Multifunctional 2-bit coded reconfigurable metasurface based on graphene-vanadium dioxide.

In this paper, a graphene-vanadium dioxide-based reconfigurable metasurface unit structure is proposed. Using the change at a graphene Fermi energy level on the surface of the unit structure to satisfy the 2-bit coding condition, four reflection units with a phase difference of 90 ∘ can be discovered. The modulating impact of the multi-beam reflection wave with 1-bit coding is then confirmed. Then we study the control of a single-beam reflected wave by metasurfaces combined with a convolution theorem in a 2-bit coding mode. Finally, when vanadium dioxide is in an insulating condition, the structure can also be transformed into a terahertz absorber. It is possible to switch between a reflection beam controller and a terahertz multifrequency absorber simply by changing the temperature of the vanadium dioxide layer without retooling a new metasurface. Moreover, compared with the 1-bit coded metasurface, it increases the ability of single-beam regulation, which makes the device more powerful for beam regulation.

Clinical and biochemical evaluation of rituximab as add on therapy in neuromyelitis optica spectrum disorders.

OBJECTIVE: This study assesses the efficacy of rituximab in the treatment of neuromyelitis optica spectrum disorders (NMOSD). METHODS: The study initially included 40 patients with NMOSD diagnosed, after excluding patients who did not meet the complete inclusion criteria. Patients in the conventional group received routine clinical treatment, while patients in the study group received additional treatment with rituximab on the basis of the conventional treatment. Baseline data and clinically relevant indicators were collected for all patients, and the efficacy was compared between the two groups. RESULTS: Baseline data were comparable between the two groups (p > 0.05). The EDSS scores after clinical treatment in the study group were lower than those in the conventional group, and the difference in EDSS scores before and after treatment was higher than that in the conventional group (p < 0.05). The difference in visual acuity correction before and after treatment was not significant between the two groups (p > 0.05). Laboratory indicators in the study group after clinical treatment were superior to those in the conventional group (all p < 0.05). The recurrence rate after clinical treatment in the study group was significantly lower than that in the conventional group (p < 0.05). Adverse reactions after clinical treatment in the study group were less than those in the conventional group (p < 0.05). CONCLUSION: This study found that rituximab demonstrated significant efficacy in the acute attacks and recurrence prevention of NMOSD, emphasizing its relatively good safety and tolerability. It highlights the potential of rituximab in treating NMOSD and provides valuable insights for future disease management.

Generalized latent multi-view clustering with tensorized bipartite graph.

Tensor-based multi-view spectral clustering algorithms use tensors to model the structure of multi-dimensional data to take advantage of the complementary information and high-order correlations embedded in the graph, thus achieving impressive clustering performance. However, these algorithms use linear models to obtain consensus, which prevents the learned consensus from adequately representing the nonlinear structure of complex data. In order to address this issue, we propose a method called Generalized Latent Multi-View Clustering with Tensorized Bipartite Graph (GLMC-TBG). Specifically, in this paper we introduce neural networks to learn highly nonlinear mappings that encode nonlinear structures in graphs into latent representations. In addition, multiple views share the same latent consensus through nonlinear interactions. In this way, a more comprehensive common representation from multiple views can be achieved. An Augmented Lagrangian Multiplier with Alternating Direction Minimization (ALM-ADM) framework is designed to optimize the model. Experiments on seven real-world data sets verify that the proposed algorithm is superior to state-of-the-art algorithms.

Reprogramming macrophage by targeting VEGF and CD40 potentiates OX40 immunotherapy.

The low clinical response rate of checkpoint blockades, such as PD-1 and CTLA-4, highlighted the requirements of agonistic antibodies to boost optimal T cell responses. OX40, a co-stimulatory receptor on the T cells, plays a crucial role in promoting T cell survival and differentiation. However, the clinical efficacy of anti-OX40 agonistic antibodies was unimpressive. To explore the mechanism underlying the action of anti-OX40 agonists to improve the anti-tumor efficacy, we analyzed the dynamic changes of tumor-infiltrating immune cells at different days post-treatments using single-cell RNA-sequencing (scRNA-seq). In this study, we found that tumor-infiltrating regulatory T (Treg) cells were reduced after two rounds of anti-OX40 treatment, but the increase of infiltration and activation of CD8+ effector T cells, as well as M1 polarization in the tumor were only observed after three rounds of treatments. Moreover, our group first analyzed the antitumor effect of anti-OX40 treatments on regulating the macrophages and discovered the dynamic changes of vascular endothelial growth factor (VEGF) and CD40 signaling pathways on macrophages, indicating their possibility to being potential combination targets to improve the anti-OX40 agonists efficacy. The combination of VEGFR inhibitors or anti-CD40 agonist antibody with anti-OX40 agonists exhibited more remarkable inhibition of tumor growth. Therefore, the mechanism-driven combination of anti-OX40 agonists with VEGFR inhibitors or anti-CD40 agonists represented promising strategies.

Role of prognostic gene DKK1 in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is one of the most common squamous cell carcinomas of the head and neck. The morbidity and mortality rates of OSCC have increased in recent years. However, the pathogenesis of this disease remains unknown. The present study aimed to identify predictive biomarkers and therapeutic targets for OSCC. Bioinformatics screening of differentially expressed genes in OSCC was performed based on data from The Cancer Genome Atlas and Gene Expression Omnibus databases. Dickkopf Wnt signaling pathway inhibitor 1 (DKK1) was identified to be associated with survival, tumor immunity and DNA repair in OSCC. Furthermore, the effects of DKK1 were evaluated by the knockdown of DKK1 in two OSCC cell lines. The proliferation, clonogenicity, migration and invasion of the cells were assessed in vitro using Cell Counting Kit-8, colony formation, wound healing and Transwell assays, respectively, and were found to be inhibited by DKK1 knockdown. The present study suggests that DKK1 may be used in the prognosis of patients with OSCC and that targeting DKK1 is a potential strategy for OSCC therapy.

Rice PIFs: Critical regulators in rice development and stress response.

Phytochrome-interacting factors (PIFs) belong to a subfamily of the basic helix-loop-helix (bHLH) family of transcription factors, which serve as a "hub" for development and growth of plants. They have the capability to regulate the expression of many downstream genes, integrate multiple signaling pathways, and act as a signaling center within the cell. In rice (Oryza sativa), the PIF family genes, known as OsPILs, play a crucial part in many different aspects. OsPILs play a crucial role in regulating various aspects of photomorphogenesis, skotomorphogenesis, plant growth, and development in rice. These vital processes include chlorophyll synthesis, plant gravitropism, plant height, flowering, and response to abiotic stress factors such as low temperature, drought, and high salt. Additionally, OsPILs are involved in controlling several important agronomic traits in rice. Some OsPILs members coordinate with each other to function. This review summarizes and prospects the latest research progress on the biological functions of OsPILs transcription factors and provides a reference for further exploring the functions and mechanism of OsPILs.

Graphene electromagnetically induced transparent polarization-insensitive sensors in the mid-infrared frequency band.

In this paper, a polarization-insensitive sensor based on graphene electromagnetically induced transparency (EIT) is proposed. The device consists of two graphene orthogonal T-shaped structures. This T-shaped resonator produces transparent windows that largely overlap under x and y polarizations, and the results demonstrate its good polarization insensitivity. The device can accomplish detection performance with sensitivity higher than 4960 nm/RIU and figure of merit (FOM) greater than 11.4. Meanwhile, when the Fermi energy level of graphene changes from 0.5 to 0.8 eV, it enables arbitrary modulation of the operating frequency over a wide frequency range of about 4.5 terahertz in the mid-infrared band. Our work has the potential to significantly advance the area of biological molecular detection.

Terahertz Bessel beam generator.

The Bessel beam has broad application prospects in wireless energy transmission and high-speed communications. The traditional Bessel beam generation method has the problems of large volume, low efficiency, and complex manufacturing. To solve the above problems, we present a terahertz Bessel beam generator based on the reflective metasurface, which is composed of a metal pattern, dielectric layer, and bottom metal plate. Under the incidence of right circularly polarized (RCP) wave, the zero-order Bessel beam and zero-order symmetric double Bessel beam are generated. It can be found that the bottom angle of the axicon of the first-order Bessel beam is inversely proportional to the propagation distance of the Bessel beam. Comparing the electric field intensity distribution, phase distribution, and mode purity of the second-order Bessel beam and the second-order vortex beam in different observation planes, it can be seen that the energy of the higher-order Bessel beam is more concentrated and the field distribution is more stable than those of the ordinary vortex beam. The reflective terahertz Bessel beam generator has potential application value in terahertz wireless communications, measurement, radar detection, and imaging.

An Automatic Classification System for Environmental Sound in Smart Cities.

With the continuous promotion of "smart cities" worldwide, the approach to be used in combining smart cities with modern advanced technologies (Internet of Things, cloud computing, artificial intelligence) has become a hot topic. However, due to the non-stationary nature of environmental sound and the interference of urban noise, it is challenging to fully extract features from the model with a single input and achieve ideal classification results, even with deep learning methods. To improve the recognition accuracy of ESC (environmental sound classification), we propose a dual-branch residual network (dual-resnet) based on feature fusion. Furthermore, in terms of data pre-processing, a loop-padding method is proposed to patch shorter data, enabling it to obtain more useful information. At the same time, in order to prevent the occurrence of overfitting, we use the time-frequency data enhancement method to expand the dataset. After uniform pre-processing of all the original audio, the dual-branch residual network automatically extracts the frequency domain features of the log-Mel spectrogram and log-spectrogram. Then, the two different audio features are fused to make the representation of the audio features more comprehensive. The experimental results show that compared with other models, the classification accuracy of the UrbanSound8k dataset has been improved to different degrees.

Knowledge mapping of extracellular vesicles in wound healing: A bibliometric analysis (2002-2022).

Extracellular vesicles in wound healing have become an active research field with substantial value and potential. Nevertheless, there are few bibliometric studies in this field. We aimed to visualise the research hot spots and trends of extracellular vesicles in wound healing using a bibliometric analysis to help understand the future development of basic and clinical research. The articles and reviews regarding extracellular vesicles in the wound healing were selected from the Web of Science Core Collection. VOSviewers, CiteSpace and R package "bibliometric" were used to conduct this bibliometric analysis. A total of 1225 articles from 56 countries led by China and the United States were included. The number of publications related to extracellular vesicles increased year by year. Shanghai Jiaotong University, Huazhong University of Science and Technology, Sun Yat-sen University and Central South University are the main research institutions. International Journal of Molecular Sciences is the most popular journal in this field, while Stem Cell Research & Therapy is the most frequently cited journal. These papers come from 7546 authors, among which Zhang Wei has published the most papers and Zhang Bin has the most cocited papers. The research on the treatment strategy of extracellular vesicles in the process of wound healing is the main topic in this field. "exosomes", "miRNA", "angiogenesis", "regenerative medicine", "inflammation" and "diabetic wound" are the main key words of emerging research hotspots. This is the first bibliometric study, which comprehensively summarises the research trend and development of extracellular vesicles and exocrine bodies in wound healing. These informations determine the latest research frontiers and hot directions, and provide reference for the study of extracellular vesicles and exosomes.

Data-Augmented Deep Learning Models for Abnormal Road Manhole Cover Detection.

Anomalous road manhole covers pose a potential risk to road safety in cities. In the development of smart cities, computer vision techniques use deep learning to automatically detect anomalous manhole covers to avoid these risks. One important problem is that a large amount of data are required to train a road anomaly manhole cover detection model. The number of anomalous manhole covers is usually small, which makes it a challenge to create training datasets quickly. To expand the dataset and improve the generalization of the model, researchers usually copy and paste samples from the original data to other data in order to achieve data augmentation. In this paper, we propose a new data augmentation method, which uses data that do not exist in the original dataset as samples to automatically select the pasting position of manhole cover samples and predict the transformation parameters via visual prior experience and perspective transformations, making it more accurately capture the actual shape of manhole covers on a road. Without using other data enhancement processes, our method raises the mean average precision (mAP) by at least 6.8 compared with the baseline model.

A Solar Irradiance Forecasting Framework Based on the CEE-WGAN-LSTM Model.

With the rapid development of solar energy plants in recent years, the accurate prediction of solar power generation has become an important and challenging problem in modern intelligent grid systems. To improve the forecasting accuracy of solar energy generation, an effective and robust decomposition-integration method for two-channel solar irradiance forecasting is proposed in this study, which uses complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), a Wasserstein generative adversarial network (WGAN), and a long short-term memory network (LSTM). The proposed method consists of three essential stages. First, the solar output signal is divided into several relatively simple subsequences using the CEEMDAN method, which has noticeable frequency differences. Second, high and low-frequency subsequences are predicted using the WGAN and LSTM models, respectively. Last, the predicted values of each component are integrated to obtain the final prediction results. The developed model uses data decomposition technology, together with advanced machine learning (ML) and deep learning (DL) models to identify the appropriate dependencies and network topology. The experiments show that compared with many traditional prediction methods and decomposition-integration models, the developed model can produce accurate solar output prediction results under different evaluation criteria. Compared to the suboptimal model, the MAEs, MAPEs, and RMSEs of the four seasons decreased by 3.51%, 6.11%, and 2.25%, respectively.

Superior Performances of Self-Driven Near-Infrared Photodetectors Based on the SnTe:Si/Si Heterostructure Boosted by Bulk Photovoltaic Effect.

The upsurge of new materials that can be used for near-infrared (NIR) photodetectors operated without cooling is crucial. As a novel material with a small bandgap of ≈0.28 eV, the topological crystalline insulator SnTe has attracted considerable attention. Herein, this work demonstrates self-driven NIR photodetectors based on SnTe/Si and SnTe:Si/Si heterostructures. The SnTe/Si heterostructure has a high detectivity D* of 3.3 × 1012 Jones. By Si doping, the SnTe:Si/Si heterostructure reduces the dark current density and increases the photocurrent by ≈1 order of magnitude simultaneously, which improves the detectivity D* by ≈2 orders of magnitude up to 1.59 × 1014 Jones. Further theoretical analysis indicates that the improved device performance may be ascribed to the bulk photovoltaic effect (BPVE), in which doped Si atoms break the inversion symmetry and thus enable the generation of additional photocurrents beyond the heterostructure. In addition, the external quantum efficiency (EQE) measured at room temperature at 850 nm increases by a factor of 7.5 times, from 38.5% to 289%. A high responsivity of 1979 mA W-1 without bias and fast rising time of 8 µs are also observed. The significantly improved photodetection achieved by the Si doping is of great interest and may provide a novel strategy for superior photodetectors.

Anorectal manometry after rectal surgery: a case report with rectal bleeding and perforation.

Background: Anorectal manometry (ARM) is primarily used to assess anorectal sensorimotor function. ARM provides comprehensive information about the anal sphincter and rectal sensation in patients with constipation or fecal incontinence. Generally, ARM can be applied to both adults and children. This study is the first to report a case of post-rectal resection ARM with constipation complicating rectal bleeding and perforation in a patient with no history of rectal cancer, aiming to provide guidelines for the treatment of patients who undergo ARM after rectal surgery. Case Description: A 58-year-old female patient with previous history of "hypertension and cerebral infarction" underwent "proctocolectomy" for "rectal prolapse" 11+ months ago and recovered well after the operation, but developed constipation. The patient was admitted to our hospital for anorectal manometry (ARM) for "constipation for 11+ months". 2+ hours after the examination, the patient developed blood in the stool and was hospitalized in the Department of Anorectal Surgery of our hospital. The anorectal manometry was performed 2+ hours after the patient developed blood in the stool. The patient was discharged after 30 days of hospitalization without any complications. During treatment, the patient suffered from rectal rupture and perforation. Following timely and aggressive surgery, the patient recovered and was discharged without any complications. Conclusions: ARM with balloon, as a method for detecting anorectal function, should only be performed cautiously after rectal surgery, especially among patients with comorbidities. If patients suffer from anorectal bleeding and perforation during ARM, prompt and aggressive surgical intervention is necessary. At present, there is little literature on ARM teaching courses. To improve the operation level of ARM and reduce the incidence of complications, we should extend understandings of ARM, develop a systematic management plan, and continuously summarize ARM-related experiences.

Phytochrome interacting factor regulates stomatal aperture by coordinating red light and abscisic acid.

Stomata are crucial valves coordinating the fixation of carbon dioxide by photosynthesis and water loss through leaf transpiration. Phytochrome interacting factors (PIFs) are negative regulators of red light responses that belong to the basic helix-loop-helix family of transcription factors. Here, we show that the rice (Oryza sativa) PIF family gene OsPIL15 acts as a negative regulator of stomatal aperture to control transpiration in rice. OsPIL15 reduces stomatal aperture by activating rice ABSCISIC ACID INSENSITIVE 5 (OsABI5), which encodes a critical positive regulator of ABSCISIC ACID (ABA) signaling in rice. Moreover, OsPIL15 interacts with the NIGT1/HRS1/HHO family transcription factor rice HRS1 HOMOLOG 3 (OsHHO3) to possibly enhance the regulation of stomatal aperture. Notably, we discovered that the maize (Zea mays) PIF family genes ZmPIF1 and ZmPIF3, which are homologous to OsPIL15, are also involved in the regulation of stomatal aperture in maize, indicating that PIF-mediated regulation of stomatal aperture may be conserved in the plant lineage. Our findings explain the molecular mechanism by which PIFs play a role in red-light-mediated stomatal opening, and demonstrate that PIFs regulate stomatal aperture by coordinating the red light and ABA signaling pathways.

Visualizing Uncertainty in Probabilistic Graphs with Network Hypothetical Outcome Plots (NetHOPs).

Probabilistic graphs are challenging to visualize using the traditional node-link diagram. Encoding edge probability using visual variables like width or fuzziness makes it difficult for users of static network visualizations to estimate network statistics like densities, isolates, path lengths, or clustering under uncertainty. We introduce Network Hypothetical Outcome Plots (NetHOPs), a visualization technique that animates a sequence of network realizations sampled from a network distribution defined by probabilistic edges. NetHOPs employ an aggregation and anchoring algorithm used in dynamic and longitudinal graph drawing to parameterize layout stability for uncertainty estimation. We present a community matching algorithm to enable visualizing the uncertainty of cluster membership and community occurrence. We describe the results of a study in which 51 network experts used NetHOPs to complete a set of common visual analysis tasks and reported how they perceived network structures and properties subject to uncertainty. Participants' estimates fell, on average, within 11% of the ground truth statistics, suggesting NetHOPs can be a reasonable approach for enabling network analysts to reason about multiple properties under uncertainty. Participants appeared to articulate the distribution of network statistics slightly more accurately when they could manipulate the layout anchoring and the animation speed. Based on these findings, we synthesize design recommendations for developing and using animated visualizations for probabilistic networks.

Nanocrystalline ZnSnN2 Prepared by Reactive Sputtering, Its Schottky Diodes and Heterojunction Solar Cells.

ZnSnN2 has potential applications in photocatalysis and photovoltaics. However, the difficulty in preparing nondegenerate ZnSnN2 hinders its device application. Here, the preparation of low-electron-density nanocrystalline ZnSnN2 and its device application are demonstrated. Nanocrystalline ZnSnN2 was prepared with reactive sputtering. Nanocrystalline ZnSnN2 with an electron density of approximately 1017 cm-3 can be obtained after annealing at 300 °C. Nanocrystalline ZnSnN2 is found to form Schottky contact with Ag. Both the current I vs. voltage V curves and the capacitance C vs. voltage V curves of these samples follow the related theories of crystalline semiconductors due to the limited long-range order provided by the crystallites with sizes of 2-10 nm. The I-V curves together with the nonlinear C-2-V curves imply that there are interface states at the Ag-nanocrystalline ZnSnN2 interface. The application of nanocrystalline ZnSnN2 to heterojunction solar cells is also demonstrated.

Plant NIGT1/HRS1/HHO Transcription Factors: Key Regulators with Multiple Roles in Plant Growth, Development, and Stress Responses.

The NIGT1/HRS1/HHO transcription factor (TF) family is a new subfamily of the G2-like TF family in the GARP superfamily and contains two conserved domains: the Myb-DNA binding domain and the hydrophobic and globular domain. Some studies showed that NIGT1/HRS1/HHO TFs are involved in coordinating the absorption and utilization of nitrogen and phosphorus. NIGT1/HRS1/HHO TFs also play an important role in plant growth and development and in the responses to abiotic stresses. This review focuses on recent advances in the structural characteristics of the NIGT1/HRS1/HHO TF family and discusses how the roles and functions of the NIGT1/HRS1/HHO TFs operate in terms of in plant growth, development, and stress responses.