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Background: Programmed cell death is an important mechanism for the development of hepatic ischemia and reperfusion (IR) injury, and multiple novel forms of programmed cell death are involved in the pathological process of hepatic IR. ERRFI1 is involved in the regulation of cell apoptosis in myocardial IR. However, the function of ERRFI1 in hepatic IR injury and its modulation of programmed cell death remain largely unknown. Methods: Here, we performed functional and molecular mechanism studies in hepatocyte-specific knockout mice and ERRFI1-silenced hepatocytes to investigate the significance of ERRFI1 in hepatic IR injury. The histological severity of livers, enzyme activities, hepatocyte apoptosis and ferroptosis were determined. Results: ERRFI1 expression increased in liver tissues from mice with IR injury and hepatocytes under oxygen-glucose deprivation/reoxygenation (OGD/R) conditions. Hepatocyte-specific ERRFI1 knockout alleviated IR-induced liver injury in mice by reducing cell apoptosis and ferroptosis. ERRFI1 knockdown reduced apoptotic and ferroptotic hepatocytes induced by OGD/R. Mechanistically, ERRFI1 interacted with GRB2 to maintain its stability by hindering its proteasomal degradation. Overexpression of GRB2 abrogated the effects of ERRFI1 silencing on hepatocyte apoptosis and ferroptosis. Conclusions: Our results revealed that the ERRFI1-GRB2 interaction and GRB2 stability are essential for ERRFI1-regulated hepatic IR injury, indicating that inhibition of ERRFI1 or blockade of the ERRFI1-GRB2 interaction may be potential therapeutic strategies in response to hepatic IR injury. [ABSTRACT FROM AUTHOR]

This paper proposes the capacity flexibility models of transit networks to describe the ability of urban transit networks to accommodate the changes in passenger demands. In order to keep the variations of the average passenger travel time in a reasonable way, the concept of coefficient of variation (CoV) is introduced to measure and limit the deviation from a baseline time of the average passenger travel time. The CoV could transform the capacity flexibility values to non-dimensional form in order to compare the capacity flexibility characteristics of different scale transit networks on an equal basis. The genetic algorithm with deep search (GA-DS) for this problem is proposed to find the approximating optimal solution of the capacity flexibility models more effectively. The algorithm has been tested with benchmark problems reported in the existing literature. The optimal solution of the flexibility models shows that the flexibility values are further improved by reducing the number of stops for transit routes under different transit operation conditions. At last, the influence factors of the capacity flexibility of transit systems are discussed to address reliable transit services. [ABSTRACT FROM AUTHOR]

Questions: Stomata can reflect the plant's adaptation to environmental changes. However, the variation patterns of stomatal traits across different habitats and their relationships with environmental drivers are still poorly understood. Here, we assessed the extent of interspecific and intraspecific variation in stomatal traits in two typical riparian forests, and investigated how stomatal traits adapt to habitat change as well as trait–environment relationships. Location: The Irtysh River Basin in China. Methods: We measured the stomatal density (SD), stomatal size (SS), and stomatal relative area (SRA) of dominant plant species from two riparian forests: (1) a riparian forest in the valley and (2) a riparian forest in the pediment plain. We analyzed the stomatal trait variation patterns of dominant plant species in different habitats. We then quantified the magnitude of intraspecific and interspecific stomatal trait variability and evaluated the relationships between stomatal traits and environmental factors. Results: We found that SD and SRA were significantly higher in pediment plain forests than in valley forests, whereas SS was not significantly different between these habitats. The SD and SRA of trees in pediment plain forests were significantly higher than those in valley forests, whereas there were no significant differences in understory plants between habitats. The interspecific variation in each stomatal trait was significantly higher than the intraspecific variation. Stomatal traits were more related to the soil environment than to climatic factors. Conclusions: Response strategies of stomatal traits to habitat changes differed between species and functional groups, and trait–environment relationships depended on the habitat type of the riparian forest. Our analysis of stomata trait variation implies adaptive strategies in species of natural riparian forest. Insights into trait–environment relationships could be used to predict carbon and water cycling, and vegetation changes in riparian forests of arid regions, especially in the context of climate change. [ABSTRACT FROM AUTHOR]

Polymer dielectrics possessing the superiorities of easy processing and high power density are widely used in pulsed power and power electronics. However, the low energy storage density (Ue) of polymer dielectrics limits their application in the modern electronic industries. In this work, we present the sea-island structure multilayered composites based on polymethylmethacrylate (PMMA) matrix and polyvinylidene fluoride (PVDF) nanoparticles, which is constructed by the solution blending with typical solubility differences method and the layer-by-layer solution casting method. The PVDF/PMMA composite incorporated with high PVDF content is placed in the middle of the sandwich-structured composite as a non-traditional intermediate polarization layer. The PVDF/PMMA composite with low PVDF loading is placed in the outer layer to improve the insulating property of the composite. The results show that the PVDF/PMMA composites with inner and outer PVDF volume content of 30% and 10%, respectively, obtained an excellent dielectric constant value (εr ~ 4.35), which is 45% higher than that of PMMA (εr ~ 3). Meanwhile, the maximum Ue (~ 4.95 J cm−3) of the PVDF/PMMA composites at an electric field of 422.48 MV m−1 was obtained, which is 207% higher than that of PMMA (Ue ~ 1.61 J cm−3). The improved energy storage capability could be attributed to the introduction of highly polarizing particles, the increased number of heterogeneous interfaces, and the multilayered construction of composite. This work provides a strategy for the preparation of advanced all-organic dielectrics with a higher discharge energy density. [ABSTRACT FROM AUTHOR]

Friction plays a key role in the assessment of the safety and stability of mechanical systems (such as superconducting magnet quench explosion, aerospace vehicle bearing wear, etc.). Due to the closeness of the interfaces in engineering structures and the randomness of the contact surfaces, existing methods for measuring static friction force are unable to measure it at the contact interfaces of engineering structures under service conditions. In this paper, a new method for measuring the static friction force at the interface based on electrical signals is proposed. This method enables the measurement of the static friction force at interfaces of complex engineering structures under service conditions solely through electrical signals. The results indicate that the contact resistance gradually decreases with the increase in tangential load during the static friction stage until a monotonic behavior of macroscopic sliding occurs. The evolution of contact resistance is linked to the evolution of the real contact area, and this monotonic behavior can be explained as the deformation form of contact points. The accuracy of the proposed electrical measurement method is verified by comparison with experimental results (with an error of less than 9%). The indirect measurement method of friction force proposed in this paper can effectively measure the static friction force at the interfaces of engineering structures under service conditions, and it is expected to be applied to the detection of friction performance at engineering structure interfaces in extreme service environments. [ABSTRACT FROM AUTHOR]

In this paper, a new axial-type magnetic gear with an auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AMGs, it has a higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of the proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterparts in RMGs, the AFS-AMG achieves a small size. Then, the geometrical parameters of the AFS-AMG are optimized to obtain better electromagnetic performance, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume. [ABSTRACT FROM AUTHOR]

This paper proposes an analytical model of the double-stator spoke-type permanent magnet vernier machine (DSSTVM) using the subdomain method (SDM), which can be used to calculate the magnetic field distribution and corresponding electromagnetic parameters of the DSSTVM. The whole field domain is divided into several subdomains according to the magnetic characteristics of each region, within which Laplace's and Poisson's equations are solved accordingly in terms of magnetic vector potential (MVP). Then, the corresponding magnetic flux density distribution, back electromotive force (EMF), and electromagnetic torque of the DSSTVM can be obtained. Ultimately, finite element analysis (FEA) is adopted to validate the proposed analytical model's effectiveness for quickly predicting the no-load and on-load performances of the DSSTVM. [ABSTRACT FROM AUTHOR]

Late flowering is a serious bottleneck in pumpkin (Cucurbita moschata Duch.) agriculture production. Although key genes governing flowering time have been reported in many species, the regulatory network of flowering in pumpkin remains largely obscure, thereby impeding the resolution of industry‐wide challenges associated with delayed fruit ripening in pumpkin cultivation. Here, we report an early flowering pumpkin germplasm accession (LXX‐4). Using LXX‐4 and a late flowering germplasm accession (HYM‐9), we constructed an F2 segregation population. A significant difference in FLOWERING LOCUS T‐LIKE 2 (FTL2) expression level was identified to be the causal factor of the flowering time trait discrepancy in LXX‐4 and HYM‐9. Moreover, we have shown that a 21 bp InDel in the FTL2 promoter was the key reason for the waxing and waning of its transcript level. The 21 bp deletion excluded a repressor‐AGL19 and recruited activators‐BBX7, WRKY40 and SVP to the FTL2 promoter in LXX‐4. Together, our data add a useful element to our knowledge which could be used to simplify breeding efforts for early‐maturing pumpkin. Summary statement: An InDel in FTL2 promoter exclude repressor AGL19 and recruit activators BBX7, WRKY40 and SVP to the promoter, leading to increase of FTL2 transcript level and early floral initiation under short‐day conditions. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD), which is a prevailing type of dementia, presents a significant global health concern. The current therapies do not meet clinical expectations. Amyloid-beta (Aβ) has been found to induce endogenous formaldehyde (FA) accumulation by inactivating FA dehydrogenase (FDH); in turn, excessive FA triggers Aβ aggregation that eventually leads to AD onset. Hence, scavenging FA by astaxanthin (ATX, a strong exogenous antioxidant) may be pursued as a promising disease-modifying approach. Here, we report that liposomal nanoparticles coupled with PEG (PEG-ATX@NPs) could enhance water-solubility of ATX and alleviate cognitive impairments by scavenging FA and reducing Aβ deposition. To enable drug delivery to the brain, liposomes were used to encapsulate ATX and then coupled with PEG, which produced liposomal nanoparticles (PEGATX@NPs) with a diameter of <100 nm. The PEG-ATX@NPs reduced Aβ neurotoxicity by both degrading FA and reducing FA-induced Aβ assembly in vitro. Intraperitoneal administration of PEG-ATX@NPs in APPswe/PS1dE9 mice (APP/PS1, a familial model of AD), not only decreased the levels of brain FA and malondialdehyde (MDA, a typical product of oxidative stress), but also attenuated both intracellular Aβ oligomerization and extracellular Aβ-related senile plaque (SP) formation. These pathological changes were accompanied by rescued ability of spatial learning and memory. Collectively, PEG-ATX@NPs improved the water-solubility, bioavailability, and effectiveness of ATX. Thus, it has the potential to be developed as a safe and effective strategy for treating AD. [Display omitted] • Liposomal NPs of ATX with PEG enhances its bioavailability and drug delivery. • Scavenging FA by PEG-ATX@NPs decreases Aβ oligomerization and deposition. • PEG-ATX@NPs more than ATX reduce Aβ neurotoxicity by scavenging FA. • PEG-ATX@NPs may be a promising strategy for treating Alzheimer's disease. [ABSTRACT FROM AUTHOR]

In recent years, key generation schemes based on the reciprocity of wireless channels have gained widespread attention in the field of wireless physical layer security. However, due to the openness of wireless channels, eavesdroppers may obtain partial legitimate keys by eavesdropping on the wireless channel. To address this issue, this paper proposes a wireless channel coding scheme that induces an "avalanche" of errors for eavesdroppers, which could maximize eavesdropper's bit error rate. The design of this scheme is based on the significant differences between the eavesdropping channel and the legitimate channel, and the average bit key disagreement ratio of the keys generated by the legitimate channel is around 8%. The scheme selects polar codes with strong error correction capabilities and chooses a coding rate matching the error level of the legitimate channel, forcing the eavesdropping channel's error rate into an "avalanche" state, where the error rate approaches 50%. This paper presents the structure of the encoder and determines the coding rate through simulation. Simulation results demonstrate that this scheme can significantly degrade the error rate of the eavesdropping channel while ensuring the prevention of eavesdroppers from obtaining secret information transmitted through the legitimate channel. [ABSTRACT FROM AUTHOR]

Laser-induced liquid plasma is expected to be an efficient medium for a new generation of terahertz (THz) devices. However, the mechanism of interaction between liquid plasma and THz waves is currently unclear. Here, we observed two phenomena related to THz wave interaction with water plasma: THz-induced second harmonic (TISH) radiation in water plasma and THz absorption by water plasma. We established an internal relationship between these two macroscopic phenomena by utilizing a photocurrent model and the Drude model. Using liquid water and air as examples, a scheme is proposed to analyze the photonic characteristics of plasma in different physical states. This study offers an experimental basis for predicting the TISH phenomenon across various substances and states and also provides the theoretical support for the practical implementation of liquid-based detection of THz waves. [ABSTRACT FROM AUTHOR]

In situ dual‐modal detection of electrophysiology (EP) and blood oxygen (BO) during muscle–vascular activity is crucial for healthcare and human–machine interaction. It requires an integrated monitoring system: a transparent electrode for EP detection directly adhered to skin and a near‐infrared spectroscopy (NIRs) layer for BO detection. In particular, the multi‐channel, highly transparent, stretchable electrodes should be well developed. In this study, 16‐channel transparent ionotronic electrodes are fabricated based on a stretchable and printable ionogel, demonstrating excellent properties such as high transparency, large stretchability, wet adhesion, biocompatibility, softness, and long‐term stability. The electrode exhibits stable contact impedance for 24 h and a 2‐week periodic EP monitoring. The 16‐channel transparent ionotronic electrode outperforms stretchable gold electrodes by providing stable EP monitoring with minimal interference in NIRs for blood oxygen detection. An in situ negative correlation is found between EP intensity and blood oxygen level over time. This study paves the way for designing transparent ionotronics for synchronous optical‐related monitoring and highlights the potential use of an in situ dual‐modal monitoring system for the study of muscle–vascular coupling in neurocience and rehabilitation. [ABSTRACT FROM AUTHOR]

The influence mechanism of tensile load on the conductivity of thin films is a key issue in evaluating the conductivity of engineering structural thin films under complex loading conditions. How to reveal the correlation mechanisms of different physical quantities of metal films, and to predict the variation of film resistance with tensile load is a very critical and challenging problem. In this paper, a multiscale model of film resistance under tensile neching is established to describe the mechanical behavior, resistivity, and resistance of metal films under tensile load. The results show that the tensile load has a significant effect on the resistivity and conductivity of the film. This provides a reference for the evaluation and optimization of the conductivity of thin films with complex engineering structures. [ABSTRACT FROM AUTHOR]

Volumetric measurement for the non-cavitating tip vortex in the near field of an elliptical hydrofoil is conducted using tomographic particle image velocimetry, which provides a fully three-dimensional diagnose of the vortex formation and development. The wandering motion and flow properties of the near-field tip vortex under different incident angles and Reynolds numbers are investigated in detail. Unlike in the far field, the wandering motion in the near field is mainly subject to the local flow unsteadiness rather than the flow condition. By the "re-centered" post-processing, the deviations introduced by the wandering motion can be technically corrected, and more accurate vortex properties can be thus obtained. In the near field, a turning point of the vortex center trajectory is detected, the position of which is basically independent of the flow condition. By investigating the local flow properties, it is found that this turning point is the position where the tip vortex completely leaves the trailing edge of hydrofoil and enters the wake region. At this turning point, the external supply to the vortex core starts to be restricted, and the vortex circulation reaches a rather constant value. Further according to the local flow properties, the development process of the near-field tip vortex can be divided into three stages: vortex-attached stage, vortex-lifting stage and vortex-detached stage, which are found to be closely relevant to the hydrofoil configuration. [ABSTRACT FROM AUTHOR]

Accurate prediction of photovoltaic power generation is a critical technical problem for utilizing solar energy. Aiming at the problem that the model parameters are difficult to obtain in applying photovoltaic power prediction methods, this paper has used long‐term monitoring data of output power, various meteorological data, and solar irradiation intensity of photovoltaic modules. This paper establishes the functional relationship between the output power of photovoltaic modules and the irradiation intensity through Pearson correlation analysis. By deducing the distribution relationship of irradiation intensity, the prediction model of irradiation intensity based on peak sunshine hours and sunshine duration is constructed and based on 340 sites across the country 64 years peak sunshine hours and sunshine duration query database. In this work, the theoretical value of the prediction model on sunny days is close to the measured value (R2 = 0.918–0.985). The solar radiation intensity on rainy days is weak, and the prediction accuracy is low (R2 = 0.838–0.930). The relative errors between the sunshine duration and the peak sunshine hours in the database are less than 4.55% and 4.79%, respectively, under sunny conditions in each quarter, indicating that the accuracy of the database meets the actual needs. [ABSTRACT FROM AUTHOR]

Epithelial polarity is critical for proper functions of epithelial tissues, tumorigenesis, and metastasis. The evolutionarily conserved transmembrane protein Crumbs (Crb) is a key regulator of epithelial polarity. Both Crb protein and its transcripts are apically localized in epithelial cells. However, it remains not fully understood how they are targeted to the apical domain. Here, using Drosophila ovarian follicular epithelia as a model, we show that epithelial polarity is lost and Crb protein is absent in the apical domain in follicular cells (FCs) in the absence of Diamond (Dind). Interestingly, Dind is found to associate with different components of the dynactin‐dynein complex through co‐IP‐MS analysis. Dind stabilizes dynactin and depletion of dynactin results in almost identical defects as those observed in dind‐defective FCs. Finally, both Dind and dynactin are also required for the apical localization of crb transcripts in FCs. Thus our data illustrate that Dind functions through dynactin/dynein‐mediated transport of both Crb protein and its transcripts to the apical domain to control epithelial apico‐basal (A/B) polarity. [ABSTRACT FROM AUTHOR]

Simple Summary: The gut microbiota and metabolites play a crucial role in the physiological health of the host and are influenced by various factors, including seasons. We utilized 16s sequencing and untargeted metabolomics to uncover the impact of seasonal change on the gut microbiota and metabolites of Tibetan antelopes. Overall, this study revealed differences in the gut microbiota and metabolites of Tibetan antelopes during the cold and warm seasons. These findings can provide a basis for the conservation of Tibetan antelopes. The Tibetan antelope is an endangered species suffering from poaching and habitat fragmentation. The intestinal flora and metabolites play a crucial role in the physiological homeostasis of hosts, which are influenced by various environmental factors like seasonal variation. In this particular research, our main goal was to explore the alterations in the metabolism and gut microbiota of Tibetan antelopes between the cold season (XB) and warm season (DA), using untargeted metabolomics and 16S rRNA gene-sequencing analyses. The findings indicated that Tibetan antelopes had a higher alpha-diversity of intestinal microbes during the cold season than during the warm season. Principal co-ordinate analysis revealed notable seasonal discrepancies in the function and structure of intestinal microbes in Tibetan antelopes. The relative abundance of Firmicutes was significantly increased during the cold season compared to during the warm season. Furthermore, the Tibetan antelope's primary metabolic functions of the intestinal micro-organisms were significantly higher during the cold season. The untargeted metabolomics analysis results showed a total of 532 metabolites that were significantly different between the cold season and warm season groups. These metabolites were found to be enriched in a total of 62 metabolic pathways. Among the most significant pathways of enrichment were the purine metabolism and pyrimidine metabolism. The levels of related metabolites in those pathways were remarkably higher in the warm season compared to the cold season. The comprehensive analysis of 16S rRNA and the metabolome reveals there is a significant correlation between differential microbiota and differential metabolites. Therefore, the gut microbiota changes caused by seasonal changes influenced the metabolites as well. This research reveals the function of seasonal changes in the intestinal flora and metabolites in the adaptation of Tibetan antelopes to environmental fluctuations and supplies a theoretical basis for instructing the protection management of Tibetan antelopes. [ABSTRACT FROM AUTHOR]

In recent years, the proliferation of remote sensing satellites has dramatically increased the demands of Earth observation and observing efficiency. Designing a promising satellite resource scheduling method is a pivotal way to meet the requirements of this scenario. However, with hundreds or more satellites involved, the existing optimization methods struggle to address the NP-hard resource scheduling problem effectively. In this paper, an approach named software-defined satellite observation (SDSO) is proposed. First, adopting the new design ideology, we define a unified specification based on a discrete spatial grid to describe the observation capability of all satellites. The observation resources are virtualized using the virtual resource pool technique and then stored in the database in advance, implementing on-demand acquisition for observation resources. Next, we designed a model of the remote sensing satellite resource scheduling problem based on a virtual resource pool and designed a solution method for searching information within the virtual resource pool. Finally, the experimental results show that the computational efficiency of the proposed SDSO methodology has a substantial advantage over the traditional methods. Meanwhile, with the growing number of satellites involved in scheduling, there is only a slight degradation in the execution performance of our method, while the time complexity of optimization-based approaches increases exponentially. [ABSTRACT FROM AUTHOR]

The influence mechanism of cyclic loading on the stiffness, thermal resistance, and electrical resistance of rough contact surfaces is a key issue in evaluating the interface contact performance of engineering structures under complex loading conditions. How to characterize this random contact process and reveal the correlation mechanism of different physical quantities at the contact interface, and to predict the changes of interface contact stiffness, thermal resistance and electrical resistance with cyclic load is a very critical and challenging problem. In this paper, a probabilistic characterization method for the random contact process is proposed. Then, based on this method, theoretical models are established to describe the mechanical behavior, thermal and electrical contact resistance of the rough contact surface under cyclic loading. The results show that the cyclic load has a significant effect on the thermal and electrical contact resistance. The stiffness, thermal insulation capacity, and electrical conductivity of the interface are closely related to the number of cyclic loads, which provides a reference for the evaluation of interface performance and life prediction of engineering structures in complex environments. [ABSTRACT FROM AUTHOR]

The cultivation of early maturing crop varieties will aid in expanding the range of planting latitudes and enhancing the adaptability of plants to seasonal climates. There are remarkable parallels and discrepancies between the roles and regulatory networks of early maturing regulators in different crops. The breeding process is hindered by the negative correlation between early maturity, multi-resistance, and yield. Breaking this negative association and effectively polymerizing multiple desirable features is a key objective of modern plant breeding. Gene pleiotropy facilitates the highly efficient polymerization of early maturity, multi-resistance, optimal plant architecture, and high yield. Many newly created early maturing varieties exhibit poor stress resistance and low yield, whereas stress-resistant varieties are typically late maturing. For this reason, the polymerization of early maturity and other desired agronomic qualities requires overcoming the negative connection between early maturity, multi-resistance, and yield, which presents a formidable challenge in current breeding techniques. We review the most salient constraints of early maturity breeding in current crop planting practices and the molecular mechanisms of different maturation timeframes in diverse crops from their origin center to production areas. We explore current breeding tactics and the future direction of crop breeding and the issues that must be resolved to accomplish the polymerization of desirable traits in light of the current obstacles and limitations. [ABSTRACT FROM AUTHOR]

Background: Subjective well-being has a significant impact on an individual's physical and mental health. Socioeconomic status, class identity, and social activity participation play important roles in subjective well-being. Therefore, the aim of this study was to uncover the mechanisms through which these factors influence subjective well-being. Methods: A total of 1926 valid samples were recruited using the Chinese General Social Survey 2021 (CGSS 2021). The Chinese Citizen's Subjective Well-Being Scale (SWBS-CC) was employed to assess subjective well-being. Socioeconomic status was measured using income and education, and class identity and social activity participation were measured using Likert scales. Pearson correlation analysis and the chain mediation model were conducted to explore the relationship between these factors. Finally, the Bootstrap method was used to examine the path coefficients. Results: A significant correlation was found between socioeconomic status, class identity, social activity, and subjective well-being (p < 0.01). The indirect effect of socioeconomic status on subjective well-being mediated by class identity was 0.351 (95% CI: 0.721, 1.587), while the indirect effect of socioeconomic status on subjective well-being mediated by social activity was 0.380 (95% CI: 0.059, 0.240). The effect mediated by both class status and social activities was 0.011 (95% CI: 0.010, 0.093). Conclusions: The study showed that socioeconomic status, class identity, and social activity had significant effects on subjective well-being. Class identity and social activity partially mediated the effects of socioeconomic status on subjective well-being, and they had a chain mediating effect between socioeconomic status and subjective well-being. Therefore, policymakers have the opportunity to enhance subjective well-being in lower socioeconomic status groups by promoting individual class identity and encouraging greater social activity participation. [ABSTRACT FROM AUTHOR]

Object detection in remote sensing images (RSIs) has become crucial in recent years. However, researchers often prioritize detecting small objects, neglecting medium- to large-sized ones. Moreover, detecting objects hidden in shadows is challenging. Additionally, most detectors have extensive parameters, leading to higher hardware costs. To address these issues, this paper proposes a multi-scale and high-precision lightweight object detector named MHLDet. Firstly, we integrated the SimAM attention mechanism into the backbone and constructed a new feature-extraction module called validity-neat feature extract (VNFE). This module captures more feature information while simultaneously reducing the number of parameters. Secondly, we propose an improved spatial pyramid pooling model, named SPPE, to integrate multi-scale feature information better, enhancing the model to detect multi-scale objects. Finally, this paper introduces the convolution aggregation crosslayer (CACL) into the network. This module can reduce the size of the feature map and enhance the ability to fuse context information, thereby obtaining a feature map with more semantic information. We performed evaluation experiments on both the SIMD dataset and the UCAS-AOD dataset. Compared to other methods, our approach achieved the highest detection accuracy. Furthermore, it reduced the number of parameters by 12.7% compared to YOLOv7-Tiny. The experimental results illustrated that our proposed method is more lightweight and exhibits superior detection accuracy compared to other lightweight models. [ABSTRACT FROM AUTHOR]

Background: In previous observational studies, food-derived antioxidant vitamins have been suggested to be associated with breast cancer. However, the findings were inconsistent and the causal relationship could not be clearly elucidated. To confirm the potential causal relationship between food-derived antioxidants (retinol, carotene, vitamin C and vitamin E) and the risk of breast cancer, we conducted a two-sample Mendelian randomization (MR) study. Methods: The instrumental variables (IVs) as proxies of genetic liability to food-derived antioxidant vitamins were obtained from the UK Biobank Database. We extracted breast cancer data (122,977 cases and 105,974 controls) from the Breast Cancer Consortium (BCAC). In addition, we studied estrogen expression status categorically, including estrogen receptor positive (ER+) breast cancer (69,501 cases and 105,974 controls) and versus estrogen receptor (ER−) negative breast cancer (21,468 cases and 105,974 controls). We performed two-sample Mendelian randomization study, and inverse variance–weighted (IVW) test was regarded as main analysis. Sensitivity analyses were further conducted to assess heterogeneity and horizontal pleiotropy. Results: The results of IVW showed that among the four food-derived antioxidants, only vitamin E had protective effect on the risk of overall breast cancer (OR = 0.837, 95% CI 0.757–0.926, P = 0.001) and ER+ breast cancer (OR = 0.823, 95% CI 0.693–0.977, P = 0.026). However, we found no association between food-derived vitamin E and ER− breast cancer. Conclusions: Our study suggested food-derived vitamin E can decrease the risk of breast cancer overall and ER+ breast cancer, and the robustness of our results was confirmed by sensitivity analyses. [ABSTRACT FROM AUTHOR]

Recently, non-magnetic carbon-based composite has been regarded as one of the most promising electromagnetic wave absorbing (EMWA) materials. How to realize high EMWA performances at ultra-thin matching thickness is a hot research topic. In this study, a strategy to construct three-dimensional (3D) porous BaTiO 3 @reduced graphene oxide (BTO@rGO) composite aerogel was performed by successively hydrothermal process, chemical reduction and freeze-drying. The results show that defect-rich BTO nanoparticles are dispersedly immobilized into 3D conductive rGO framework by a form of Ba2+ bonding to rGO, enhancing conduction loss and dipole polarization, which contributes to enhanced EMWA performance. As a result, a minimum reflection loss of −50.49 dB with a matching thickness of only 1.46 mm, along with an effective absorption bandwidth of 3.74 GHz (13.07 GHz–16.81 GHz) with a matching thickness of only 1.39 mm, is achieved for 3D porous BTO@rGO composite aerogel. Therefore, this study paves a way for designing and preparing excellent non-magnetic EMWA materials at ultra-thin matching thickness. [ABSTRACT FROM AUTHOR]

Gaussian graphical model is a strong tool for identifying interactions from metabolomics data based on conditional correlation. However, data may be collected from different stages or subgroups of subjects with heterogeneity or hierarchical structure. There are different integrating strategies of graphical models for multi-group data proposed by data scientists. It is challenging to select the methods for metabolism data analysis. This study aimed to evaluate the performance of several different integrating graphical models for multi-group data and provide support for the choice of strategy for similar characteristic data. We compared the performance of seven methods in estimating graph structures through simulation study. We also applied all the methods in breast cancer metabolomics data grouped by stages to illustrate the real data application. The method of Shaddox et al. achieved the highest average area under the receiver operating characteristic curve and area under the precision-recall curve across most scenarios, and it was the only approach with all indicators ranked at the top. Nevertheless, it also cost the most time in all settings. Stochastic search structure learning tends to result in estimates that focus on the precision of identified edges, while BEAM, hierarchical Bayesian approach and birth–death Markov chain Monte Carlo may identify more potential edges. In the real metabolomics data analysis from three stages of breast cancer patients, results were in line with that in simulation study. [ABSTRACT FROM AUTHOR]

Dielectric capacitors are fundamental energy storage components in electronics and electric power systems due to their unique ultrahigh power density. However, their relatively low energy storage density is a long‐standing challenge which greatly limits their practical application range. Chitosan (CS) and montmorillonite (MMT) are two kinds of materials that exist abundantly on the earth with natural surface charges. The positively charged CS and negatively charged MMT can be self‐assembled into the typical sandwich‐structured CS/MMT/CS 2D structure through an electrostatic attraction. Loading these surface‐charged sandwich‐structured nanosheets into poly(vinylidene fluoride)‐based composite with a weight fraction as tiny as 0.3 wt.%, an ultrahigh energy storage density of 32.5 J cm−3 accompanied with a high efficiency of 64% are concurrently achieved with a very low cost and scalable process. Guided by finite element simulation, it is revealed that a number of electric potential wells that exist in the charged sandwich nanosheets impede the acceleration of internal charges and hinder the growth of electrical trees. The results offer a novel paradigm for exploring ultrahigh energy storage density capacitors in an economical way. [ABSTRACT FROM AUTHOR]

Against the background of the ongoing atmospheric warming, the glacial lakes that are nourished and expanded in High Mountain Asia pose growing risks of glacial lake outburst floods (GLOFs) hazards and increasing threats to the downstream areas. Effectively extracting the area and consistently monitoring the dynamics of these lakes are of great significance in predicting and preventing GLOF events. To automatically extract the lake areas, many deep learning (DL) methods capable of capturing the multi-level features of lakes have been proposed in segmentation and classification tasks. However, the portability of these supervised DL methods need to be improved in order to be directly applied to different data sources, as they require laborious effort to collect the labeled lake masks. In this work, we proposed a simple glacial lake extraction model (SimGL) via weakly-supervised contrastive learning to extend and improve the extraction performances in cases that lack the labeled lake masks. In SimGL, a Siamese network was employed to learn similar objects by maximizing the similarity between the input image and its augmentations. Then, a simple Normalized Difference Water Index (NDWI) map was provided as the location cue instead of the labeled lake masks to constrain the model to capture the representations related to the glacial lakes and the segmentations to coincide with the true lake areas. Finally, the experimental results of the glacial lake extraction on the 1540 Landsat-8 image patches showed that our approach, SimGL, offers a competitive effort with some supervised methods (such as Random Forest) and outperforms other unsupervised image segmentation methods in cases that lack true image labels. [ABSTRACT FROM AUTHOR]

Summary: Cotton's fundamental requirements for long periods of growth and specific seasonal temperatures limit the global arable areas that can be utilized to cultivate cotton. This constraint can be alleviated by breeding for early‐maturing varieties. By delaying the sowing dates without impacting the boll‐opening time, early‐maturing varieties not only mitigate the yield losses brought on by unfavorable weathers in early spring and late autumn but also help reducing the competition between cotton and other crops for arable land, thereby optimizing the cropping system. This review presents studies and breeding efforts for early‐maturing cotton, which efficiently pyramid early maturity, high‐quality, multiresistance traits, and suitable plant architecture by leveraging pleiotropic genes. Attempts are also made to summarize our current understanding of the molecular mechanisms underlying early maturation, which involves many pathways such as epigenetic, circadian clock, and hormone signaling pathways. Moreover, new avenues and effective measures are proposed for fine‐scale breeding of early‐maturing crops to ensure the healthy development of the agricultural industry. [ABSTRACT FROM AUTHOR]

Aiming at the obstacle avoidance trajectory problem of robotic manipulators in operation space, a combinatorial optimisation solution of the obstacle avoidance path and near time-optimal trajectory planning is proposed. The robotic manipulator and the obstacles are modelled by a swept sphere volume (SSV) envelope and a capsule envelope, respectively. Based on the target offset and the target preference expansion strategy in the repulsion field, an improved RRT* algorithm is adopted to avoid collision to realise obstacle-free path planning at the end-effector level in Cartesian space and the link level in joint space. The thresholds of velocity, acceleration and jerk are set as constraints, and the interval time between nodes is optimised as position information of the improved whale optimisation algorithm. Near time-optimal trajectory planning of robotic manipulators with motion constraints is further completed. The IWOA obtains a high-quality initial population by covering the search space, and the population is updated by the thermal memory (TM) to improve individual quality. Thermal exchange optimisation (TEO) is applied to enhance the exploitation performance of IWOA, and the hierarchical structure strategy is introduced to explore potential optimal solutions. The simulation results show that the method limits the jerk of the robotic manipulator, ensures smooth movement and has higher obstacle avoidance ability and work efficiency than previous methods. [ABSTRACT FROM AUTHOR]

Registration of 3D spatial data and models is a fundamental task in applications such as mapping, positioning and virtual/augmented reality. Most of the existing 3D registration methods such as iterative closest point (ICP) and recent learning‐based methods are dedicated to point cloud registration, and rely heavily on point‐wise correspondences, which limits their ability to address registration problems across different data types. Since man‐made objects and buildings usually contain many planar surfaces, it is possible to use the planes for accurate registration of different data and models. In this paper, a unified registration framework is proposed consisting of a plane extraction module, which can extract planes from various forms of spatial data such as point clouds or surface‐based 3D models, and a registration module, which performs automatic registration based on the extracted planes. Tests show that the proposed method can handle small‐overlap registration across all these data types with high success rates. The result of point cloud registration also indicates that the method achieves better accuracy as compared to ICP. [ABSTRACT FROM AUTHOR]

Due to their feature of the conversion from electrical to mechanical energy under an applied electric field, dielectric elastomers (DEs) have been widely adopted in smart devices. However, the significant electro-actuated property of DEs is always obtained under a giant driving electric field, which raises a potential safety hazard and limits their practical application range. Moreover, the traditional strategy of regulating the flexibility of DEs via physical swelling effect would result in an undesired plasticizer leakage and an irreversible reduction in both electromechanical stability and lifetime. Herein, a typical heterogeneous multi-layered polydimethylsiloxane (PDMS)-based DE composite was prepared by solution blending and the layer-by-layer casting method. Through synchronously introducing the high-permittivity BaTiO3 and the plasticizer dimethyl silicone oil in the middle layer, both the dielectric and mechanical property of the composite are effectively regulated. Not only the interlayered mechanical mismatch is eliminated but also the problem of plasticizer leakage is optimized through this reasonable structural design. The maximum electro-actuated strain obtained in the sandwiched DE composite was as large as 24.25% under 60 V/μm, which is 338.52% higher than that of pristine PDMS. Furthermore, the composite exhibits the largest driving strain (58.31%) near its breakdown electric field of 77.82 V/μm. Therefore, this study provides a promising route for the preparation of advanced DE composite with an improved low-field electro-actuated property. [ABSTRACT FROM AUTHOR]

Background: It is well known that carbapenem-resistant Klebsiella pneumoniae (CRKP) has become a more problematic public health issue due to its widespread spread worldwide. In China, ST11-type CRKP is the most prevalent CRKP, but ST15-type CRKP, a recently prevalent high-risk clone, has emerged widely throughout China, posing a serious public health risk. Therefore, we conducted an epidemiological of an outbreak of ST15 CRKP of producing CTX-M-15, KPC-2 and SHV-106 in a tertiary hospital in Anhui, China, to Understanding the potential risks of the current STT15 CRKP outbreak. Results: From July 2021 to December 2021, 13 ST15 CRKP isolates were identified by collecting non-repeated clinical multidrug-resistant isolates, with all capsular typing of serotype KL19. All ST15 CRKP isolates were resistant to cephalosporins, carbapenems and quinolones, but were sensitive to amikacin, tigecycline and polymyxin B. In addition, isolates carried blaSHV−106 (100%), blaKPC−2 (69%), blaCTX−M−15 (69%), blaTEM−1B (69%), blaOXA−1 (62%) and blaLAP−2 (8%), as well as iron chelators (iutA, ybt, fyuA, ent, fepA, irp1, irp2, 100%) were detected. In phenotyping experiments, all ST15 CRKP exhibited lower growth rates than NTUH-K2044, and all ST15 CRKP did not exhibit mucoviscositty characteristics. However, in the Galleria mellonella infection model, isolates 21081212, 21081241 and 21091216 were more lethal than the hypervirulent isolates NTUH-K2044. Sequencing results showed that the genetic environment surrounding the genes blaSHV−106, blaKPC−2, blaCTX−M−15, blaOXA−1 and blaTEM−1B were all identical in the ST15 CRKP isolates. Phylogenetic analysis showed that 13 ST15 CRKP isolates were divided into three subgroups, and when placed in global analysis, 10 of them were highly homologous to isolates from Jiangsu, two were highly homologous to isolates from Zhejiang, and one was homologous to an isolate from an unlabelled region. Conclusion: Our research shows that ST15 CRKP, which carries multiple β-lactamases genes and siderophores-encoding genes, may be evolving to hypervirulence and may have spread widely in localised areas. Therefore, environmental surveillance and clinical infection control in hospitals should be strengthened to prevent further spread of ST15 CRKP. [ABSTRACT FROM AUTHOR]

In this article, a novel dual-rotor multiple-winding machine (DRMWM) is proposed for the continuous variable transmission (CVT) in hybrid electric vehicles (HEVs). First, a mathematical model of the proposed machine is constructed by using the harmonic modeling method. Then, on the basis of the magnetic field analysis, the operating principle of the DRMWM is deduced. By introducing multiple windings with two different working harmonics, namely the permanent magnet (PM) harmonics, and the magnetic gear harmonics, the proposed DRMWM can cope with various operating conditions of HEVs. To further obtain optimal performance, a finite-element analysis and multiobjective genetic algorithm II combined sequential optimization is carried out for the proposed DRMWM. The proposed optimization method is proven to be more computationally efficient compared to the global optimization method. Finally, a prototype is manufactured and tested in various operating modes. The results validate the simulation and analytical method predictions. Also, it proves that the proposed DRMWM is suitable to work as the CVT in HEVs. [ABSTRACT FROM AUTHOR]

The Bi 2 Sr 2 CaCu 2 O 8+ x (Bi-2212) material, a high-temperature superconductor, holds significant promise for future high-field applications because of its multifilamentary, twistable production capabilities, coupled with a high upper critical field. Bi-2212 round wire (RW) is made by the powder-in-tube (PIT) technique, and Bi-2212 coils are usually being developed using the wind-and-react method and a high temperature and over-pressure (OP) heat treatment (50 atm, 890℃) is then required to achieve the high current performance. However, over-pressure (OP) heat treatment can lead to a reduction in wire diameter, compromising the stability of the coil structure. Addressing this issue, the pre-overpressure (pre-OP) heat treatment is used and proves effective in mitigating the reduction in Bi-2212 wire diameter. In this paper, to comprehensively investigate the impact of pre-OP heat treatment on the microstructure of Bi-2212 wire, a metallographic analysis of two kinds of Bi-2212 wires was carried out by the scanning electron microscope (SEM) and the ImageJ software. It was found that larger-area filaments experienced a greater reduction in area after pre-OP heat treatment, that pre-OP heat treatment increases the aspect ratio of filaments, and polygonal bundle structure helps maintain filament structure stability during pre-OP heat treatment. Additionally, the impact of pre-OP heat treatment on the performance of Bi-2212 wires was analyzed through critical current testing under high fields. [ABSTRACT FROM AUTHOR]

Current label-free surface-enhanced Raman spectroscopy (SERS) assay for the detection and analysis of organophosphorus pesticides has achieved initial success, but the application still faces constraints of substrate portability and specificity. To this end, this paper demonstrates a method for portable, rapid, and specific detection of low concentrations of fenthion pesticides based on a solid substrate of gold nanoparticle monolayers combined with molecularly imprinted polymers (MIPs). The nano-monolayers were transferred to the surface of mercapto-silicon wafers by interfacial self-assembly technique to form a stable connection with S–Au bonds and, at the same time, prevent nanoparticles from dropping off during the surfactant removal process. Then, the fenthion MIPs were directly generated on the surface of the monolayer film by spin-coating with a pre-polymerization solution and ultraviolet-induced polymerization. Tests showed that the molecular imprint was able to accurately bind to fenthion, but not other molecules, in a mixture of structural analogs, achieving a low concentration detection of 10–8 mol/L. The composite substrate maintained a signal uniformity of a relative standard deviation (RSD)  =  7.05% and a batch-to-batch reproducibility of RSD  =  10.40%, making it a potential pathway for the extended application of SERS technology. [ABSTRACT FROM AUTHOR]

• Crystal plasticity finite element model exhibits higher accuracy in evaluation of surface roughness and thickness distribution of cups fabricated by micro deep drawing. • The magnitude of surface roughness S z is almost linearly dependent on the average grain size of austenitic stainless steel foils. • The brass components are beneficial to the formation of drawn cups with uniform thickness distribution and the absence of severe defects. The present work involves the numerical simulation and experimental study on the surface roughness evolution and heterogeneous plastic deformation (strain localization and concomitant surface morphology evolution) in grain scale of micro deep drawn parts of austenitic stainless steel (ASS) 304 foils. A three-dimensional modeling framework was used to simulate the micro deep drawing (MDD) process. The simulation involved the development of a Voronoi-based polycrystalline geometry model (VPGM), a multi-stress-strain response model, and a crystal plasticity finite element methods (CPFEM) model. The results indicate that CPFEM model exhibits higher accuracy in the localized stress and strain, thickness distribution fluctuation and surface roughness evolution of the fabricated parts compared to multi-stress-strain response model. Therefore, the plastic deformation heterogeneity in MDD is in-depth discussed based on CPFEM model. The results show that the coarse-grained foils correspond to the intense strain localization, which is the main cause of surface roughening. Considering the average grain size is close to the thickness of ASS foils, mounding features on the rough surface may readily develop further into potentially fractured sites during deformation. On the other hand, crystal orientation influence plastic deformation by affecting the slip behavior of materials. The effect of crystal orientations including {011} 〈211〉 (Brass), {011} 〈100〉 (Goss), and {112} 〈110〉 components on deformation is discussed. The results indicate a strong correlation between the magnitude of the Schmid's factor and the ease of deformation. Additionally, variations in Schmid's factor across different directions result in differences in deformation accumulation, which affects the thickness distribution along the radial direction and the distribution of earrings and wrinkles along the circumferential direction of the fabricated micro parts. [ABSTRACT FROM AUTHOR]

[Display omitted] • Classical trigeminal neuralgia is associated with altered structural connections between its cerebral cortex and thalamus. • Probabilistic fiber tracking can be used for thalamic subdivisions based on connectivity of fibers. • Individualized thalamic segmentation mapping helps provide clinical treatment targets. Classical trigeminal neuralgia (CTN) refers to episodic pain that is strictly confined to the trigeminal distribution area, and the thalamus is an important component of the trigeminal sensory pathway. Probabilistic tracking imaging algorithm was used to identify specific connections between the thalamus and the cortex, in order to identify structural changes in the thalamus of patients with CTN and perform thalamic segmentation. A total of 32 patients with CTN and 32 healthy controls underwent DTI-MRI scanning (3.0 T). Differences in fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) between the groups were studied. Correlation analysis was performed with clinical course and pain level. Compared to the healthy controls, patients in the CTN group had significantly reduced FA, increased AD, RD and MD in somatosensory subregion of the bilateral thalamus, increased RD in frontal subregion, increased RD and MD in motor subregion. Correlation analysis showed that patient history was positively correlated with pain grading, and that medical history was positively correlated with significantly reduced FA in somatosensory subregion, negatively correlated with increased RD and MD in motor subregion. We used DTI-based probabilistic fiber tracking to discover altered structural connectivity between the thalamus and cerebral cortex in patients with CTN and to obtain a thalamic segmentation atlas, which will help to further understand the pathophysiology of CTN and serve as a future reference for thalamic deep brain stimulation electrode implantation for the treatment of intractable pain. [ABSTRACT FROM AUTHOR]

The dielectric capacitors with high energy storage capability are demand for power electronic devices to keep pace with the development of the modern electronic and electrical industry. Although polymer-based dielectric composites showing the superiorities of ease processing, self-healing and low cost have a great potential in various applications, their energy storage capability is still severely limited by the negative coupling effect between dielectric permittivity and breakdown strength. In this study, we present a two-dimensional graphene oxide@silica core–shell nanoplatelets (GO@SiO2) constructed through the classical Stöber method. Moreover, a series of polyvinylidene fluoride (PVDF)/GO@SiO2/PVDF sandwich-structured composites were assembled layer-by-layer and obtained through combining the spray coating and solution casting procedures. The GO@SiO2 nanoplatelets were closely aligned and orientated along the direction that perpendicular to the electric field, forming the non-traditional inorganic middle layer. The thickness of the middle layer is dependent on the GO@SiO2 loading fraction, which directly influenced the overall dielectric and electrical performances of the sandwich-structured composites. An enhanced breakdown strength (~ 253 MV m−1) and discharged density (~ 5.19 J cm−3) can be obtained from the PVDF/GO@SiO2/PVDF composite filled with the GO@SiO2 loading fraction as small as 1.37 wt%, which are 23.4% and 161% higher than those of neat PVDF (~ 1.99 J cm−3 at 205 MV m−1), respectively. The improved energy storage capability could be attributed to the synergetic contribution of highly insulating SiO2 shell, the additional core–shell interfacial interaction, the orientation that perpendicular to electric field and the multilayered construction of composite. Thus, this research provides a promising approach for the design of advanced composites with an improved dielectric energy storage property. [ABSTRACT FROM AUTHOR]

At present, high-speed trains have become popular modern transportation. As a significant part of the high-speed train riding activity, the stowing and unloading luggage task has its characteristics. To comprehensively and reasonably evaluate passenger comfort of the stowing and unloading luggage task in high-speed trains. In this paper, passenger behavior characteristics are firstly analyzed by the author, the theoretical architecture of passenger comfort evaluation is constructed with the perspective of product aesthetics and ergonomics, and then the process of the passenger comfort evaluation is put forward. Secondly, a combination of Rough Number (RN) and Decision Making Trial and Evaluation Laboratory (DEMATEL) (i.e. R-DEMATEL) is utilized to solve the centrality degree of comfort influencing factors and determine comfort evaluation indexes. Furthermore, the passenger comfort evaluation model with Fuzzy Neural Network (FNN) is constructed and trained. After that, the sample data of the evaluation are collected through the simulated experiment of the stowing and unloading luggage task, and they are trained with FNN comparing to Back Propagation Neural Network (BPNN). Eventually, the result of examples testing is verified that the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The magnetic field calculation for axial flux motors (AFMs) is always intricate and time-consuming. To this end, a fast quasi-three-dimensional (3D) analytical model is proposed in this paper for magnetic field prediction in AFMs. The 3D magnetic field problem can be simplified into a two-dimensional (2D) one by dividing the AFM into several annular slices in the radial direction. Then, for the first time, the harmonic modeling method (HMM) in Cartesian coordinates is adopted to solve the magnetic field in these slices cut from the AFM. The corresponding electromagnetic parameters of the AFM can be acquired subsequently. The critical step for the field prediction of using HMM in Cartesian coordinates is to adopt a variable substitution method when solving the partial differential equations. Next, the magnetic saturation of soft-magnetic material within AFMs is considered by adopting an iterative approach. Ultimately, the effectiveness of the proposed quasi-3D analytical model is validated by the nonlinear finite element analysis (FEA). The proposed analytical model is computationally efficient, which makes it suitable for the preliminary design of AFMs. [ABSTRACT FROM AUTHOR]

Stem cells maintain adult tissue homeostasis under physiological conditions. Uncontrolled stem cell proliferation will lead to tumorigenesis. How stem cell proliferation is precisely controlled is still not fully understood. Phosphorylation of Yun is essential for ISC proliferation. Yun is essential for the proliferation of normal and transformed intestinal stem cells. Our mass spectrometry and biochemical data suggest that Yun can be phosphorylated at multiple residues in vivo. Interestingly, we show that the phosphorylation among these residues is likely interdependent. Furthermore, phosphorylation of each residue in Yun is important for its function in ISC proliferation regulation. Thus, our study unveils the important role of post‐translational modification of Yun in stem cell proliferation. [ABSTRACT FROM AUTHOR]

Pseudomonas aeruginosa is a significant opportunistic pathogen responsible for numerous human infections. Its high pathogenicity resides in a diverse array of virulence factors and an ability to adapt to hostile environments. We report that these factors are tied to the activity of condensins, SMC and MksBEF, which primarily function in structural chromosome maintenance. This study revealed that both proteins are required for P. aeruginosa virulence during corneal infection. The reduction in virulence was traced to broad changes in gene expression. Transcriptional signatures of smc and mksB mutants were largely dissimilar and non‐additive, with the double mutant displaying a distinct gene expression profile. Affected regulons included those responsible for lifestyle control, primary metabolism, surface adhesion and biofilm growth, iron and sulfur assimilation, and numerous virulence factors, including type 3 and type 6 secretion systems. The in vitro phenotypes of condensin mutants mirrored their transcriptional profiles and included impaired production and secretion of multiple virulence factors, growth deficiencies under nutrient limiting conditions, and altered c‐di‐GMP signaling. Notably, c‐di‐GMP mediated some but not all transcriptional responses of the mutants. Thus, condensins are integrated into the control of multiple genetic programs related to epigenetic and virulent behavior of P. aeruginosa. [ABSTRACT FROM AUTHOR]

Fault detection (FD) is important for health monitoring and safe operation of dynamical systems. Previous studies use model-based approaches which are sensitive to system specifics, attenuating the robustness. Data-driven methods have claimed accurate performances which scale well to different cases, but the algorithmic structures and enclosed operations are "black," jeopardizing its robustness. To address these issues, exemplifying the FD problem of aircraft air data sensors, we explore to develop a robust (accurate, scalable, explainable, and interpretable) FD scheme using a typical data-driven method, i.e., deep neural networks (DNN). To guarantee the scalability, aircraft inertial reference unit measurements are adopted as equivalent inputs to the DNN, and a database associated with 6 different aircraft/flight conditions is constructed. Convolutional neural networks (CNN) and long-short time memory (LSTM) blocks are used in the DNN scheme for accurate FD performances. To enhance robustness of the DNN, we also develop two new concepts: "large structure" which corresponds to the parameters that can be objectively optimized (e.g., CNN kernel size) via certain metrics (e.g., accuracy) and "small structure" that conveys subjective understanding of humans (e.g., class activation mapping in CNN) within a certain context (e.g., object detection). We illustrate the optimization process we adopted in devising the DNN large structure, which yields accurate (90%) and scalable (24 diverse cases) performances. We also interpret the DNN small structure via class activation mapping, which yields promising results and solidifies the robustness of DNN. Lessons and experiences we learned are also summarized in the paper, which we believe is instructive for addressing the FD problems in other similar fields. [ABSTRACT FROM AUTHOR]

Background: Studies have shown that the high incidence of type 2 diabetes in China is associated with low birth weight and excessive nutrition in adulthood, which occurred during the famine years of the 1950s and 1960s, though the specific molecular mechanisms are unclear. In this study, we proposed a severe maternal caloric restriction during late pregnancy, followed by a post weaning high-fat diet in mice. After weaning, normal and high-fat diets were provided to mice to simulate the dietary pattern of modern society. Methods: The pregnant mice were divided into two groups: normal birth weight (NBW) group and low birth weight (LBW) group. After 3 weeks for weaning, the male offspring mice in the NBW and LBW groups were then randomly divided into four subgroups: NC, NH, LC and LC groups. The offspring mice in the NC, NH, LC and LC groups were respectively fed with normal diet, normal diet, high-fat diet and high-fat diet for 18 weeks. After 18 weeks of dietary intervention, detailed analyses of mRNA and protein expression patterns, signaling pathway activities, and promoter methylation states were conducted for all relevant genes. Results: After dietary intervention for 18 weeks, the expressions of CD36, Fabp4, PPARγ, FAS, and ACC1 in the skeletal muscle tissue of the LH group were significantly increased compared with the LC and NH groups (P < 0.05). The level of p-AMPK/AMPK in the skeletal muscle tissue of the LH group was significantly decreased compared with the LC and NH groups (P < 0.05). CPT1 and PGC-1α protein expressions were up-regulated in the LH group (P < 0.05) compared to the LC group. Additionally, the DNA methylation levels of the PGC-1α and GLUT4 gene promoters in the skeletal muscle of the LH groups were higher than those of the LC and NH groups (P < 0.05). However, PPARγ DNA methylation level in the LH group was lower than those of the LC and NH groups (P < 0.05). Conclusions: LBW combined with high-fat diets may increase insulin resistance and diabetes through regulating the CD36-related Fabp4-PPARγ and AMPK/ACC signaling pathways. [ABSTRACT FROM AUTHOR]

In this article, a new compound consequent-pole double-rotor electric machine (CCPDRM) is proposed for hybrid propulsion system application. First, the operating principle and harmonic components in CCPDRMs are elucidated. The winding factor theory for conventional permanent magnet (PM) electric machines is further extended and applied in CCPDRMs. Then, this improved theory is adopted to investigate the structure and winding scheme requirement of the proposed CCPDRMs. In addition, the control strategy for the proposed CCPDRM is established. By utilizing a parameter sweep method, the variation trends of CCPDRMs’ torque density with respect to various geometrical parameters are revealed. Based on this, the structure of CCPDRMs is optimized to acquire a better electromagnetic performance. Next, the proposed CCPDRM is compared with a conventional compound bipolar double-rotor electric machine (CBDRM). It is found that the improved topology has a similar torque density but a much higher PM utilization factor and a lower PM demagnetization risk when compared with the CBDRM. Finally, a prototype is manufactured and tested in different operating modes. Furthermore, various mode-switching processes are performed to emulate the practical driving cycle of hybrid transportation. Both steady-state and dynamic mode-switching experimental results prove the effectiveness of CCPDRMs. [ABSTRACT FROM AUTHOR]

• Zr-based metallic glasses produced through atomic manufacturing exhibit remarkably enhanced thermal stability and crystallization resistance. • These atomically engineered metallic glasses display synergistically improved strength, hardness and plasticity compared to conventional processing. • Abundant medium range order induced during synthesis leads to concurrent enhancement across multiple properties. • Atomic manufacturing can modulate the energy state and properties of metallic glasses over a wider range than conventional melt-quenching methods. Atomic manufacturing is a new and attractive manufacturing method proposed to prepare metallic glasses (MGs). In this work, the mechanical and stability properties of Zr-based MGs manifested by atomic manufacturing method (pulsed laser deposition) and conventional quenching are investigated. Compared with MGs produced through conventional processing, our atomically engineered glassy state displays synergistically improved properties including strength, hardness and deformability alongside a substantially elevated crystallization resistance. Comprehensive characterization reveals that the concurrent enhancement of multiple properties originates from the abundance of medium-range-order woven into the glassy structure. This work presents an effective path to construct MGs with excellent properties through atomic manufacturing, thereby propelling novel perspectives on harnessing the intrinsically metastable nature of the glassy state for advanced material design. [ABSTRACT FROM AUTHOR]

In recent years, NIR-II-type fluorophores with emission wavelengths within the 1000–1700 nm range have garnered widespread attention in the field of bioimaging due to their high tissue penetration ability. Here, Mn-doped BaAl 2 O 4 , Ba 3 Al 2 O 6 , and Ba 7 Al 2 O 10 with NIR-II-type luminescence were synthesized by solid-phase or liquid-phase methods. Confirmed by XPS and EDS analysis, Mn is found uniformly distributed in the structure in the valence state of + 5. The optimal doping concentration of Mn5+ in the three matrices was analyzed by PLE and PL spectroscopy. In addition, the samples exhibit a wide excitation range spanning from 600 to 900 nm, coupled with a narrow emission band peaking between 1150 and 1200 nm. As both the excitation and emission wavelengths have excellent penetration capabilities in biological tissues, the synthesized fluorescent phosphors in this study hold potential for meaningful applications in the realm of fluorescence imaging. • Mn5+-doped Ba 3 Al 2 O 6 , BaAl 2 O 4 , and Ba 7 Al 2 O 10 phosphors were synthesized. • The emission wavelengths are between 1150 and 1200 nm, in the second near-infrared window. • The phosphors have potential in fluorescence imaging. [ABSTRACT FROM AUTHOR]