Miracle-dz/UniFAR-FTUs huggingface dataset:
Super-Resolution 3D Reconstruction from Multiple Cameras

In this paper, we propose a novel method for reconstructing high resolution 3D structure and texture of the scene. In the image processing, it is known that image super-resolution is possible from multiple low resolution images. In this paper, we extend the image super-resolution into 3D space, and show that it is possible to recover high resolution 3D structure and high resolution texture of the scene from low resolution images taken at different viewpoints. The experimental results from real and synthetic images show the efficiency of the proposed method.
Low-velocity impact of honeycomb sandwich composite plates

The performances of low-velocity impact (LVI) and compression after impact (CAI) of honeycomb sandwich composite panels are investigated experimentally and numerically. Honeycomb sandwich panels with different facesheet thicknesses are impacted by drop-weight machine under gradually increasing impact energies. The visible surface damage is recorded and ultrasonic C-scan technology is used to inspect the internal damage of sandwich plates. Numerical simulation is conducted using finite element method, taking into account both facesheet damage and honeycomb damage. The facesheet damage model is based on the continuum damage mechanics and cohesive zone model to simulate intralaminar and interlaminar damage respectively. The honeycomb damage model, which takes into account of both compressive damage and shear damage, is addressed and verified by three-point bending experimental tests. The numerical results show good agreements on LVI and CAI with the experiments, thus verifying the validity of the presented numerical model. Then we use the numerical model to simulate the LVI properties of sandwich plates under compressive and tensile preloading. We conclude that the interlaminar delamination damage of facesheet easily evolves under compressive preloading while intralaminar fiber fracture damage could expand under tensile preloading. The conclusion in our article could be useful to the design and analysis of composite sandwich structures.
A novel Cre‐inducible knock‐in ARL13B‐tRFP fusion cilium reporter

Cilia play a major role in the regulation of numerous signaling pathways and are essential for embryonic development. Mutations in genes affecting ciliary function can cause a variety of diseases in humans summarized as ciliopathies. To facilitate the detection and visualization of cilia in a temporal and spatial manner in mouse tissues, we generated a Cre‐inducible cilium‐specific reporter mouse line expressing an ARL13B‐tRFP fusion protein driven by a CMV enhancer/chicken β actin promotor (pCAG) from the Hprt locus. We detected bright and specific ciliary signals by immunostainings of various mono‐ and multiciliated tissues and by time‐lapse live‐cell analysis of cultured embryos and organ explant cultures. Additionally, we monitored cilium assembly and disassembly in embryonic fibroblast cells using live‐cell imaging. Thus, the ARL13B‐tRFP reporter mouse strain is a valuable tool for the investigation of ciliary structure and function in a tissue‐specific manner to understand processes, such as ciliary protein trafficking or cilium‐dependent signaling in vitro and in vivo.
Meta-Analyses of QTLs Associated with Protein and Oil Contents and Compositions in Soybean [Glycine max (L.) Merr.] Seed

Soybean [Glycine max (L.) Merr. ] is a valuable and nutritious crop in part due to the high protein meal and vegetable oil produced from its seed. Soybean producers desire cultivars with both elevated seed protein and oil concentrations as well as specific amino acid and fatty acid profiles. Numerous studies have identified quantitative trait loci (QTLs) associated with seed composition traits, but validation of these QTLs has rarely been carried out. In this study, we have collected information, including genetic location and additive effects, on each QTL for seed contents of protein and oil, as well as amino acid and fatty acid compositions from over 80 studies. Using BioMercator V. 4.2, a meta-QTL analysis was performed with genetic information comprised of 175 QTLs for protein, 205 QTLs for oil, 156 QTLs for amino acids, and 113 QTLs for fatty acids. A total of 55 meta-QTL for seed composition were detected on 6 out of 20 chromosomes. Meta-QTL possessed narrower confidence intervals than the original QTL and candidate genes were identified within each meta-QTL. These candidate genes elucidate potential natural genetic variation in genes contributing to protein and oil biosynthesis and accumulation, providing meaningful information to further soybean breeding programs.
Insights into eukaryotic DNA priming from the structure and functional interactions of the 4Fe-4S cluster domain of human DNA primase

DNA replication requires priming of DNA templates by enzymes known as primases. Although DNA primase structures are available from archaea and bacteria, the mechanism of DNA priming in higher eukaryotes remains poorly understood in large part due to the absence of the structure of the unique, highly conserved C-terminal regulatory domain of the large subunit (p58C). Here, we present the structure of this domain determined to 1.7-Å resolution by X-ray crystallography. The p58C structure reveals a novel arrangement of an evolutionarily conserved 4Fe-4S cluster buried deeply within the protein core and is not similar to any known protein structure. Analysis of the binding of DNA to p58C by fluorescence anisotropy measurements revealed a strong preference for ss/dsDNA junction substrates. This approach was combined with site-directed mutagenesis to confirm that the binding of DNA occurs to a distinctively basic surface on p58C. A specific interaction of p58C with the C-terminal domain of the intermediate subunit of replication protein A (RPA32C) was identified and characterized by isothermal titration calorimetry and NMR. Restraints from NMR experiments were used to drive computational docking of the two domains and generate a model of the p58C–RPA32C complex. Together, our results explain functional defects in human DNA primase mutants and provide insights into primosome loading on RPA-coated ssDNA and regulation of primase activity.
COX2/mPGES1/PGE2 pathway regulates PD-L1 expression in tumor-associated macrophages and myeloid-derived suppressor cells

Significance Programmed cell death protein ligand 1 (PD-L1)–expressing cells mediate tumor evasion from immune system by suppressing activated T lymphocytes. A bioactive lipid prostaglandin E2 (PGE2) formed from arachidonic acid by COXs and PGE2 synthases (PGESs) facilitates both cancer inflammation and immune suppression. Here, we show that tumor cells can induce PD-L1 expression in bone marrow–derived cells by affecting PGE2 metabolism in hematopoietic cells. The tumor-induced PD-L1 expression was limited to the myeloid cell lineage and, specifically, to the macrophages and myeloid-derived suppressor cells. Collectively, the obtained results demonstrate that selective inhibition of PGE2-forming enzymes COX2, murine PGES1, or genetic overexpression of PGE2-degrading enzyme 15-hydroxyprostaglandin dehydrogenase could provide a novel approach to regulate both PGE2 levels and PD-L1 expression in cancer, thus alleviating the immune suppression and stimulating antitumor immune response. In recent years, it has been established that programmed cell death protein ligand 1 (PD-L1)–mediated inhibition of activated PD-1+ T lymphocytes plays a major role in tumor escape from immune system during cancer progression. Lately, the anti–PD-L1 and –PD-1 immune therapies have become an important tool for treatment of advanced human cancers, including bladder cancer. However, the underlying mechanisms of PD-L1 expression in cancer are not fully understood. We found that coculture of murine bone marrow cells with bladder tumor cells promoted strong expression of PD-L1 in bone marrow–derived myeloid cells. Tumor-induced expression of PD-L1 was limited to F4/80+ macrophages and Ly-6C+ myeloid-derived suppressor cells. These PD-L1–expressing cells were immunosuppressive and were capable of eliminating CD8 T cells in vitro. Tumor-infiltrating PD-L1+ cells isolated from tumor-bearing mice also exerted morphology of tumor-associated macrophages and expressed high levels of prostaglandin E2 (PGE2)-forming enzymes microsomal PGE2 synthase 1 (mPGES1) and COX2. Inhibition of PGE2 formation, using pharmacologic mPGES1 and COX2 inhibitors or genetic overexpression of PGE2-degrading enzyme 15-hydroxyprostaglandin dehydrogenase (15-PGDH), resulted in reduced PD-L1 expression. Together, our study demonstrates that the COX2/mPGES1/PGE2 pathway involved in the regulation of PD-L1 expression in tumor-infiltrating myeloid cells and, therefore, reprogramming of PGE2 metabolism in tumor microenvironment provides an opportunity to reduce immune suppression in tumor host.
Noisy Adaptive Group Testing: Bounds and Algorithms

The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly noisy tests, and is relevant in applications such as medical testing, communication protocols, pattern matching, and many more. One of the defining features of the group testing problem is the distinction between the non-adaptive and adaptive settings. In the non-adaptive case, all tests must be designed in advance, whereas in the adaptive case, each test can be designed based on the previous outcomes. While tight information-theoretic limits and near-optimal practical algorithms are known for the adaptive setting in the absence of noise, surprisingly little is known in the noisy adaptive setting. In this paper, we address this gap by providing information-theoretic achievability and converse bounds under various noise models, as well as a slightly weaker achievability bound for a computationally efficient variant. These bounds are shown to be tight or near-tight in a broad range of scaling regimes, particularly at low noise levels. The algorithms used for the achievability results have the notable feature of only using two or three stages of adaptivity.
Review on Conducting Polymers and Their Applications

Conducting polymers (CPs) have drawn considerable attention because of their economical importance, good environmental stability and electrical conductivity as well as due to their useful mechanical, optical and electronic properties. Some of the widest applications of conducting polymers include: they are used in electrostatic materials, conducting adhesives, electromagnetic shielding against electromagnetic interference (EMI), artificial nerves, aircraft structures, diodes, and transistors. This review covers some of the potential applications of these nanofibers and nanotubes in sensors, nanodiodes, field effect transistors, field emission and electrochromic displays, super-capacitors and energy storage, actuators, drug delivery, neural interfaces, and protein purification and its future prospects.
Dosimetric and clinical effects of interfraction and intrafraction correlation errors during marker-based real-time tumor tracking for liver SBRT

Abstract Correlation model error (CME) between the internal target and the external surrogate, and marker–tumor correlation error (MTCE) between the tumor and the implanted marker occur during marker-based real-time tumor tracking. The effects of these intrafraction and interfraction errors on the dose coverage in the clinical target volume (CTV) and on tumor control probability (TCP) for hepatocellular carcinoma (HCC) were evaluated in this study. Eight HCC patients treated with non-isocentric dose delivery by a robotic radiosurgery system were enrolled. The CMEs were extracted from the treatment log file, and the MTCEs were calculated from the preceding study. The CMEs and MTCEs were randomly added to each beam’s robot position, and the changes in the TCP and the 2%, 95% and 99% dose coverage values for the CTV (D2, D95 and D99) were simulated. The data were statistically analyzed as a function of the CTV to planning target volume (PTV) margin, the dose fraction and the marker–tumor distance. Significant differences were observed in the majority of the CTV D2, D95 and D99 values and the TCP values. However, a linear regression revealed that ∆CTV D2, D95 and D99 have a weak correlation with ∆TCP. A dose-difference metric would be unable to detect a critical error for tumor control if the coverage changes for the CTV and ∆TCP were weakly correlated. Because the simulated TCP-based parameter determination was based on the dose simulation, including predicted interfraction and intrafraction errors, we concluded that a 95th percentile TCP-based parameter determination would be a robust strategy for ensuring tumor control while reducing doses to normal structures.
One-step preparation of hierarchical structures using a dissipative process

Abstaract: A dissipative process enabled us to prepare hierarchical structures by one-step fabrication. A variety of periodic structures arose spontaneously from volatile oil droplets (organic solvent with amphiphilic polymer) and water droplets (particle water suspension) under high humidity. The resulting material had a honeycomb-like structure (the pore size was 1 m), packed with functional fi ne particles, fl uorescent polystyrene or titanium dioxide. This process suggested to us that many materials suspended in water, such as viruses (10 -200 nm diameter) and liposomes (20 -50 nm), could self-organize into periodic structures.
Workforce migration and its economic implications: A perspective from social media in China

The workforce remains the most basic element of social production, even in modern societies. Its migration, especially for developing economies such as China, plays a strong role in the reallocation of productive resources and offers a promising proxy for understanding socio-economic issues. Nevertheless, due to long cycle, expensive cost and coarse granularity, conventional surveys face challenges in comprehensively profiling it. With the permeation of smart and mobile devices in recent decades, booming social media has essentially broken spatio-temporal constraints and enabled the continuous sensing of the real-time mobility of massive numbers of individuals. In this study, we demonstrate that similar to a natural shock, the Spring Festival culturally drives workforce travel between workplaces and hometowns, and the trajectory footprints from social media therefore open a window with unparalleled richness and fine granularity to explore laws in national-level workforce migration. To understand the core driving forces of workforce migration flux between cities in China, various indicators reflecting the benefits and costs of migration are introduced into our prediction model. We find that urban GDP (gross domestic product) and travel time are two excellent indicators to help make predictions. Diverse migration patterns are then revealed by clustering the trajectories, which give important clues to help understand the different roles of Chinese cities in their own development and in regional economic development. These patterns are further explained as a joint effect of the subjective will to seek personal benefits and the capacity requirements of local labour markets. Our study implies that the non-negligible entanglement between social media and macroeconomic behaviours can be insightful for policymaking in social-economic issues.
Analyzing Latent Topics in Student Confessions Communities on Facebook

In recent years, confessions pages have grown popular on social media sites such as Facebook and Twitter, particularly within college communities. Such pages allow users to anonymously submit confessions related to collegiate experience that are subsequently publicly broadcasted. Because of the anonymous nature of disclosure, we believe that confessions pages are novel data sources from which to discover trends and issues in a collegiate community. Aggregating a dataset of more than 20,000 posts from one such page, we analyze natural language characteristics of the originating community with LDA, pointwise mutual information and sentiment analysis. Using a Markov topic model, we examine the latent topics in our corpus and find that loneliness is a highly regular pattern. Our findings on student confession communities support contemporary sociological theories contextualizing student loneliness in the framework of social networks.
Combined Framework for Real-time Head Pose Estimation using Facial Landmark Detection and Salient Feature Tracking

This paper presents a novel approach to address the head pose estimation (HPE) problem in real world and demanding applications. We propose a new framework that combines the detection of facial landmarks with the tracking of salient features within the head region. That is, rigid facial landmarks are detected from a given face image, while at the same time, salient features are detected within the head region. The 3D coordinates of both set of features result from their intersection on a simple geometric head model (e.g., cylinder or ellipsoid). We then formulate the HPE problem as a perspective-n-point problem that we separately solve by minimizing the reprojection error of each 3D features set and their corresponding facial or salient features in the next face image. The resulting head pose estimations are then combined using Kalman Filter, which allows us to take advantage of the high accuracy when using facial landmarks while enabling us to handle extreme head poses by using salient features. Results are comparable to those from the related literature, with the advantage of being robust under real world situations that might not be covered in the evaluated datasets.
Immunomodulatory Effect of Agave tequilana Evaluated on an Autoimmunity Like-SLE Model Induced in Balb/c Mice with Pristane

In this work, the immunomodulatory activity of the acetone extract and the fructans obtained from Agave tequilana were evaluated, on the systemic autoimmunity type-SLE model generated by the administration of 2,6,10,14-tetramethylpentadecane (TMPD, also known as pristane) on Balb/c female mice. The systemic autoimmunity type-SLE was observed seven months after the application of TMPD, in which the animals from the negative control group (animals with damage and without any other treatment) developed articular inflammation, proteinuria, an increment of the antinuclear antibody titters and tissue pro-inflammatory cytokines levels (IL-1β, IL-6, TNF-α e IFN-γ) as well as the anti-inflammatory cytokine IL-10. The administration of the different treatments and the extracts of A. tequilana, provoked the decrease of: articular inflammation, the development of proteinuria, ssDNA/dsDNA antinuclear antibody titters and cytokines IL-1β, IL-6, TNF-α, IFN-γ and IL-10. The phytochemical analysis of the acetone extract identified the presence of the following compounds: β-sitosterol glycoside; 3,7,11,15-tetramethyl-2-hexadecen-1-ol (phytol); octadecadienoic acid-2,3-dihydroxypropyl ester; stigmasta-3,5-dien-7-one; cycloartenone and cycloartenol. Therefore, A. tequilana contains active compounds with the capacity to modify the evolution of the systemic autoimmunity type-SLE on a murine model.
Web Multimedia Object Classification Using Cross-Domain Correlation Knowledge

Given a collection of web images with the corresponding textual descriptions, in this paper, we propose a novel cross-domain learning method to classify these web multimedia objects by transferring the correlation knowledge among different information sources. Here, the knowledge is extracted from unlabeled objects through unsupervised learning and applied to perform supervised classification tasks. To mine more meaningful correlation knowledge, instead of using commonly used visual words in the traditional bag-of-visual-words (BoW) model, we discover higher level visual components (words and phrases) to incorporate the spatial and semantic information into our image representation model, i.e., bag-of-visual-phrases (BoP). By combining the enriched visual components with the textual words, we calculate the frequently co-occurring pairs among them to construct a cross-domain correlated graph in which the correlation knowledge is mined. After that, we investigate two different strategies to apply such knowledge to enrich the feature space where the supervised classification is performed. By transferring such knowledge, our cross-domain transfer learning method can not only handle large scale web multimedia objects, but also deal with the situation that the textual descriptions of a small portion of web images are missing. Empirical experiments on two different datasets of web multimedia objects are conducted to demonstrate the efficacy and effectiveness of our proposed cross-domain transfer learning method.
Demystifying Core Ranking in Pinterest Image Search

Pinterest Image Search Engine helps hundreds of millions of users discover interesting content everyday. This motivates us to improve the image search quality by evolving our ranking techniques. In this work, we share how we practically design and deploy various ranking pipelines into Pinterest image search ecosystem. Specifically, we focus on introducing our novel research and study on three aspects: training data, user/image featurization and ranking models. Extensive offline and online studies compared the performance of different models and demonstrated the efficiency and effectiveness of our final launched ranking models.