Recycling and high-value utilization of polyethylene terephthalate wastes: A review.

Polyethelene terephthalate (PET) is a well-known thermoplastic, and recycling PET waste is important for the natural environment and human health. This study provides a comprehensive overview of the recycling and reuse of PET waste through energy recovery and physical, chemical, and biological recycling. This article summarizes the recycling methods and the high-value products derived from PET waste, specifically detailing the research progress on regenerated PET prepared by the mechanical recycling of fiber/yarn, fabric, and composite materials, and introduces the application of PET nanofibers recycled by physical dissolution and electrospinning in fields such as filtration, adsorption, electronics, and antibacterial materials. This article explains the energy recovery of PET through thermal decomposition and comprehensively discusses various chemical recycling methods, including the reaction mechanisms, catalysts, conversion efficiencies, and reaction products, with a brief introduction to PET biodegradation using hydrolytic enzymes provided. The analysis and comparison of various recycling methods indicated that the mechanical recycling method yielded PET products with a wide range of applications in composite materials. Electrospinning is a highly promising recycling strategy for fabricating recycled PET nanofibers. Compared to other methods, physical recycling has advantages such as low cost, low energy consumption, high value, simple processing, and environmental friendliness, making it the preferred choice for the recycling and high-value utilization of waste PET.

An immunogenic cell death-related gene expression signature in predicting prognosis of pancreatic ductal adenocarcinoma.

BACKGROUND: Immunogenic cell death (ICD) has been identified as regulated cell death, which is sufficient to activate the adaptive immune response. This study aimed to research ICD-related genes and create a gene model to predict pancreatic ductal adenocarcinoma (PAAD) patients' prognosis. METHODS: The RNA sequencing and clinical data were downloaded from the TGCA and GEO databases. The PAAD samples were classified into two subtypes based on the expression levels of ICD-related genes using consensus clustering. Based on the differentially expressed genes (DEGs), a prognostic scoring model was constructed using LASSO regression and Cox regression, and the scoring model was used to predict the prognosis of PAAD patients. Moreover, colony formation assay was performed to confirm the prognostic value of those genes. RESULTS: We identified two ICD cluster by consensus clustering, and found that the the ICD-high group was closely associated with immune-hot phenotype, favorable clinical outcomes. We established an ICD-related prognostic model which can predict the prognosis of pancreatic ductal adenocarcinoma. Moreover, depletion of NT5E, ATG5, FOXP3, and IFNG inhibited the colony formation ability of pancreatic cancer cell. CONCLUSION: We identified a novel classification for PAAD based on the expression of ICD-related genes, which may provide a potential strategy for therapeutics against PAAD.

Diverse Motion In-betweening from Sparse Keyframes with Dual Posture Stitching.

In-betweening is a technique for generating transitions given start and target character states. The majority of existing works require multiple (often ≥ 10) frames as input, which are not always available. In addition, they produce results that lack diversity, which may not fulfill artists' requirements. Addressing these gaps, our work deals with a focused yet challenging problem: generating diverse and high-quality transitions given exactly two frames (only the start and target frames). To cope with this challenging scenario, we propose a bi-directional motion generation and stitching scheme which generates forward and backward transitions from the start and target frames with two adversarial autoregressive networks, respectively, and stitches them midway between the start and target frames. In contrast to stitching at the start or target frames, where the ground truth cannot be altered, there is no strict midway ground truth. Thus, our method can capitalize on this flexibility and generate high-quality and diverse transitions simultaneously. Specifically, we employ conditional variational autoencoders (CVAEs) to implement our autoregressive networks and propose a novel stitching loss to stitch the bi-directional generated motions around the midway point.

Universal method using a pre-deformed reference subset to eliminate the interpolation bias in digital image correlation.

The high measurement accuracy of the digital image correlation (DIC) method is derived from the sub-pixel registration algorithm, which interpolates the intensities at the sub-pixel position in the image. The displacement error caused by the interpolation is a systematic bias in the DIC method, known as the sinusoidal bias in the sub-pixel translation experiment. Although the interpolation bias has been well researched, there is a lack of a universal method to eliminate interpolation bias. In this work, we propose a universal method to eliminate the interpolation bias using a pre-deformed reference subset; pixel points in the pre-deformed subset are deviated from the integer-pixel location. The purpose of the adjustment is to set the deformed pixel points at a specific position, so that the interpolation bias of all deformed pixel points cancels each other out, close to zero. The adjustment of the pre-deformed reference subset is related with the subset size and subset deformation. Numerical experiments including DIC challenge data and a real uniaxial tensile test were conducted to verify the effectiveness and universality of the proposed method, contributing to improved measurement accuracy. Considering the effect of pixel point location on the interpolation bias, this work proposes a universal method to eliminate the interpolation bias and provides a perspective to study DIC errors.

Enhanced Catalytic Performance of Ag NP/0.95AgNbO3-0.05LiTaO3 Heterojunction from the Combination of Surface Plasma Resonance Effect and Piezoelectric Effect Using Facile Mechanical Milling.

An internal built electric field can suppress the recombination of electron-hole pairs and distinctly enhance the catalytic activity of a photocatalyst. Novel t-Ag/0.95AgNbO3-0.05LiTaO3 heterojunction was prepared by reducing silver nanoparticles (Ag NPs) on the surface of the piezoelectric powder 0.95AgNbO3-0.05LiTaO3 (0.05-ANLT) using a simple mechanical milling method. The effects of milling time and excitation source used for the degradation of organic dye by heterojunction catalysts were investigated. The results demonstrate that the optimized 1.5-Ag/0.05-ANLT heterojunction removes 97% RhB within 40 min, which is 7.8 times higher than that of single piezoelectric catalysis and 25.4 times higher than that of single photocatalysis. The significant enhancement of photocatalytic activity can be attributed to the synergistic coupling of the surface plasmon resonance (SPR) effect and the piezoelectric effect.

Electrochemical Fe-catalysed radical cyclization for the synthesis of oxindoles.

We report an efficient and sustainable electrocatalytic approach for the synthesis of 3,3-disubstituted 2-oxindoles bearing ester groups from readily accessible N-arylacrylamides and carbazates. The reaction proceeds through an electrochemical iron-catalyzed radical addition/cyclization sequence with a commercially available iron catalyst and carbazates as alkoxycarbonyl radical precursors. This mild and operationally simple method transforms a wide range of structurally diverse N-arylacrylamides into oxindole derivatives in good yields and can be smoothly scaled up for the preparation of synthetically valuable oxindoles that are key intermediates for the synthesis of natural products.