Brain APOE expression quantitative trait loci-based association study identified one susceptibility locus for Alzheimer\u27s disease by interacting with APOE epsilon 4

AbstractSome studies have demonstrated interactions of AD-risk single nucleotide polymorphisms (SNPs) in non-APOE regions with APOE genotype. Nevertheless, no study reported interactions of expression quantitative trait locus (eQTL) for APOE with APOE genotype. In present study, we included 9286 unrelated AD patients and 8479 normal controls from 12 cohorts of NIA Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS) and Alzheimer’s Disease Neuroimaging Initiative (ADNI). 34 unrelated brain eQTLs for APOE were compiled from BRAINEAC and GTEx. We used multi-covariate logistic regression analysis to identify eQTLs interacted with APOE ε4. Adjusted for age and gender, substantia nigra eQTL rs438811 for APOE showed significantly strong interaction with APOE ε4 status (OR, 1.448; CI, 1.124–1.430; P-value = 7.94 × 10−6). APOE ε4-based sub-group analyses revealed that carrying one minor allele T of rs438811 can increase the opportunity of developing to AD by 26.75% in APOE ε4 carriers but not in non-carriers. We revealed substantia nigra eQTL rs438811 for APOE can interact with APOE ε4 and confers risk in APOE ε4 carriers only.</jats:p

3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification

Object goal navigation (ObjectNav) in unseen environments is a fundamental task for Embodied AI. Agents in existing works learn ObjectNav policies based on 2D maps, scene graphs, or image sequences. Considering this task happens in 3D space, a 3D-aware agent can advance its ObjectNav capability via learning from fine-grained spatial information. However, leveraging 3D scene representation can be prohibitively unpractical for policy learning in this floor-level task, due to low sample efficiency and expensive computational cost. In this work, we propose a framework for the challenging 3D-aware ObjectNav based on two straightforward sub-policies. The two sub-polices, namely corner-guided exploration policy and category-aware identification policy, simultaneously perform by utilizing online fused 3D points as observation. Through extensive experiments, we show that this framework can dramatically improve the performance in ObjectNav through learning from 3D scene representation. Our framework achieves the best performance among all modular-based methods on the Matterport3D and Gibson datasets, while requiring (up to 30x) less computational cost for training.Comment: To appear in CVPR 202

InstructBrush: Learning Attention-based Instruction Optimization for Image Editing

In recent years, instruction-based image editing methods have garnered significant attention in image editing. However, despite encompassing a wide range of editing priors, these methods are helpless when handling editing tasks that are challenging to accurately describe through language. We propose InstructBrush, an inversion method for instruction-based image editing methods to bridge this gap. It extracts editing effects from exemplar image pairs as editing instructions, which are further applied for image editing. Two key techniques are introduced into InstructBrush, Attention-based Instruction Optimization and Transformation-oriented Instruction Initialization, to address the limitations of the previous method in terms of inversion effects and instruction generalization. To explore the ability of instruction inversion methods to guide image editing in open scenarios, we establish a TransformationOriented Paired Benchmark (TOP-Bench), which contains a rich set of scenes and editing types. The creation of this benchmark paves the way for further exploration of instruction inversion. Quantitatively and qualitatively, our approach achieves superior performance in editing and is more semantically consistent with the target editing effects.Comment: Project Page: https://royzhao926.github.io/InstructBrush

A Review on Modification Methods of Adsorbents for Naphthalene in Environment

Naphthalene is one of the most hazardous polycyclic aromatic hydrocarbons to public health. This paper comprehensively summarized the recent development of modification methods of adsorbents for naphthalene removal in the environment. Various modification methods used in the adsorbent were summarized, mainly including acid oxidation modification, salt modification, doping modification, amino modification, microwave modification, and plasma modification. These methods enhance the adsorption performance of naphthalene mainly by changing the pore size and the oxygen content on the surface of the adsorbent. The modification parameters and their effects on naphthalene removal as well as the advantages and disadvantages of each method are described in detail. This review provides the necessary inspiration and guidance for the researchers who develop polycyclic aromatic hydrocarbons adsorption materials in the environment

A Review on Modification Methods of Adsorbents for Naphthalene in Environment

Naphthalene is one of the most hazardous polycyclic aromatic hydrocarbons to public health. This paper comprehensively summarized the recent development of modification methods of adsorbents for naphthalene removal in the environment. Various modification methods used in the adsorbent were summarized, mainly including acid oxidation modification, salt modification, doping modification, amino modification, microwave modification, and plasma modification. These methods enhance the adsorption performance of naphthalene mainly by changing the pore size and the oxygen content on the surface of the adsorbent. The modification parameters and their effects on naphthalene removal as well as the advantages and disadvantages of each method are described in detail. This review provides the necessary inspiration and guidance for the researchers who develop polycyclic aromatic hydrocarbons adsorption materials in the environment

Infrared Dim and Small Target Detection Based on the Improved Tensor Nuclear Norm

In the face of complex scenes with strong edge contours and high levels of noise, suppressing edge contours and noise levels is challenging with infrared dim and small target detection algorithms. Many advanced algorithms suffer from high false alarm rates when facing this problem. To solve this, a new anisotropic background feature weight function based on the infrared patch tensor (IPT) model was developed in this study to characterize the background airspace difference features by effectively combining the local features with the global features to suppress the strong edge contours in the structural tensor. Secondly, to enhance the target energy in the a priori model, an improved high-order cumulative model was proposed to establish the local significance region of the target as a way to achieve energy enhancement of the significant target in the structural tensor. Finally, the energy-enhanced structural tensor was introduced into the partial sum of the sensor nuclear norm (PSTNN) model as a local feature information weight matrix; the detection results were obtained by solving the model with the help of ADMM. A series of experiments show that the algorithm in this paper achieves better detection results compared with other algorithms

The current fertilizer regimes cause phosphorus deficit in paddy soils and decreased rice phosphorus uptake: a study in Shanghai, China

13 Pág.Excessive phosphorus (P) fertilization in intensive rice-cultivation areas in China has caused serious environmental problems. However, relatively little research has been done on investigating the soil P balance in rice production systems based on different fertilizer regimes. Our study investigated the dynamic variation of soil P balance and rice P use efficiency and productivity from 2014 to 2018 in the paddy fields under synthetic fertilizer (CF) and manure application (OF) regimes based on the practices of local farmers. Flooding water on the paddy fields tends to cause P loss via runoff and leaching. A lysimeter system was used to monitor P loss from paddy fields, which overcame the limitations of real-time monitoring discharge volume and sample-collection. The results with relatively higher rainfall intensity in 2014 and 2015, in total, 4.69 kg P ha−1 under CF and 8.39 kg P ha−1 under OF were lost via runoff in 2014, with 13.6 kg P ha−1 under CF and 17.8 kg P ha−1 under OF in 2015, whereas from 2015 to 2018, no more than 5 kg P ha−1 was lost in CF or OF via runoff. Leaching showed a similar, varying trend for both CF and OF. Furthermore, during the 5 years, a continuous soil P deficit was observed, except in 2017 and 2018 for CF and 2018 for OF. The net P retention ranged from −15.31 to 6.2 kg ha−1 for CF and from −23.65 to 2.64 kg ha−1 for OF. The continuous P deficit in paddy soils might have reduced soil P storage. These huge P losses undermined rice yield production. In parallel, after 2014, the grain yield decreased from 10,885.7 in 2014 to 6266.7 kg ha−1 in 2017 under CF and from 10,607.6 to 6649.6 kg ha−1 under OF. Overall, these results reveal a risk of declining P storage in paddy soils and a potential menace on food safety under the current fertilizer management, suggesting that novel fertilizer strategies need to be developed for reserving P storage in paddy fields.Financial support for this study was provided by the Shanghai “Science and Technology Innovation Action Plan” Project (22002400300) and National Key Research And Development Program of China (No. 2016YFD0801106).Peer reviewe

High-Efficiency Adsorption of SARS-CoV-2 Spike 1 Protein by Plasma-Modified Porous Polymers

Under the background of the COVID-19 pandemic, this study reports an affordable and easily prepared porous material modified by nanosecond-pulsed discharge plasma, which can adsorb SARS-CoV-2 S1 protein efficiently. Both Western blotting and an enzyme-linked immunosorbent assay were used to detect the adsorption efficiency of SARS-CoV-2 S1 protein. The physical and chemical properties of the modified porous polymer were characterized by scanning electron microscopy, X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy. We found that the new type of porous polymer material presented an excellent performance on SARS-CoV-2 S1 protein adsorption, whose adsorption efficiency reached 99.99% in 1 min. Both the physical and chemical characterizations showed that the material has many fresh pores on the material surface and that the surface is implanted with polar functional groups (C&minus;O, C=O, O&minus;C=O and &minus;NH), which gives the material a high chemisorption performance along with an enhanced physical adsorption performance. Notably, the material can be prepared at prices ranging in the tens of dollars per kilogram, which shows that it could have great applications for respiratory virus protection in global epidemic states

Numerical Analysis of Dynamic Characteristics of an Asymmetric Tri-Stable Piezoelectric Energy Harvester under Random Vibrations in Building Structures

This study presents a novel design for a tri-stable piezoelectric vibration energy harvester with an asymmetric structure, which is enhanced with an elastic base (TPVEH + EB), meticulously designed to enhance energy extraction from irregular vibrations in architectural structures. The cornerstone of this design is the asymmetric tri-stable piezoelectric cantilever beam, distinctively arranged within a U-shaped block and fortified with an elastic foundation. A carefully positioned spring (kf)-mass (Mf) system between the U-shaped block and the beam’s fixed end significantly boosts the vertical displacement of the beam during oscillations. Utilizing Lagrange’s equations, we formulated a dynamic model for the asymmetric TPVEH + EB, examining the effects of potential well asymmetry, the stiffness of the elastic base and spring-mass system, the mass of the spring-mass system, and the tip magnet mass on the system’s nonlinear dynamic responses. Our results demonstrate that the asymmetric TPVEH + EB significantly enhances energy harvesting from low-amplitude random vibrations (1.5 g), with the output voltage of the asymmetric TPVEH + EB increasing by 30% and the output power by 25%. Extensive numerical and theoretical analyses verify that the asymmetric TPVEH + EB provides a highly efficient solution for scenarios typically hindered by low energy conversion rates. Its reliable performance under varied and unpredictable excitation conditions highlights its excellence in advanced energy harvesting applications. The improvements detailed in this research underscore the potential of the asymmetric TPVEH + EB to boost energy harvesting efficiency, particularly in powering wireless sensor nodes for structural health monitoring in buildings. By overcoming the limitations of traditional harvesters, the asymmetric TPVEH + EB ensures enhanced efficiency and reliability, making it an ideal solution for a wide range of practical applications in diverse environmental conditions within buildings