A New Chase-type Soft-decision Decoding Algorithm for Reed-Solomon Codes

This paper addresses three relevant issues arising in designing Chase-type algorithms for Reed-Solomon codes: 1) how to choose the set of testing patterns; 2) given the set of testing patterns, what is the optimal testing order in the sense that the most-likely codeword is expected to appear earlier; and 3) how to identify the most-likely codeword. A new Chase-type soft-decision decoding algorithm is proposed, referred to as tree-based Chase-type algorithm. The proposed algorithm takes the set of all vectors as the set of testing patterns, and hence definitely delivers the most-likely codeword provided that the computational resources are allowed. All the testing patterns are arranged in an ordered rooted tree according to the likelihood bounds of the possibly generated codewords. While performing the algorithm, the ordered rooted tree is constructed progressively by adding at most two leafs at each trial. The ordered tree naturally induces a sufficient condition for the most-likely codeword. That is, whenever the proposed algorithm exits before a preset maximum number of trials is reached, the output codeword must be the most-likely one. When the proposed algorithm is combined with Guruswami-Sudan (GS) algorithm, each trial can be implement in an extremely simple way by removing one old point and interpolating one new point. Simulation results show that the proposed algorithm performs better than the recently proposed Chase-type algorithm by Bellorado et al with less trials given that the maximum number of trials is the same. Also proposed are simulation-based performance bounds on the MLD algorithm, which are utilized to illustrate the near-optimality of the proposed algorithm in the high SNR region. In addition, the proposed algorithm admits decoding with a likelihood threshold, that searches the most-likely codeword within an Euclidean sphere rather than a Hamming sphere

Surface Normal Estimation with Transformers

We propose the use of a Transformer to accurately predict normals from point clouds with noise and density variations. Previous learning-based methods utilize PointNet variants to explicitly extract multi-scale features at different input scales, then focus on a surface fitting method by which local point cloud neighborhoods are fitted to a geometric surface approximated by either a polynomial function or a multi-layer perceptron (MLP). However, fitting surfaces to fixed-order polynomial functions can suffer from overfitting or underfitting, and learning MLP-represented hyper-surfaces requires pre-generated per-point weights. To avoid these limitations, we first unify the design choices in previous works and then propose a simplified Transformer-based model to extract richer and more robust geometric features for the surface normal estimation task. Through extensive experiments, we demonstrate that our Transformer-based method achieves state-of-the-art performance on both the synthetic shape dataset PCPNet, and the real-world indoor scene dataset SceneNN, exhibiting more noise-resilient behavior and significantly faster inference. Most importantly, we demonstrate that the sophisticated hand-designed modules in existing works are not necessary to excel at the task of surface normal estimation

Subtle distinction in molecular structure of flavonoids leads to vastly different coating efficiency and mechanism of metal-polyphenol networks with excellent antioxidant activities

Metal-polyphenol networks (MPNs) are of immense scientific interest because of their simple and rapid process to deposit on various substrates or particles with different shapes. However, there are rare reports on the effect of polyphenol molecular structure on coating efficiency and mechanism of MPNs. Herein, three typical flavonoid polyphenols, catechin (Cat), epigallocatechin (EGC) and procyanidin (PC), with the same skeleton (C6-C3-C6) but subtle distinction in molecular structure, were selected to build MPN coatings with ferric ions (Fe3+). And various techniques combined with the density functional theory (DFT) were applied to deeply reveal the roles of coordinative phenolic hydroxyl groups as well as noncovalent interactions (hydrogen bonding and π − π stacking) in the formation of flavonoid-based MPNs. We found that more accessible numbers of coordinative phenolic hydroxyl groups, the higher coating efficiency. In these flavonoid-based MPNs, the single-complex is the predominant during the coordinative modes between phenolic hydroxyl and Fe3+, not the previously reported mono-complex, bis-complex and/or tris-complex. Besides coordinative interaction, noncovalent interactions also contribute to MPNs formation, and hydrogen bonds prevail in the noncovalent interaction compared with π-π stacking. And these engineered MPN coatings can endow the substrate with excellent antioxidant activities. This study contributes to in-depth understanding the building mechanism of flavonoid-based MPNs, and increasing coating efficiency by choosing proper polyphenols

Airborne microplastics: Occurrence, sources, fate, risks and mitigation

This paper serves to enhance the current knowledge base of airborne microplastics which is significantly smaller than that of microplastics in marine, freshwater and terrestrial environments. It systematically presents the prevalence, sources, fate, risks and mitigations of airborne microplastics through the review of >140 scientific papers published mainly in the last 10 years. Unlike the extant review, it places an emphasis on the indoor microplastics, the risks of airborne microplastics on animals and plants and their mitigations. The outdoor microplastics are mostly generated by the wear and tear of tires, brake pads, waste incineration and industrial activities. They have been detected in many regions worldwide at concentrations ranging from 0.3 particles/m3 to 154,000 particles/L of air even in the Pyrenees Mountains and the Arctic. As for indoor microplastics, the reported concentrations range from 1 piece/m3 to 9900 pieces/m2/day, and are frequently higher than those of the outdoor microplastics. They come from the wear and tear of walls and ceilings, synthetic textiles and furniture finishings. Airborne microplastics could be suspended and resuspended, entrapped, settle under gravity as well as interact with chemicals, microorganisms and other microplastic particles. In the outdoors, they could also interact with sunlight and be carried by the wind over long distance. Airborne microplastics could adversely affect plants, animals and humans, leading to reduced photosynthetic rate, retarded growth, oxidative stress, inflammatory responses and increased cancer risks in humans. They could be mitigated indirectly through filters attached to air-conditioning system and directly through source reduction, regulation and biodegradable substitutes.24 month embargo; available online: 07 November 2022This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Follow-Up Infarct Volume Prediction by CTP-Based Hypoperfusion Index, and the Discrepancy between Small Follow-Up Infarct Volume and Poor Functional Outcome—A Multicenter Study

(1) Background: Follow-up infarct volume (FIV) may have implications for prognostication in acute ischemic stroke patients. Factors predicting the discrepancy between FIV and 90-day outcomes are poorly understood. We aimed to develop a comprehensive predictive model of FIV and explore factors associated with the discrepancy. (2) Methods: Patients with acute anterior circulation large vessel occlusion were included. Baseline clinical and CT features were extracted and analyzed, including the CTP-based hypoperfusion index (HI) and the NCCT-based e-ASPECT, measured by automated software. FIV was assessed on follow-up NCCT at 3–7 days. Multiple linear regression was used to construct the predictive model. Subgroup analysis was performed to explore factors associated with poor outcomes (90-mRS scores 3–6) in small FIV (<70 mL). (3) Results: There were 170 patients included. Baseline e-ASPECT, infarct core volume, hypoperfusion volume, HI, baseline international normalized ratio, and successful recanalization were associated with FIV and included in constructing the predictive model. Baseline NIHSS, baseline hypertension, stroke history, and current tobacco use were associated with poor outcomes in small FIV. (4) Conclusions: A comprehensive predictive model (including HI) of FIV was constructed. We also emphasized the importance of hypertension and smoking status at baseline for the functional outcomes in patients with a small FIV

Circular RNA circATP9A promotes non-small cell lung cancer progression by interacting with HuR and by promoting extracellular vesicles-mediated macrophage M2 polarization

Abstract Background CircRNA is recognized for its significant regulatory function across various cancers. However, its regulatory role in non-small cell lung cancer (NSCLC) is still largely uncharted. Methods Analysis based on public databases is completed using R software. circATP9A was identified by two circRNA datasets of NSCLC from the Gene Expression Omnibus database. To examine the impact of circATP9A on the phenotype of NSCLC, we conducted both in vitro and in vivo functional experiments. The mRNA and protein levels of specific molecules were determined through quantitative real-time PCR and western blot assays. RNA pulldown and RNA immunoprecipitation assays were performed to verify the interaction between RNA and protein. The functional role of extracellular vesicles (EVs)-circATP9A on tumor-associated macrophage (TAM) polarization was assessed using co-culture system and cell flow cytometry. Results Here, we elucidates the functional role of circATP9A in NSCLC. We demonstrated that circATP9A can foster the progression of NSCLC through in vivo and in vitro experiments. From a mechanistic standpoint, circATP9A can interact with the HuR protein to form an RNA–protein complex, subsequently amplifying the mRNA and protein levels of the target gene NUCKS1. Further, the PI3K/AKT/mTOR signaling was identified as the downstream pathways of circATP9A/HuR/NUCKS1 axis. More notably, hnRNPA2B1 can mediate the incorporation of circATP9A into EVs. Subsequently, these EVs containing circATP9A induce the M2 phenotype of TAMs, thereby facilitating NSCLC development. Conclusions Our discoveries indicate that circATP9A could serve as a promising diagnostic indicator and a therapeutic target for NSCLC

Phase-tailored assembly and encoding of dissipative soliton molecules

Abstract Self-assembly of particle-like dissipative solitons, in the presence of mutual interactions, emphasizes the vibrant concept of soliton molecules in varieties of laser resonators. Controllable manipulation of the molecular patterns, held by the degrees of freedom of internal motions, still remains challenging to explore more efficient and subtle tailoring approaches for the increasing demands. Here, we report a new phase-tailored quaternary encoding format based on the controllable internal assembly of dissipative soliton molecules. Artificial manipulation of the energy exchange of soliton-molecular elements stimulates the deterministic harnessing of the assemblies of internal dynamics. Self-assembled soliton molecules are tailored into four phase-defined regimes, thus constituting the phase-tailored quaternary encoding format. Such phase-tailored streams are endowed with great robustness and are resistant to significant timing jitter. All these results experimentally demonstrate the programmable phase tailoring and exemplify the application of the phase-tailored quaternary encoding, prospectively promoting high-capacity all-optical storage