V3D: Video Diffusion Models are Effective 3D Generators

Automatic 3D generation has recently attracted widespread attention. Recent methods have greatly accelerated the generation speed, but usually produce less-detailed objects due to limited model capacity or 3D data. Motivated by recent advancements in video diffusion models, we introduce V3D, which leverages the world simulation capacity of pre-trained video diffusion models to facilitate 3D generation. To fully unleash the potential of video diffusion to perceive the 3D world, we further introduce geometrical consistency prior and extend the video diffusion model to a multi-view consistent 3D generator. Benefiting from this, the state-of-the-art video diffusion model could be fine-tuned to generate 360degree orbit frames surrounding an object given a single image. With our tailored reconstruction pipelines, we can generate high-quality meshes or 3D Gaussians within 3 minutes. Furthermore, our method can be extended to scene-level novel view synthesis, achieving precise control over the camera path with sparse input views. Extensive experiments demonstrate the superior performance of the proposed approach, especially in terms of generation quality and multi-view consistency. Our code is available at https://github.com/heheyas/V3DComment: Code available at https://github.com/heheyas/V3D Project page: https://heheyas.github.io/V3D

Item-side Fairness of Large Language Model-based Recommendation System

Recommendation systems for Web content distribution intricately connect to the information access and exposure opportunities for vulnerable populations. The emergence of Large Language Models-based Recommendation System (LRS) may introduce additional societal challenges to recommendation systems due to the inherent biases in Large Language Models (LLMs). From the perspective of item-side fairness, there remains a lack of comprehensive investigation into the item-side fairness of LRS given the unique characteristics of LRS compared to conventional recommendation systems. To bridge this gap, this study examines the property of LRS with respect to item-side fairness and reveals the influencing factors of both historical users' interactions and inherent semantic biases of LLMs, shedding light on the need to extend conventional item-side fairness methods for LRS. Towards this goal, we develop a concise and effective framework called IFairLRS to enhance the item-side fairness of an LRS. IFairLRS covers the main stages of building an LRS with specifically adapted strategies to calibrate the recommendations of LRS. We utilize IFairLRS to fine-tune LLaMA, a representative LLM, on \textit{MovieLens} and \textit{Steam} datasets, and observe significant item-side fairness improvements. The code can be found in https://github.com/JiangM-C/IFairLRS.git.Comment: Accepted by the Proceedings of the ACM Web Conference 202

松本歯学 第45巻 第1号 表紙・目次

This study, under zero initial condition, aims to characterize the reachable set bound for a class of neutral Markovian jump systems (NMJSs) with interval time-varying delays and bounded disturbances. To begin with, the time-delays are considered to be mode-dependent while delay mode and system mode are different. By utilizing free-weighting matrix method and reciprocally convex combination technique, an ellipsoid-like bound is characterized for the concerned NMJS with completely known transition probabilities. Based on the provided analytical framework, the case of same delay mode and system mode is also handled. Then, benefitting from a group of free-connection weighting matrices, the reachable set estimation issue is tackled for the NMJS involving mode-independent time-varying delays and partially known transition probabilities. The theoretical analysis is confirmed by numerical simulations

Collaborative interactions of heterogenous ribonucleoproteins contribute to transcriptional regulation of sterol metabolism in mice.

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are a group of functionally versatile proteins that play critical roles in the biogenesis, cellular localization and transport of RNA. Here, we outline a role for hnRNPs in gene regulatory circuits controlling sterol homeostasis. Specifically, we find that tissue-selective loss of the conserved hnRNP RALY enriches for metabolic pathways. Liver-specific deletion of RALY alters hepatic lipid content and serum cholesterol level. In vivo interrogation of chromatin architecture and genome-wide RALY-binding pattern reveal insights into its cooperative interactions and mode of action in regulating cholesterogenesis. Interestingly, we find that RALY binds the promoter region of the master metabolic regulator Srebp2 and show that it directly interacts with coactivator Nuclear Transcription Factor Y (NFY) to influence cholesterogenic gene expression. Our work offers insights into mechanisms orchestrating selective promoter activation in metabolic control and a model by which hnRNPs can impact health and disease states

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

As the focus on Large Language Models (LLMs) in the field of recommendation intensifies, the optimization of LLMs for recommendation purposes (referred to as LLM4Rec) assumes a crucial role in augmenting their effectiveness in providing recommendations. However, existing approaches for LLM4Rec often assess performance using restricted sets of candidates, which may not accurately reflect the models' overall ranking capabilities. In this paper, our objective is to investigate the comprehensive ranking capacity of LLMs and propose a two-step grounding framework known as BIGRec (Bi-step Grounding Paradigm for Recommendation). It initially grounds LLMs to the recommendation space by fine-tuning them to generate meaningful tokens for items and subsequently identifies appropriate actual items that correspond to the generated tokens. By conducting extensive experiments on two datasets, we substantiate the superior performance, capacity for handling few-shot scenarios, and versatility across multiple domains exhibited by BIGRec. Furthermore, we observe that the marginal benefits derived from increasing the quantity of training samples are modest for BIGRec, implying that LLMs possess the limited capability to assimilate statistical information, such as popularity and collaborative filtering, due to their robust semantic priors. These findings also underline the efficacy of integrating diverse statistical information into the LLM4Rec framework, thereby pointing towards a potential avenue for future research. Our code and data are available at https://github.com/SAI990323/Grounding4Rec.Comment: 17 page

Mechanical behaviour of PVC-CFRP confined concrete column with RC beam joint subjected to axial load

U radu je prikazano eksperimentalno istraživanje oblika loma, granične čvrstoće, deformacija i krivulja opterećenje-pomak spoja betonskog stupa obavijenog PVC-CFRP-om i AB grede (PCRBJ) za slučaj osnog opterećenja. Uzorci spoja betonskog stupa obavijenog PVC-om i AB grede (PRBJ) i devet uzoraka PCRBJ projektirani su prema načelu slabog stupa i čvrstog spoja. Predložen je pristup numeričke analize za prikladno predviđanje krivulje opterećenje – pomak. Utvrđeno je da se numerički predviđene vrijednosti dobro podudaraju s rezultatima ispitivanja.An experimental investigation on failure mode, ultimate strength, strain variation, and load-displacement curves of PVC-CFRP confined concrete column with reinforced concrete (RC) beam joint (PCRBJ) subjected to axial load was conducted in this study. Samples of a PVC confined concrete column with RC beam joint (PRBJ) and nine PCRBJs were designed using the principle of weak column and strong joint. A numerical analysis approach for convenient prediction of the load-displacement curve of specimen was proposed. It was established that the estimated values are in good agreement with test data

The Clumpy Structure Of Five Star-bursting Dwarf Galaxies In The MaNGA Survey

The star-forming clumps in star-bursting dwarf galaxies provide valuable insights into the understanding of the evolution of dwarf galaxies. In this paper, we focus on five star-bursting dwarf galaxies featuring off-centered clumps in the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Using the stellar population synthesis software FADO, we obtain the spatially-resolved distribution of the star formation history, which allows us to construct the $g$-band images of the five galaxies at different ages. These images can help us to probe the evolution of the morphological structures of these galaxies. While images of stellar population older than 1 Gyr are typically smooth, images of stellar population younger than 1 Gyr reveal significant clumps, including multiple clumps which appear at different locations and even different ages. To study the evolutionary connections of these five galaxies to other dwarf galaxies before their star-forming clumps appear, we construct the images of the stellar populations older than three age nodes, and define them to be the images of the "host" galaxies. We find that the properties such as the central surface brightness and the effective radii of the hosts of the five galaxies are in between those of dwarf ellipticals (dEs) and dwarf irregulars (dIrrs), with two clearly more similar to dEs and one more similar to dIrrs. Among the five galaxies, 8257-3704 is particularly interesting, as it shows a previous starburst event that is not quite visible from its $gri$ image, but only visible from images of the stellar population at a few hundred million years. The star-forming clump associated with this event may have appeared at around 600 Myr and disappeared at around 40 Myr.Comment: 21 pages, 16 figures, accepted for publication in RA

Senescence: novel insight into DLX3 mutations leading to enhanced bone formation in Tricho-Dento-Osseous syndrome

The homeodomain transcription factor distal-less homeobox 3 gene (DLX3) is required for hair, tooth and skeletal development. DLX3 mutations have been found to be responsible for Tricho-Dento-Osseous (TDO) syndrome, characterized by kinky hair, thin-pitted enamel and increased bone density. Here we show that the DLX3 mutation (c.533 A>G; Q178R) attenuates osteogenic potential and senescence of bone mesenchymal stem cells (BMSCs) isolated from a TDO patient, providing a molecular explanation for abnormal increased bone density. Both DLX3 mutations (c.533 A>G and c.571_574delGGGG) delayed cellular senescence when they were introduced into pre-osteoblastic cells MC3T3-E1. Furthermore, the attenuated skeletal aging and bone loss in DLX3 (Q178R) transgenic mice not only reconfirmed that DLX3 mutation (Q178R) delayed cellular senescence, but also prevented aging-mediated bone loss. Taken together, these results indicate that DLX3 mutations act as a loss of function in senescence. The delayed senescence of BMSCs leads to increased bone formation by compensating decreased osteogenic potentials with more generations and extended functional lifespan. Our findings in the rare human genetic disease unravel a novel mechanism of DLX3 involving the senescence regulation of bone formation

Perioperative Outcomes of Using Different Temperature Management Strategies on Pediatric Patients Undergoing Aortic Arch Surgery: A Single-Center, 8-Year Study

Background: With the widespread application of regional low-flow perfusion (RLFP), development of surgical techniques, and shortened circulatory arrest time, deep hypothermia is indispensable for organ protection. Clinicians have begun to increase the temperature to reduce hypothermia-related adverse outcomes. The aim of this study was to evaluate the safety and efficacy of elevated temperatures during aortic arch surgery with lower body circulatory arrest (LBCA) combined with RLFP.Methods: We retrospectively analyzed data from 207 consecutive pediatric patients who underwent aortic arch repair with LBCA & RLFP between January 2010 and July 2017 and evaluated different hypothermia management strategies. The overall cohort was divided into three groups: deep hypothermia (DH, 20.0–25.0°C), moderate hypothermia (MoH, 25.1–30.0°C) and mild hypothermia (MH, 30.1–34.0°C).Results: The percentage of AKI-1 occurrences was significantly increased in the MH group (51.52%) compared to those in the DH (25.40%) and MoH (37.84%) groups (P = 0.036); prolonged hospital stay occurrences were decreased with elevated temperature (DH 47.62%, MoH 28.83%, MH 18.18%, P = 0.006). Neurological complications, peritoneal dialysis, hepatic dysfunction, 30-day hospital mortality, delay extubation occurrences were no significant among the groups. Logistic analysis showed that the MH group was negatively associated with post-op AKI-1 compared with the DH group [OR = 0.329 (0.137–0.788), P = 0.013], no differences were found between the MoH and the MH group. Compared to other groups, the intubation time (P = 0.006) and postoperative hospital stay (P = 0.009) were significantly decreased in the MH group. Multivariate logistic analysis showed hypothermia levels were not significant with prolonged hospital stay.Conclusions: This retrospective analysis demonstrated that for pediatric patients undergoing surgeries with RLFP & LBCA, three different gradient temperature management strategies are available: deep, moderate, and mild hypothermia. Utilizing mild or moderate hypothermia is safe and feasible. Although the number of AKI-1 occurrences in the MH group was significantly increased compared to those in the other groups, further analysis showed no significance in the MoH and MH group, mild hypothermia management is as safe as others when used appropriately