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HfO2-based ferroelectric materials as the most promising candidate for the ferroelectric memories, have been widely studied for more than a decade due to their excellent ferroelectric properties and CMOS compatibility. In order to realize its industrialization as soon as possible, researchers have been devoted to improving the reliability performance, such as wake up, imprint, limited endurance, et al. Among them, the breakdown characteristic is one of main failure mechanisms of HfO2-based ferroelectric devices, which limits the write/read reliability of the devices. Based on this, we systematically studied the effect of thickness on the time-dependent dielectric breakdown (TDDB) tolerate capability of HfO2–ZrO2 (HZO) FE films under both forward and reverse electrical stress conditions. The thickness of HZO FE film ranged from 6 to 20 nm. Our findings reveal that decreasing the thickness of the HZO FE film leads to an improvement in TDDB tolerance capability which is attributed to the fact that higher density of oxygen vacancies in thinner HZO FE films can effectively inhibit the generation of new oxygen vacancies and the growth of conductive filaments, thus effectively improving the TDDB characteristics. These results provide a potential solution for mitigating breakdown characteristics of HfO2-based ferroelectric devices in memory applications. [ABSTRACT FROM AUTHOR]

Structural monitoring is crucial for assessing structural health, and high-precision deformation prediction can provide early warnings for safety monitoring. To address the issue of low prediction accuracy caused by the non-stationary and nonlinear characteristics of deformation sequences, this paper proposes a similarity clustering (SC) deformation prediction model based on GNSS/accelerometer time-frequency analysis. First, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm is used to decompose the original monitoring data, and the time-frequency characteristic correlations of the deformation data are established. Then, similarity clustering is conducted for the monitoring sub-sequences based on their frequency domain characteristics, and clustered sequences are combined subsequently. Finally, the Long Short-Term Memory (LSTM) model is used to separately predict GNSS displacement and acceleration with clustered time series, and the overall deformation displacement is reconstructed based on the predicted GNSS displacement and acceleration-derived displacement. A shake table simulation experiment was conducted to validate the feasibility and performance of the proposed CEEMDAN-SC-LSTM model. A duration of 5 s displacement prediction is analyzed after 153 s of monitoring data training. The results demonstrate that the root mean square error (RMSE) of predicted displacement is 0.011 m with the proposed model, which achieves an improvement of 64.45% and 61.51% in comparison to the CEEMDAN-LSTM and LSTM models, respectively. The acceleration predictions also show an improvement of 96.49% and 95.58%, respectively, the RMSE of the predicted acceleration-reconstructed displacement is less than 1 mm, with a reconstruction similarity of over 99%. The overall displacement reconstruction similarity can reach over 95%. [ABSTRACT FROM AUTHOR]

There is no ideal therapy for testicular damage induced by Cr(VI); however, bone marrow mesenchymal stem cells (BMSCs) transplantation may be a promising therapy. A Cr(VI) solution was administered to rats by intraperitoneal injection for 30 days, then BMSCs from donor rats were transplanted. Two weeks later, decreased activity and appetite, along with other pathological changes, were improved in the BMSCs group. The location of BMSCs in damaged testes was observed via laser confocal microscopy. Chromium content in the Cr(VI) and BMSCs groups significantly increased compared with that in the control group, but there was no significant difference between the two groups, as revealed by atomic absorption spectrometry. The ferrous iron and the total iron content of testes in the BMSCs group were significantly lower than those in the Cr(VI) group, as observed by Lillie staining and a tissue iron assay kit. Western blotting and immunohistochemical analyses revealed that the expression of Beclin 1, LC3B, 4‐hydroxynonenal, and transferrin receptor 1 was decreased in the BMSCs group, compared with the Cr(VI) group. The expression of glutathione peroxidase 4 (GPX4), SLC7A11, p‐AKT, mammalian target of rapamycin (mTOR), and p‐mTOR in the BMSCs group was higher than that in the Cr(VI) group. Taken together, we propose that BMSCs repair Cr(VI)‐damaged testes by alleviating ferroptosis and downregulating autophagy‐associated proteins through the upregulation of AKT and mTOR phosphorylation. [ABSTRACT FROM AUTHOR]

The problem of lower total-factor energy efficiency (TFEE) has become a bottleneck for economic growth, and how to break this bottleneck and achieve high-quality development is one of the urgent issues to be solved nowadays. The study selects 30 provincial units in mainland China during 13 years, from 2008 to 2020; then adopts slack-based measure (SBM) method to measure the TFEE values of each province; and on this basis, finally explores the impact of educational human capital and green finance on regional TFEE in China; It concludes as follows: (1) The average value of TFEE in China is 0.776, which is at a lower level, and TFEE shows a gradual increase during the study period; the mean value decreases from east to west in descending order. (2) Educational human capital's impact on the TFEE of the whole country and all regions is negative, and it does not show a significant U-shaped relationship; the effect of eastern region is the smallest; green finance's impact on TFEE shows a U-shaped relationship, except in eastern regions, where it is not significant; and the coefficient of the central region is stronger. (3) Environmental regulation's impact on TFEE show a U-shaped relationship in all regions; science and technology investment can improve TFEE all regions; and in the eastern region, it is most significant. Industrial structure is positively correlated with TFEE in all regions, and it has the most obvious effect on the improvement of TFEE in the central region; economic development can promote TFEE in all regions. This research has important theoretical implications for achieving regional TFEE improvement. [ABSTRACT FROM AUTHOR]

Developing semiconductor catalysts with high catalytic activity and good economic benefits is an important and challenging task in the field of photocatalysis. In this study, CdS nanosheets with a three-dimensional hollow structure were grown on MoS2 nanosheets by a hydrothermal method. The hydrogen production of the CdS@MoS2-25 wt% composites is 8.2 mmol in 3 h, which is 43.71 times that of pure CdS and 4.7 times that of Pt. Density functional theory (DFT) was used to further study the band structure of the composites. The experimental and calculation results show that the addition of co-catalyst MoS2 reduces the band gap of CdS and accelerates the transfer rate of photogenerated electrons. The construction of a n–n homogeneous structure reduces the interface transmission resistance of the carriers, and the photocatalytic performance of the composite material has been significantly improved. Therefore, the composite material is an excellent semiconductor photocatalyst that can replace precious metals in the reaction. In addition, after adding the promoter MoS2 to participate in the photocatalytic reaction for 12 h, the composite material still maintains high photocatalytic activity, and the recombination rate of photogenerated carriers is greatly reduced, which proves that the photocatalyst has good stability. [ABSTRACT FROM AUTHOR]

CdS is widely used in the field of photocatalysis owing to its excellent photocatalytic H2 evolution (PHE) activity, but the photocatalytic stability of CdS is inhibited because of the drawback of photocorrosion. Under light, the introduction of WS2 cocatalysts induces the growth of layered CdS on the WS2 nanosheets. Through the photocatalytic activity measurement, after adding ultrathin WS2 nanosheets, the amount of H2 released can reach 139.15 mmol g−1 after 7 h, which is 11.3 times higher than that of pure CdS nanoparticles. Furthermore, these composites illustrate excellent light absorption performance in the near-infrared region. A heterojunction is formed between WS2 and CdS under light, which greatly promotes the mobility of interface carriers and limits the recombination of photogenerated carriers. The hydrogen evolution output remains stable after 42 h, and the photocorrosion problem is effectively suppressed. In this work, we provide an effective and simple method to improve photocatalytic activity and stability, which is beneficial to the practical development of photocatalysis. [ABSTRACT FROM AUTHOR]

A series of full-scale self-propulsion simulations of a four-screw ship with different bracket installation angles using the Reynolds-averaged Navier–Stokes (RANS) method were conducted. The effects of the bracket installation angle on the propeller wake field and propulsion performance were investigated and studied. The result shows that the nominal wake low-speed region generated by the shedding vortex moved inward with the bracket angle increased. When the bracket angle turns inward 3 ° , the effect of shedding vortex almost disappeared in the outer propeller disc. The outer propeller shows a significant increase in thrust and torque, and the time-average load difference between inner and outer propeller drops to below 5 %. The research conducted in this paper fills a gap in the study of full-scale four-screw ship appendages. The design method for determining the bracket installation angle by inflow direction is of practical significance to the design of four-screw ships. • The wake field and propeller performance in a four-screw ship with different bracket installation angles is studied. • Full-scale simulations are conducted to avoid scale effect. • Two sets of comparisons are focused: the inner and outer propeller, and the comparison of different bracket angles. • The inner bracket angle should be greater than that of the outer bracket to achieve the better inner propeller efficiency. [ABSTRACT FROM AUTHOR]

Highlights • This work represents our original findings demonstrating that iTregs isolated from Young-mice exhibited stronger immunosuppressive ability in vitro and had a greater response during IRI in vivo. Our results showed that Young-mice were less susceptible to IRI as a result of having iTregs with stronger immune suppressive ability in vitro and in vivo. • Adoptive transfer of iTregs ameliorated liver IRI and promoted liver recovery with decreased levels of interferon-γ (IFN-γ) and interleukin-17 (IL-17). • Our findings suggest that the exacerbated IRI observed in aged-mice is a result of decreased iTreg function while Young-mice have an increased tolerance to IRI resulting from iTreg protection in the liver following injury. • Improving iTreg function is important for disease treatment in elder patients.This mechanism of how age affects function and induction of iTregs may be beneficial in utilizing iTreg-related immune therapy. Abstract Previous studies demonstrate that the number of induced regulatory T cells (iTregs) increases in aged mice. However, these studies do not characterize iTregs across different ages or how these immune modulators contribute to the dysregulation of immunity in murine disease models. Therefore, this study aimed to examine the relationship between age and iTreg function using a mouse model of hepatic ischemia-reperfusion injury (IRI). In this model, aged-mice suffered more serious injury than Young-mice, with higher serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) and higher histological scores from liver biopsies. iTregs isolated from Young-mice exhibited stronger immunosuppressive ability in vitro and had a greater response during IRI in vivo. In addition, aged-mice that were pretreated with iTregs generated in Young-mice (Y-iTregs) had alleviated injury compared with mice pretreated with iTregs from aged-mice (A-iTregs) or no treatment group. Adoptive transfer of iTregs ameliorated liver IRI and promoted liver recovery with decreased levels of interferon-γ (IFN-γ) and interleukin-17 (IL-17). These results demonstrate that the exacerbated IRI observed in aged-mice is a result of decreased iTreg function. Therefore, improving iTreg function is important for disease treatment in elder patients. [ABSTRACT FROM AUTHOR]

Herpes zoster remains an important global health issue and mainly occurs in aged and immunocompromised individuals with an early exposure history to Varicella Zoster Virus (VZV). Although the licensed vaccine Shingrix has remarkably high efficacy, undesired reactogenicity and increasing global demand causing vaccine shortage urged the development of improved or novel VZV vaccines. In this study, we developed a novel VZV mRNA vaccine candidate (named as ZOSAL) containing sequence-optimized mRNAs encoding full-length glycoprotein E encapsulated in an ionizable lipid nanoparticle. In mice and rhesus macaques, ZOSAL demonstrated superior immunogenicity and safety in multiple aspects over Shingrix, especially in the induction of strong T-cell immunity. Transcriptomic analysis revealed that both ZOSAL and Shingrix could robustly activate innate immune compartments, especially Type-I IFN signalling and antigen processing/presentation. Multivariate correlation analysis further identified several early factors of innate compartments that can predict the magnitude of T-cell responses, which further increased our understanding of the mode of action of two different VZV vaccine modalities. Collectively, our data demonstrated the superiority of VZV mRNA vaccine over licensed subunit vaccine. The mRNA platform therefore holds prospects for further investigations in next-generation VZV vaccine development.

HfO 2 -based ferroelectric materials as the most promising candidate for the ferroelectric memories, have been widely studied for more than a decade due to their excellent ferroelectric properties and CMOS compatibility. In order to realize its industrialization as soon as possible, researchers have been devoted to improving the reliability performance, such as wake up, imprint, limited endurance, et al. Among them, the breakdown characteristic is one of main failure mechanisms of HfO 2 -based ferroelectric devices, which limits the write/read reliability of the devices. Based on this, we systematically studied the effect of thickness on the time-dependent dielectric breakdown (TDDB) tolerate capability of HfO 2 -ZrO 2 (HZO) FE films under both forward and reverse electrical stress conditions. The thickness of HZO FE film ranged from 6 to 20 nm. Our findings reveal that decreasing the thickness of the HZO FE film leads to an improvement in TDDB tolerance capability which is attributed to the fact that higher density of oxygen vacancies in thinner HZO FE films can effectively inhibit the generation of new oxygen vacancies and the growth of conductive filaments, thus effectively improving the TDDB characteristics. These results provide a potential solution for mitigating breakdown characteristics of HfO 2 -based ferroelectric devices in memory applications., (© 2024 IOP Publishing Ltd.)

To improve the uncertainty quantification of variance networks, we propose a novel tree-structured local neural network model that partitions the feature space into multiple regions based on uncertainty heterogeneity. A tree is built upon giving the training data, whose leaf nodes represent different regions where region-specific neural networks are trained to predict both the mean and the variance for quantifying uncertainty. The proposed uncertainty-splitting neural regression tree (USNRT) employs novel splitting criteria. At each node, a neural network is trained on the full data first, and a statistical test for the residuals is conducted to find the best split, corresponding to the two subregions with the most significant uncertainty heterogeneity between them. USNRT is computationally friendly, because very few leaf nodes are sufficient and pruning is unnecessary. Furthermore, an ensemble version can be easily constructed to estimate the total uncertainty, including the aleatory and epistemic. On extensive UCI datasets, USNRT or its ensemble shows superior performance compared to some recent popular methods for quantifying uncertainty with variances. Through comprehensive visualization and analysis, we uncover how USNRT works and show its merits, revealing that uncertainty heterogeneity does exist in many datasets and can be learned by USNRT.

Active domain adaptation (ADA), which enormously improves the performance of unsupervised domain adaptation (UDA) at the expense of annotating limited target data, has attracted a surge of interest. However, in real-world applications, the source data in conventional ADA are not always accessible due to data privacy and security issues. To alleviate this dilemma, we introduce a more practical and challenging setting, dubbed as source-free ADA (SFADA), where one can select a small quota of target samples for label query to assist the model learning, but labeled source data are unavailable. Therefore, how to query the most informative target samples and mitigate the domain gap without the aid of source data are two key challenges in SFADA. To address SFADA, we propose a unified method SQAdapt via augmentation-based Sample Query and progressive model Adaptation. In specific, an active selection module (ASM) is built for target label query, which exploits data augmentation to select the most informative target samples with high predictive sensitivity and uncertainty. Then, we further introduce a classifier adaptation module (CAM) to leverage both the labeled and unlabeled target data for progressively calibrating the classifier weights. Meanwhile, the source-like target samples with low selection scores are taken as source surrogates to realize the distribution alignment in the source-free scenario by the proposed distribution alignment module (DAM). Moreover, as a general active label query method, SQAdapt can be easily integrated into other source-free UDA (SFUDA) methods, and improve their performance. Comprehensive experiments on multiple benchmarks have shown that SQAdapt can achieve superior performance and even surpass most of the ADA methods.

We propose a novel, succinct, and effective approach for distribution prediction to quantify uncertainty in machine learning. It incorporates adaptively flexible distribution prediction of [Formula: see text] in regression tasks. This conditional distribution's quantiles of probability levels spreading the interval (0,1) are boosted by additive models which are designed by us with intuitions and interpretability. We seek an adaptive balance between the structural integrity and the flexibility for [Formula: see text], while Gaussian assumption results in a lack of flexibility for real data and highly flexible approaches (e.g., estimating the quantiles separately without a distribution structure) inevitably have drawbacks and may not lead to good generalization. This ensemble multi-quantiles approach called EMQ proposed by us is totally data-driven, and can gradually depart from Gaussian and discover the optimal conditional distribution in the boosting. On extensive regression tasks from UCI datasets, we show that EMQ achieves state-of-the-art performance comparing to many recent uncertainty quantification methods. Visualization results further illustrate the necessity and the merits of such an ensemble model.

Recent years have seen remarkable progress of learning-based methods on Ultrasound Thyroid Nodules segmentation. However, with very limited annotations, the multi-site training data from different domains makes the task remain challenging. Due to domain shift, the existing methods cannot be well generalized to the out-of-set data, which limits the practical application of deep learning in the field of medical imaging. In this work, we propose an effective domain adaptation framework which consists of a bidirectional image translation module and two symmetrical image segmentation modules. The framework improves the generalization ability of deep neural networks in medical image segmentation. The image translation module conducts the mutual conversion between the source domain and the target domain, while the symmetrical image segmentation modules perform image segmentation tasks in both domains. Besides, we utilize adversarial constraint to further bridge the domain gap in feature space. Meanwhile, a consistency loss is also utilized to make the training process more stable and efficient. Experiments on a multi-site ultrasound thyroid nodule dataset achieve 96.22% for PA and 87.06% for DSC in average, demonstrating that our method performs competitively in cross-domain generalization ability with state-of-the-art segmentation methods., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ma, Li, Zou, Fan and Wu.)

Background: There have been lingering controversies reported decompression and plus fusion. And the relative safety of fusion in addition to standard decompression remains unclear. This study aimed to assess the effectiveness and safety of decompression alone or combined with fusion in lumbar spinal stenosis (LSS) with degenerative spondylolisthesis (DS)., Methods: In this systematic review and meta-analysis, we searched the databases of PubMed, Embase, Cochrane Library, and Web of Science for relevant literature from their inception to 28th December 2021. We identified the eligible studies based on the PICOS principles, populations (LSS with DS), interventions (decompression alone), controls (decompression combined with fusion), outcomes [overall reoperation rate, complications, Oswestry Disability Index (ODI), operative time, the amount of blood lost, length of stay (LOS), and visual analog scales (VAS)], study design (cohort studies). Quality assessment for individual study was performed with the Newcastle-Ottawa Scale (NOS)., Results: In all, 12 articles involving a total of 14,693 patients were finally included in the study, the majority of patients underwent decompression alone (DA group: n=11,598) and the rest underwent decompression associated with fusion (FU group: n=3,095). The quality of most of the included studies was regarded as high quality. The results indicated that the FU group had a higher rate of complication [relative risk (RR): 1.770, 95% confidence interval (CI): 1.485 to 2.110], longer operative time [weighted mean difference (WMD): 51.037, 95% CI: 13.743 to 88.330], and increased blood loss (WMD: 258.354, 95% CI: 150.468 to 366.239) than the DA group (all P<0.05), with no significant differences for overall reoperation rate (RR: 0.879, 95% CI: 0.432 to 1.786), ODI (WMD: -2.569, 95% CI: -6.548 to 1.409), LOS (WMD: 3.838, 95% CI: -2.172 to 9.848), and VAS found between the two groups (P>0.05)., Conclusions: In patients with LSS + DS, the effectiveness and safety of decompression alone may be superior to decompression plus fusion in terms of complication rate, operative time, and the amount of bleeding. However, more high-quality literature is needed in the future to confirm the best treatment choice for patients with LSS + DS., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-22-2208/coif). The authors have no conflicts of interest to declare., (2022 Annals of Translational Medicine. All rights reserved.)

The successful preparation and application of graphene shows that it is feasible for the materials with a thickness of a single atom or few atomic layers to exist stably in nature. These materials can exhibit unusual physical and chemical properties due to their special dimension effects. At present, researchers have made great achievements in the preparation, characterization, modification, and theoretical research of 2D materials. Because the structure of 2D materials is often similar, it has a certain degree of qualitative versatility. Besides, 2D materials often carry good catalytic performance on account of their more active sites and adjustable harmonic electronic structure. In this review, taking 2D materials as examples [graphene, boron nitride (h-BN), transition metal sulfide and so on], we review the crystal structure and preparation methods of these materials in recent years, focus on their photocatalyst properties (carbon dioxide reduction and hydrogen production), and discuss their applications and development prospects in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Hao, Zhao, Cheng, Xing, Ma, Wang, Zhao and Xu.)