The Therapeutic Effect of Hydroxychloroquine on Patients with Recurrent Miscarriage and the Risk Assessment of its Ocular Retinal Toxicity

Background: Recurrent miscarriage (RM) refers to the unfortunate loss of pregnancy at least three times before the 20th week of gestation. The present study examined hydroxychloroquine (HCQ)'s therapeutic effects in recurrent miscarriage owing to potential positive outcomes like increased rate of live births and negative outcomes like ocular and retinal toxicity.Methods: The investigation involved the randomization of 400 mg of HCQ intervention in 91 pregnant women attending a monthly clinic at the Wenzhou TCM Hospital of Zhejiang Chinese Medical University.Results: According to the results, HCQ results in positive pregnancy outcomes, with improving rates of live births with continued use of the medication. At the same time, the results produced significant safety issues, including HCQ deposition in the retina and ocular toxicity. An investigation of HCQ's effects on the retinal nerve fiber layer measurements, ganglion cell layer measurements, and the inner plexiform layer measurements revealed a dynamic trend.Conclusion: We did not obtain conclusive outcomes regarding HCQ's effects on the changes in retinal measurements. However, the deposition of HCQ in the retina and the resulting vision loss, especially loss of color vision, stood out. These outcomes represent the safety and therapeutic effects of HCQ in pregnancy, posing concerns and creating the need for further studies. Interestingly, none of these outcomes were related to or dependent on the participants' age.Keywords: HCQ; Recurrent miscarriage; Ocular retinal toxicity; Effects; Live births; Still birth

FocusDet: an efficient object detector for small object

Abstract The object scale of a small object scene changes greatly, and the object is easily disturbed by a complex background. Generic object detectors do not perform well on small object detection tasks. In this paper, we focus on small object detection based on FocusDet. FocusDet refers to the small object detector proposed in this paper. It consists of three parts: backbone, feature fusion structure, and detection head. STCF-EANet was used as the backbone for feature extraction, the Bottom Focus-PAN for feature fusion, and the detection head for object localization and recognition.To maintain sufficient global context information and extract multi-scale features, the STCF-EANet network backbone is used as the feature extraction network.PAN is a feature fusion module used in general object detectors. It is used to perform feature fusion on the extracted feature maps to supplement feature information.In the feature fusion network, FocusDet uses Bottom Focus-PAN to capture a wider range of locations and lower-level feature information of small objects.SIOU-SoftNMS is the proposed algorithm for removing redundant prediction boxes in the post-processing stage. SIOU multi-dimension accurately locates the prediction box, and SoftNMS uses the Gaussian algorithm to remove redundant prediction boxes. FocusDet uses SIOU-SoftNMS to address the missed detection problem common in dense tiny objects.The VisDrone2021-DET and CCTSDB2021 object detection datasets are used as benchmarks, and tests are carried out on VisDrone2021-det-test-dev and CCTSDB-val datasets. Experimental results show that FocusDet improves [email protected]% from 33.6% to 46.7% on the VisDrone dataset. [email protected]% on the CCTSDB2021 dataset is improved from 81.6% to 87.8%. It is shown that the model has good performance for small object detection, and the research is innovative

DCTransformer: A Channel Attention Combined Discrete Cosine Transform to Extract Spatial–Spectral Feature for Hyperspectral Image Classification

Hyperspectral image (HSI) classification tasks have been adopted in huge applications of remote sensing recently. With the rise of deep learning development, it becomes crucial to investigate how to exploit spatial–spectral features. The traditional approach is to stack models that can encode spatial–spectral features, coupling sufficient information as much as possible, before the classification model. However, this sequential stacking tends to cause information redundancy. In this paper, a novel network utilizing the channel attention combined discrete cosine transform (DCTransformer) to extract spatial–spectral features has been proposed to address this issue. It consists of a detail spatial feature extractor (DFE) with CNN blocks and a base spectral feature extractor (BFE) utilizing the channel attention mechanism (CAM) with a discrete cosine transform (DCT). Firstly, the DFE can extract detailed context information using a series of layers of a CNN. Further, the BFE captures spectral features using channel attention and stores the wider frequency information by utilizing the DCT. Ultimately, the dynamic fusion mechanism has been adopted to fuse the detail and base features. Comprehensive experiments show that the DCTransformer achieves a state-of-the-art (SOTA) performance in the HSI classification task, compared to other methods on four datasets, the University of Houston (UH), Indian Pines (IP), MUUFL, and Trento datasets. On the UH dataset, the DCTransformer achieves an OA of 94.40%, AA of 94.89%, and kappa of 93.92

Inverse optimal control for linearizable nonlinear systems with input delays

summary:We consider inverse optimal control for linearizable nonlinear systems with input delays based on predictor control. Under a continuously reversible change of variable, a nonlinear system is transferred to a linear system. A predictor control law is designed such that the closed-loop system is asymptotically stable. We show that the basic predictor control is inverse optimal with respect to a differential game. A mechanical system is provided to illustrate the effectiveness of the proposed method

Color-Tunable Dual-Mode Organic Afterglow for White-Light Emission and Information Encryption Based on Carbazole Doping

10.1002/anie.202310335ANGEWANDTE CHEMIE-INTERNATIONAL EDITION624

The Advanced Synthesis of MOFs-Based Materials in Photocatalytic HER in Recent Three Years

Since the advent of metal–organic frameworks (MOFs), researchers have paid extensive attention to MOFs due to their determined structural composition, controllable pore size, and diverse physical and chemical properties. Photocatalysis, as a significant application of MOFs catalysts, has developed rapidly in recent years and become a research hotspot continuously. Various methods and approaches to construct and modify MOFs and their derivatives can not only affect the structure and morphology, but also largely determine their properties. Herein, we summarize the advanced synthesis of MOFs-based materials in the field of the photocatalytic decomposition of water to produce hydrogen in the recent three years. The main contents include the overview of the novel synthesis strategies in four aspects: internal modification and structure optimization of MOFs materials, MOFs/semiconductor composites, MOFs/COFs-based hybrids, and MOFs-derived materials. In addition, the problems and challenges faced in this direction and the future development goals were also discussed. We hope this review will help deepen the reader’s understanding and promote continued high-quality development in this field

Multi-objective parameter optimization strategy based on engine coordinated control for improving shifting quality

In order to address the poor shifting quality issue of a certain model of heavy-duty vehicles, a multi-objective parameter optimization strategy based on engine coordinated control is proposed. This strategy aims to improve shifting quality by reducing the sliding friction work and impact during the shifting process. The Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is employed to perform multi-objective optimization on the coordinated control parameters, which include external control torque of the engine, start of fuel cut-off timing, and duration of fuel cut-off. By comparing the performance of different parameter combinations in terms of sliding friction work and impact, the optimal parameter combination is determined. Through bench testing verification, it has been demonstrated that utilizing the optimized parameters for engine coordinated control during the torque phase of the shifting process can significantly enhance shifting quality. This strategy provides an effective solution for addressing shifting quality issues

Research on the Operational Strategy of the Hybrid Wind/PV/Small-Hydropower/Facility-Agriculture System Based on a Microgrid

The use of renewable energy sources, such as wind, photovoltaics (PV), and hydropower, to supply facility agriculture may effectively mitigate food and environmental pollution problems and ensure continuity of the energy supply. The operating conditions of a hybrid system are complex, so the operating strategy is very important for system configuration and scheduling purposes. In the current study, first, a hybrid wind/PV/small-hydropower/facility-agricultural system was constructed. Then, the chaotic particle swarm method was applied to optimize hybrid system operation, and a scheduling strategy of the hybrid system was proposed. Finally, combined with an example, according to wind and PV power output and load curves, supply-to-load curves for wind, PV, and small hydropower were obtained. The operational strategy proposed in this study maximizes the utilization of wind and solar resources and rationally allocates hydropower resources. The aforementioned operational strategy provides a basis for hybrid system capacity allocation and scheduling

Upregulation of KHDC1L promotes the proliferation and inhibits apoptosis in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) remains a dreadful malignancy bearing poor clinical efficacy, with emerging evidences indicating RNA-binding proteins’ (RBPs’) relevance to the evolution of the disease. Categorized as RBPs, the K-homology domain-containing 1 (KHDC1) family is proved to be closely related to cell survival and death. As a novel KHDC1 member, only one study is currently available in osteoarthritis synovial cells to unveil KHDC1L’s function of promoting proliferation. Nevertheless, to the best of our knowledge, the role of KHDC1L in human tumour is yet to be fully explored. On the basis of The Cancer Genome Atlas (TCGA) database and cell lines comparison with normal counterparts in this study, we first discovered KHDC1L to be overexpressed in HNSCC. According to bioinformatics analysis, apoptosis and P53 pathways were remarkably enriched in the KHDC1L low-expression group in TCGA database. Moreover, in vitro experiments were applied to verify that upregulation of KHDC1L could promote the proliferation and inhibit apoptosis in HNSCC cells CAL27. Transcriptome sequencing ascertained downstream differentially expressed genes to be significantly enriched in PI3K-AKT pathways. Furthermore, as validated by western blot, we found an elevated expression level of pAKT/AKT and Bcl-2, constant expression level of BAX, together with decreased activity of Caspase-3 and PARP-1 in the KHDC1L-upregulated group. In conclusion, our study pioneeringly elaborated that KHDC1L could promote proliferation and inhibit apoptosis in HNSCC cell CAL27 via AKT and Bcl-2 pathways, representing a crucial step for seeking a new diagnostic and therapeutic target in HNSCC