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Infrared small target detection (ISTD) boasts extensive applications across civil and military domains, owing to its exceptional all-day performance. Neural network innovations have led to deep ISTD models that achieve heightened accuracy through extensive datasets. However, these general networks often fail to perceive the sensitivity of small targets and adopt heavy constructions to preserve potential target features, neglecting domain-specific insights and suffering from poor explainability. Our work seeks to rectify this by revisiting the saliency principles inherent to ISTD and developing a learnable local saliency kernel network (L2SKNet). This approach implements a learnable local saliency kernel module (LLSKM) that embodies the concept of “Center subtracts Neighbors,” guiding the network to capture the saliency features (points or edges). We enhance LLSKM by incorporating strategic dilation and structuring it hierarchically, which boosts its capability to capture multiscale infrared features while avoiding parameter explosion. In pursuit of efficiency, we also refine LLSKM into a more compact form by factorizing it into two orthogonal 1-D kernels, yielding a lightweight version. Heatmap visualizations and rigorous quantitative analyses corroborate the effectiveness of our local saliency-guided networks. Comprehensive testing reveals that L2SKNet variants outperform established baselines, demonstrating significant improvements in both visual and numerical assessments. The code is available at https://github.com/fengyiwu98/L2SKNet.

Infrared small target detection (ISTD) is vital for civil and military applications. However, existing methods often face challenges in coping with complex scenes, discriminating targets from similar objects, or leveraging temporal information effectively. To tackle these limitations, we offer an innovative approach that exploits the spatiotemporal structure of infrared images. A 4-D infrared tensor is initially constructed from a sequence of infrared images and decomposed into lower dimensional tensors using the tensor train (TT) and its extension—tensor ring (TR) techniques. The ISTD problem is then formulated as a sparse plus low-rank decomposition problem, where the sparse part is the target and the low-rank part is the background. We factorize the composed tensors into matrices via TT and TR unfolding approaches, which mitigates the imbalance between different modes containing spatial and temporal information. By constraining the balanced unfolded components with the weighted sum of nuclear norm, we solve the problem using the alternating direction multiplier method (ADMM). Furthermore, we validate models on several datasets and benchmark them with state-of-the-art techniques in detection accuracy and background suppression. Comparison results demonstrate the superiority of our approach over the existing methods. Moreover, the results of an ablation study with 3-D tensor structures show the effectiveness and feasibility of the dimension expansion to 4-D.

Blind image super-resolution (SR), aiming to super-resolve low-resolution images with unknown degradation, has attracted increasing attention due to its significance in promoting real-world applications. Many novel and effective solutions have been proposed recently, especially with powerful deep learning techniques. Despite years of efforts, it still remains as a challenging research problem. This paper serves as a systematic review on recent progress in blind image SR, and proposes a taxonomy to categorize existing methods into three different classes according to their ways of degradation modelling and the data used to solve the SR model. This taxonomy helps summarize and distinguish among existing methods. We hope to provide insights into current research states, as well as revealing novel research directions worth exploring. In addition, we make a summary on commonly used datasets and previous competitions related to blind image SR. Last but not least, a comparison among different methods is provided with detailed analysis on their merits and demerits using both synthetic and real testing images.

The health impact of environmental pollution involving an increase in human diseases has been subject to extensive study in recent decades. The methodology in biomimetic investigation of these pathophysiologic events is still in progress to uncover the gaps in knowledge associated with pollution and its influences on health. Herein, we describe a comprehensive evaluation of environmental pollutant-caused lung inflammation and injury using a microfluidic pulmonary alveolus platform with alveolar-capillary interfaces. We performed a microfluidic three-dimensional coculture with physiological microenvironment simulation at microscale control and demonstrated a reliable reconstruction of tissue layers including alveolar epithelium and microvascular endothelium with typical mechanical, structural, and junctional integrity, as well as viability. On-chip detection and analysis of pulmonary alveolus responses focusing on various inflammatory and injurious dynamics to the respective pollutant stimulations were achieved in the coculture-based microfluidic pulmonary alveolus model, in comparison with common on-chip monoculture and off-chip culture tools. We confirmed the synergistic effects of the epithelial and endothelial interfaces on the stimuli resistance and verified the importance of creating complex tissue microenvironments in vitroto explore pollution-involved human pathology. We believe the microfluidic approach presents great promise in environmental monitoring, drug discovery, and tissue engineering.

●What is the primary question addressed by this study?Are there birth cohort effects in depression symptoms among older adults?●What is the main finding of this study?More recently born cohorts of older adults report fewer depression symptoms than earlier born cohorts, particularly symptoms involving depressed mood, anergia, and hopelessness.●What is the meaning of the finding?Reduced rates of depression symptoms in more recently born older adults may reflect birth cohort trends in compression of medical morbidity and cognitive morbidity.

More than 500 000 neonatal deaths per year result from possible serious bacterial infections (pSBIs), but the causes are largely unknown. We investigated the incidence of community-acquired infections caused by specific organisms among neonates in south Asia.

Carbon Nanomaterials are excellent electrode materials due to their extraordinary conductivity, prolific structures, and morphologies. Herein, a novel nanocarbon-based material (Au@NCNC) was synthesized by embedding gold nanoparticles (AuNPs) inside the pores of three-dimensional hierarchical nitrogen-doped carbon nanocages (NCNC) through an in situ chemical deposition method. The resultant Au@NCNC was employed as an electrochemical catalyst for the oxygen reduction reaction (ORR) and as an electrode material for supercapacitors. The conductivity and hydrophilicity of Au@NCNC were much more improved than those of pristine NCNC. Meanwhile, the bubble adhesive force on the Au@NCNC film was much lower underwater than that of NCNC, which provided easy accessibility to the active sites of reactants, such as hydrated O2. Therefore, the deposition of AuNPs inside pores of NCNC facilitated the transfer of electrons and diffusion of ions, promoting the electrocatalytic performance of Au@NCNC. As a result, Au@NCNC exhibited high performance toward ORR, which manifested in high numbers of electron transfer (3.7–3.9), high kinetic current density, enhanced electrocatalytic stability, and remarkable methanol durability. Moreover, Au@NCNC displayed high specific capacitance, good rate capability, and cycling stability with ∼97% of its initial capacitance retained at the high current density of 10 A g–1after 5000 cycles. This could be attributed to the synergetic effect of ultrafine gold nanoparticles, the hierarchical porous structure, and the hydrophilic surface of NCNC as well. This work offers an excellent alternative for Pt-based catalysts in fuel cells, ORR, and supercapacitive electrode materials by enhancing the conductivity and surface hydrophilicity of electrocatalysts.

A three-dimensional hemin-functionalized graphene hydrogel (Hem/GH) was prepared by a facile self-assembly approach. The as-prepared Hem/GH showed good mechanical strength with a storage modulus of 609–642 kPa and a high adsorption capacity to organic dye contaminants (341 mg g–1for rhodamine B). Moreover, Hem/GH could be used as a photosensitizer for the photocatalytic degradation of organic dyes and displayed superior photodegradation activity of methylene blue (MB). This result was better than that of counterparts such as graphene hydrogel (GH) and commercial catalyst P25. The excellent cycling performance of the Hem/GH was well maintained even after multiple cycles on adsorption process and photocatalytic reaction. Interestingly, after the photodegradation of MB, a light-induced pH change of the solution from alkaline pH 8.99 to acidic pH 3.82 was observed, and 10 wt % total organic carbon remained. The liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS) analysis confirmed the generation of acidic degradation products. The photocatalytic mechanism was further investigated by trapping experiments, which revealed that the MB degradation was driven mainly by the participation of O2•–radicals in the photocatalytic reaction. As an extended application, visually intuitive observation showed the as-prepared Hem/GH also had strong antibacterial properties. These results suggest that Hem/GH could be potentially used for practical application due to its high adsorption ability, excellent photocatalytic activity, and strong antibacterial properties.

Responsive assembly of 2D materials is of great interest for a range of applications. In this work, interfacial functionalized carbon nitride (CN) nanofibers were synthesized by hydrolyzing bulk CN in sodium hydroxide solution. The reversible assemble and disassemble behavior of the as-prepared CN nanofibers was investigated by using CO2as a trigger to form a hydrogel network at first. Compared to the most widespread absorbent materials such as active carbon, graphene and previously reported supramolecular gel, the proposed CN hydrogel not only exhibited a competitive absorbing capacity (maximum absorbing capacity of methylene blue up to 402 mg/g) but also overcame the typical deficiencies such as poor selectivity and high energy-consuming regeneration. This work would provide a strategy to construct a 3D CN network and open an avenue for developing smart assembly for potential applications ranging from environment to selective extraction.

Graphene quantum dots (GQDs) and carbon dots (C-dots) have various alluring properties and potential applications, but they are often limited by unsatisfied optical performance such as low quantum yield, ambiguous fluorescence emission mechanism, and narrow emission wavelength. Herein, we report that bulk polymeric carbon nitride could be utilized as a layered precursor to prepare carbon nitride nanostructures such as nanorods, nanoleaves and quantum dots by chemical tailoring. As doped carbon materials, these carbon nitride nanostructures not only intrinsically emitted UV lights but also well inherited the explicit photoluminescence mechanism of the bulk pristine precursor, both of which were rarely reported for GQDs and C-dots. Especially, carbon nitride quantum dots (CNQDs) had a photoluminescence quantum yield (QY) up to 46%, among the highest QY for metal-free quantum dots so far. As examples, the CNQDs were utilized as a photoluminescence probe for rapid detection of Fe3+with a detection limit of 1 μM in 2 min and a photoconductor in an all-solid-state device. This work would open up an avenue for doped nanocarbon in developing photoelectrical devices and sensors.

We report a general method for the fabrication of three-dimensional (3D) macroporous graphene/conducting polymer modified electrode and nitrogen-doped graphene modified electrode. This method involves three consecutive steps. First, the 3D macroporous graphene (3D MG) electrode was fabricated electrochemically by reducing graphene oxide dispersion on different conducting substrates and used hydrogen bubbles as the dynamic template. The morphology and pore size of 3D MG could be governed by the use of surfactants and the dynamics of bubble generation and departure. Second, 3D macroporous graphene/polypyrrole (MGPPy) composites were constructed via directly electropolymerizing pyrrole monomer onto the networks of 3D MG. Due to the benefit of the good conductivity of 3D MG and pseudocapacitance of PPy, the composites manifest outstanding area specific capacitance of 196 mF cm–2at a current density of 1 mA cm–2. The symmetric supercapacitor device assembled by the composite materials had a good capacity property. Finally, the nitrogen-doped MGPPy (N-MGPPy or MGPPy-X) with 3D macroporous nanostructure and well-regulated nitrogen doping was prepared via thermal treatment of the composites. The resultant N-MGPPy electrode was explored as a good electrocatalyst for the oxygen reduction reaction (ORR) with the current density value of 5.56 mA cm–2(−0.132 V vs Ag/AgCl). Moreover, the fuel tolerance and durability under the electrochemical environment of the N-MGPPy catalyst were found to be superior to the Pt/C catalyst.

Composite films of sulfonated graphene (SG) and polypyrrole (PPy) were electrochemically deposited from the aqueous solutions containing pyrrole monomer, SG sheets, and dodecylbenzene sulfonic acid (DBSA). During the process of electrochemical polymerization, negatively charged SG sheets acted as a dopant of PPy. Thus, they were uniformly dispersed in the PPy matrices of resulting composites. The introduction of SG sheets improved the conductivity and electrochemical properties of PPy films. The composite films containing about 40% (by weight) SG showed a high specific capacitance of 285 F g−1at a discharge rate of 0.5 A g−1. They also exhibited greatly improved electrochemical stability and rate performances.

Composite films of chemically converted graphene (CCG) and polyaniline nanofibers (PANI-NFs) were prepared by vacuum filtration the mixed dispersions of both components. The composite film has a layered structure, and PANI-NFs are sandwiched between CCG layers. Furthermore, it is mechanically stable and has a high flexibility; thus, it can be bent into large angles or be shaped into various desired structures. The conductivity of the composite film containing 44% CCG (5.5 × 102S m−1) is about 10 times that of a PANI-NF film. Supercapacitor devices based on this conductive flexible composite film showed large electrochemical capacitance (210 F g−1) at a discharge rate of 0.3 A g−1. They also exhibited greatly improved electrochemical stability and rate performances.

A gold/polypyrrole (Au/PPy) bilayer actuator was fabricated by electrochemical deposition, and its surface was modified with a bioadhesive polymer, polydopamine. The actuator exhibited high performances of actuation in physiological media. Furthermore, the surface of the actuator is sticky in water and thus can seize bacteria from their aqueous solutions. Actuation greatly increased the efficiency of adhering bacteria on the actuator surface, and this technique provides a cheap and convenient approach for accumulating bacteria from physiological media.

Background: Parkinson’s disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease. The oxidative stress is an important component of the pathogenesis of PD. Artemisinin (ART) has antioxidant and neuroprotective effects. The purpose of this study is to explore the neuroprotective effect of ART on 1-methyl-4-phenyliodine iodide (MPP +)-treated SH-SY5Y cells and underlying mechanism. Methods: We used MPP+-treated SH-SY5Y cells to study the neuroprotective effect of ART. Cell viability was measured by MTT assay after incubating the cells with MPP+and/or ART for 24 h. DCFH-DA was used to detect the level of intracellular reactive oxygen species (ROS), and WST-8 was used to detect the level of superoxide dismutase (SOD). The level of intracellular reduced glutathione (GSH) was detected with 5,5΄-dithiobis-(2-nitrobenzoic acid), and the level of malondialdehyde (MDA) was assessed based on the reaction of MDA and thiobarbituric acid. A mitochondrial membrane potential detection kit (JC-1) was used to detect changes in the mitochondrial membrane potential (MMP), and an Annexin V-FITC cell apoptosis kit was used to detect cell apoptosis. The expression levels of caspase-3, cleaved caspase-3 and the autophagy-related proteins LC3, beclin-1, and p62 were detected by Western blotting. In addition, to verify the change in autophagy, we used immunofluorescence to detect the expression of LC3 and p62. Results: No significant cytotoxicity was observed at ART concentrations up to 40 μM. ART could significantly increase the viability of SH-SY5Y cells treated with MPP+and reduce oxidative stress damage and apoptosis. In addition, the Western blotting and immunofluorescence results showed that MPP+treatment could increase the protein expression of beclin1 and LC3II/LC3I and decrease the protein expression of p62, indicating that MPP+treatment could induce autophagy. Simultaneous treatment with ART and MPP+could decrease the protein expression of beclin1 and LC3II/LC3I and increase the protein expression of p62, indicating that ART could decrease the level of autophagy induced by MPP+. Conclusion: Our results indicate that ART has a protective effect on MPP+-treated SH-SY5Y cells by the antioxidant, antiapoptotic activities and inhibition of autophagy. Our findings may provide new hope for the prevention and treatment of PD.

Many older adults with depressive symptoms have adverse health outcomes and reduced quality of life, but do not meet the clinical threshold for Major Depressive Disorder (MDD). Studies suggest that prevalence of MDD and depressive symptoms is increasing in children and younger adults, but little is known about population trends in depressive symptoms in older adults over age 65.