Practically Solving LPN in High Noise Regimes Faster Using Neural Networks

We conduct a systematic study of solving the learning parity with noise problem (LPN) using neural networks. Our main contribution is designing families of two-layer neural networks that practically outperform classical algorithms in high-noise, low-dimension regimes. We consider three settings where the numbers of LPN samples are abundant, very limited, and in between. In each setting we provide neural network models that solve LPN as fast as possible. For some settings we are also able to provide theories that explain the rationale of the design of our models. Comparing with the previous experiments of Esser, Kubler, and May (CRYPTO 2017), for dimension $n = 26$, noise rate $\tau = 0.498$, the ''Guess-then-Gaussian-elimination'' algorithm takes 3.12 days on 64 CPU cores, whereas our neural network algorithm takes 66 minutes on 8 GPUs. Our algorithm can also be plugged into the hybrid algorithms for solving middle or large dimension LPN instances.Comment: 37 page

Functional Mapping of Plant Growth in Arabidopsis thaliana

Most traits important to agriculture, biology, and biomedicine are complex traits, determined by both genetic and environmental factors. The complex traits that change their phenotypes over different stages of development are called dynamic traits. Traditional quantitative trait loci (QTLs) mapping approaches ignore the dynamic changes of complex traits. Functional mapping, as a powerful statistical tool, can not only map QTLs that control the developmental pattern and process of complex traits, but also describe the dynamic changes of complex traits. In this study, we used functional mapping to identify those QTLs that affect height growth in 10th generation recombinant inbred lines derived from two different Arabidopsis thaliana accessions. Functional mapping identified 48 QTLs that are related to height traits. The growth curves of different genotypes can be drawn for each significant locus. By GO gene function annotations, we found that these QTLs detected are associated with the synthesis of biological macromolecules and the regulation of biological functions. Our findings provide unique insights into the genetic control of height growth of A. thaliana and will provide a theoretical basis for the study of complex traits

Genome-scale MicroRNA target prediction through clustering with Dirichlet process mixture model

Background: MicroRNA regulation is fundamentally responsible for fine-tuning the whole gene network in human and has been implicated in most physiological and pathological conditions. Studying regulatory impact of microRNA on various cellular and disease processes has resulted in numerous computational tools that investigate microRNA-mRNA interactions through the prediction of static binding site highly dependent on sequence pairing. However, what hindered the practical use of such target prediction is the interplay between competing and cooperative microRNA binding that complicates the whole regulatory process exceptionally. Results: We developed a new method for improved microRNA target prediction based on Dirichlet Process Gaussian Mixture Model (DPGMM) using a large collection of molecular features associated with microRNA, mRNA, and the interaction sites. Multiple validations based on microRNA-mRNA interactions reported in recent large-scale sequencing analyses and a screening test on the entire human transcriptome show that our model outperformed several state-of-the-art tools in terms of promising predictive power on binding sites specific to transcript isoforms with reduced false positive prediction. Last, we illustrated the use of predicted targets in constructing conditional microRNA-mediated gene regulation networks in human cancer. Conclusion: The probability-based binding site prediction provides not only a useful tool for differentiating microRNA targets according to the estimated binding potential but also a capability highly important for exploring dynamic regulation where binding competition is involved

EMDB: The Electromagnetic Database of Global 3D Human Pose and Shape in the Wild

We present EMDB, the Electromagnetic Database of Global 3D Human Pose and Shape in the Wild. EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters with global body and camera trajectories for in-the-wild videos. We use body-worn, wireless electromagnetic (EM) sensors and a hand-held iPhone to record a total of 58 minutes of motion data, distributed over 81 indoor and outdoor sequences and 10 participants. Together with accurate body poses and shapes, we also provide global camera poses and body root trajectories. To construct EMDB, we propose a multi-stage optimization procedure, which first fits SMPL to the 6-DoF EM measurements and then refines the poses via image observations. To achieve high-quality results, we leverage a neural implicit avatar model to reconstruct detailed human surface geometry and appearance, which allows for improved alignment and smoothness via a dense pixel-level objective. Our evaluations, conducted with a multi-view volumetric capture system, indicate that EMDB has an expected accuracy of 2.3 cm positional and 10.6 degrees angular error, surpassing the accuracy of previous in-the-wild datasets. We evaluate existing state-of-the-art monocular RGB methods for camera-relative and global pose estimation on EMDB. EMDB is publicly available under https://ait.ethz.ch/emdbComment: Accepted to ICCV 202

Optimization and simulation of pulsed electric field treatment chamber for food sterilization

Abstract Pulsed Electric field (PEF) cell lysis technology, as a new technology, has been widely used in the fields of food sterilization. Nowadays, there are still several problems in PEF cell lysis: low cell lysis rate, high temperature rise, the presence of low velocity regions, etc. In this study, COMSOL Multiphysics was used to conduct simulation research, and the electric field, flow field and temperature field of plate treatment chamber, coaxial treatment chamber and co-field treatment chamber were coupled to simulate, and the advantages and disadvantages of the three classical treatment chamber structures were analyzed. In addition, this paper proposes a new structure of the co-field treatment chamber. Through the comparison and simulation of the coupling between our design and other four structures, the electric field intensity of our design treatment area is 20.03 kV/m, which is 46.2% higher than the highest of others. The temperature rise within 1s is 0.93 K, which is 2/3 lower than others. Our design almost eliminates the peak electric field area at the junction between the inside of the electrode and the insulator, and the maximum electric field intensity in this area is reduced by 24.4% compared with others

Polyarylether-based 2D covalent-organic frameworks with in-plane D–A structures and tunable energy levels for energy storage

The robust fully conjugated covalent organic frameworks (COFs) are emerging as a novel type of semi-conductive COFs for optoelectronic and energy devices due to their controllable architectures and easily tunable the highest occupied molecular orbital (HOMO) and the lowest occupied molecular orbital (LUMO) levels. However, the carrier mobility of such materials is still beyond requirements due to limited π-conjugation. In this study, a series of new polyarylether-based COFs are rationally synthesized via a direct reaction between hexadecafluorophthalocyanine (electron acceptor) and octahydroxyphthalocyanine (electron donor). These COFs have typical crystalline layered structures, narrow band gaps as low as ≈0.65 eV and ultra-low resistance (1.31 × 10−6 S cm−1). Such COFs can be composed of two different metal-sites and contribute improved carrier mobility via layer-altered staking mode according to density functional theory calculation. Due to the narrow pore size of 1.4 nm and promising conductivity, such COFs and electrochemically exfoliated graphene based free-standing films are fabricated for in-plane micro-supercapacitors, which demonstrate excellent volumetric capacitances (28.1 F cm−3) and excellent stability of 10 000 charge–discharge cycling in acidic electrolyte. This study provides a new approach toward dioxin-linked COFs with donor-acceptor structure and easily tunable energy levels for versatile energy storage and optoelectronic device

Effectiveness of WeChat-Group-Based Parental Health Education in Preventing Unintentional Injuries Among Children Aged 0-3: Randomized Controlled Trial in Shanghai

BACKGROUND: Unintentional injuries to children are a major public health problem. The online social media is a potential way to implement health education for caregivers in online communities. Using WeChat, a free and popular social media service in China, this study evaluated the effectiveness of social online community-based parental health education in preventing unintentional injuries in children aged 0-3. METHODS: We recruited 365 parents from two community health centers in Shanghai and allocated them into intervention and control groups randomly. Follow-up lasted for one year. The intervention group received and followed their WeChat group and a WeChat official account for dissemination of reliable medical information. The control group received only the WeChat group. RESULTS: Between the intervention and control groups, changes in unintentional injuries (OR = 1.71, 95% CI: 1.02-2.87, P = .04), preventability (β = 0.344, 95% CI: 0.152-0.537, P \u3c .001), daily supervision behavior (β = 0.503, 95% CI: 0.036-0.970, P = .04), and behaviors for preventing specific injuries (β = 2.198, 95% CI: 1.530-2.865, P \u3c .001) were significantly different, and change in first-aid skills for treating a tracheal foreign body were nearly significant (P = .06). CONCLUSIONS: The WeChat-group-based parental health education can reduce the occurrence of unintentional child injuries by improving parents\u27 skills, beliefs, and behaviors. Online social communities promote health education and reduce unintentional injuries among children. TRIAL REGISTRATION: ChiCTR1900020753. Registered on January 17, 2019

The pattern of late gadolinium enhancement by cardiac MRI in fulminant myocarditis and its prognostic implication: a two-year follow-up study

BackgroundMyocardial fibrosis, as quantified by late gadolinium enhancement (LGE) in cardiac magnetic resonance (CMR), provides valuable prognostic information for patients with myocarditis. However, due to the low incidence rate of fulminant myocarditis (FM) and accordingly small sample size, the knowledge about the role of LGE to patients with FM is limited.Methods and resultsA total of 44 adults with viral-FM receiving the Chinese treating regimen were included in this retrospective study. They were divided into the low LGE group and the high LGE group according to the ratio of LGE to left ventricular mass (LGE mass%). CMR exams and LGE were performed after hemodynamic assistance at discharge in all patients with FM. Routine echocardiography parameters and global longitudinal strain (GLS) at discharge and at 2-year follow-up were obtained and then compared. Both left ventricular ejection fraction (LVEF) and GLS showed no significant difference in both groups at discharge, whereas significant differences were observed at 2-year follow-up between two groups. Moreover, there were significant improvements of LVEF and GLS in the low LGE group, but not in the high LGE group during the 2-year period. Furthermore, LGE mass% was negatively correlated with GLS and LVEF.ConclusionsThere were two distinct forms of LGE presentation in patients with FM. Moreover, the cardiac function of patients with low LGE was significantly better than those with high LGE at 2-year follow-up. LGE mass% at discharge provided significant prognosis information about cardiac function of patients with FM

Dermatophagoides farinae microRNAs released to external environments via exosomes regulate inflammation-related gene expression in human bronchial epithelial cells

BackgroundDermatophagoides farinae (DFA) is an important species of house dust mites (HDMs) that causes allergic diseases. Previous studies have focused on allergens with protein components to explain the allergic effect of HDMs; however, there is little knowledge on the role of microRNAs (miRNAs) in the allergic effect of HDMs. This study aimed to unravel the new mechanism of dust mite sensitization from the perspective of cross-species transport of extracellular vesicles-encapsulated miRNAs from HDMs.MethodsSmall RNA (sRNA) sequencing was performed to detect miRNAs expression profiles from DFA, DFA-derived exosomes and DFA culture supernatants. A quantitative fluorescent real-time PCR (qPCR) assay was used to detect miRNAs expression in dust specimens. BEAS-2B cells endocytosed exosomes were modeled in vitro to detect miRNAs from DFA and the expression of related inflammatory factors. Representative dfa-miR-276-3p and dfa-novel-miR2 were transfected into BEAS-2B cells, and then differentially expressed genes (DEGs) were analyzed by RNA sequencing. Protein-protein interaction (PPI) network analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) terms enrichment analyses were performed on the first 300 nodes of DEGs.ResultssRNA sequencing identified 42 conserved miRNAs and 66 novel miRNAs in DFA, DFA-derived exosomes, and DFA culture supernatants. A homology analysis was performed on the top 18 conserved miRNAs with high expression levels. The presence of dust mites and miRNAs from HDMs in living environment were also validated. Following uptake of DFA-derived exosomes by BEAS-2B cells, exosomes transported miRNAs from DFA to target cells and produced pro-inflammatory effects in corresponding cells. RNA sequencing identified DEGs in dfa-miR-276-3p and dfa-novel-miR2 transfected BEAS-2B cells. GO and KEGG enrichment analyses revealed the role of exosomes with cross-species transporting of DFA miRNAs in inflammatory signaling pathways, such as JAK-STAT signaling pathway, PI3K/AKT signaling pathway and IL-6-mediated signaling pathway.ConclusionOur findings demonstrate the miRNAs expression profiles in DFA for the first time. The DFA miRNAs are delivered into living environments via exosomes, and engulfed by human bronchial epithelial cells, and cross-species regulation may contribute to inflammation-related processes

Multi-walled carbon nanotubes modified by polyaniline for the removal of alizarin yellow R from aqueous solutions

Multi-walled carbon nanotubes (MWCNTs) encapsulated by polyaniline (PANI) were synthesized by in situ polymerization. Scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy and thermal gravimetric analysis (TGA) were used to characterize the synthesized composites (O-MWCNTs/PANI), and the surface area was calculated by the Brunauer–Emmett–Teller (BET) method. The removal capacity of alizarin yellow R (AYR) with O-MWCNTs/PANI was further investigated. Experiments were conducted to optimize the adsorption conditions, including contact time, pH, initial concentration of AYR and temperature. The results showed that the maximum adsorption capacity for AYR was 884.80 mg/g. The adsorption kinetics and the adsorption isotherm could be better described by the pseudo-second-order model and the Langmuir isotherm, respectively. Energy changes revealed that the adsorption process was exothermic and spontaneous in nature. Additionally, the O-MWCNTs/PANI showed higher adsorption capacity than pristine MWCNTs or PANI. Therefore, O-MWCNTs/PANI would be applied as an efficient adsorbent for the removal of dye from water