Meta-learning based blind image super-resolution approach to different degradations.

Although recent studies on blind single image super-resolution (SISR) have achieved significant success, most of them typically require supervised training on synthetic low resolution (LR)-high resolution (HR) paired images. This leads to re-training necessity for different degradations and restricted applications in real-world scenarios with unfavorable inputs. In this paper, we propose an unsupervised blind SISR method with input underlying different degradations, named different degradations blind super-resolution (DDSR). It formulates a Gaussian modeling on blur degradation and employs a meta-learning framework for solving different image degradations. Specifically, a neural network-based kernel generator is optimized by learning from random kernel samples, referred to as random kernel learning. This operation provides effective initialization for blur degradation optimization. At the same time, a meta-learning framework is proposed to resolve multiple degradation modelings on the basis of alternative optimization between blur degradation and image restoration, respectively. Differing from the pre-trained deep-learning methods, the proposed DDSR is implemented in a plug-and-play manner, and is capable of restoring HR image from unfavorable LR input with degradations such as partial coverage, noise addition, and darkening. Extensive simulations illustrate the superior performance of the proposed DDSR approach compared to the state-of-the-arts on public datasets with comparable memory load and time consumption, yet exhibiting better application flexibility and convenience, and significantly better generalization ability towards multiple degradations. Our code is available at https://github.com/XYLGroup/DDSR.

Blind Super-Resolution Via Meta-Learning and Markov Chain Monte Carlo Simulation.

Learning based approaches have witnessed great successes in blind single image super-resolution (SISR) tasks, however, handcrafted kernel priors and learning based kernel priors are typically required. In this paper, we propose a Meta-learning and Markov Chain Monte Carlo based SISR approach to learn kernel priors from organized randomness. In concrete, a lightweight network is adopted as kernel generator, and is optimized via learning from the MCMC simulation on random Gaussian distributions. This procedure provides an approximation for the rational blur kernel, and introduces a network-level Langevin dynamics into SISR optimization processes, which contributes to preventing bad local optimal solutions for kernel estimation. Meanwhile, a meta-learning based alternating optimization procedure is proposed to optimize the kernel generator and image restorer, respectively. In contrast to the conventional alternating minimization strategy, a meta-learning based framework is applied to learn an adaptive optimization strategy, which is less-greedy and results in better convergence performance. These two procedures are iteratively processed in a plug-and-play fashion, for the first time, realizing a learning-based but plug-and-play blind SISR solution in unsupervised inference. Extensive simulations demonstrate the superior performance and generalization ability of the proposed approach when comparing with state-of-the-arts on synthesis and real-world datasets.

Ultra-flat bands at large twist angles in group-V twisted bilayer materials.

Flat bands in 2D twisted materials are key to the realization of correlation-related exotic phenomena. However, a flat band often was achieved in the large system with a very small twist angle, which enormously increases the computational and experimental complexity. In this work, we proposed group-V twisted bilayer materials, including P, As, and Sb in the ß phase with large twist angles. The band structure of twisted bilayer materials up to 2524 atoms has been investigated by a deep learning method DeepH, which significantly reduces the computational time. Our results show that the bandgap and the flat bandwidth of twisted bilayer ß-P, ß-As, and ß-Sb reduce gradually with the decreasing of twist angle, and the ultra-flat band with bandwidth approaching 0 eV is achieved. Interestingly, we found that a twist angle of 9.43° is sufficient to achieve the band flatness for ß-As comparable to that of twist bilayer graphene at the magic angle of 1.08°. Moreover, we also find that the bandgap reduces with decreasing interlayer distance while the flat band is still preserved, which suggests interlayer distance as an effective routine to tune the bandgap of flat band systems. Our research provides a feasible platform for exploring physical phenomena related to flat bands in twisted layered 2D materials.

Degradation of microplastic in water by advanced oxidation processes.

Plastic products have gained global popularity due to their lightweight, excellent ductility, high durability, and portability. However, out of the 8.3 billion tons of plastic waste generated by human activities, 80% of plastic waste is discarded due to improper disposal, and then transformed into microplastic pollution under the combined influence of environmental factors and microorganisms. In this comprehensive study, we present a thorough review of recent advancements in research on the source, distribution, and effect of microplastics. More importantly, we conducted deep research on the catalytic degradation technologies of microplastics in water, including advanced oxidation and photocatalytic technologies, and elaborated on the mechanisms of microplastics degradation in water. Besides, various strategies for mitigating microplastic pollution in aquatic ecosystems are discussed, ranging from policy interventions, the initiative for plastic recycling, the development of efficient catalytic materials, and the integration of multiple technological approaches. This review serves as a valuable resource for addressing the challenge of removing microplastic contaminants from water bodies, offering insights into effective and sustainable solutions.

Facet-dependent activation of oxalic acid over hematite nanocrystals under the irradiation of visible light for efficient degradation of pollutants.

Naturally occurring hematite has been widely studied in the Fenton-like system for water pollutant remediation due to its abundance and non-toxicity. However, its inadequate catalytic activity results in difficulty in effectively degrading pollutants in the catalytic degradation system that it constitutes. Thus, we constructed a photochemical system composed of hematite with {001} facet of high activity facet and low-cost and non-toxic oxalic acid (OA) for the removal of various types of pollutants. The removal rate for the degradation of metronidazole, tetracycline hydrochloride, Rhodamine B, and hexavalent chromium by hematite nanoplate with the exposed {001} facet activating OA under visible light irradiation was 4.75, 2.25, 2.33, and 2.74 times than that by the exposed {110} facet, respectively. Density functional theory (DFT) calculation proved that the OA molecule was more easily adsorbed on the {001} facet of hematite than that on the {110} facet, which would favor the formation of the more Fe(III)-OA complex and reactive species. In addition, the reactive site of metronidazole for the attraction of radicals was identified on the basis of the DFT calculation on the molecular occupied orbitals, and the possible degradation pathway for metronidazole included carbon chain fracture, hydroxyethyl-cleavage, denitrogenation, and hydroxylation. Thus, this finding may offer a valuable direction in designing an efficient iron-based catalyst based on facet engineering for the improved activity of Fenton-like systems such as OA activation.

Suppression of the long non-coding RNA LINC01279 triggers autophagy and apoptosis in lung cancer by regulating FAK and SIN3A.

Long non-coding RNAs play critical roles in the development of lung cancer by functioning as tumor suppressors or oncogenes. Changes in the expression of LINC01279 have been associated with cell differentiation and human diseases. However, the mechanism underlying LINC01279 activity in tumorigenesis is not clear. Here, we analyzed the function of LINC01279 in lung adenocarcinoma using clinical samples, xenografts, and non-small-cell lung cancer cell lines. We found that LINC01279 is highly expressed in lung adenocarcinoma and may be considered as a predictive factor for this cancer. Knockdown of LINC01279 prevents tumor growth in xenografts and in cancer cell lines by activating autophagy and apoptosis. Molecularly, we revealed that LINC01279 regulates the expression of focal adhesion kinase and extracellular-regulated kinase signaling. In addition, it complexes with and stabilizes the transcriptional co-repressor SIN3A protein. Suppression of focal adhesion kinase and SIN3A also induces apoptosis and prevents tumor progression, suggesting that they may at least in part mediate the oncogenic activity of LINC01279. These results identify LINC01279 as a possible oncogene that plays an important role in the development of lung cancer. Our findings provide insights into the mechanism underlying LINC01279-mediated oncogenesis of lung adenocarcinoma. They may help to discover potential therapeutic targets for cancer diagnosis and prognosis.

Perioperative Toripalimab Plus Chemotherapy for Patients With Resectable Non-Small Cell Lung Cancer: The Neotorch Randomized Clinical Trial.

Importance: Adjuvant and neoadjuvant immunotherapy have improved clinical outcomes for patients with early-stage non-small cell lung cancer (NSCLC). However, the optimal combination of checkpoint inhibition with chemotherapy remains unknown. Objective: To determine whether toripalimab in combination with platinum-based chemotherapy will improve event-free survival and major pathological response in patients with stage II or III resectable NSCLC compared with chemotherapy alone. Design, Setting, and Participants: This randomized clinical trial enrolled patients with stage II or III resectable NSCLC (without EGFR or ALK alterations for nonsquamous NSCLC) from March 12, 2020, to June 19, 2023, at 50 participating hospitals in China. The data cutoff date for this interim analysis was November 30, 2022. Interventions: Patients were randomized in a 1:1 ratio to receive 240 mg of toripalimab or placebo once every 3 weeks combined with platinum-based chemotherapy for 3 cycles before surgery and 1 cycle after surgery, followed by toripalimab only (240 mg) or placebo once every 3 weeks for up to 13 cycles. Main Outcomes and Measures: The primary outcomes were event-free survival (assessed by the investigators) and the major pathological response rate (assessed by blinded, independent pathological review). The secondary outcomes included the pathological complete response rate (assessed by blinded, independent pathological review) and adverse events. Results: Of the 501 patients randomized, 404 had stage III NSCLC (202 in the toripalimab + chemotherapy group and 202 in the placebo + chemotherapy group) and 97 had stage II NSCLC and were excluded from this interim analysis. The median age was 62 years (IQR, 56-65 years), 92% of patients were male, and the median follow-up was 18.3 months (IQR, 12.7-22.5 months). For the primary outcome of event-free survival, the median length was not estimable (95% CI, 24.4 months-not estimable) in the toripalimab group compared with 15.1 months (95% CI, 10.6-21.9 months) in the placebo group (hazard ratio, 0.40 [95% CI, 0.28-0.57], P < .001). The major pathological response rate (another primary outcome) was 48.5% (95% CI, 41.4%-55.6%) in the toripalimab group compared with 8.4% (95% CI, 5.0%-13.1%) in the placebo group (between-group difference, 40.2% [95% CI, 32.2%-48.1%], P < .001). The pathological complete response rate (secondary outcome) was 24.8% (95% CI, 19.0%-31.3%) in the toripalimab group compared with 1.0% (95% CI, 0.1%-3.5%) in the placebo group (between-group difference, 23.7% [95% CI, 17.6%-29.8%]). The incidence of immune-related adverse events occurred more frequently in the toripalimab group. No unexpected treatment-related toxic effects were identified. The incidence of grade 3 or higher adverse events, fatal adverse events, and adverse events leading to discontinuation of treatment were comparable between the groups. Conclusions and Relevance: The addition of toripalimab to perioperative chemotherapy led to a significant improvement in event-free survival for patients with resectable stage III NSCLC and this treatment strategy had a manageable safety profile. Trial Registration: ClinicalTrials.gov Identifier: NCT04158440.

Long noncoding RNA LINC00482 silencing sensitizes non-small cell lung cancer cells to cisplatin by downregulating CLASRP via E2F1.

Long noncoding RNA LINC00482 (LINC00482) is dysregulated in non-small cell lung cancer cells (NSCLC). Herein, this research examined the actions and specific mechanisms of LINC00482 in cisplatin (DDP) resistance in NSCLC. LINC00482 expression was assessed using RT-qPCR in clinical NSCLC tissues and cell lines. Knockdown and ectopic expression assays were conducted in A549 and HCC44 cells, followed by determination of cell proliferation with CCK-8 and clone formation assays, apoptosis with flow cytometry, and DDP sensitivity. The association between LINC00482, E2F1, and CLASRP was evaluated with dual-luciferase reporter, ChIP, and RIP assays. The role of LINC00482 in NSCLC was confirmed in nude mice. NSCLC tissues and cells had upregulated LINC00482 expression. LINC00482 was mainly localized in the cell nucleus, and LINC00482 recruited E2F1 to enhance CLASRP expression in NSCLC cells. LINC00482 knockdown enhanced the DDP sensitivity and apoptosis of NSCLC cells while reducing cell proliferation, which was negated by overexpressing CLASRP. LINC00482 knockdown restricted tumor growth and enhanced DDP sensitivity in NSCLC in vivo. LINC00482 silencing downregulated CLASRP through E2F1 to facilitate the sensitivity to DDP in NSCLC.

Efficacy, safety and pharmacokinetics of Unecritinib (TQ-B3101) for patients with ROS1 positive advanced non-small cell lung cancer: a Phase I/II Trial.

This phase I/II trial characterized the tolerability, safety, and antitumor activities of unecritinib, a novel derivative of crizotinib and a multi-tyrosine kinase inhibitor targeting ROS1, ALK, and c-MET, in advanced tumors and ROS1 inhibitor-naive advanced or metastatic non-small cell lung cancer (NSCLC) harboring ROS1 rearrangements. Eligible patients received unecritinib 100, 200, and 300 mg QD, and 200, 250, 300, and 350 mg BID in a 3 + 3 design during dose escalation and 300 and 350 mg BID during expansion. Phase II trial patients received unecritinib 300 mg BID in continuous 28-day cycles until disease progression or unacceptable toxicity. The primary endpoint was the objective response rate (ORR) per independent review committee (IRC). Key secondary endpoints included intracranial ORR and safety. The ORR of 36 efficacy evaluable patients in the phase I trial was 63.9% (95% CI 46.2%, 79.2%). In the phase II trial, 111 eligible patients in the main study cohort received unecritinib. The ORR per IRC was 80.2% (95% CI 71.5%, 87.1%) and the median progression-free survival (PFS) per IRC was 16.5 months (95% CI 10.2, 27.0). Additionally, 46.9% of the patients who received recommended phase II dose of 300 mg BID experienced grade 3 or higher treatment-related adverse events. Treatment-related ocular disorders and neurotoxicity occurred in 28.1% and 34.4% of patients, respectively, but none was grade 3 or higher. Unecritinib is efficacious and safe for ROS1 inhibitor-naive patients with ROS1-positive advanced NSCLC, particularly patients with brain metastases at baseline, strongly supporting that unecritinib should become one of the standards of care for ROS1-positive NSCLC.ClinicalTrials.gov identifier: NCT03019276 and NCT03972189.

Central nervous system efficacy of rezivertinib (BPI-7711) in advanced NSCLC patients with EGFR T790M mutation: A pooled analysis of two clinical studies.

BACKGROUND: Rezivertinib (BPI-7711) is a novel third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) which revealed the systematic and central nervous system (CNS) antitumor activities for EGFR T790M-mutated advanced NSCLC in previous clinical studies and is further analyzed here. METHODS: Eligible patients from the previous phase I and phase IIb studies of rezivertinib were included for pooled analysis. Post-progressive patients who received a prescribed dosage (≥180 mg) of rezivertinib orally once daily were included in full analysis set (FAS), while those with stable, asymptomatic CNS lesions, including measurable and non-measurable ones at baseline were included in CNS full analysis set (cFAS). Patients with measurable CNS lesions were included in CNS evaluable for response set (cEFR). BICR-assessed CNS objective response rate (CNS-ORR), CNS disease control rate (CNS-DCR), CNS duration of response (CNS-DoR), CNS progression-free survival (CNS-PFS), and CNS depth of response (CNS-DepOR) were evaluated. RESULTS: 355 patients were included in FAS, among whom 150 and 45 patients were included in cFAS and cEFR. This pooled analysis showed the CNS-ORR was 32.0% (48/150; 95% CI: 24.6-40.1%) and the CNS-DCR was 42.0% (63/150; 95% CI: 34.0-50.3%) in cFAS, while that in cEFR were 68.9% (31/45; 95% CI: 53.4-81.8%) and 100% (45/45; 95% CI: 92.1-100.0%). In cEFR, the median CNS-DepOR and the mean of CNS-DepOR were -52.0% (range: -100.0 to 16.1%) and -46.8% (95% CI: -55.5 to -38.1%). In cFAS, the median CNS-DoR and CNS-PFS were 13.8 (95% CI: 9.6-not calculable [NC]) and 16.5 (95% CI: 13.7-NC) months. CONCLUSIONS: Rezivertinib demonstrated encouraging clinical CNS efficacy among advanced NSCLC patients with EGFR T790M mutation and CNS metastases.

Circular RNA-mediated ceRNA network was identified in human lung adenocarcinoma by high-throughput sequencing.

OBJECTIVES: Aberrantly expressed circular RNAs (circRNAs) have been detected in many types of tumors. Hence, they are currently investigated as candidate biomarkers for diagnostic and potential targets for therapy in cancers. The objective of this study was to assess the expression profile of circRNA in lung adenocarcinoma (LUAD). METHODS: This study included 14 pairs of postoperative lung adenocarcinoma specimens, including cancer tissues and matched adjacent tissues. Second-generation sequencing was applied to the specimens to determine the circRNA expression in them among the 5242 distinct circRNAs detected. RESULTS: We identified a total of 18 significantly dysregulated circRNAs in the LUAD tissues: upregulation in four and downregulation in 14. ROC (The receiver operating characteristic curve) further suggested that hsa_circ_0120106, has_circ_0007342, has_circ_0005937, and circRNA_0000826 could potentially be used as biomarkers in the diagnosis of LUAD. Furthermore, study of the circRNA-microRNA (miRNA)-messenger RNA (mRNA) revealed interactions between the 18 dysregulated circRNA and several cancer-related miRNAs. Finally, a further Kyoto Encyclopedia of Genes and Genomes analysis showed that the cell cycle phase transition, p53 signaling pathway, AMP-activated protein kinase (AMPK) relative signaling pathway, and so on were key putative pathways in the process of LUAD. CONCLUSIONS: These findings demonstrated the correlation between abnormality in circRNA expression and LUAD, which lays the foundation of making CircRNAs candidate biomarkers in the diagnosis of LUAD.

Spectral Measurements of Muzzle Flash with a Temporally and Spatially Modulated LWIR-Imaging Fourier Transform Spectrometer.

It is important to obtain information on an instantaneous target. A high-speed camera can capture a picture of an immediate scene, but spectral information about the object cannot be retrieved. Spectrographic analysis is a key tool for identifying chemicals. Detecting dangerous gas quickly can help ensure personal safety. In this paper, a temporally and spatially modulated long-wave infrared (LWIR)-imaging Fourier transform spectrometer was used to realize hyperspectral imaging. The spectral range was 700~1450 cm-1 (7~14.5 µm). The frame rate of infrared imaging was 200 Hz. The muzzle-flash area of guns with calibers of 5.56 mm, 7.62 mm, and 14.5 mm were detected. LWIR images of muzzle flash were obtained. Spectral information on muzzle flash was obtained using instantaneous interferograms. The main peak of the spectrum of the muzzle flash appeared at 970 cm-1 (10.31 µm). Two secondary peaks near 930 cm-1 (10.75 µm) and 1030 cm-1 (9.71 µm) were observed. Radiance and brightness temperature were also measured. The spatiotemporal modulation of the LWIR-imaging Fourier transform spectrometer provides a new method for rapid spectral detection. The high-speed identification of hazardous gas leakage can ensure personal safety.

Comprehensive Comparative Analysis Sheds Light on the Patterns of Microsatellite Distribution across Birds Based on the Chromosome-Level Genomes.

Microsatellites (SSRs) are widely distributed in the genomes of organisms and are an important genetic basis for genome evolution and phenotypic adaptation. Although the distribution patterns of microsatellites have been investigated in many phylogenetic lineages, they remain unclear within the morphologically and physiologically diverse avian clades. Here, based on high-quality chromosome-level genomes, we examined the microsatellite distribution patterns for 53 birds from 16 orders. The results demonstrated that each type of SSR had the same ratio between taxa. For example, the frequency of imperfect SSRs (I-SSRs) was 69.90-84.61%, while perfect SSRs (P-SSRs) were 14.86-28.13% and compound SSRs (C-SSRs) were 0.39-2.24%. Mononucleotide SSRs were dominant for perfect SSRs (32.66-76.48%) in most bird species (98.11%), and A(n) was the most abundant repeat motifs of P-SSRs in all birds (5.42-68.22%). Our study further confirmed that the abundance and diversity of microsatellites were less effected by evolutionary history but its length. The number of P-SSRs decreased with increasing repeat times, and longer P-SSRs motifs had a higher variability coefficient of the repeat copy number and lower diversity, indicating that longer motifs tended to have more stable preferences in avian genomes. We also found that P-SSRs were mainly distributed at the gene ends, and the functional annotation for these genes demonstrated that they were related to signal transduction and cellular process. In conclusion, our research provided avian SSR distribution patterns, which will help to explore the genetic basis for phenotypic diversity in birds.

Air-GR: An Over-the-Air Handwritten Character Recognition System Based on Coordinate Correction YOLOv5 Algorithm and LGR-CNN.

Traditional human-computer interaction technology relies heavily on input devices such as mice and keyboards, which limit the speed and naturalness of interaction and can no longer meet the more advanced interaction needs of users. With the development of computer vision (CV) technology, research on contactless gesture recognition has become a new research hotspot. However, current CV-based gesture recognition technology has the limitation of a limited number of gesture recognition and cannot achieve fast and accurate text input operations. To solve this problem, this paper proposes an over-the-air handwritten character recognition system based on the coordinate correction YOLOv5 algorithm and a lightweight convolutional neural network (LGR-CNN), referred to as Air-GR. Unlike the direct recognition of captured gesture pictures, the system uses the trajectory points of gesture actions to generate images for gesture recognition. Firstly, by combining YOLOv5 with the gesture coordinate correction algorithm proposed in this paper, the system can effectively improve gesture detection accuracy. Secondly, considering that the captured gesture coordinates may contain multiple gestures, this paper proposes a time-window-based algorithm for segmenting the gesture coordinates. Finally, the system recognizes user gestures by plotting the segmented gesture coordinates in a two-dimensional coordinate system and feeding them into the constructed lightweight convolutional neural network, LGR-CNN. For the gesture trajectory image classification task, the accuracy of LGR-CNN is 13.2%, 12.2%, and 4.5% higher than that of the mainstream networks VGG16, ResNet, and GoogLeNet, respectively. The experimental results show that Air-GR can quickly and effectively recognize any combination of 26 English letters and numbers, and its recognition accuracy reaches 95.24%.

RF-Alphabet: Cross Domain Alphabet Recognition System Based on RFID Differential Threshold Similarity Calculation Model.

Gesture recognition can help people with a speech impairment to communicate and promote the development of Human-Computer Interaction (HCI) technology. With the development of wireless technology, passive gesture recognition based on RFID has become a research hotspot. In this paper, we propose a low-cost, non-invasive and scalable gesture recognition technology, and successfully implement the RF-alphabet, a gesture recognition system for complex, fine-grained, domain-independent 26 English letters; the RF-alphabet has three major advantages: first, this paper achieves complete capture of complex, fine-grained gesture data by designing a dual-tag, dual-antenna layout. Secondly, to overcome the disadvantages of the large training sets and long training times of traditional deep learning. We design and combine the Difference threshold similarity calculation prediction model to extract digital signal features to achieve real-time feature analysis of gesture signals. Finally, the RF alphabet solves the problem of confusing the signal characteristics of letters. Confused letters are distinguished by comparing the phase values of feature points. The RF-alphabet ends up with an average accuracy of 90.28% and 89.7% in different domains for new users and new environments, respectively, by performing feature analysis on similar signals. The real-time, robustness, and scalability of the RF-alphabet are proven.

Chemical Gas Telemetry System Based on Multispectral Infrared Imaging.

Environmental monitoring, public safety, safe production, and other areas all benefit greatly from the use of gas detection technologies. The infrared image of a gas could be used to determine its type from a long distance in gas detection. The infrared image can show the spatial distribution of the gas cloud and the background, allowing for long-distance and non-contact detection during safety production and hazardous chemical accident rescue. In this study, a gas detection system based on multispectral infrared imaging is devised, which can detect a variety of gases and determine the types of gas by separating the infrared radiation. It is made up of an imaging optical system, an uncooled focal plane detector, a filter controller, and a data gathering and processing system. The resolution of the infrared image is 640 × 512 and the working band of the system is 6.5~15 µm. The system can detect traces of pollutants in ambient air or gas clouds at higher concentrations. Ammonia, sulfur hexafluoride, methane, sulfur dioxide, and dimethyl methyl phosphonate were all successfully detected in real time. Ammonia clouds could be detected at a distance of 1124.5 m.

Metalearning-Based Alternating Minimization Algorithm for Nonconvex Optimization.

In this article, we propose a novel solution for nonconvex problems of multiple variables, especially for those typically solved by an alternating minimization (AM) strategy that splits the original optimization problem into a set of subproblems corresponding to each variable and then iteratively optimizes each subproblem using a fixed updating rule. However, due to the intrinsic nonconvexity of the original optimization problem, the optimization can be trapped into a spurious local minimum even when each subproblem can be optimally solved at each iteration. Meanwhile, learning-based approaches, such as deep unfolding algorithms, have gained popularity for nonconvex optimization; however, they are highly limited by the availability of labeled data and insufficient explainability. To tackle these issues, we propose a meta-learning based alternating minimization (MLAM) method that aims to minimize a part of the global losses over iterations instead of carrying minimization on each subproblem, and it tends to learn an adaptive strategy to replace the handcrafted counterpart resulting in advance on superior performance. The proposed MLAM maintains the original algorithmic principle, providing certain interpretability. We evaluate the proposed method on two representative problems, namely, bilinear inverse problem: matrix completion and nonlinear problem: Gaussian mixture models. The experimental results validate the proposed approach outperforms AM-based methods.

Plate-on-plate structured MoS2/Cd0.6Zn0.4S Z-scheme heterostructure with enhanced photocatalytic hydrogen production activity via hole sacrificial agent synchronously strengthen half-reactions.

The practicable technology for producing hydrogen energy was mainly photocatalytic water splitting. Recently, heterostructural photocatalysts have attracted much attention due to its unique band structures and interfacial interactions. Herein, plate-on-plate MoS2/Cd0.6Zn0.4S heterostructure was rationally designed and fabricated by a simple strategy. It was revealed that Zn-doping content in the Cd0.6Zn0.4S solid solution as well as the mass ratio of MoS2 in the MoS2/Cd0.6Zn0.4S heterostructure can significantly affect the photocatalytic hydrogen evolution reaction (HER) activity. Especially, when Zn doping content is 40 % and the mass ratio of MoS2 is approximately 0.8 % (0.8 % MoS2/Cd0.6Zn0.4S), it exhibits the highest hydrogen production (47.68 µmol·g-1 at 2.5 h) without sacrificial agents. When Na2S/Na2SO3 is employed as sacrificial agent, its HER activity reaches 13466.50 µmol·g-1·h-1, 1.3 folds higher than Cd0.6Zn0.4S. The boosted HER activity of the Z-scheme MoS2/Cd0.6Zn0.4S heterostructure was ascribed to the greatly improved separation efficiency of photogenerated carriers. Most importantly, studies have revealed that the existence of sacrificial agents (Na2S/Na2SO3) can not only accelerate the kinetics of oxidation half reaction, but also synchronously strengthen HER half-reactions. The present work reveals a facile strategy for construction of Z-scheme heterostructures for efficient hydrogen evolution via hole sacrificial agent synchronously strengthen half-reactions.

Facet-Dependent Activation of Oxalic Acid over Magnetic Recyclable Fe3S4 for Efficient Pollutant Removal under Visible Light Irradiation: Enhanced Catalytic Activity, DFT Calculations, and Mechanism Insight.

Photo-Fenton-like reaction based on oxalic acid (OA) activation is a promising method for the fast degradation of pollutants due to the low cost and safety. Hence, the magnetic recyclable greigite (Fe3S4) with the exposed {011} facet (FS-011) was prepared using a facile one-pot hydrothermal method and activated OA under visible light irradiation for pollutant removal, in which the removal efficiency values of FS-011 for metronidazole (MNZ) and hexavalent chromium were 2.02 and 1.88 times higher than that of Fe3S4 with the exposed {112} facet, respectively. Density functional theory calculations revealed that OA was more easily adsorbed by the {011} facet of Fe3S4 than by the {112} facet, and the in situ-generated H2O2 preferred to diffuse away from the active sites of the {011} facet of Fe3S4 than from that of the {112} facet, which was conducive to the continuous adsorption and efficient activation of OA. Moreover, the analyses of Fukui index and dual descriptor confirmed the degradation mechanism that the imidazole ring of MNZ was easy to be attacked by electrophilic species, while the amino group of MNZ was easy to be attacked by nucleophilic species. These findings deeply analyzed the mechanism of enhanced OA activation by facet engineering and consolidated the theoretical basis for practical application of Fenton-like reactions.

Comprehensive Analysis of DMRT3 as a Potential Biomarker Associated with the Immune Infiltration in a Pan-Cancer Analysis and Validation in Lung Adenocarcinoma.

Doublesex and Mab-3 related Transcription Factor 3 (DMRT3) is associated with the prognosis of some tumors. It is possible to explore the role of DMRT3 in the cancer process using bioinformatic approaches and experimental validation. We comprehensively explored the clinical and immunological characteristics of DMRT3. The DMRT3 expression is abnormal in human cancers and correlates with clinical staging. A high DMRT3 expression is significantly associated with poor overall survival (OS) in KIRC, KIRP, LUAD, and UCEC. Amplification was the greatest frequency of the DMRT3 alterations in pan-cancer. The OS was significantly lower in the DMRT3 altered group than in the DMRT3 unaltered group (P = 0.0276). The DMRT3 expression was significantly associated with MSI in three cancer types and TMB in six cancer types. The DMRT3 expression was significantly correlated with the level of the immune cell infiltration and the immune checkpoint genes. The DMRT3 was involved in some pathways in pan-cancer. DMRT3 may play a role in chemotherapy and may be associated with chemoresistance. A ceRNA network of KCNQ1OT1/miR-335-5p/DMRT3 was constructed in LUAD. DMRT3 was significantly upregulated in the LUAD cell lines. DMRT3 was aberrantly expressed in pan-cancer and may promote tumorigenesis and progression via different mechanisms. DMRT3 can be used as a therapeutic target to treat cancer in humans.