of coronary risk factors were observed between the two groups. Body mass index, hemoglobin level, albumin level and estimated glomerular filtration rate were significantly lower in the constipation group than in the non-constipation group. The prevalence of frailty was significantly higher in the constipation group than in the non-constipation group. Physical ability, seclusion and depression scores were significantly higher in the constipation group than the non-constipation group. Conclusions Constipation was associated with physical function and depression score as components of frailty in patients undergoing CR.
Dissociation, Cognitive Reflection and Health Literacy Have a Modest Effect on Belief in Conspiracy Theories about COVID-19

Introduction Understanding the predictors of belief in covid-related conspiracy theories and willingness to get vaccinated against COVID-19 may aid the resolution of current and future pandemics. Objectives We aim to investigate how psychological and cognitive characteristics influence general conspiracy mentality and covid-related conspiracy theories. Methods A cross-sectional study was conducted based on data from an online survey of a sample of Czech university students (n=866) collected in January 2021, using multivariate linear regression and mediation analysis. Results Sixteen percent of respondents believed that COVID-19 is a hoax; 17% believed that COVID-19 was intentionally created by humans. Seven percent of the variance of the hoax theory and 10% of the variance of the creation theory was explained by (in descending order of relevance) low cognitive reflection, low digital health literacy, high experience with dissociation and, to some extent, high bullshit receptivity. Belief in covid-related conspiracy theories depended less on psychological and cognitive variables compared to conspiracy mentality (16% of the variance explained). The effect of digital health literacy on belief in covid-related theories was moderated by cognitive reflection. Conclusions Belief in conspiracy theories related to COVID-19 was influenced by experience with dissociation, cognitive reflection, digital health literacy and bullshit receptivity. Disclosure No significant relationships.