Layer-Dependent Superconductivity in Iron-Based Superconductors CsCa2Fe4As4F2 and CaKFe4As4.

In the quasi-two-dimensional superconductor NbSe2, the superconducting transition temperature (Tc) is layer-dependent, decreasing by about 60% in the monolayer limit. However, for the extremely anisotropic copper-based high-Tc superconductor Bi2Sr2CaCu2O8+δ (Bi-2212), the Tc of the monolayer is almost identical with that of its bulk counterpart. To clarify the effect of dimensionality on superconductivity, here, we successfully fabricate ultrathin flakes of iron-based high-Tc superconductors CsCa2Fe4As4F2 and CaKFe4As4. It is found that the Tc of monolayer CsCa2Fe4As4F2 (after tuning to the optimal doping by ionic liquid gating) is about 20% lower than that of the bulk crystal, while the Tc of three-layer CaKFe4As4 decreases by 46%, showing a more pronounced dimensional effect than that of CsCa2Fe4As4F2. By carefully examining their anisotropy and the c-axis coherence length, we reveal the general trend and empirical law of the layer-dependent superconductivity in these quasi-two-dimensional superconductors.

Blood MALT1 expression could help predict treatment outcomes in psoriasis patients, especially in those receiving biologics.

INTRODUCTION: Mucosa-associated lymphoid tissue 1 (MALT1) modulates T helper cell differentiation, pro-inflammatory cytokine production, and epidermal hyperplasia to participate in the pathology of psoriasis. This study aimed to explore the correlation of blood MALT1 with treatment outcomes in psoriasis patients. METHODS: MALT1 was detected in peripheral blood mononuclear cells by reverse transcription-quantitative polymerase chain reaction in 210 psoriasis patients before starting or converting to a new therapy, 50 disease controls, and 50 healthy controls. The psoriasis area severity index (PASI) score was evaluated at month (M)1, M3, and M6 in psoriasis patients. RESULTS: MALT1 was increased in psoriasis patients versus disease controls and healthy controls (both p < .001); and positively related to body mass index (p = .019) and PASI score (p < .001) in psoriasis patients. PASI75 rate at M1, M3, and M6 was 22.9%, 46.2%, and 71.0%, respectively; while PASI90 rate at M1, M3, and M6 was 3.8%, 29.0%, and 50.5%, respectively, in psoriasis patients. PASI75/90 rates at M1, M3, and M6 were increased in psoriasis patients receiving biologics versus those without (all p < .05). Pretreatment MALT1 was higher in psoriasis patients who achieved PASI75 (p = .001) and PASI90 (p < .001) at M6 compared to those who did not achieve that. Subgroup analyses discovered that pretreatment MALT1 had a stronger ability to predict PASI75 and 90 realizations in psoriasis patients receiving biologics (area under the curve [AUC]: 0.723 and 0.808) versus those without (AUC: 0.594 and 0.675). CONCLUSION: Blood MALT1 measurement may assist in predicting outcomes in psoriasis patients, especially in those receiving biologics.

Rebalanced Zero-Shot Learning.

Zero-shot learning (ZSL) aims to identify unseen classes with zero samples during training. Broadly speaking, present ZSL methods usually adopt class-level semantic labels and compare them with instance-level semantic predictions to infer unseen classes. However, we find that such existing models mostly produce imbalanced semantic predictions, i.e. these models could perform precisely for some semantics, but may not for others. To address the drawback, we aim to introduce an imbalanced learning framework into ZSL. However, we find that imbalanced ZSL has two unique challenges: (1) Its imbalanced predictions are highly correlated with the value of semantic labels rather than the number of samples as typically considered in the traditional imbalanced learning; (2) Different semantics follow quite different error distributions between classes. To mitigate these issues, we first formalize ZSL as an imbalanced regression problem which offers empirical evidences to interpret how semantic labels lead to imbalanced semantic predictions. We then propose a re-weighted loss termed Re-balanced Mean-Squared Error (ReMSE), which tracks the mean and variance of error distributions, thus ensuring rebalanced learning across classes. As a major contribution, we conduct a series of analyses showing that ReMSE is theoretically well established. Extensive experiments demonstrate that the proposed method effectively alleviates the imbalance in semantic prediction and outperforms many state-of-the-art ZSL methods.

Modulating Charge-Density Wave Order and Superconductivity from Two Alternative Stacked Monolayers in a Bulk 4Hb-TaSe2 Heterostructure via Pressure.

Two-dimensional (2D) van der Waals heterostructures (VDWHs) containing a charge-density wave (CDW) and superconductivity (SC) have revealed rich tunability in their properties, which provide a new route for optimizing their novel exotic states. The interaction between SC and CDW is critical to its properties; however, understanding this interaction within VDWHs is very limited. A comprehensive in situ study and theoretical calculation on bulk 4Hb-TaSe2 VDWHs consisting of alternately stacking 1T-TaSe2 and 1H-TaSe2 monolayers are investigated under high pressure. Surprisingly, the superconductivity competes with the intralayer and adjacent-layer CDW order in 4Hb-TaSe2, which results in substantially and continually boosted superconductivity under compression. Upon total suppression of the CDW, the superconductivity in the individual layers responds differently to the charge transfer. Our results provide an excellent method to efficiently tune the interplay between SC and CDW in VDWHs and a new avenue for designing materials with tailored properties.

Analysis of Prognostic Factors in Osteoporotic Patients Who Were Treated with Percutaneous Vertebroplasty for Refracture After Vertebral Augmentation.

OBJECTIVE: To retrospectively analyze prognostic factors in osteoporotic patients who treated with percutaneous vertebroplasty for refracture after vertebral augmentation. METHODS: A retrospective analysis was performed of 61 patients with refractures after vertebral augmentation who received percutaneous vertebroplasty treatment again from January 2019 to December 2021. Based on the presence of back pain at the last follow-up, 17 patients were placed in the pain group, and 44 patients were placed in the pain-free group. The following covariates were reviewed: age; bone mineral density; bone cement dosage; bone cement leakage; body mass index; and rate of anterior vertebral height (AVH) loss in the target before surgery, 1 week after surgery, and at last follow-up. Patients were assessed using visual analogue scale score and Oswestry Disability Index. RESULTS: Binary logistic regression analysis revealed that the rate of AVH loss after surgery was associated with postoperative back pain. According to the receiver operating characteristic curve analysis, the area under the curve of AVH loss rate at 1 week after surgery was 0.6845, and the cutoff value was 0.18; the area under the curve of AVH loss rate at the last follow-up was 0.7306, and the cutoff value was 0.2815. Kaplan-Meier survival analysis showed that patients with lower AVH loss rates had lower incidence of postoperative back pain and better prognosis. CONCLUSIONS: Occurrence of postoperative back pain was strongly associated with AVH loss after surgery. Patients with a lower rate of AVH loss had a lower incidence of postoperative back pain and a better prognosis.

[Serological Diagnosis and Clinical Data Analysis of Neonatal Alloimmune Thrombocytopenia].

OBJECTIVE: To investigate the pathogenesis and clinical diagnosis of fetal/neonatal alloimmune thrombocytopenia (FNAIT) and analyze the laboratory test results and clinical data related to the disease, so as to provide reference for clinical treatment and improvement of prognosis. METHODS: The clinical data of six neonatal patients with FNAIT in the Neonatology Department of our hospital from March 2017 to September 2020 were retrospectively analyzed, which included laboratory diagnosis, clinical symptoms, treatment, and prognosis. RESULTS: Among six patients, two cases occurred in the first pregnancy and four cases in the second pregnancy. The platelet count of six cases were decreased at admission or during hospitalization and maternal and neonatal serum autoimmune platelet antibody tests were positive. Five cases were accompanied by different degrees of skin and facial bleeding spots or petechiae and ecchymosis, intracranial hemorrhage. Four cases were treated with immunoglobulin and/or steroid hormone therapy (one of them received cross-matched platelets transfusion), while the symptoms of the other two cases improved spontaneously. Five cases recovered and were discharged from the hospital, while one case had not recovered but the family members requested to be discharged forwardly. Four cases were hospitalized within two weeks, but two cases were hospitalized for more than two weeks due to other diseases or factors (e.g., neonatal sepsis, neonatal enteritis, congenital heart disease, neonatal asphyxia, etc.). CONCLUSION: FNAIT is characterized by decreased platelet count, with or without bleeding symptoms, and may occur in the first and following pregnancy. FNAIT can recover spontaneously or have a good prognosis after treatment. However, the complication with other diseases or factors may affect the prognosis.

Stochastic Conjugate Gradient Algorithm With Variance Reduction.

Conjugate gradient (CG) methods are a class of important methods for solving linear equations and nonlinear optimization problems. In this paper, we propose a new stochastic CG algorithm with variance reduction1 and we prove its linear convergence with the Fletcher and Reeves method for strongly convex and smooth functions. We experimentally demonstrate that the CG with variance reduction algorithm converges faster than its counterparts for four learning models, which may be convex, nonconvex or nonsmooth. In addition, its area under the curve performance on six large-scale data sets is comparable to that of the LIBLINEAR solver for the L2 -regularized L2 -loss but with a significant improvement in computational efficiency.1CGVR algorithm is available on github: https://github.com/xbjin/cgvr.

Correction to: Graphical Representation and Similarity Analysis of DNA Sequences Based on Trigonometric Functions.

In the original publication of the article, the y axis labels present in Figs. 1a and 2a are incorrect. The correct Figs. 1a and 2a are provided here.

Graphical Representation and Similarity Analysis of DNA Sequences Based on Trigonometric Functions.

In this paper, we propose two four-base related 2D curves of DNA primary sequences (termed as F-B curves) and their corresponding single-base related 2D curves (termed as A-related, G-related, T-related and C-related curves). The constructions of these graphical curves are based on the assignments of individual base to four different sinusoidal (or tangent) functions; then by connecting all these points on these four sinusoidal (tangent) functions, we can get the F-B curves; similarly, by connecting the points on each of the four sinusoidal (tangent) functions, we get the single-base related 2D curves. The proposed 2D curves are all strictly non degenerate. Then, a 8-component characteristic vector is constructed to compare similarity among DNA sequences from different species based on a normalized geometrical centers of the proposed curves. As examples, we examine similarity among the coding sequences of the first exon of beta-globin gene from eleven species, similarity of cDNA sequences of beta-globin gene from eight species, and similarity of the whole mitochondrial genomes of 18 eutherian mammals. The experimental results well demonstrate the effectiveness of the proposed method.

Hierarchical Morphology-Dependent Gas-Sensing Performances of Three-Dimensional SnO2 Nanostructures.

Hierarchical morphology-dependent gas-sensing performances have been demonstrated for three-dimensional SnO2 nanostructures. First, hierarchical SnO2 nanostructures assembled with ultrathin shuttle-shaped nanosheets have been synthesized via a facile and one-step hydrothermal approach. Due to thermal instability of hierarchical nanosheets, they are gradually shrunk into cone-shaped nanostructures and finally deduced into rod-shaped ones under a thermal treatment. Given the intrinsic advantages of three-dimensional hierarchical nanostructures, their gas-sensing properties have been further explored. The results indicate that their sensing behaviors are greatly related with their hierarchical morphologies. Among the achieved hierarchical morphologies, three-dimensional cone-shaped hierarchical SnO2 nanostructures display the highest relative response up to about 175 toward 100 ppm of acetone as an example. Furthermore, they also exhibit good sensing responses toward other typical volatile organic compounds (VOCs). Microstructured analyses suggest that these results are mainly ascribed to the formation of more active surface defects and mismatches for the cone-shaped hierarchical nanostructures during the process of thermal recrystallization. Promisingly, this surface-engineering strategy can be extended to prepare other three-dimensional metal oxide hierarchical nanostructures with good gas-sensing performances.

Porous and single-crystalline ZnO nanobelts: fabrication with annealing precursor nanobelts, and gas-sensing and optoelectronic performance.

Porous and single-crystalline ZnO nanobelts have been prepared through annealing precursors of ZnSe · 0.5N2H4 well-defined and smooth nanobelts, which have been synthesized via a simple hydrothermal method. The composition and morphology evolutions with the calcination temperatures have been investigated in detail for as-prepared precursor nanobelts, suggesting that they can be easily transformed into ZnO nanobelts by preserving their initial morphology via calcination in air. In contrast, the obtained ZnO nanobelts are densely porous, owing to the thermal decomposition and oxidization of the precursor nanobelts. More importantly, the achieved porous ZnO nanobelts are single-crystalline, different from previously reported ones. Motivated by the intrinsic properties of the porous structure and good electronic transporting ability of single crystals, their gas-sensing performance has been further explored. It is demonstrated that porous ZnO single-crystalline nanobelts exhibit high response and repeatability toward volatile organic compounds, such as ethanol and acetone, with a short response/recovery time. Furthermore, their optoelectronic behaviors indicate that they can be promisingly employed to fabricate photoelectrochemical sensors.