A topical VAEGAN-IHMM approach for automatic story segmentation.

Feature representations with rich topic information can greatly improve the performance of story segmentation tasks. VAEGAN offers distinct advantages in feature learning by combining variational autoencoder (VAE) and generative adversarial network (GAN), which not only captures intricate data representations through VAE's probabilistic encoding and decoding mechanism but also enhances feature diversity and quality via GAN's adversarial training. To better learn topical domain representation, we used a topical classifier to supervise the training process of VAEGAN. Based on the learned feature, a segmentor splits the document into shorter ones with different topics. Hidden Markov model (HMM) is a popular approach for story segmentation, in which stories are viewed as instances of topics (hidden states). The number of states has to be set manually but it is often unknown in real scenarios. To solve this problem, we proposed an infinite HMM (IHMM) approach which utilized an HDP prior on transition matrices over countably infinite state spaces to automatically infer the state's number from the data. Given a running text, a Blocked Gibbis sampler labeled the states with topic classes. The position where the topic changes was a story boundary. Experimental results on the TDT2 corpus demonstrated that the proposed topical VAEGAN-IHMM approach was significantly better than the traditional HMM method in story segmentation tasks and achieved state-of-the-art performance.

Flexible Wearable Electrochemical Sensors Based on AuNR/PEDOT:PSS for Simultaneous Monitoring of Levodopa and Uric Acid in Sweat.

As a facile substitute for the invasive technique of blood testing, wearable electrochemical sensors exhibit high potential for the noninvasive and real-time monitoring of biomarkers in human sweat. However, owing to enzyme specificity, the simultaneous detection of multiple biomarkers by enzymatic analysis is challenging. Moreover, sweat accumulation under sensors causes sweat contamination, which hinders real-time biomarker detection from sweat. This study reports the design and fabrication of flexible wearable electrochemical sensors containing a composite comprising Au nanorods (AuNRs) and poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) for the nonenzymatic detection of levodopa (LD) and uric acid (UA) in sweat. Each sensor was integrated with a flexible three-electrode system and a microfluidic patch for sweat sampling. AuNRs immobilized by PEG-doped PEDOT:PSS showed excellent analytical performance for LD and UA at different potentials. Thus, the newly fabricated sensors could detect LD and UA over a broad detection range with high sensitivity and showed a low limit of detection for both species. On-body assessments confirmed the ability of these sensors to simultaneously detect LD and UA in real time. Therefore, this study could open new frontiers in the fabrication of wearable electrochemical sensors for the pharmacokinetic profile tracking of LD and gout management.

Stereoselective Synthesis of Polysubstituted Conjugated Dienes Enabled by Photo-Driven Sequential Sigmatropic Rearrangement.

We here reported a highly stereoselective method for the synthesis of polysubstituted conjugated dienes from α-aryl α-diazo alkynyl ketones and pyrazole-substituted unsymmetric aminals under mild conditions, which was promoted by photo-irridation and involved with 1,6-dipolar intermediate and quadruple sigmatropic rearrangements, was successfully developed. In this transformation, the cleavage of four bonds and the recombination of five bonds were implemented in one operational step. This protocol provided a modular tool for constructing dienes from amines, pyrazoles and α-alkynyl-α-diazoketones in one-pot manner. The results of mechanistic investigation indicated that the plausible reaction path underwent the 1,6-sigmatropic rearrangement instead of the 1,5-sigmatropic rearrangement.

Self-supervised Signal Denoising for Magnetic Particle Imaging.

Magnetic particle imaging (MPI) is a medical imaging technology with high resolution and high sensitivity, which tracks the distribution of superparamagnetic iron oxide nanoparticles (SPIONs) in the nonlinear response to dynamic excitation at a field-free region. However, various noises distort the signals resulting in a decline in imaging quality. Traditional threshold-based methods cannot remove dynamic noise in MPI signals. Therefore, a self-supervised denoising method is proposed to denoise MPI signals in this study. The approach adopted U-net as the backbone and modified the network for MPI signals. The network is trained using two periods of noisy signals and the shape prior knowledge of the MPI signals is introduced for promoting the convergence of the self-supervised net. The experiments show that the learning-based method can still denoising the MPI signal without labeling data and eventually improve image quality, and our approach can achieve the best performance compared with other self-supervised methods in MPI signal denoising.

Remote sensing traffic scene retrieval based on learning control algorithm for robot multimodal sensing information fusion and human-machine interaction and collaboration.

In light of advancing socio-economic development and urban infrastructure, urban traffic congestion and accidents have become pressing issues. High-resolution remote sensing images are crucial for supporting urban geographic information systems (GIS), road planning, and vehicle navigation. Additionally, the emergence of robotics presents new possibilities for traffic management and road safety. This study introduces an innovative approach that combines attention mechanisms and robotic multimodal information fusion for retrieving traffic scenes from remote sensing images. Attention mechanisms focus on specific road and traffic features, reducing computation and enhancing detail capture. Graph neural algorithms improve scene retrieval accuracy. To achieve efficient traffic scene retrieval, a robot equipped with advanced sensing technology autonomously navigates urban environments, capturing high-accuracy, wide-coverage images. This facilitates comprehensive traffic databases and real-time traffic information retrieval for precise traffic management. Extensive experiments on large-scale remote sensing datasets demonstrate the feasibility and effectiveness of this approach. The integration of attention mechanisms, graph neural algorithms, and robotic multimodal information fusion enhances traffic scene retrieval, promising improved information extraction accuracy for more effective traffic management, road safety, and intelligent transportation systems. In conclusion, this interdisciplinary approach, combining attention mechanisms, graph neural algorithms, and robotic technology, represents significant progress in traffic scene retrieval from remote sensing images, with potential applications in traffic management, road safety, and urban planning.

Rationally Designed ZnTe@C Nanowires with Superior Zinc Storage Performance for Aqueous Zn Batteries.

Te-based materials with excellent electrical conductivity and ultra-high volume specific capacity have attracted much attention for the cost-efficient aqueous Zn batteries. However, the construction of functional structures with mild volume expansion and suppressed shuttle effects, enabling an expanded lifespan, is still a challenge for conversion-type materials. Herein, the carbon-coated zinc telluride nanowires (ZnTe@C NWs) are rationally designed as a high-performance cathode material for aqueous Zn batteries. The carbon-coated1D nanostructure could not only provide optimized transmission path for electrons and ions, but also help to maintain structure integrity upon volume variation and suppress intermediates dissolution, endowing the ZnTe@C NWs with improved cycling stability and reaction kinetics. Consequently, a reversible six-electron reaction mechanism of ZnTe@C NWs based on Te2- /Te4+ conversion with excellent output capacity (586 mAh g-1 at 0.1 A g-1 ) and lifespan (>250 mAh g-1 retained for 400 cycles at 1 A g-1 ) is eventually achieved.

Chaotic medical image encryption method using attention mechanism fusion ResNet model.

Introduction: With the rapid advancement of artificial intelligence (AI) technology, the protection of patient medical image privacy and security has become a critical concern in current research on image privacy protection. However, traditional methods for encrypting medical images have faced criticism due to their limited flexibility and inadequate security. To overcome these limitations, this study proposes a novel chaotic medical image encryption method, called AT-ResNet-CM, which incorporates the attention mechanism fused with the ResNet model. Methods: The proposed method utilizes the ResNet model as the underlying network for constructing the encryption and decryption framework. The ResNet's residual structure and jump connections are employed to effectively extract profound information from medical images and expedite the model's convergence. To enhance security, the output of the ResNet model is encrypted using a logistic chaotic system, introducing randomness and complexity to the encryption process. Additionally, an attention mechanism is introduced to enhance the model's response to the region of interest within the medical image, thereby strengthening the security of the encrypted network. Results: Experimental simulations and analyses were conducted to evaluate the performance of the proposed approach. The results demonstrate that the proposed method outperforms alternative models in terms of encryption effectiveness, as indicated by a horizontal correlation coefficient of 0.0021 and information entropy of 0.9887. Furthermore, the incorporation of the attention mechanism significantly improves the encryption performance, reducing the horizontal correlation coefficient to 0.0010 and increasing the information entropy to 0.9965. These findings validate the efficacy of the proposed method for medical image encryption tasks, as it offers enhanced security and flexibility compared to existing approaches. Discussion: In conclusion, the AT-ResNet-CM method presents a promising solution to address the limitations of traditional encryption techniques in protecting patient medical images. By leveraging the attention mechanism fused with the ResNet model, the method achieves improved security and flexibility. The experimental results substantiate the superiority of the proposed method in terms of encryption effectiveness, horizontal correlation coefficient, and information entropy. The proposed method not only addresses the shortcomings of traditional methods but also provides a more robust and reliable approach for safeguarding patient medical image privacy and security.

Pt/MXene-Based Flexible Wearable Non-Enzymatic Electrochemical Sensor for Continuous Glucose Detection in Sweat.

Wearable non-invasive sensors facilitate the continuous measurement of glucose in sweat for the treatment and management of diabetes. However, the catalysis of glucose and sweat sampling are challenges in the development of efficient wearable glucose sensors. Herein, we report a flexible wearable non-enzymatic electrochemical sensor for continuous glucose detection in sweat. We synthesized a catalyst (Pt/MXene) by the hybridization of Pt nanoparticles onto MXene (Ti3C2Tx) nanosheets with a broad linear range of glucose detection (0-8 mmol/L) under neutral conditions. Furthermore, we optimized the structure of the sensor by immobilizing Pt/MXene with a conductive hydrogel to enhance the stability of the sensor. Based on Pt/MXene and the optimized structure, we fabricated a flexible wearable glucose sensor by integrating a microfluidic patch for sweat collection onto a flexible sensor. We evaluated the utility of the sensor for the detection of glucose in sweat, and the sensor could detect the glucose change with the replenishment and consumption of energy by the body, and a similar trend was observed in the blood. An in vivo glucose test in sweat indicated that the fabricated sensor is promising for the continuous measurement of glucose, which is essential for the treatment and management of diabetes.

Boosting Cathode Activity and Anode Stability of Zn-S Batteries in Aqueous Media Through Cosolvent-Catalyst Synergy.

Aqueous Zn-S battery with high energy density represents a promising large-scale energy storage technology, but its application is severely hindered by the poor reversibility of both S cathode and Zn anode. Herein, we develop a "cocktail optimized" electrolyte containing tetraglyme (G4) and water as co-solvents and I2 as additive. The G4-I2 synergy could activate efficient polar I3 - /I- catalyst couple and shield the cathode from water, thus facilitating the conversion kinetics of S and suppressing the interfacial side reactions. Simultaneously, it could stabilize Zn anode by forming an organic-inorganic interphase upon cycling. With boosted electrodes reversibility, the Zn-S cell delivers a high capacity of 775 mAh g-1 at 2 A g-1 , and retains over 70 % capacity after 600 cycles at 4 A g-1 . The advances can also be readily generalized to other ethers/water hybrid electrolytes, showing the universality of the "cocktail optimized" electrolyte design strategy.

Genetic Disruption of KLF1 K74 SUMOylation in Hematopoietic System Promotes Healthy Longevity in Mice.

The quest for rejuvenation and prolonged lifespan through transfusion of young blood has been studied for decades with the hope of unlocking the mystery of the key substance(s) that exists in the circulating blood of juvenile organisms. However, a pivotal mediator has yet been identified. Here, atypical findings are presented that are observed in a knockin mouse model carrying a lysine to arginine substitution at residue 74 of Krüppel-like factor 1 (KLF1/EKLF), the SUMOylation-deficient Klf1K74R/K74R mouse, that displayed significant improvement in geriatric disorders and lifespan extension. Klf1K74R/K74R mice exhibit a marked delay in age-related physical performance decline and disease progression as evidenced by physiological and pathological examinations. Furthermore, the KLF1(K74R) knockin affects a subset of lymphoid lineage cells; the abundance of tumor infiltrating effector CD8+ T cells and NKT cells is increased resulting in antitumor immune enhancement in response to tumor cell administration. Significantly, infusion of hematopoietic stem cells (HSCs) from Klf1K74R/K74R mice extends the lifespan of the wild-type mice. The Klf1K74R/K74R mice appear to be an ideal animal model system for further understanding of the molecular/cellular basis of aging and development of new strategies for antiaging and prevention/treatment of age-related diseases thus extending the healthspan as well as lifespan.

NIR-II-Responsive CeO2-x@HA Nanotheranostics for Photoacoustic Imaging-Guided Sonodynamic-Enhanced Synergistic Phototherapy.

The therapeutic effect of photothermal therapy (PTT) and photodynamic therapy (PDT) is severely limited because of the shallow tissue penetration depth of the first near-infrared (NIR-I) light. Multifunctional nanotheranostics irradiated by the second near-infrared (NIR-II) light have received wide interest with respect to deeper tissue penetration, and sonodynamic therapy (SDT) synergistic phototherapy can achieve the complete elimination of tumors. Herein, we successfully constructed a single NIR-II light-induced nanotheranostic using cerium oxide (CeO2-x) with abundant oxygen vacancies for photoacoustic imaging-guided SDT-enhanced phototherapy for the first time. CeO2-x with surface crystalline disorder showed extensive NIR-II region absorption and an outstanding photothermal conversion ability. In addition, the CeO2-x layer with numerous oxygen defects can promote the separation of holes and electrons by ultrasound irradiation, which can remarkably enhance the efficacy of phototherapy to achieve high-efficiency tumor ablation. CeO2-x was surface modified with hyaluronic acid (HA) to prepare CeO2-x@HA to allow active tumor targeting efficiency. Both cell and animal experiments confirmed that all-in-one CeO2-x@HA exhibited a high therapeutic efficacy of SDT-enhanced PDT/PTT under 1064 nm laser irradiation, which achieved complete tumor eradication without systemic toxicity. This study significantly broadened the application of NIR-II-responsive CeO2-x for photoacoustic imaging-mediated SDT-enhanced phototherapy to the highly efficient and precise elimination of tumors.

Multilevel 2-D Quantum Wavelet Transforms.

Wavelet transform is being widely used in classical image processing. One-dimension quantum wavelet transforms (QWTs) have been proposed. Generalizations of the 1-D QWT into multilevel and multidimension have been investigated but restricted to the quantum wavelet packet transform (QWPTs), which is the direct product of 1-D QWPTs, and there is no transform between the packets in different dimensions. A 2-D QWT is vital for image processing. We construct the multilevel 2-D QWT's general theory. Explicitly, we built multilevel 2-D Haar QWT and the multilevel Daubechies D4 QWT, respectively. We have given the complete quantum circuits for these wavelet transforms, using both noniterative and iterative methods. Compared to the 1-D QWT and wavelet packet transform, the multilevel 2-D QWT involves the entanglement between components in different degrees. Complexity analysis reveals that the proposed transforms offer exponential speedup over their classical counterparts. Also, the proposed wavelet transforms are used to realize quantum image compression. Simulation results demonstrate that the proposed wavelet transforms are significant and obtain the same results as their classical counterparts with an exponential speedup.

Two new species of genus Svistella Gorochov, 1987 from China (Orthoptera: Trigonidiidae: Trigonidiinae).

The genus Svistella contains 8 species worldwide with 7 recorded from China. In this study, we reconstructed the gene tree based on COI gene, and reported two new species, S. wuyong He sp. nov. and S. malu He sp. nov. The new species differs from allied species in color, male genitalia, songs and molecular study. The type specimens are deposited in the Museum of Biology, East China Normal University (ECNU).

A new species of genus Homoeoxipha Saussure, 1874 from China (Orthoptera: Trigonidiidae: Trigonidiinae).

The genus Homoeoxipha contains 11 species worldwide with 4 recorded from China. In this study, we reconstructed the gene tree based on COI gene, and reported one new species, H. oscillantenna He sp. nov. The new species is similar to H. eurylobus Ma, Liu Zhang, but differs in the color of fore femur and the structure of male genitalia. Calling songs and nymph morphology are also provided. The type specimens are deposited in the Museum of Biology, East China Normal University (ECNU).

Proanthocyanidins as a Potential Novel Way for the Treatment of Hemangioma.

Hemangioma, the most common benign vascular tumor, not only affects the appearance and psychology but also has a life-threatening potential. It is considered that clonal vascular endothelial cell proliferation and excessive angiogenesis are responsible for hemangioma pathogenesis, in which abnormal cytokines/pathways are closely implicated, primarily including high expression of hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) as well as their downstream pathways, especially phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt). These further stimulate the migration and proliferation of vascular endothelial cells and promote the formation of new vessels, ultimately leading to the occurrence and development of hemangioma. Proanthocyanidins are naturally active substance from plants and fruits. They possess multiple functions like antiproliferation, antiangiogenesis, and antitumor. It has been demonstrated that proanthocyanidins effectively work in various diseases via inhibiting the expression of various factors, e.g., HIF-1α, VEGF, PI3K, and Akt. Considering the pathogenesis of hemangioma and the effect of proanthocyanidins, we hold a hypothesis that proanthocyanidins would be applied in hemangioma via downregulating cytokine/pathway expression, suppressing vascular cell proliferation and arrest abnormal angiogenesis. Taken together, proanthocyanidins may be a potential novel way for the treatment of hemangioma.

Regulating the Polarization of Macrophages: A Promising Approach to Vascular Dermatosis.

Macrophages, a kind of innate immune cells, derive from monocytes in circulation and play a crucial role in the innate and adaptive immunity. Under the stimulation of the signals from local microenvironment, macrophages generally tend to differentiate into two main functional phenotypes depending on their high plasticity and heterogeneity, namely, classically activated macrophage (M1) and alternatively activated macrophage (M2). This phenomenon is often called macrophage polarization. In pathological conditions, chronic persistent inflammation could induce an aberrant response of macrophage and cause a shift in their phenotypes. Moreover, this shift would result in the alteration of macrophage polarization in some vascular dermatoses; e.g., an increase in proinflammatory M1 emerges from Behcet's disease (BD), psoriasis, and systemic lupus erythematosus (SLE), whereas an enhancement in anti-inflammatory M2 appears in infantile hemangioma (IH). Individual polarized phenotypes and their complicated cytokine networks may crucially mediate in the pathological processes of some vascular diseases (vascular dermatosis in particular) by activation of T cell subsets (such as Th1, Th2, Th17, and Treg cells), deterioration of oxidative stress damage, and induction of angiogenesis, but the specific mechanism remains ambiguous. Therefore, in this review, we discuss the possible role of macrophage polarization in the pathological processes of vascular skin diseases. In addition, it is proposed that regulation of macrophage polarization may become a potential strategy for controlling these disorders.

Exploring the phytoremediation potential of water hyacinth by FTIR Spectroscopy and ICP-OES for treatment of heavy metal contaminated water.

Toxic heavy metal pollution of water is a major environmental problem and the current remediation approaches are not optimal as they are non-eco-friendly and lacking in efficiency. As such phytoremediation, a green remediation technology is recognized as a better approach. In this study, both Fourier Transform Infrared (FTIR) Spectroscopy and Inductive Coupled Plasma-Optical Emission Spectroscopy (ICP-OES) were used to investigate the capability of an aquatic plant, water hyacinth (Eichhornia crassipes) to remove heavy metals of lead, copper, cadmium and arsenic from aqueous solution at concentrations of 2 mg/L and 8 mg/L. Overall, the results showed that the uptake was rapid with the plants removing >80% of all the heavy metals at both concentrations. This uptake was proven by the detection of metal accumulation in plant tissues. Roots proved to be better accumulator than leaves. Maximum bioconcentration factor values indicating that the plant is a hyperaccumulator for lead and a moderate accumulator for the other heavy metals. Ligands such as O-H, C-O, C-C and C-H were found to aid the plant in accumulating heavy metal in its tissues. This study concludes that water hyacinth can be utilized as a phytoremediation agent to clean up heavy metal polluted water.

Insight into the fate of antibiotic resistance genes and bacterial community in co-composting green tea residues with swine manure.

Green tea residues (GTRs) are byproducts of tea production and processing, and this type of agricultural waste retains nutritious components. This study investigated the co-composting of GTRs with swine manure, as well as the effects of GTRs on antibiotic resistance genes (ARGs) and the bacterial community during co-composting. The temperature and C/N ratio indicate compost was mature after processing. The addition of GTRs effectively promoted the reduction in the abundances of most targeted ARGs (tet and sul genes), mobile genetic element (MGE; intI1), and metal resistance genes (MRGs; pcoA and tcrB). Redundancy analysis (RDA) showed that GTRs can reduce the abundance of MRGs and ARGs by reducing the bioavailability of heavy metals. Network analysis shows that Firmicutes and Actinobacteria were the main hosts of ARGs and ARGs, MGEs, and MRGs shared the same potential host bacteria. Adding GTRs during composting may reduce ARGs transmission through horizontal gene transfer (HGT). GTRs affected the bacterial community, thereby influencing the variations in the ARG profiles and reducing the potential risk associated with the compost product.

Effects of macroporous adsorption resin on antibiotic resistance genes and the bacterial community during composting.

Swine manure is considered a reservoir for antibiotic resistance genes (ARGs), which may enter the soil and then the food chain to endanger human health. This study investigated the effects of adding 0%, 5%, and 15% (w/w) macroporous adsorption resin (MAR) on ARGs and the bacterial community during composting. The results showed that the addition of MAR reduced the abundances of ARGs (14.14-99.44%) and mobile genetic elements (MGEs) (47.83-99.48%) after swine manure composting. Significant positive correlations were detected between ARGs and MGEs, and thus the variations in MGEs may have led to the changes in ARGs. Redundancy analysis showed that MGEs had stronger effects on ARGs than environmental factors and the bacterial community. Network analysis suggested that ARGs and MGEs co-existed in common host bacteria. In conclusion, the results showed that adding 5% MAR can reduce the risk of ARG transmission.

Effects of nano-zerovalent iron on antibiotic resistance genes and mobile genetic elements during swine manure composting.

Livestock manure is a reservoir for antibiotic resistance genes (ARGs), and aerobic composting is used widely for recycling animal manure. This study investigated the effects of adding nano-zerovalent iron (nZVI) at 0, 100, and 1000 mg/kg on the fates of ARGs and mobile genetic elements (MGEs) during swine manure composting. Under nZVI at 100 mg/kg, the relative abundances of sul1, sul2, dfrA7, ermF, and ermX decreased by 33.26-99.31% after composting, and the relative abundances of intI2 and Tn916/1545 decreased by 95.59% and 97.65%, respectively. Most of the ARGs and MGEs co-occurred and they had strong correlations with each other. The bacterial community structure was significantly separated by the composting periods, and they clustered together under different treatments in the same phase. Network analysis showed that Solibacillus, Clostridium_sensu_stricto_1, Terrisporobacter, Romboutsia, Turicibacter, Lactobacillus, Planococcus, Dietzia, and Corynebacterium_1 were common potential hosts of ARGs and MGEs. Redundancy analysis suggested that MGEs had key effects on the variations in the relative abundances of ARGs. Adding 100 mg/kg nZVI could reduce the environmental risk of ARGs by decreasing the abundances of MGEs.