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Abstract Emerging reconfigurable metasurfaces offer various possibilities for programmatically manipulating electromagnetic waves across spatial, spectral, and temporal domains, showcasing great potential for enhancing terahertz applications. However, they are hindered by limited tunability, particularly evident in relatively small phase tuning over 270°, due to the design constraints with time‐intensive forward design methodologies. Here, a multi‐bit programmable metasurface is demonstrated capable of terahertz beam steering facilitated by a developed physics‐informed inverse design (PIID) approach. Through integrating a modified coupled mode theory (MCMT) into residual neural networks, the PIID algorithm not only significantly increases the design accuracy compared to conventional neural networks but also elucidates the intricate physical relations between the geometry and the modes. Without decreasing the reflection intensity, the method achieves the enhanced phase tuning as large as 300°. Additionally, the inverse‐designed programmable beam steering metasurface is experimentally validated, which is adaptable across 1‐bit, 2‐bit, and tri‐state coding schemes, yielding a deflection angle up to 68° and broadened steering coverage. The demonstration provides a promising pathway for rapidly exploring advanced metasurface devices, with potentially great impact on communication and imaging technologies.

ABSTRACTTo evaluate the performance of “Vaccination Rates Monitoring Report System” implemented by Shenzhen CDC, we conducted an analysis of the data quality and identify key areas for system improvement. Following evaluation guidelines provided by WHO and United States CDC, we established six evaluation attributes: representativeness, simplicity, acceptability, data reliability, stability and timeliness. In eastern, central and western regions of Shenzhen, we selected one district from each region, of which the local CDC and ten CHSCs under jurisdiction were chosen for evaluation. On-site inspections, questionnaires survey and interviews were utilized for data collection, while the Likert scale method was used for attributes rating evaluation. A total of 70 participants were surveyed, consisting of 60 CHSCs and 10 CDCs staff. The gender ratio was 1:2.5 (males to females), with the majority falling within the 25–34 age range (46%). Most participants held full-time positions (80%) and had more than 5 years of work experience (62%). The system achieved 100% coverage of all CHSCs and CDCs (100%). The cumulative percentage scores for the overall favorable options of simplicity, acceptability, data reliability, stability, and timeliness were 79%, 85%, 73%, 50%, and 71% respectively. The system operates normally with strong representativeness. Acceptability was rated as “good.” Simplicity, data reliability, and system timeliness were rated as “average,” while system stability was rated as “poor.” Based on these survey results, developers should urgently investigate reasons for poor stability, particularly addressing concerns from CHSCs users. Additionally, the issues and shortcomings identified in other attributes should also be gradually improved.

PurposeDiabetes and its complications cause a heavy burden of disease worldwide. In recent years, Mendelian randomization (MR) has been widely used to discover the pathogenesis and epidemiology of diseases, as well as to discover new therapeutic targets. Therefore, based on systematic “druggable” genomics, we aim to identify new therapeutic targets for diabetes and analyze its pathophysiological mechanisms to promote its new therapeutic strategies.Material and methodWe used double sample MR to integrate the identified druggable genomics to evaluate the causal effect of quantitative trait loci (eQTLs) expressed by druggable genes in blood on type 1 and 2 diabetes (T1DM and T2DM). Repeat the study using different data sources on diabetes and its complications to verify the identified genes. Not only that, we also use Bayesian co-localization analysis to evaluate the posterior probabilities of different causal variations, shared causal variations, and co-localization probabilities to examine the possibility of genetic confounding. Finally, using diabetes markers with available genome-wide association studies data, we evaluated the causal relationship between established diabetes markers to explore possible mechanisms.ResultOverall, a total of 4,477 unique druggable genes have been gathered. After filtering using methods such as Bonferroni significance (P

Population and economy are crucial factors contributing to regional disparities. Studying the patterns and relationships between these two elements is essential for promoting sustainable development in regions and cities. This study constructs multi-scale geographic concentration indices and inconsistency indices, utilizing NPP/VIIRS and LandScan data to quantitatively analyze the spatial pattern changes of population and economy in the Yangtze River Delta across various spatial scales, revealing the matching relationships between population and economic elements within cities. The results indicate that the economy in the Yangtze River Delta is spreading outward from the core areas, with the average population–nightlight inconsistency index decreasing from 1.57 to 1.33. This suggests that the imbalance between population and economy within the urban agglomeration is gradually improving, consistent with trends observed in statistical survey data. Within individual cities, there is a noticeable spatial mismatch between population and nightlight intensity, with the population primarily concentrated in urban core areas. As urban spaces expand, the areas where population concentration is significantly lower than nightlight concentration are gradually diminishing. By 2022, the land area where population and economic concentration are coordinated within the Yangtze River Delta urban areas increased from 9.13% to 16.24%. Population concentration in these coordinated regions rose from 11.33% to 16.33%, while nightlight concentration increased from 9.98% to 13.63%. The improved geographic concentration and inconsistency indices are effective indicators for multi-scale monitoring of population and economic spatial changes. The integration of NPP/VIIRS nighttime light data and LandScan data provides an effective method for uncovering different spatial patterns of population and socio-economic element aggregation in urban structures. This can offer insights for promoting sustainable regional and urban development.

Accurately mapping urban built-up areas is critical for monitoring urbanization and development. Previous studies have shown that Night light (NTL) data is effective in characterizing the extent of human activity. But its inherently low spatial resolution and saturation effect limit its application in the construction of urban built-up extraction. In this study, we developed a new index called VNRT (Vegetation, Nighttime Light, Road, and Temperature) to address these challenges and improve the accuracy of built-up area extraction. The VNRT index is the first to fuse the Normalized Difference Vegetation Index (NDVI), NPP-VIIRS Nighttime NTL data, road density data, and land surface temperature (LST) through factor multiplication. To verify the good performance of VNRT in extracting built-up areas, the built-up area ranges of four national central cities in China (Chengdu, Wuhan, Xi’an, and Zhengzhou) in 2019 are extracted by the local optimum thresholding method and compared with the actual validation points. The results show that the spatial distribution of VNRT is highly consistent with the actual built-up area. THE VNRT increases the variability between urban built-up areas and non-built-up areas, and can effectively distinguish some types of land cover that are easily ignored in previous urban indices, such as urban parks and water bodies. The VNRT index had the highest Accuracy (0.97), F1-score (0.94), Kappa coefficient (0.80), and overall accuracy (92%) compared to the two proposed urban indices. Therefore, the VNRT index could improve the identification of urban built-up areas and be an effective tool for long-term monitoring of regional-scale urbanization.

BackgroundThe mpox (monkeypox) outbreak has been declared to be a public health emergency of international concern by the Director-General of World Health Organization in July 2022. However, evidence regarding the awareness, knowledge, and worry about mpox in the general population remains scant.MethodsA community-based survey targeting community residents was preliminarily conducted in Shenzhen, China in August 2022 by using a convenience sampling method. Information on mpox-related awareness, knowledge, and worry was collected from each participant. Binary logistic regression analyses with the stepwise procedure were applied to explore the factors associated with awareness, knowledge, and worry about mpox.ResultsA total of 1028 community residents were included in the analysis (mean age: 34.70 years). Among these participants, 77.9% had ever heard of mpox, and 65.3% were aware of the global outbreak of mpox. However, only about half of them had a high level of knowledge regarding mpox (56.5%) and related symptoms (49.7%). More than one-third of them (37.1%) expressed a high level of worry about mpox. Having high knowledge levels of mpox and related symptoms were positively associated with a high level of worry (OR: 1.79, 95%CI: 1.22~2.63 for a single high knowledge level; OR: 1.98, 95%CI: 1.47~2.66 for both high knowledge levels).ConclusionsThis study identified the gaps in public awareness and specific knowledge of mpox in Chinese people, providing scientific evidence for the prevention and control network of mpox at the community level. Targeted health education programs are of urgent need, which should be implemented along with psychological interventions to release public worry if necessary.

Because of its high prevalence and poor long-term clinical treatment effect, liver disease is regarded as a major public health problem around the world. Among them, viral hepatitis, fatty liver, cirrhosis, non-alcoholic fatty liver disease (NAFLD), and autoimmune liver disease are common causes and inducements of liver injury, and play an important role in the occurrence and development of hepatocellular carcinoma (HCC). Tanshinone IIA (TsIIA) is a fat soluble polyphenol of Salvia miltiorrhiza that is extracted from Salvia miltiorrhiza. Because of its strong biological activity (anti-inflammatory, antioxidant), it is widely used in Asia to treat cardiovascular and liver diseases. In addition, TsIIA has shown significant anti-HCC activity in previous studies. It not only has significant anti proliferation and pro apoptotic properties. It can also play an anti-cancer role by mediating a variety of signal pathways, including phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt)/rapamycin (mTOR), mitogen-activated protein kinase (MAPK), and nuclear factor kappa-B (NF-κB). This review not only reviews the existing evidence and molecular mechanism of TsIIA’s anti-HCC effect but also reviews the liver-protective effect of TsIIA and its impact on liver fibrosis, NAFLD, and other risk factors for liver cancer. In addition, we also conducted network pharmacological analysis on TsIIA and HCC to further screen and explore the possible targets of TsIIA against hepatocellular carcinoma. It is expected to provide a theoretical basis for the development of anti-HCC-related drugs based on TsIIA.

Point cloud registration plays a crucial role in 3D mapping and localization. Urban scene point clouds pose significant challenges for registration due to their large data volume, similar scenarios, and dynamic objects. Estimating the location by instances (bulidings, traffic lights, etc.) in urban scenes is a more humanized matter. In this paper, we propose PCRMLP (point cloud registration MLP), a novel model for urban scene point cloud registration that achieves comparable registration performance to prior learning-based methods. Compared to previous works that focused on extracting features and estimating correspondence, PCRMLP estimates transformation implicitly from concrete instances. The key innovation lies in the instance-level urban scene representation method, which leverages semantic segmentation and density-based spatial clustering of applications with noise (DBSCAN) to generate instance descriptors, enabling robust feature extraction, dynamic object filtering, and logical transformation estimation. Then, a lightweight network consisting of Multilayer Perceptrons (MLPs) is employed to obtain transformation in an encoder–decoder manner. Experimental validation on the KITTI dataset demonstrates that PCRMLP achieves satisfactory coarse transformation estimates from instance descriptors within a remarkable time of 0.0028 s. With the incorporation of an ICP refinement module, our proposed method outperforms prior learning-based approaches, yielding a rotation error of 2.01° and a translation error of 1.58 m. The experimental results highlight PCRMLP’s potential for coarse registration of urban scene point clouds, thereby paving the way for its application in instance-level semantic mapping and localization.

Sentiment analysis of netizens’ comments can accurately grasp the psychology of netizens and reduce the risks brought by online public opinion. However, there is currently no effective method to solve the problems of short text, open word range, and sometimes reversed word order in comments. To better solve the above problems, this article proposes a hybrid model of sentiment classification, which is based on bidirectional encoder representations from transformers (BERT), bidirectional long short-term memory (BiLSTM) and a text convolution neural network (TextCNN) (BERT-BiLSTM-TextCNN). The experimental results show that (1) the hybrid model proposed in this article can better combine the advantages of BiLSTM and TextCNN; it not only captures local correlation while retaining context information but also has high accuracy and stability. (2) The BERT-BiLSTM-TextCNN model can extract important emotional information more flexibly in text and achieve multiclass classification tasks of emotions more accurately. The innovations of this study are as follows: (1) the use of BERT to generate word vectors has the advantages of more prior information and a full combination of contextual semantics; (2) the BiLSTM model, as a bidirectional context mechanism model, can obtain contextual information well; and (3) the TextCNN model can obtain important features well in the problem of text classification, and the combined effect of the three modules can significantly improve the accuracy of emotional multilabel classification.

Superparamagnetic Fe3O4 particles have been synthesized by solvothermal method, and a layer of dense silica sol polymer is coated on the surface prepared by sol-gel technique; then La(OH)3 covered the surface of silica sol polymer in an irregular shape by controlled in situ growth technology. These magnetic materials are characterized by TEM, FT-IR, XRD, SEM, EDS and VSM; the results show that La(OH)3 nanoparticles have successfully modified on Fe3O4 surface. The prepared Fe3O4@La(OH)3 inorganic polymer has been used as adsorbent to remove phosphate efficiently. The effects of solution pH, adsorbent dosage and co-existing ions on phosphate removal are investigated. Moreover, the adsorption kinetic equation and isothermal model are used to describe the adsorption performance of Fe3O4@La(OH)3. It was observed that Fe3O4@La(OH)3 exhibits a fast equilibrium time of 20 min, high phosphate removal rate (>95.7%), high sorption capacity of 63.72 mgP/g, excellent selectivity for phosphate in the presence of competing ions, under the conditions of phosphate concentration 30 mgP/L, pH = 7, adsorbent dose 0.6 g/L and room temperature. The phosphate adsorption process by Fe3O4@La(OH)3 is best described by the pseudo-second-order equation and Langmuir isotherm model. Furthermore, the real samples and reusability experiment indicate that Fe3O4@La(OH)3 could be regenerated after desorption, and 92.78% phosphate removing remained after five cycles. Therefore, La(OH)3 nanoparticles deposited on the surface of monodisperse Fe3O4 microspheres have been synthesized for the first time by a controlled in-situ growth method. Experiments have proved that Fe3O4@La(OH)3 particles with fast separability, large adsorption capacity and easy reusability can be used as a promising material in the treatment of phosphate wastewater or organic pollutants containing phosphoric acid functional group.

From September 1 to October 27, 2015, an outbreak of bacillary dysentery occurred in the Shenzhen Children Welfare Institute (SCWI). The shigellosis was uncommon in Shenzhen and no related outbreak was reported during the last 5 years. An epidemiological investigation was conducted and the children and nursing workers in SCWI were surveyed for gastrointestinal symptoms; 28 of children reported having a diarrheal illness. Rectal swabs or fecal specimens from 14 case patients and 24 nursing workers or cook, as well as 17 swabs from implicated items were collected and examined for Shigella, Vibrio parahaemolyticus, and Salmonella. Susceptibility testing and pulse-field gel electrophoresis (PFGE) were performed on the Shigella isolates.The multiple-antibiotic-resistant Shigella flexneri 2a was isolated from 10 ill children aged less than 5 years. The source of the outbreak was most likely a new welfare child transferred from an institute in another county and the secondary transmission of the illness was facilitated by the limited activity space and the cohabiting of ill and well residents. The outbreak was controlled after quarantine of ill residents, introduction of new antibiotics and the improvements of hygienic condition. This was the first time that shigellosis outbreak was reported at such settings in Shenzhen and the results of this investigation underscored the need for adequate precautions to prevent secondary transmission of multiple-antibiotic-resistant strain in the welfare setting. Keywords: Outbreak, Shigellosis, Children Welfare Institute, Multiple-antibiotic-resistant, Shigella flexneri 2a

For the first time, we illuminate the complete mitochondrial genome (mitogenome) sequence of the Paradiplospinus antarcticus, which is 16,988 bp in size and contains 13 protein-coding (PCGs), 2 rRNA genes, 22 tRNA genes, and one control region.The base composition of the mitogenome is 26.08% A, 26.77% T, 28.46% C and 18.69% G. Here, we selected 11 genera of species from the mostly monotypic snake mackerel family, including representative Antarctic Paradiplospinus antarcticus that have been identified, and constructed phylogenetic trees to better study the snake mackerel family.

The mathematical modeling of the magnetoelectric (ME) effect in ME laminates has been established for some simple structures. However, these methods, which are based on the differential equation approach, are difficult to use in other complex structures (e.g., ring structures). In this work, a new established approach based on the generalized Hamilton’s principle is used to analyze the ME effect in an ME laminated ring. Analytical expressions for ME voltage coefficients are derived. A comparison with the conventional method indicates that this approach is more convenient when the modeling analysis is performed on complex structures. Further, experimental data are also obtained to compare with the theoretical calculations in order to validate the new approach.

The nature of interchain π-system contacts, and their relationship to hole transport, are elucidated for the high-mobility, noncrystalline conjugated polymer C16-IDTBT by the application of scanning tunneling microscopy, molecular dynamics, and quantum chemical calculations. The microstructure is shown to favor an unusual packing motif in which paired chains cross-over one another at near-perpendicular angles. By linking to mesoscale microstructural features, revealed by coarse-grained molecular dynamics and previous studies, and performing simulations of charge transport, it is demonstrated that the high mobility of C16-IDTBT can be explained by the promotion of a highly interconnected transport network, stemming from the adoption of perpendicular contacts at the nanoscale, in combination with fast intrachain transport. [ABSTRACT FROM AUTHOR]

Abstract CD8+ T cells are the workhorses executing adaptive anti-tumour response, and targets of various cancer immunotherapies. Latest advances have unearthed the sheer heterogeneity of CD8+ tumour infiltrating lymphocytes, and made it increasingly clear that the bulk of the endogenous and therapeutically induced tumour-suppressive momentum hinges on a particular selection of CD8+ T cells with advantageous attributes, namely the memory and stem-like exhausted subsets. A scrutiny of the contemporary perception of CD8+ T cells in cancer and the subgroups of interest along with the factors arbitrating their infiltration contextures, presented herein, may serve as the groundwork for future endeavours to probe further into the regulatory networks underlying their differentiation and migration, and optimise T cell-based immunotherapies accordingly.

Abstract Pair density wave (PDW) is a distinct superconducting state characterized by a periodic modulation of its order parameter in real space. Its intricate interplay with the charge density wave (CDW) state is a continuing topic of interest in condensed matter physics. While PDW states have been discovered in cuprates and other unconventional superconductors, the understanding of diverse PDWs and their interactions with different types of CDWs remains limited. Here, utilizing scanning tunneling microscopy, we unveil the subtle correlations between PDW ground states and two distinct CDW phases — namely, anion-centered-CDW (AC-CDW) and hollow-centered-CDW (HC-CDW) — in 2H-NbSe2. In both CDW regions, we observe coexisting PDWs with a commensurate structure that aligns with the underlying CDW phase. The superconducting gap size, Δ(r), related to the pairing order parameter is in phase with the charge density in both CDW regions. Meanwhile, the coherence peak height, H(r), qualitatively reflecting the electron-pair density, exhibits a phase difference of approximately 2π/3 relative to the CDW. The three-fold rotational symmetry is preserved in the HC-CDW region but is spontaneously broken in the AC-CDW region due to the PDW state, leading to the emergence of nematic superconductivity.

Low back pain is among the most grave public health concerns worldwide and the major clinical manifestation of intervertebral disc degeneration (IVDD). The destruction of annulus fibrosus (AF) is the primary cause of IVDD. A sustainable and stable treatment system for IVDD is lacking because of the special organizational structure and low nutrient supply of AF. We here found that IVDD results in the impaired mitochondrial function of AF tissue, and mitochondrial autophagy (mitophagy) plays a protective role in this process. We therefore reported a thread-structural microneedle (T-MN) matching the ring structure of AF. Based on the adsorption effect of laminin, our T-MN could load with bone marrow mesenchymal stem cell-derived exosomes to envelope the regulating mitophagy microRNA (miRNA 378), named as T-MN@EXO@miR−378. In general, we offered in situ locking in the defect site of AF to prevent nucleus pulposus leakage and promoted AF repair. The design of the thread structure was aimed at bionically matching the layered AF structure, thereby providing stronger adhesion. The T-MN@EXO@miR−378 effectively attached to AF and slowly released therapeutic engineered exosomes, and prevented IVDD progression by restoring mitophagy, promoting AF cell proliferation and migration, and inhibiting the pathological remodeling of the extracellular matrix. This functional system can be used as an excellent tool for sustained drug release and has a certain prospect in substituting the conventional treatment of IVDD.