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In the context of the evolving landscape of reduction in carbon emissions and integration of renewable energy, this study uses system dynamics (SD) modeling to explore the interconnected dynamics of carbon trading (CT), tradable green certificate (TGC) trading, and electricity markets. Using differential equations with time delays, the study provides a comprehensive analysis of structural relationships and feedback mechanisms within and between these markets. Key findings reveal the intricate interplay between carbon prices, green certificate prices, and electricity prices under various coupling mechanisms. For example, under the three-market coupling mechanism, carbon trading prices stabilize around 150 Yuan/ton, while green certificate prices reach a peak of 0.45 Yuan/KWH, impacting electricity prices, which fluctuate between 0.33 and 1.09 Yuan / KWH during the simulation period. These quantitative results shed light on nuanced fluctuations in market prices and the dynamics of anticipated purchases and sales volumes within each market. The insights gleaned from this study offer valuable implications for policy makers and market stakeholders in navigating the complexities of carbon emission reduction strategies, the integration of renewable energy and market equilibrium. By understanding the dynamics of multi-market coupling, stakeholders can better formulate policies and strategies to achieve sustainable energy transitions and mitigate impacts of climate change. [ABSTRACT FROM AUTHOR]

Despite accumulating evidence linking defective lysosome function with autoimmune diseases, how the catabolic machinery is regulated to maintain immune homeostasis remains unknown. Late endosomal/lysosomal adaptor, MAPK and mTOR activator 5 (Lamtor5) is a subunit of the Ragulator mediating mechanistic target of rapamycin complex 1 (mTORC1) activation in response to amino acids, but its action mode and physiological role are still unclear. Here it is demonstrated that Lamtor5 level is markedly decreased in peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE). In parallel, the mice with myeloid Lamtor5 ablation developed SLE‐like manifestation. Impaired lysosomal function and aberrant activation of mTORC1 are evidenced in Lamtor5 deficient macrophages and PBMCs of SLE patients, accompanied by blunted autolysosomal pathway and undesirable inflammatory responses. Mechanistically, it is shown that Lamtor5 is physically associated with ATP6V1A, an essential subunit of vacuolar H+‐ATPase (v‐ATPase), and promoted the V0/V1 holoenzyme assembly to facilitate lysosome acidification. The binding of Lamtor5 to v‐ATPase affected the lysosomal tethering of Rag GTPase and weakened its interaction with mTORC1 for activation. Overall, Lamtor5 is identified as a critical factor for immune homeostasis by intergrading v‐ATPase activity, lysosome function, and mTOR pathway. The findings provide a potential therapeutic target for SLE and/or other autoimmune diseases. [ABSTRACT FROM AUTHOR]

The association between serum copper and polycystic ovary syndrome (PCOS) lacks definitive conclusions, and the intricate interactions with in vitro fertilization (IVF) cycle characteristics in infertility remain insufficiently explored. This retrospective study included 560 patients with tubal infertility (no‐PCOS) and 266 patients with PCOS undergoing IVF at the Affiliated Suzhou Hospital of Nanjing Medical University from January 2018 to December 2022. Patients' basic characteristics, hormonal and metabolic parameters, essential trace elements, and IVF cycle characteristics were measured and analyzed. The results revealed a significantly elevated serum copper level in the PCOS group compared to the control group [17.27 (15.54, 19.67) vs 15.4 (13.87, 17.35), μmol/L; p < .001]. Spearman correlation analyses revealed a significant positive correlation between serum copper concentration and body mass index (BMI), fasting glucose (FG), triglyceride (TG), total cholesterol (TC), and low‐density lipoprotein (LDL) in the no‐PCOS group. Additionally, a notable negative correlation with high‐density lipoprotein (HDL) was observed (r = −.184, p < .001). Within the PCOS group, serum copper concentration correlated significantly with BMI (r = .198, p = .004) and TG (r = .214, p = .002). The linear trend analysis indicated no significant relationship between serum copper concentration and ovarian response as well as preimplantation outcomes in both groups after adjusting for confounding factors. Our study provided evidence of elevated serum copper concentration in PCOS patients, closely associated with lipid metabolism but showing no correlation with IVF outcomes. These findings provide valuable real‐world data, enriching our nuanced understanding of the role of copper in female fertility. [ABSTRACT FROM AUTHOR]

Optical resonators are indispensable tools in optical metrology that usually benefit from an evacuated and highly-isolated environment to achieve peak performance. Even in the more sophisticated design of Fabry-Perot (FP) cavities, the material choice limits the achievable quality factors. For this reason, monolithic resonators are emerging as promising alternative to traditional designs, but their design is still at preliminary stage and far from being optimized. Here, we demonstrate a monolithic FP resonator with 4.5 cm3 volume and 2 × 105 finesse. In the ambient environment, we achieve 18 Hz integrated laser linewidth and 7 × 10−14 frequency stability measured from 0.08 s to 0.3 s averaging time, the highest spectral purity and stability demonstrated to date in the context of monolithic reference resonators. By locking two separate lasers to distinct modes of the same resonator, a 96 GHz microwave signals is generated with phase noise -100 dBc/Hz at 10 kHz frequency offset, achieving orders of magnitude improvement in the approach of photonic heterodyne synthesis. The compact monolithic FP resonator is promising for applications in spectrally-pure, high-frequency microwave photonic references as well as optical clocks and other metrological devices. ©2024. All rights reserved. Optical resonators are essential tools for high precision metrology and applications where the spectral purity is highly demanded. Here, the authors demonstrate a monolithic resonator made of fused silica to support 18 Hz integrated laser linewidth in the ambient environment, and W-band microwave generation with low phase noise of -100 dBc/Hz at 10 kHz frequency offset. [ABSTRACT FROM AUTHOR]

This study subjected nuclear-grade 20# pipeline steel to cyclic freeze–thaw ice plugging tests, simulating the plastic deformation experienced by pipes during ice plug removal procedures. Subsequently, the dislocation morphology and mechanical properties of the specimens post cyclic ice plugging were examined. The cyclic ice plugging process led to an increase in the dislocation density within the specimens. After 20 and 40 cycles of ice plugging, the internal dislocation structures evolved from individual dislocation lines and dislocation tangles to high-density dislocation walls and dislocation cells. These high-density dislocation walls and cells hindered dislocation motion, giving rise to strain hardening phenomena, thereby resulting in increased strength and hardness of the specimens with an increasing number of ice plugging cycles. In addition, a large stress field was generated around the dislocation buildup, which reduced the pipe material's plastic toughness. The findings elucidate the effects of cyclic ice plugging on the microstructure and properties of nuclear-grade 20# pipeline steel, aiming to provide a theoretical basis for the safe and stable application of ice plugging technology in nuclear piping systems. [ABSTRACT FROM AUTHOR]

In this work, a hot extrusion forming process for magnesium (Mg) alloy square tubes, namely, tube-extrusion-continuous expending shear (TECES), was proposed. The thin-walled hollow square tube of Mg alloy with a thickness of 3 mm was successfully prepared by hot extrusion experiment. The evolution rules of effective stress, effective strain, and flow velocity in the process of tube forming were analyzed by numerical simulation, and the influence of different expanding ratios on tube forming was compared. The results show that the effective stress distribution of the tube is not uniform during the forming process, and the maximum stress appears at the first shear corner. In the shear deformation (SD) zone, there is a high strain zone at the corner of the square tube and outside the tube wall. As the tube is extruded, the uniformity of strain distribution in the deformation zone is improved. In the whole forming process, the flow rate of the tube increases first and then decreases, and the whole remains stable. As the expansion ratio increases when the expansion ratio is greater than 1.6, the resistance of plastic deformation increases, the fluidity of the metal becomes worse, and the formed tube cracks at the corner or is difficult to fill. When the expansion ratio is less than 1.6, the damage value area appears on the inner side of the tube wall, and the distribution uniformity is poor, which may lead to cracks or uneven thickness of the tube wall. The microstructure characterization of different deformation zones of the tube was carried out, and the results show that the TECES process can effectively refine the grain, and the average grain size of the formed tube is 10.1 μm. [ABSTRACT FROM AUTHOR]

Highly reliable software systems rarely fail during tests because they are usually designed with fault-tolerant mechanisms and tested comprehensively. It is usually difficult to obtain sufficient failure data to carry out reliability measurements by using traditional software reliability models. These models are typically based on probabilistic statistics, and the measurement accuracy cannot be guaranteed with insufficient failure data. We propose a nonparametric bootstrap (NBP) resampling method and six parametric bootstrap (PB) resampling methods to construct software reliability models for small sample conditions based on commonly used models, i.e., the Jelinski–Moranda (J–M), Goel–Okumoto (G–O), Musa–Okumoto (M–O), Schneidewind, Duane and Littlewood-Verrall models. The bootstrap is a statistical procedure that resamples a single dataset to create many simulated samples. Our experimental results on fourteen failure datasets collected from industry and academia show that the proposed models improve by 10.2–18.0% failure time prediction accuracy, 24.7–30.7% curve fitting accuracy, and 7.7–42.9% reliability measurement accuracy compared with the original models. Furthermore, our approaches achieve 58.3–91.1% better failure time prediction accuracy in the case of small sample conditions compared to state-of-the-art machine learning and neural network-based methods. Overall, our approaches can perform more accurate reliability measurements than the original models even in scenarios with limited failure data. [ABSTRACT FROM AUTHOR]

Background: The Patented Medicine Prices Review Board (PMPRB), the agency that regulates the prices of patented medicines in Canada, published proposed amendments to the regulatory framework in December 2017. Because of a series of changes and delays, the revised policy has not yet been finalized. We sought to evaluate the potential early impact of the uncertainty about the PMPRB policy on patented-medicine launches. Methods: We developed a retrospective cohort of patented medicines (molecules) sold in Canada and the 13 countries that the PMPRB currently uses or has proposed to use as price comparators, from sales data from the IQVIA MIDAS database for 2012–2021. The outcome was whether a molecule was launched (i.e., sold) in a specific country within 2 years of its global first launch (2-yr launch). We compared the change of 2-year launch before (2012–2017) and after the proposed amendments were published ("uncertain period," 2018–2021) in Canada with the change in the United States and the other 12 countries as a group ("other-countries group"), using interrupted time series and logistic regressions, respectively. We further conducted analyses for each individual country and subgroups by molecule characteristics, such as therapeutic benefit, separately. Results: We included 242 and 107 new molecules launched before publication of the proposed amendments and during the uncertain period, respectively. The corresponding 2-year launch proportions were 45.0% and 30.8% in Canada, 81.4% and 82.2% in the US, and 83.9% and 70.1% in the other-countries group. All analyses showed changes in 2-year launch during the uncertain period in the US and in the other-countries group that were similar to the changes in Canada. Greater decreases were observed in Norway and Sweden than in Canada. The 2-year launch proportion for molecules with major therapeutic benefit decreased from 45.8% to 31.3% in Canada during the uncertain period and from 87.5% to 62.5% in the other-countries group, but increased from 91.7% to 100% in the US. Interpretation: No negative impact of the PMPRB-policy uncertainty on molecule launches was observed when comparing Canada with price-comparator countries, except for molecules with major therapeutic benefit. The reduction in launches of medicines with major therapeutic benefit in Canada requires continuing investigation. [ABSTRACT FROM AUTHOR]

Background: WHO stated the environment is an important factor affecting the development of hospice care. The environment is the sum of factors affecting behavior besides the individual factors. Currently, a scale to comprehensively assess the hospice environment of nurse is still lacking. This study aimed to develop an instrument to investigate the environmental factors affecting hospice care of nurses. Methods: Literature review and a semi-structured interview were conducted to form the items pool of the Hospice Care Environment Scale. Two rounds of Delphi expert consultation were conducted by 16 experts to revise the scale dimensions and entries to form the Hospice Care Environment Scale. A psychometric evaluation was then performed among 530 oncology nurses in a large tertiary oncology hospital in Hubei Province. The 500 valid questionnaires were randomly divided into two groups in a 1:1 ratio, sample 1 (n1 = 250) for item screening and sample 2 (n2 = 250) for quality evaluation of the resulting scale. Item analysis, reliability analysis, validity analysis and acceptability analysis were performed. Result: The Hospice Care Environment Scale consists of two dimensions and 13 entries. The Cronbach's α coefficient of the Hospice Care Environment Scale was 0.970, and the Cronbach's α coefficient of the two dimensions were 0.952 and 0.969, respectively, with the Item-content validity index and average Scale- content validity index of the scale was both 1.000. The validation factor analysis showed the standardized path coefficients of each item were basically above 0.5, and the factor structure model was stable and suitable. The average completion time of the scale was about 3 min, which had good feasibility. Conclusion: The Hospice Care Environment Scale to assess the environment of hospice care services, has good content and construct validity and reliability. This scale can provide guidance to evaluate the hospice care environment. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is a serious threat to women's health with high morbidity and mortality. The development of more effective therapies for the treatment of breast cancer is strongly warranted. Growing evidence suggests that targeting glucose metabolism may be a promising cancer treatment strategy. We previously identified a new glyceraldehyde-3-phosphate dehydrogenase (GAPDH) inhibitor, DC-5163, which shows great potential in inhibiting tumor growth. Here, we evaluated the anticancer potential of DC-5163 in breast cancer cells. Methods: The effects of DC-5163 on breast cancer cells were investigated in vitro and in vivo. Seahorse, glucose uptake, lactate production, and cellular ATP content assays were performed to examine the impact of DC-5163 on cellular glycolysis. Cell viability, colony-forming ability, cell cycle, and apoptosis were assessed by CCK8 assay, colony formation assay, flow cytometry, and immunoblotting respectively. The anticancer activity of DC-5163 in vivo was evaluated in a mouse breast cancer xenograft model. Results: DC-5163 suppressed aerobic glycolysis and reduced energy supply of breast cancer cells, thereby inhibiting breast cancer cell growth, inducing cell cycle arrest in the G0/G1 phase, and increasing apoptosis. The therapeutic efficacy was assessed using a breast cancer xenograft mouse model. DC-5163 treatment markedly suppressed tumor growth in vivo without inducing evident systemic toxicity. Micro-PET/CT scans revealed a notable reduction in tumor 18F-FDG and 18F-FLT uptake in the DC-5163 treatment group compared to the DMSO control group. Conclusions: Our results suggest that DC-5163 is a promising GAPDH inhibitor for suppressing breast cancer growth without obvious side effects. 18F-FDG and 18F-FLT PET/CT can noninvasively assess the levels of glycolysis and proliferation in tumors following treatment with DC-5163. [ABSTRACT FROM AUTHOR]

Recently, community detection has emerged as a prominent research area in the analysis of complex network structures. Community detection models based on non-negative matrix factorization (NMF) are shallow and fail to fully discover the internal structure of complex networks. Thus, this article introduces a novel constrained symmetric non-negative matrix factorization with deep autoencoders (CSDNMF) as a solution to this issue. The model possesses the following advantages: (1) By integrating a deep autoencoder to discern the latent attributes bridging the original network and community assignments, it adeptly captures hierarchical information. (2) Introducing a graph regularizer facilitates a thorough comprehension of the community structure inherent within the target network. (3) By integrating a symmetry regularizer, the model's capacity to learn undirected networks is augmented, thereby facilitating the precise detection of symmetry within the target network. The proposed CSDNMF model exhibits superior performance in community detection when compared to state-of-the-art models, as demonstrated by eight experimental results conducted on real-world networks. [ABSTRACT FROM AUTHOR]

The use of solar interface evaporation for seawater desalination or sewage treatment is an environmentally friendly and sustainable approach; however, achieving efficient solar energy utilization and ensuring the long-term stability of the evaporation devices are two major challenges for practical application. To address these issues, we developed a novel ceramic fiber@bioderived carbon composite aerogel with a continuous through-hole structure via electrospinning and freeze-casting methods. Specifically, an aerogel was prepared by incorporating perovskite oxide (Ca0.25La0.5Dy0.25)CrO3 ceramic fibers (CCFs) and amylopectin-derived carbon (ADC). The CCFs exhibited remarkable photothermal conversion efficiencies, and the ADC served as a connecting agent and imparted hydrophilicity to the aerogel due to its abundant oxygen-containing functional groups. After optimizing the composition and microstructure, the (Ca0.25La0.5Dy0.25)CrO3 ceramic fiber@biomass-derived carbon aerogel demonstrated remarkable properties, including efficient light absorption and rapid transport of water and solutes. Under 1 kW m−2 light intensity irradiation, this novel material exhibited a high temperature (48.3 °C), high evaporation rate (1.68 kg m−2 h−1), and impressive solar vapor conversion efficiency (91.6%). Moreover, it exhibited long-term stability in water evaporation even with highly concentrated salt solutions (25 wt%). Therefore, the (Ca0.25La0.5Dy0.25)CrO3 ceramic fiber@biomass-derived carbon aerogel holds great promise for various applications of solar interface evaporation. [ABSTRACT FROM AUTHOR]

The development of immobilized enzymes with high activity and stability is critical. Metal–organic frameworks (MOFs) have attracted much academic and industrial interest in the field of enzyme immobilization due to their unique properties. In this study, the amino-functionalized ionic liquid (NIL)-modified metal–organic framework (UiO-66-NH2) was prepared to immobilize Candida rugosa lipase (CRL), using dialdehyde starch (DAS) as the cross-linker. The results of the Fourier transform infrared (FT-IR) spectra, X-ray powder diffraction (XRD), and scanning electronic microscopy (SEM) confirmed that the NIL was successfully grafted to UiO-66-NH2. The CRL immobilized on NIL-modified UiO-66-NH2 (UiO-66-NH2-NIL-DAS@CRL) exhibited satisfactory activity recovery (79.33%), stability, reusability, and excellent organic solvent tolerance. The research results indicated that ionic liquid-modified UiO-66-NH2 had practical potential for application in enzyme immobilization. [ABSTRACT FROM AUTHOR]

Simple Summary: The aim of this study was to detect the copy number variations in 25 Wannan spotted pigs and 10 Asian wild boars with whole genome sequencing data. The selection signatures of Wannan spotted pigs compared to those of Asian wild boars were calculated with fixation index (Fst). A total of 195 selected CNVs were under selected, harboring 80 genes. The selected genes were associated with reproduction, fatty acid composition, immune system, ear size, and feed efficiency. This study provides a new insight for understanding the characteristics of Wannan spotted pigs based on copy number variations. Copy number variation (CNV) is an important structural variation used to elucidate complex economic traits. In this study, we sequenced 25 Wannan spotted pigs (WSPs) to detect their CNVs and identify their selection signatures compared with those of 10 Asian wild boars. A total of 14,161 CNVs were detected in the WSPs, accounting for 0.72% of the porcine genome. The fixation index (Fst) was used to identify the selection signatures, and 195 CNVs with the top 1% of the Fst value were selected. Eighty genes were identified in the selected CNV regions. Functional GO and KEGG analyses revealed that the genes within these selected CNVs are associated with key traits such as reproduction (GAL3ST1 and SETD2), fatty acid composition (PRKG1, ACACA, ACSL3, UGT8), immune system (LYZ), ear size (WIF1), and feed efficiency (VIPR2). The findings of this study contribute novel insights into the genetic CNVs underlying WSP characteristics and provide essential information for the protection and utilization of WSP populations. [ABSTRACT FROM AUTHOR]

Efficiently removing excess reactive oxygen species (ROS) generated by various factors on the ocular surface is a promising strategy for preventing the development of dry eye disease (DED). The currently available eye drops for DED treatment are palliative, short-lived and frequently administered due to the short precorneal residence time. Here, we developed nanozyme-based eye drops for DED by exploiting borate-mediated dynamic covalent complexation between n-FeZIF-8 nanozymes (n-Z(Fe)) and poly(vinyl alcohol) (PVA) to overcome these problems. The resultant formulation (PBnZ), which has dual-ROS scavenging abilities and prolonged corneal retention can effectively reduce oxidative stress, thereby providing an excellent preventive effect to alleviate DED. In vitro and in vivo experiments revealed that PBnZ could eliminate excess ROS through both its multienzyme-like activity and the ROS-scavenging activity of borate bonds. The positively charged nanozyme-based eye drops displayed a longer precorneal residence time due to physical adhesion and the dynamic borate bonds between phenyboronic acid and PVA or o-diol with mucin. The in vivo results showed that eye drops could effectively alleviate DED. These dual-function PBnZ nanozyme-based eye drops can provide insights into the development of novel treatment strategies for DED and other ROS-mediated inflammatory diseases and a rationale for the application of nanomaterials in clinical settings. Highlights: Modification of dynamic covalent bonds based on borate bonds can improve the solubility and dispersion of Fe-based nanozymes in solution. The nanozyme-based eye drops enable reactive groups to bind to the chemical groups present in the mucin layer to confer carrier adhesion, thereby increasing the retention time of the carrier on the ocular surface. Nanozyme-based eye drops have synergistic effects on Fe-based nanozymes, and borate bonds effectively neutralize excess ROS in the microenvironment of the ocular surface, thereby reducing oxidative stress and direct oxidative damage. Nanozyme-based eye drops could effectively alleviate DED and may be a promising nanotherapeutic strategy for DED treatment. [ABSTRACT FROM AUTHOR]

In the current complex situations of electronic intelligence (ELINT), the authors present a radar emitter structure (RES) identification method based on deep learning at a new level to address the issue of incomplete cognitive information. Firstly, due to the fact that existing simulation data cannot fully reflect the structure features of the entire radar emitter, the structure feature‐level RES model is built using direct digital synthesiser (DDS) technology and radio frequency (RF) simulation platform. Afterwards, considering that the structure features are reflected in the frequency domain, a stacked frequency sparse auto encoder (sFSAE) network is constructed by adding a constraint term in frequency domain to the loss function of sparse auto encoder (SAE). Using deep learning to extract structure features with constraints in different domains is instructive for feature extraction techniques under variable operating parameters. Finally, the extracted structure features are input into the Softmax classifier to perform the identification from the radar signal to the RES. The experimental results show that the proposed method has high generalisation ability and robustness under different modulation types, different operating parameters and different signal to noise ratio (SNR). It also has a high identification rate even for untrained modulated signals. [ABSTRACT FROM AUTHOR]

The snap-through behaviors and nonlinear vibrations are investigated for a bistable composite laminated cantilever shell subjected to transversal foundation excitation based on experimental and theoretical approaches. An improved experimental specimen is designed in order to satisfy the cantilever support boundary condition, which is composed of an asymmetric region and a symmetric region. The symmetric region of the experimental specimen is entirely clamped, which is rigidly connected to an electromagnetic shaker, while the asymmetric region remains free of constraint. Different motion paths are realized for the bistable cantilever shell by changing the input signal levels of the electromagnetic shaker, and the displacement responses of the shell are collected by the laser displacement sensors. The numerical simulation is conducted based on the established theoretical model of the bistable composite laminated cantilever shell, and an off-axis three-dimensional dynamic snap-through domain is obtained. The numerical solutions are in good agreement with the experimental results. The nonlinear stiffness characteristics, dynamic snap-through domain, and chaos and bifurcation behaviors of the shell are quantitatively analyzed. Due to the asymmetry of the boundary condition and the shell, the upper stable-state of the shell exhibits an obvious soft spring stiffness characteristic, and the lower stable-state shows a linear stiffness characteristic of the shell. [ABSTRACT FROM AUTHOR]

Ice plug technology is an effective method for isolating the pipeline system, which are promising methods utilized in the nuclear, chemical, and power industries. To reduce the cold energy consumption and temperature stress, the multi-stage (1–10) of time-dependent thermal boundary conditions was proposed for the formation of ice plug, while the gradient cooling wall temperature of multi-stage was applied. A numerical model considering the liquid–solid phase change, heat transfer, and time-dependent thermal boundary condition has been established. The effects of the ratio of length and diameter of the cooling wall lc/d (1–9) on the formation rate and heat flux of ice plug in the pipe has been investigated. The fastest formation rate of ice plug with 800 mm in the axial direction (7.47 cm3/s) was observed in the pipe with the lc/d of 5. The formation rate of ice plug and the ice formation volume under unit energy consumption VE under various stages (1–10) of cooling wall temperature have been compared. The VE of eight temperature stages (1.45 cm3/kJ) was 1.16 times than the VE of one temperature stage, which satisfied the freezing rate at the same time. This investigation provides insight for proposing an energy-saving system for the formation of ice plug. [ABSTRACT FROM AUTHOR]

Despite the existence of various super‐resolution (SR) methods, most of them focus on designing models for specific upscaling factors rather than fully exploiting inter‐scale correlation to improve efficiency. In contrast, multi‐scale SR methods can effectively reduce the redundancy of network parameters by aggregating the feature extraction processes corresponding to multiple scales into a unified process. The aim of this study is to enhance the compactness and efficiency of the SR model. Thus, an efficient multi‐scale SR method called the diverse branch feature refinement network (DBFRN) is proposed. By decoupling the training process and inference process based on the idea of structural re‐parameterization, multi‐branch topology is adopted to enrich multi‐scale learning and merge branches to achieve efficient inference with equivalent effects. Specifically, two re‐parameterization strategies are designed and two corresponding feature refinement blocks for different feature levels in multi‐scale SR network. Extensive experiments demonstrate that the proposed multi‐scale SR method is effective and efficient, and it can outperform advanced single‐scale methods in terms of quantity and quality. [ABSTRACT FROM AUTHOR]

Black spot, caused by Alternaria brassicicola (Ab), poses a serious threat to crucifer production, and knowledge of how plants respond to Ab infection is essential for black spot management. In the current study, combined transcriptomic and metabolic analysis was employed to investigate the response to Ab infection in two cabbage (Brassica oleracea var. capitata) genotypes, Bo257 (resistant to Ab) and Bo190 (susceptible to Ab). A total of 1100 and 7490 differentially expressed genes were identified in Bo257 (R_mock vs. R_Ab) and Bo190 (S_mock vs. S_Ab), respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that "metabolic pathways", "biosynthesis of secondary metabolites", and "glucosinolate biosynthesis" were the top three enriched KEGG pathways in Bo257, while "metabolic pathways", "biosynthesis of secondary metabolites", and "carbon metabolism" were the top three enriched KEGG pathways in Bo190. Further analysis showed that genes involved in extracellular reactive oxygen species (ROS) production, jasmonic acid signaling pathway, and indolic glucosinolate biosynthesis pathway were differentially expressed in response to Ab infection. Notably, when infected with Ab, genes involved in extracellular ROS production were largely unchanged in Bo257, whereas most of these genes were upregulated in Bo190. Metabolic profiling revealed 24 and 56 differentially accumulated metabolites in Bo257 and Bo190, respectively, with the majority being primary metabolites. Further analysis revealed that dramatic accumulation of succinate was observed in Bo257 and Bo190, which may provide energy for resistance responses against Ab infection via the tricarboxylic acid cycle pathway. Collectively, this study provides comprehensive insights into the Ab–cabbage interactions and helps uncover targets for breeding Ab-resistant varieties in cabbage. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusions To compare safety and efficacy of isolated and combined UV‐light corneal crosslinking (CXL) and fine‐needle diathermy (FND) to regress pathological corneal vessels in vivo.Mice with inflamed and pathologically vascularized corneas received CXL or FND as monotherapy or a combination of both treatments. Corneal pathological blood and lymphatic vessels, immune cells and the morphology of anterior segment structures were evaluated.All three approaches were able to regress blood and lymphatic vessels in mice. A comparative analysis of the three methods revealed that the FND monotherapy and the CXL + FND combination were significantly more effective than the CXL monotherapy, one and 2 weeks after therapy and especially in regressing lymphatic vessels. Furthermore, the combination therapy induced significantly less immune cell recruitment compared to the monotherapies. All three methods were safe to use in regards of corneal integrity.A combination of FND and CXL led to regression of pathological corneal lymphatic and blood vessels and reduced the infiltration of immune cells into inflamed murine corneas. This approach offers a new effective, safe and clinically usable strategy to treat eyes with mature pathological blood vessels and even more so for lymphatic vessels, for example prior to high‐risk corneal transplantation. [ABSTRACT FROM AUTHOR]

Background: Single-cell clustering has played an important role in exploring the molecular mechanisms about cell differentiation and human diseases. Due to highly-stochastic transcriptomics data, accurate detection of cell types is still challenged, especially for RNA-sequencing data from human beings. In this case, deep neural networks have been increasingly employed to mine cell type specific patterns and have outperformed statistic approaches in cell clustering. Results: Using cross-correlation to capture gene–gene interactions, this study proposes the scCompressSA method to integrate topological patterns from scRNA-seq data, with support of self-attention (SA) based coefficient compression (CC) block. This SA-based CC block is able to extract and employ static gene–gene interactions from scRNA-seq data. This proposed scCompressSA method has enhanced clustering accuracy in multiple benchmark scRNA-seq datasets by integrating topological and temporal features. Conclusion: Static gene–gene interactions have been extracted as temporal features to boost clustering performance in single-cell clustering For the scCompressSA method, dual-channel SA based CC block is able to integrate topological features and has exhibited extraordinary detection accuracy compared with previous clustering approaches that only employ temporal patterns. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to assess the microbial variations and biomarkers in the vaginal and oral environments of patients with human papillomavirus (HPV) and cervical cancer (CC) and to develop novel prediction models. Materials and methods: This study included 164 samples collected from both the vaginal tract and oral subgingival plaque of 82 women. The participants were divided into four distinct groups based on their vaginal and oral samples: the control group (Z/KZ, n = 22), abortion group (AB/KAB, n = 17), HPV-infected group (HP/KHP, n = 21), and cervical cancer group (CC/KCC, n = 22). Microbiota analysis was conducted using full-length 16S rDNA gene sequencing with the PacBio platform. Results: The vaginal bacterial community in the Z and AB groups exhibited a relatively simple structure predominantly dominated by Lactobacillus. However, CC group shows high abundances of anaerobic bacteria and alpha diversity. Biomarkers such as Bacteroides, Mycoplasma, Bacillus, Dialister, Porphyromonas, Anaerococcus, and Prevotella were identified as indicators of CC. Correlations were established between elevated blood C-reactive protein (CRP) levels and local/systemic inflammation, pregnancy, childbirth, and abortion, which contribute to unevenness in the vaginal microenvironment. The altered microbial diversity in the CC group was confirmed by amino acid metabolism. Oral microbial diversity exhibited an inverse pattern to that of the vaginal microbiome, indicating a unique relationship. The microbial diversity of the KCC group was significantly lower than that of the KZ group, indicating a link between oral health and cancer development. Several microbes, including Fusobacterium, Campylobacter, Capnocytophaga, Veillonella, Streptococcus, Lachnoanaerobaculum, Propionibacterium, Prevotella, Lactobacillus, and Neisseria, were identified as CC biomarkers. Moreover, periodontal pathogens were associated with blood CRP levels and oral hygiene conditions. Elevated oral microbial amino acid metabolism in the CC group was closely linked to the presence of pathogens. Positive correlations indicated a synergistic relationship between vaginal and oral bacteria. Conclusion: HPV infection and CC impact both the vaginal and oral microenvironments, affecting systemic metabolism and the synergy between bacteria. This suggests that the use of oral flora markers is a potential screening tool for the diagnosis of CC. [ABSTRACT FROM AUTHOR]

This study proposed the direct extrusion and continuous-shear deformation (DECS) process for the co-extrusion of Mg-AZ31B/Al 6063, aiming to prepare high-plasticity Mg/Al composite sheets. The effect of extrusion temperature on the microstructure and mechanical properties of the Mg/Al composite sheet was systematically studied. The results show that Mg/Al composite sheets with no voids or cracks at the interface were successfully prepared by the DECS process. The microstructure of the Mg layer at different extrusion temperatures primarily consists of equiaxed fine grains, with grain sizes of 7.29 μm, 8.98 μm, and 9.88 μm at 330℃, 360℃, and 390℃, respectively. The Mg layer exhibits a typical extrusion texture, with the c-axis of most grains parallel to the transverse direction (TD). With the increase in extrusion temperature, the c-axis of some grains deviates from the TD toward the normal direction (ND). The Al layer mainly consists of elongated deformed grains and fine dynamically recrystallized (DRXed) grains distributed along the extrusion direction (ED). The AZ31 Mg alloy with refined grains maintains the ultimate tensile strength of the Mg/Al composite sheet, while the Al matrix enhances its plasticity. At 330℃, the Mg/Al composite sheet shows an ultimate tensile strength of 244.48 MPa ± 4.35 and an elongation of 39.42% ± 0.06. The influence of the bonding layer thickness on the shear and tensile properties of the composite sheet was studied, revealing that increasing the bonding layer thickness reduces the shear strength of the Mg/Al composite sheet but positively affects its tensile strength. [ABSTRACT FROM AUTHOR]

Peripheral T-cell lymphoma (PTCL) is a heterogeneous group of hematological malignancies with poor survival, while treatment options for relapsed or refractory (R/R) disease remain quite limited, with a median progression-free survival of only 3–4 months. Notably, the emergence of innovative therapeutic agents and regimens holds promise for durable responses and improved survival for patients with R/R PTCL. We summarize recent advances in the treatment of R/R PTCL from the 2023 ASH Annual Meeting, highlighting novel agents targeting EZH1/2, JAK1, PI3K, KIR3DL2, CD38/CD3xCD28, or CDK9, as well as therapeutic regimens in combination with stem cell transplantation, immunomodulators, epigenetic modifying agents, or CD30/CD16A bispecific antibodies. [ABSTRACT FROM AUTHOR]

Aims/Introduction Materials and Methods Results Conclusions Our aim was to investigate the optimal fasting glucose (FPG) range in Chinese older adults with type 2 diabetes, and to clarify whether the optimal range varies according to the control of risk factors.The baseline survey for the cohort study began in 2018, with follow up ending in 2022. Our study enrolled 59,030 older diabetes patients with no history of cardiovascular disease (CVD). Participants were divided into nine groups based on their baseline glycemic status. The association between FPG and the risk of adverse outcomes was mainly estimated by multivariate Cox proportional risk models and restricted spline analysis.During the 4‐year follow‐up period, a total of 5,637 deaths and 4,904 CVD events occurred. The associations of FPG with mortality and CVD events showed J‐shaped curves. Among all‐cause deaths, the hazard ratios for FPG ≤4.50 and >11.50 mmol/L were 1.50 (95% confidence interval [CI] 1.31–1.71) and 1.84 (95% CI 1.67–2.02). Among CVD, the hazard ratios for FPG ≤4.50 and >11.50 mmol/L were 1.31 (95% CI 1.13–1.53) and 1.71 (95% CI 1.54–1.89), respectively. The optimal FPG ranges of all‐cause mortality and CVD were 5.50–7.50 and 4.50–7.50 mmol/L, respectively. For participants with at least two risk factors, the optimal FPG levels were higher than those with fewer risk factors.In older Chinese diabetes patients, the FPG ranges related to the minimum death and CVD event rates were 5.50–7.50 and 4.50–7.50 mmol/L, respectively. Patients with more cardiovascular risk factors had higher optimal blood glucose ranges than those with fewer risk factors. [ABSTRACT FROM AUTHOR]

The inflow of a rotating centrifugal impeller is normally perturbed by an upstream stationary component; therefore, the development of turbulent flow is different from the case with steady and uniform inflow. In this work, we performed a large-eddy simulation on turbulent flow in a centrifugal impeller, considering perturbation from the inflow and emphasizing the development of perturbation and its influence on flow in the impeller. The inflow perturbation is applied for the streamwise (w-) velocity and is time-varying as generated by a random number generator. A normal-distributed pattern of perturbation is always assumed with the intensity of perturbation, defined as the ratio between the perturbation amplitude and the mean velocity, set as fv = 0%, 5%, 10%, and 20%, where fv denotes the perturbation intensity. The inflow perturbation notably affects the passage flow. The velocity fluctuation and secondary flow increase in intensity as the perturbation intensity increases from fv = 0% to 10%, while a further increase to fv = 20% slightly weakens the velocity fluctuation. Although this phenomenon is less obvious in terms of the time-averaged characteristics of velocity, the Reynolds stress terms CtCa and CrCa under time-averaging still reflect a clear variation trend, and the Reynolds stresses are observed significantly on the blade suction surface. [ABSTRACT FROM AUTHOR]

Background: A few patients with inflammatory myopathy showed anti-mitochondrial antibody (AMA) positivity. This study aimed to report the clinical and pathological findings with vacuoles in 3 cases of such patients. Methods: Three cases with myositis from the Myositis Clinical Database of Peking University First Hospital were identified with AMA positivity. Their clinical records were retrospectively reviewed and the data was extracted. All the 3 cases underwent muscle biopsy. Results: Three middle-aged patients presented with chronic-onset weakness of proximal limbs, marked elevation of creatine kinase, and AMA-positivity. Two of the 3 cases meet the criteria of primary biliary cholangitis. All the 3 cases presented with cardiac involvement and proteinuria. Two cases developed type 2 respiratory failure. MRI of the thigh muscle showed multiple patches of edema bilaterally in both cases, mostly in the adductor magnus. Pathological findings include degeneration of muscle fibers, diffused MHC-I positivity, and complement deposits on cell membranes. Vacuoles without rims of different sizes were discovered under the membrane of the muscle fibers. A few RBFs were discovered in case 1, while a diffused proliferation of endomysium and perimysium was shown in case 2. Conclusions: AMA-positive inflammatory myopathy is a disease that could affect multiple systems. Apart from inflammatory changes, the pathological findings of muscle can also present vacuoles. [ABSTRACT FROM AUTHOR]

Objective To understand the detection of four prohibited veterinary drugs of fresh and live freshwater fish sold in Guangzhou by analyzing the test data from risk monitoring and supervision sampling, so as to provide reference basis for food safety supervision. Methods Through the Guangzhou Food Safety Risk Monitoring system and the Food Safety Supervision and Inspection Public Information report of Guangzhou Market Administration, the test results of fresh water fish samples col-lected from supermarkets, markets, and online e-commerce in Guangzhou from 2017 to 2021 were obtained. The detection of nitrofuran drugs, chloramphenicol, sodium pentachloro phenate, and malachite green drugs were analyzed. Results The total detection rate of banned veterinary drugs in risk monitoring samples was 35.3% (84/238), and that in supervised sampling samples was 3.10% (118/3 806). The banned veterinary drugs with high detection rates of the two data sources were different. The risk monitoring rates of chloramphenicol and sodium pentachloro phenate were 17.23% (41/238) and 17.23% (41/238), respectively, and that of malachite green was 2.18% (83/3 806). The drug detection rate of the samples collected by risk monitoring in the network e-commerce link was Al.50% (19/40), which was the highest among all sampling links. The results of the two data sources showed that the detection rate of banned veterinary drugs in the wholesale market was high: 47.37% (18/38) and 4.13% (5/121), respectively. Conclusion The results of data analysis from the two sources complement each other and jointly reveal the problem of banned veterinary drug residues in fresh freshwater fish sold in Guangzhou from 2017 to 2021. It is suggested that the relevant departments pay more attention to the illegal use of chloramphenicol, sodium pentachloro phenate, and malachite green drugs. [ABSTRACT FROM AUTHOR]

Introduction: The 2019 novel coronavirus (COVID-19) has been recognized as the most severe human infectious disease pandemic in the past century. To enhance our ability to control potential infectious diseases in the future, this study simulated the influence of nucleic acid testing on the transmission of COVID-19 across varied scenarios. Additionally, it assessed the demand for nucleic acid testing under different circumstances, aiming to furnish a decision-making foundation for the implementation of nucleic acid screening measures, the provision of emergency materials, and the allocation of human resources. Methods: Considering the transmission dynamics of COVID-19 and the preventive measures implemented by countries, we explored three distinct levels of epidemic intensity: community transmission, outbreak, and sporadic cases. Integrating the theory of scenario analysis, we formulated six hypothetical epidemic scenarios, each corresponding to possible occurrences during different phases of the pandemic. We developed an improved SEIR model, validated its accuracy using real-world data, and conducted a comprehensive analysis and prediction of COVID-19 infections under these six scenarios. Simultaneously, we assessed the testing resource requirements associated with each scenario. Results: We compared the predicted number of infections simulated by the modified SEIR model with the actual reported cases in Israel to validate the model. The root mean square error (RMSE) was 350.09, and the R-squared (R2) was 0.99, indicating a well-fitted model. Scenario 4 demonstrated the most effective prevention and control outcomes. Strengthening non-pharmaceutical interventions and increasing nucleic acid testing frequency, even under low testing capacity, resulted in a delayed epidemic peak by 78 days. The proportion of undetected cases decreased from 77.83% to 31.21%, and the overall testing demand significantly decreased, meeting maximum demand even with low testing capacity. The initiation of testing influenced case detection probability. Under high testing capacity, increasing testing frequency elevated the detection rate from 36.40% to 77.83%. Nucleic acid screening proved effective in reducing the demand for testing resources under diverse epidemic prevention and control strategies. While effective interventions and nucleic acid screening measures substantially diminished the demand for testing-related resources, varying degrees of insufficient testing capacity may still persist. Conclusions: The nucleic acid detection strategy proves effective in promptly identifying and isolating infected individuals, thereby mitigating the infection peak and extending the time to peak. In situations with constrained testing capacity, implementing more stringent measures can notably decrease the number of infections and alleviate resource demands. The improved SEIR model demonstrates proficiency in predicting both reported and unreported cases, offering valuable insights for future infection risk assessments. Rapid evaluations of testing requirements across diverse scenarios can aptly address resource limitations in specific regions, offering substantial evidence for the formulation of future infectious disease testing strategies. [ABSTRACT FROM AUTHOR]

Anomaly detection of multivariate time series plays a growingly crucial role in intelligent operation and maintenance. Most existing anomaly detection models tend to focus on extracting temporal information while essentially ignoring the relationships among multiple sensors. Graph neural networks simulate multivariate inter-series relationships but suffer from the independent updating of graph structure from data. To overcome such limitation, we present a graph attention network-based model to learn the sensors relationships. It is equipped with a sustainable updating similarity-constrained graph structure learning method and a time series encoder. The graph learning method performs continuous updating of the graph structure. The encoder generates augmented and representative views along the temporal dimension. Our proposed model not only efficiently learns sensor relationships but also improves the ability of anomaly detection. Experiments are performed on publicly benchmark datasets, including SWaT, WADI, and HAI, with F1 scores of 92.98%, 91.19%, and 87.12%, respectively. This confirms that the proposed model outperforms the state-of-the-art in anomaly detection performance. [ABSTRACT FROM AUTHOR]

High entropy materials are becoming more and more popular in energy storage field of supercapacitors because of their unique structure and modulated functional characteristics, but their low conductivity and instability of electrode structure limit their further electrochemical performance. In this paper, we use polyethylene glycol (PEG) with different molecular weights to modify the surface morphology of the high entropy oxides (FeCoCrMnNi) 3 O 4 in an attempt to improve their supercapacitors performance. The PEG was used as a pore-making agent to prepare porous high entropy oxides powder with a large specific surface area of 92.7559 m2 g−1, providing more active sites and ion transport channels. A high specific capacitance of 204 F g−1 at 0.5 A g−1 and good cycle performance of 60.4 % capacitance retention after 10,000 cycles were obtained. Besides, an asymmetric device with improved energy density of 53 W h kg−1 and the power density of 400.8 W kg−1 were reached via the designed microstructure of the high entropy oxide electrode. [ABSTRACT FROM AUTHOR]

Optimized fertilizer use improves crop yield and mitigates environmental pollution associated with crop production. Fertilizer and plant density are core strategies to ensure food security and cope with climate change. However, little is known about the long-term interactive effect of reduced nitrogen (N) and increased density on yield and C (Carbon) balance. In this study, field experiments were conducted in a double-cropping rice region to evaluate long-term effects on yield and carbon footprint (CF) by crop-based and soil-based methods. Treatments were set for 10% reduction in N coupling with conventional density (N1D1), 20% higher density (N1D2), 40% higher density (N1D3), and 20% reduction in N coupling with conventional density (N2D1), 20% higher density (N2D2), and 40% higher density (N2D3), with the prevailing practices as control, conventional plant density, and fertilizer dose. Results showed that the yield continued to increase with increasing density; under the same density, reducing N by 10% is more beneficial for yield improvement and for CH4 emission reduction. Compared with CK, reducing N application by 10% generally increased the annual yields by 7.34–23.25% on average, and reduced CH4 emissions by 16.19–22.11%, resulting in a reduced crop-based carbon footprint of 22.24–26.82%, and a reduced soil-based carbon footprint of 22.08–32.85%. While reducing N application by 20% increased the annual yields by 5.00–20.19% and reduced the CH4 emission by 1.66–4.93%, it reduced crop-based carbon footprints by 1.81–10.05% and reduced soil-based carbon footprints by 7.22–19.86%. As density increased, the crop-based CF decreased, whereas the soil-based CF increased. Overall, the highest yield and the lowest soil-based CF and unit yield CF (CFy) were observed in N1D3. Regarding sustainability, a 10% reduction in N, along with an increase in density to 40%, can be recommended for double-cropping rice production. [ABSTRACT FROM AUTHOR]

Repetitive transients are a key symptom for the occurrence of incipient fault of rolling element bearings. Therefore, an optimal wavelet filtering method is developed by maximizing the L-kurtosis through the genetic algorithm to extract the weak repetitive transients buried in the heavy noise and disturbed by the outliers. First, the capability of L-kurtosis for characterizing the impulsiveness and cyclostationary of repetitive transients is numerically studied at different degrees of noise. Then, the center frequency and band width of morlet wave filter are adaptively determined by the genetic algorithm and the maximization of L-kurtosis. Finally, both simulation and experiments are performed to validate the efficacy of the proposed method. Results show that the proposed method is more powerful and reliable than the other commonly used indexes-based optimal wavelet filtering methods. [ABSTRACT FROM AUTHOR]

The conventional Archie formula struggles with the interpretation of water saturation from resistivity well log data due to the increasing complexity of exploration targets. This challenge has prompted researchers to explore alternative physical parameters, such as acoustic characteristics, for breakthroughs. Clarifying the influencing factors of porous media acoustic characteristics is one of the most important approaches to help understanding the mechanism of acoustic characteristics of carbonate reservoirs. The article uses digital rock technology to characterize the pore structure, quantitatively identify fractures and pore structures in carbonate rocks, and establish digital models. Through conventional acoustic testing, the pressure wave (P-wave) and shear wave (S-wave) velocities of rock samples at different water saturations are obtained, and the dynamic elastic modulus is calculated. A finite element calculation model is established using the digital rock computational model to provide a basis for fluid saturation calculation methods. Based on real digital rock models, different combinations of virtual fractures are constructed, and factors affecting acoustic parameters are analyzed. The study finds that as porosity increases, the velocity difference between porous cores and fractured cores also increases. These findings provide important technical support and a theoretical basis for interpreting acoustic well logging data and evaluating carbonate reservoirs with different pore and fracture types. [ABSTRACT FROM AUTHOR]

This paper investigates the nonlinear bifurcation and chaos characteristics of piezoelectric composite lattice sandwich plates at 1:3 internal resonance. The nonlinear vibration partial differential equation is first discretized to become an ordinary differential equation by applying the Galerkin method. The main resonance modulation equations and the parametric resonance for the external excitation frequency that is close to the system's second-order modal frequency are then obtained by using the multiscale method. The Newton–Raphson method is subsequently applied to obtain the bifurcation diagram of the steady-state equilibrium of modulation equation with varying system parameters. The equilibrium stability is finally analyzed. We confirm the existence of static bifurcation such as saddle-node bifurcation, pitchfork bifurcation, and Hopf dynamic bifurcation. A detailed analysis is also conducted on the complex nonlinear jump phenomenon caused by the presence of multiple nonlinear steady-state solution regions. In the dynamic Hopf bifurcation interval, the fourth-order Runge–Kutta method is used to continue to track the dynamic periodic solution of the modulation equation in Cartesian coordinates. It is found that there are multiple boundary crises and attractor merging crises in the vibration system for piezoelectric composite lattice sandwich plates. [ABSTRACT FROM AUTHOR]

Exploring the complex relationship between population change and surface urban heat island (SUHI) effect has important practical significance for the ecological transformation development of shrinking cities in the context of the prevalence of urban shrinkage and the global climate change. This paper compares the population change and SUHI effect between population shrinking region (Northeast Region, NR) and population growing region (Yangtze River Delta, YRD) in China, and explores their differences in driving mechanisms, using GIS spatial analysis and Geodetector model. Our results indicated that there are significant differences in population changes and SUHI intensity between these two regions. About 72.22% of the cities in the NR were shrinking, while their SUHI intensities increased by an average of 1.69°C. On the contrary, the urban population in the YRD shows a linear growth trend, while their SUHI intensities decreased by 0.11°C on average. The results of bivariate Moran's I index also indicated that the spatial correlation between the urban population changes and the SUHI intensity changes are not significant in the above regions. Furthermore, there are significant differences in the primary drivers of SUHI variations between these two regions. In the NR, underlying surface changes, including the changes of green coverage and built-up areas, are the most important driving factors. However, atmospheric environment changes, such as carbon dioxide emission and sulfur dioxide emission, are the key drivers in the YRD. Northam's theory of three-stage urbanization and environmental Kuznets curve hypothesis are powerful to explain these differences. [ABSTRACT FROM AUTHOR]

Ex vivo red blood cell (RBC) production generates unsatisfactory erythroid cells. A deep exploration into terminally differentiated cells is required to understand the impairments for RBC generation and the underlying mechanisms. Here, we mapped an atlas of terminally differentiated cells from umbilical cord blood mononuclear cells (UCBMN) and pluripotent stem cells (PSC) and observed their dynamic regulation of erythropoiesis at single‐cell resolution. Interestingly, we detected a few progenitor cells and non‐erythroid cells from both origins. In PSC‐derived erythropoiesis (PSCE), the expression of haemoglobin switch regulators (BCL11A and ZBTB7A) were significantly absent, which could be the restraint for its adult globin expression. We also found that PSCE were less active in stress erythropoiesis than in UCBMN‐derived erythropoiesis (UCBE), and explored an agonist of stress erythropoiesis gene, TRIB3, could enhance the expression of adult globin in PSCE. Compared with UCBE, there was a lower expression of epigenetic‐related proteins (e.g., CASPASE 3 and UBE2O) and transcription factors (e.g., FOXO3 and TAL1) in PSCE, which might restrict PSCE's enucleation. Moreover, we characterized a subpopulation with high proliferation capacity marked by CD99high in colony‐forming unit‐erythroid cells. Inhibition of CD99 reduced the proliferation of PSC‐derived cells and facilitated erythroid maturation. Furthermore, CD99–CD99 mediated the interaction between macrophages and erythroid cells, illustrating a mechanism by which macrophages participate in erythropoiesis. This study provided a reference for improving ex vivo RBC generation. [ABSTRACT FROM AUTHOR]

Multimodal remote sensing data classification can enhance a model's ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks has become the focus of researchers. Inspired by the human feedback learning mechanism, causal reasoning mechanism, and knowledge induction mechanism, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposes causal meta-reinforcement learning (CMRL). First, based on the feedback learning mechanism, we overcame the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we helped the agents understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information.Second, based on the causal inference mechanism, we designed causal distribution prediction actions, classification rewards, and causal intervention rewards, capturing pure causal factors in multimodal data and preventing false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets showed that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks. [ABSTRACT FROM AUTHOR]

Using metal additive manufacturing processes can make up for traditional forging technologies when forming complex-shaped parts. At the same time, metal additive manufacturing has a fast forming speed and excellent manufacturing flexibility, so it is widely used in the aerospace industry and other fields. The fatigue strength of metal additive manufacturing is related to the microstructure of the epitaxially grown columnar grains and crystallographic texture. The crystal plasticity finite element method is widely used in the numerical simulation of the microstructure and macro-mechanical response of materials, which provides a strengthening and toughening treatment and can reveal the inner rules of material deformation. This paper briefly introduces common metal additive manufacturing processes. In terms of additive manufacturing fatigue, crystal plasticity simulations are summarized and discussed with regard to several important influencing factors, such as the microstructure, defects, surface quality, and residual stress. [ABSTRACT FROM AUTHOR]

Metering anomalies not only mean huge economic losses but also indicate the faults of equipment and power lines, especially within the substation. As a result, metering anomaly diagnosis is becoming one of the most important missions in smart grids. However, due to the insufficient and imbalanced anomaly cases, identifying the anomalies in smart meter data accurately and efficiently remains challenging. Existing methods usually employ few-shot learning models in computer vision directly, which requires the rich experience of human experts and sufficient abnormal cases for training. It blocks model generalizing to various application scenarios. To address these shortcomings, we propose a novel framework for metering anomaly diagnosis based on few-shot learning, named FSMAD. Firstly, we design a fault data injection model to emulate anomalies, so that no abnormal samples are required in the training phase. Secondly, we provide a learnable variable transformation to reveal inherent relationships among various smart meter data and help FSMAD extract more efficient features. Finally, the deeper metric network is equipped to support FSMAD in obtaining powerful comparison capability. Extensive experiments on a real-world dataset demonstrate the advantages of our FSMAD over state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Soybean (Glycine max [L.] Merr.) is one of the primary sources of plant protein and oil for human foods, animal feed, and industrial processing. The seed number per pod generally varies from one to four and is an important component of seed number per unit area and seed yield. We used natural variation in 264 landraces and improved cultivars or lines to identify candidate genes involved in the regulation of seed number per pod in soybean. Genome-wide association tests revealed 65 loci that are associated with seed number per pod trait. Among them, 11 could be detected in multiple environments. Candidate genes were identified for seed number per pod phenotype from the most significantly associated loci, including a gene encoding protein argonaute 4, a gene encoding histone acetyltransferase of the MYST family 1, a gene encoding chromosome segregation protein SMC-1 and a gene encoding exocyst complex component EXO84A. In addition, plant hormones were found to be involved in ovule and seed development and the regulation of seed number per pod in soybean. This study facilitates the dissection of genetic networks underlying seed number per pod in soybean, which will be useful for the genetic improvement of seed yield in soybean. [ABSTRACT FROM AUTHOR]

Metallurgical solid waste blast furnace water quenched slag (WBFS) was employed as carrier materials to prepare Fe–TiO 2 /WBFS composite photocatalyst using a sol-gel method for improving both the photocatalytic activity and the high-value utilization of metallurgical solid waste. The Fe3+ doping technology was adopted to increase the utilization of solar energy. The influencing factors and photocatalytic activity were systematically evaluated by thermogravimetry/differential thermal analyser (TG-DSC), X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET) method, scanning electron microscopy-energy spectrometer (SEM-EDS), X-ray photoelectric spectroscopy (XPS), UV–Vis absorption spectrum and photoluminescence spectra technology through the degradation rate of methylene blue (MB) solution. The results showed that the Fe3+ ions were successfully incorporated into the TiO 2 lattice, which had no effect on the crystalline phase of TiO 2 and expanded the spectral response range of TiO 2 from the ultraviolet region to the visible light region. When the calcination temperature was at 450 °C and the number of Fe–TiO 2 sol loading cycles was two times, the photocatalytic activity of Fe–TiO 2 /WBFS presented the strongest, and the degradation ratio of MB reach the maximum value of 98.9 %. A uniform and dense anatase TiO 2 thin film was wrapped on the surface of WBFS. The photocatalytic activity first improved and then weakened with an increase of calcination temperature, Fe3+ doping amounts and the loading cycles of sol. The TiO 2 film changed from thin to thick and uneven to uniform, until cracking and spalling phenomenon finally occurred with an increase of Fe–TiO 2 sol loading cycle from 1 to 3 times. When the Fe–TiO 2 /WBFS was reused for four times, the degradation rate of MB could still show 67.4 %, being far higher than that of TiO 2 /WBFS of 25.4 %. [ABSTRACT FROM AUTHOR]

Fluid manipulation is an important foundation of microfluidic technology. Various methods and devices have been developed for fluid control, such as electrowetting-on-dielectric-based digital microfluidic platforms, microfluidic pumps, and pneumatic valves. These devices enable precise manipulation of small volumes of fluids. However, their complexity and high cost limit the commercialization and widespread adoption of microfluidic technology. Shape memory polymers as smart materials can adjust their shape in response to external stimuli. By integrating shape memory polymers into microfluidic chips, new possibilities for expanding the application areas of microfluidic technology emerge. These shape memory polymers can serve as actuators or regulators to drive or control fluid flow in microfluidic systems, offering innovative approaches for fluid manipulation. Due to their unique properties, shape memory polymers provide a new solution for the construction of intelligent and automated microfluidic systems. Shape memory microfluidic chips are expected to be one of the future directions in the development of microfluidic technology. This article offers a summary of recent research achievements in the field of shape memory microfluidic chips for fluid and droplet manipulation and provides insights into the future development direction of shape memory microfluidic devices. [ABSTRACT FROM AUTHOR]

Previous studies have shown that Dendrobium nobile Lindl. alkaloids (DNLAs) have neuroprotective effects in several Alzheimer's disease (AD) models. Dendrobine (DDB) is one of the monomer components with the highest content in DNLAs. However, the effects of DDB on cognitive impairments in AD remain unknown. In this study, we investigated the efficacy of DDB in 3 × Tg-AD mice to determine whether DDB was a key component of the anti-AD effect of DNLAs. Five-month mice were intragastrically administrated with DDB (10 and 20 mg/kg/d) or DNLAs (20 mg/kg/d) for seven consecutive months, and the effects of DDB and DNLAs were evaluated at twelve months. The results revealed that 3 × Tg-AD mice treated with DDB showed enhanced nesting ability. DDB also effectively rescued spatial learning and memory deficits in 3 × Tg-AD mice. Meanwhile, DDB treatment prevented the loss of dendritic spine density, with increased expression levels of synaptophysin, PSD95, and NCAM in the hippocampus. Finally, DDB ameliorated the increase in APP, sAPPβ, CTF-β, and β-amyloid peptides, accompanied by the promotion of GSK phosphorylation at the Ser9 site, thereby reducing hyperphosphorylated tau levels. As the active component of DNLA, DDB can preserve cognitive function, alleviate neuronal and synaptic defects, and improve APP/tau pathology in 3 × Tg-AD mice. [ABSTRACT FROM AUTHOR]

Tumor‐related motor reorganization remains unclear. Navigated transcranial magnetic stimulation (nTMS) can investigate plasticity non‐invasively. nTMS‐induced motor‐evoked potentials (MEPs) of different muscles are commonly used to measure the center of gravity (CoG), the location with the highest density of corticospinal neurons in the precentral gyrus. We hypothesized that a peripheral innervation‐based MEP analysis could outline the tumor‐induced motor reorganization with a higher clinical and oncological relevance. Then, 21 patients harboring tumors inside the left corticospinal tract (CST) or precentral gyrus were enrolled in group one (G1), and 24 patients with tumors outside the left CST or precentral gyrus were enrolled in Group 2 (G2). Median‐ and ulnar‐nerve‐based MEP analysis combined with diffusion tensor imaging fiber tracking was used to explore motor function distribution. There was no significant difference in CoGs or size of motor regions and underlying tracts between G1 and G2. However, G1 involved a sparser distribution of motor regions and more motor‐positive sites in the supramarginal gyrus—tumors inside motor areas induced motor reorganization. We propose an "anchor‐and‐ship theory" hypothesis for this process of motor reorganization: motor CoGs are stably located in the cortical projection area of the CST, like a seated anchor, as the core area for motor output. Primary motor regions can relocate to nearby gyri via synaptic plasticity and association fibers, like a ship moving around its anchor. This principle can anticipate functional reorganization and be used as a neuro‐oncological tool for local therapy, such as radiotherapy or surgery. [ABSTRACT FROM AUTHOR]

To examine the association of adverse childhood experiences (ACEs) with anemia among older people. 24,116 participants aged 50 years or above were recruited. Multivariable linear and logistic regression was used to assess the associations of self-reported ACEs number with hemoglobin concentrations (g/dL) and presence of anemia. Older individuals with two or more ACEs, versus no ACEs, showed lower hemoglobin concentrations (β = − 0.08 g/dL, 95% confidence intervals (CI) − 0.12 to − 0.03) and higher odds of anemia (odds ratio = 1.26, 95% CI 1.01–1.59). A more pronounced association between ACEs and anemia in the lower education group was found, while the association became non-significant in those with higher education (P for ACEs-education interaction = 0.02). ACEs was associated with anemia in older people, and the association was stronger in those with lower education, highlighting the significance of early-life psychological stressors assessment and consideration of education background in geriatric care. [ABSTRACT FROM AUTHOR]

Glioblastoma is a highly aggressive and malignant type of brain cancer that originates from glial cells in the brain, with a median survival time of 15 months and a 5-year survival rate of less than 5%. Regulated cell death (RCD) is the autonomous and orderly cell death under genetic control, controlled by precise signaling pathways and molecularly defined effector mechanisms, modulated by pharmacological or genetic interventions, and plays a key role in maintaining homeostasis of the internal environment. The comprehensive and systemic landscape of the RCD in glioma is not fully investigated and explored. After collecting 18 RCD-related signatures from the opening literature, we comprehensively explored the RCD landscape, integrating the multi-omics data, including large-scale bulk data, single-cell level data, glioma cell lines, and proteome level data. We also provided a machine learning framework for screening the potentially therapeutic candidates. Here, based on bulk and single-cell sequencing samples, we explored RCD-related phenotypes, investigated the profile of the RCD, and developed an RCD gene pair scoring system, named RCD.GP signature, showing a reliable and robust performance in predicting the prognosis of glioblastoma. Using the machine learning framework consisting of Lasso, RSF, XgBoost, Enet, CoxBoost and Boruta, we identified seven RCD genes as potential therapeutic targets in glioma and verified that the SLC43A3 highly expressed in glioma grades and glioma cell lines through qRT-PCR. Our study provided comprehensive insights into the RCD roles in glioma, developed a robust RCD gene pair signature for predicting the prognosis of glioma patients, constructed a machine learning framework for screening the core candidates and identified the SLC43A3 as an oncogenic role and a prediction biomarker in glioblastoma. [ABSTRACT FROM AUTHOR]

Conducting in-situ measurements of planetary environments is a key scientific goal in the geoscience field for the extraterrestrial exploration, such as the Moon or Mars. Among these measurements, determining the thermal properties of regolith is particularly challenging due to the material's inhomogeneities. In this paper, an active thermal probing technique is proposed, utilizing a transient hot-wire technique with a needle-like probe structure integrated with temperature sensors and a heater. It is capable of measuring in-situ temperature variations and inner heat flux without disturbing the surrounding regolith. In addition, a machine-learning-based method is proposed for inverting in-situ thermophysical properties, including density, thermal conductivity, and heat capacity. An embedded artificial neural network model has been developed and trained with data sets from both finite element simulations and experiments. This machine learning model is capable of efficiently predicting temperature responses for different lunar regolith simulants. For total 12 parameters, the errors of ten cases are less than 10%, and other two cases are 12.23% and 13.17%. Finally, the proposed method is verified by heat measurement experiments under normal pressure and vacuum, and the variation of thermal properties with different compactness is obtained. The proposed probing technique provides novel ideas to measure the in-situ thermal properties of extraterrestrial regolith. [ABSTRACT FROM AUTHOR]