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In recent years and especially after the world pandemic COVID-19, the tourism sector is undergoing great changes as a result of travelers looking for unique and outdoor products to enjoy different experiences, involving new trends in tourism, especially in non-traditional destinations, and changing the needs and attitudes of tourists. In this sense, the tourist is currently more and more motivated by sensations in the search for new experiences. In this context, in which the experience is a fundamental objective, some tourist modalities such as wine tourism, already emerge as practices aimed at satisfying the new demand after the 1990s world widely. Nevertheless, this paper is present the current Chinese tourist flows after the pandemic and their relevant motivations in the growing demand for slow tourism, breaking the traditional stereotype of what we think are their demands, and presenting the possibility of wine tourism in small and middle-scale places like Priorat of Catalunya and Ribeira Sacra of Galicia, both situated in Spain. The main objective of this study is to research the development of a friendly campestre and natural wine and food local supplies, their interesting up-downs historic paths, their impressive "heroic" geographic sceneries such as the big contrast of mountains against rivers in these two still developing their international names wine regions of Spain: Priorat and Ribeira Sacra, also analyzing the high acquisitive power and potential demands of wine tourism for Chinese outbound tourists for this two regions, to identify the adjustments that must be made in the plannings and applications in these two specific wine regions, and serving as examples for others still not well known international wine regions to be developed for Chinese tourists or even Asian tourists for Europe and the rest of the world.

Taking long-term spectral and temporal dependencies into account is essential for automatic piano transcription. This is especially helpful when determining the precise onset and offset for each note in the polyphonic piano content. In this case, we may rely on the capability of self-attention mechanism in Transformers to capture these long-term dependencies in the frequency and time axes. In this work, we propose hFT-Transformer, which is an automatic music transcription method that uses a two-level hierarchical frequency-time Transformer architecture. The first hierarchy includes a convolutional block in the time axis, a Transformer encoder in the frequency axis, and a Transformer decoder that converts the dimension in the frequency axis. The output is then fed into the second hierarchy which consists of another Transformer encoder in the time axis. We evaluated our method with the widely used MAPS and MAESTRO v3.0.0 datasets, and it demonstrated state-of-the-art performance on all the F1-scores of the metrics among Frame, Note, Note with Offset, and Note with Offset and Velocity estimations., 8 pages, 6 figures, to be published in ISMIR2023

Partial discharge (PD) online monitoring is an essential part of transformer insulation condition based maintenance and prognostics and health management (CBM/PHM) in industrial power system. In order to realize online localization of multiple PD sources conveniently, an approach that uses single-channel mixed acoustic emission (AE) signal is proposed in this paper. First, the combined method based on the singular spectrum analysis and the independent component analysis is used to calculate the number of PD sources and realize the separation of mixed AE signals. Next, a difference selection algorithm is proposed to solve the problem that the inherent disorder of signal blind source separation makes the time difference of arrival technology difficult to localize the multiple PD sources directly. Then, the simulation signals and measured signals have verified that the signal separation effect of the proposed single-channel-based method is no less than that of the multi-channel-based method. Finally, the proposed approach is applied to a transformer. The disordered separated signals were successfully grouped to realize multi-source PD localization.

Background and aimsDietary factors play an important role in the development of chronic kidney disease (CKD). However, evidence on the relationship of beans consumption with CKD remains limited and inconclusive, especially in the middle-and low-income populations. The current study aimed to investigate the relationships of beans intake with indicators of kidney injury and CKD prevalence in rural adults.MethodsA total of 20,733 rural adults from the Henan Rural Cohort Study in 2018–2022 were included. The total beans intake was collected using a validated food frequency questionnaire. Indicators of kidney injury and CKD was determined by the estimated glomerular filtration rate and the urinary albumin to creatinine ratio. Generalized linear regression and logistic regression models were applied to estimate the relationship of beans intake with continuous and dichotomized indicators of renal function, respectively.ResultsOf the 20,733 participants, 2,676 (12.91%) subjects were identified as CKD patients. After adjusting for potential confounders, participants in the higher quartiles of beans intake had a lower prevalence of CKD (odds ratio and 95% confidence interval, OR (95%CI); Q2: 0.968(0.866–1.082); Q3: 0.836(0.744–0.939); Q4: 0.854(0.751–0.970)) and albuminuria (Q2: 0.982(0.875–1.102); Q3: 0.846(0.750–0.954); Q4: 0.852 (0.746–0.973)), compared with the Q1. Per 50 g/day increment in beans intake was significantly associated with a 5 and 4% decreased prevalence of albuminuria and CKD, respectively. These inverse relationships were also significant in the subgroups of men, elder, and high-income participants (p ConclusionDietary beans intake was inversely associated with the prevalence of albuminuria and CKD in rural adults, suggesting that promoting soy food intake might help reduce the occurrence of CKD in rural adults.

Transforming raw EHR data into machine learning model-ready inputs requires considerable effort. One widely used EHR database is Medical Information Mart for Intensive Care (MIMIC). Prior work on MIMIC-III cannot query the updated and improved MIMIC-IV version. Besides, the need to use multicenter datasets further highlights the challenge of EHR data extraction. Therefore, we developed an extraction pipeline that works on both MIMIC-IV and eICU Collaborative Research Database and allows for model cross validation using these 2 databases. Under the default choices, the pipeline extracted 38766 and 126448 ICU records for MIMIC-IV and eICU, respectively. Using the extracted time-dependent variables, we compared the Area Under the Curve (AUC) performance with prior works on clinically relevant tasks such as in-hospital mortality prediction. METRE achieved comparable performance with AUC 0.723- 0.888 across all tasks. Additionally, when we evaluated the model directly on MIMIC-IV data using a model trained on eICU, we observed that the AUC change can be as small as +0.019 or -0.015. Our open-source pipeline transforms MIMIC-IV and eICU into structured data frames and allows researchers to perform model training and testing using data collected from different institutions, which is of critical importance for model deployment under clinical contexts.

Deep learning models have demonstrated great potential in medical 3D imaging, but their development is limited by the expensive, large volume of annotated data required. Active learning (AL) addresses this by training a model on a subset of the most informative data samples without compromising performance. We compared different AL strategies and propose a framework that minimizes the amount of data needed for state-of-the-art performance. 638 multi-institutional brain tumor MRI images were used to train a 3D U-net model and compare AL strategies. We investigated uncertainty sampling, annotation redundancy restriction, and initial dataset selection techniques. Uncertainty estimation techniques including Bayesian estimation with dropout, bootstrapping, and margins sampling were compared to random query. Strategies to avoid annotation redundancy by removing similar images within the to-be-annotated subset were considered as well. We determined the minimum amount of data necessary to achieve similar performance to the model trained on the full dataset ({\alpha} = 0.1). A variance-based selection strategy using radiomics to identify the initial training dataset is also proposed. Bayesian approximation with dropout at training and testing showed similar results to that of the full data model with less than 20% of the training data (p=0.293) compared to random query achieving similar performance at 56.5% of the training data (p=0.814). Annotation redundancy restriction techniques achieved state-of-the-art performance at approximately 40%-50% of the training data. Radiomics dataset initialization had higher Dice with initial dataset sizes of 20 and 80 images, but improvements were not significant. In conclusion, we investigated various AL strategies with dropout uncertainty estimation achieving state-of-the-art performance with the least annotated data., Comment: 22 pages, 3 figures, 3 tables, 1 supplementary data document. Submitted to Medical Physics in Jan 2023

PurposeThoracolumbar fracture is one of the most common fractures of spine. And short-segment posterior fixation including the fractured vertebra (SSPFI) is usually used for the surgical treatment of it. However, the outcomes of SSPFI for different types of thoracolumbar fractures are not clear, and whether it is necessary to perform transpedicular bone grafting is still controversial. This study was conducted to determine the clinical efficacy of SSPFI for the treatment of different types of single-level thoracolumbar fracture, and make clear what kind of fractures need transpedicular bone grafting during the surgery.MethodsPatients with single-level thoracolumbar fracture undergoing SSPFI surgery between January 2013 and June 2020 were included in this study. The operative duration, intraoperative blood loss, anterior vertebral height ratio (AVHR) and anterior vertebral height compressive ratio (AVHC) of the fractured vertebra, local kyphotic Cobb angle (LKA), vertebral wedge angle (VWA) and correction loss during follow up period were recorded. Outcomes between unilateral and bilateral pedicle screw fixation for fractured vertebra, between SSPFI with and without transpedicular bone grafting (TBG), and among different compressive degrees of fractured vertebrae were compared, respectively.ResultsA total of 161 patients were included in this study. All the patients were followed up, and the mean follow-upped duration was 25.2 ± 3.1 months (6–52 months). At the final follow-up, the AVHR was greater, and the LKA and VWA were smaller in patients with bilateral fixation (6-screw fixation) than those with unilateral fixation (5-screw fixation) of AO type A3/A4 fractures (P 50% (P 50%, the correction loss in patients with TBG were less than those without TBG at the final follow-up (P ConclusionsSSPFI using bilateral fixation was more effective than unilateral fixation in maintaining the fractured vertebral height for AO type A3/A4 fractures. For patients with AVHC >50%, the loss of correction was more obvious and it can be decreased by transpedicular bone grafting.

Nonlinearity has enabled energy harvesting to advance towards higher power output and broader bandwidth in monostable, bistable, and multistable systems. However, challenges in operating in the high energy orbit (HEO) rather than low energy orbit (LEO) have restricted their applications. Based on a monostable nonlinear system, this paper proposes a self-contained solution for time-sharing orbit jump and energy harvesting. The joint dynamics of an electromechanical assembly consisting of a nonlinear energy harvester and a switch-mode piezoelectric interface circuit is studied for high-capability energy harvesting. The proposed solution is carried out by utilizing a cutting-edge switch-mode bidirectional energy conversion circuit (BECC), which enables time-sharing dual functions of energy harvesting and vibration exciting. A theoretical model is established based on impedance analysis and multiple time scales method to analyze the stability, frequency response, and phase evolution of the autonomous and nonautonomous nonlinear energy harvesting systems. Particularly, the detailed dynamics for the orbit jumps with vibration exciting mode of BECC are studied. Experiments are performed to validate the full-range orbit jumps with the monostable nonlinear energy harvester. The harvested power after orbit jumps yields a nine-fold increase, compensating for the energy consumption under vibration exciting mode quickly. The proposed solution also refrains the system from extra mechanical or electrical energy sources for orbit jumps, which leads to the first self-contained solution for simultaneous energy harvesting and orbit jump in nonlinear piezoelectric energy harvesting. This work enhances the practical utility of nonlinear energy harvesting technologies toward engineering applications.

Supplementary Material 2

Supplementary Material 1

Additional file 1. Supplemental information on training of the automatic segmentaion model and extraction of radiomic features.

Oil-impregnated paper (OIP) bushing is essential equipment in traction power supply systems, and its moisture status is directly related to the power transmission of high-speed railway. Also, the moisture distribution in the OIP bushing insulation is usually nonuniform. The frequency-domain dielectric spectroscopy (FDS) method is now widely accepted as the most potential method for evaluating the moisture status of the OIP traction bushing with nonuniform moisture distribution. However, as far as the FDS curve reconstruction of field bushing is concerned, it remains a challenge. In this article, based on the extended Debye model, a new curve reconstruction method (including equivalent circuit and mathematical models) of the bushing dielectric response is proposed. Then, the reconstruction method is converted into a mathematical problem of programming optimization. Based on the advantages of metaheuristic algorithms such as simplicity, flexibility, derivative-free mechanism, and local optimal avoidance, an improved metaheuristic algorithm was used to address the optimization problem. Finally, the proposed method was tested on bushing samples and real bushings. The research shows that the proposed method of curve reconstruction can well characterize the FDS curves of the traction bushing insulation with the nonuniform moisture distribution.

Natural gas loss inevitably occurs during gas injection and production operation in underground gas storage. At present, the study of gas loss is only in the qualitative description stage and cannot meet the quantitative evaluation requirements for economical gas storage. Combining the theory of inventory analysis and the experimental study of the injection-production mechanism and aimed at the phenomena of microseepage, dissolution diffusion, abnormal gas leakage and macroscale gas leakage in the process of injection and production of underground natural gas storage, gas loss evaluation mathematical models are established to quantitatively evaluate the gas loss of underground natural gas storage. The results show that the gas loss in the macrodisplacement process is the main component of geological gas loss in gas storage, which decreases with increasing injection-production cycles. On this basis, a quantitative evaluation method for the natural gas loss of gas reservoir-type gas storage is established, and the accuracy and reliability of the method are verified by the gas loss calculation results of the Banzhongnanbei (BZNB) underground natural gas storage. The validation results show that the calculation error is very small, meeting the requirements of gas storage operation accuracy and providing high application value. This calculation method can effectively reduce the loss of natural gas in gas storage, provide an early warning of leakage risk, and improve the economic benefits and injection-production safety of gas storage.

Traction transformers are one of the most important equipment in the traction power supply system. Thermal aging of transformer insulation system determines its reliable life. To achieve an estimation of the insulation life of traction power transformers operated under real load condition, the effects of traction loads on the thermal aging of oil-paper insulation in traction transformers were investigated. First, the design principles for the accelerated thermal aging experiment were studied and proposed by considering magnitude (i.e., load rate) and frequency (i.e. spare time and lasting time) of the traction load. Then, an experimental system was established in the laboratory to conduct extensive accelerated thermal aging experiments, in which the traction loads were mimicked by using positive temperature coefficient (PTC) heating plates and a programmable logic controller (PLC). Finally, the experimental results were analyzed and discussed to reveal the effects of traction load on the thermal aging of oil-paper insulation in traction transformers.

Despite the huge advancement in knowledge discovery and data mining techniques, the X-ray diffraction (XRD) analysis process has mostly remained untouched and still involves manual investigation, comparison, and verification. Due to the large volume of XRD samples from high-throughput XRD experiments, it has become impossible for domain scientists to process them manually. Recently, they have started leveraging standard clustering techniques, to reduce the XRD pattern representations requiring manual efforts for labeling and verification. Nevertheless, these standard clustering techniques do not handle problem-specific aspects such as peak shifting, adjacent peaks, background noise, and mixed phases; hence, resulting in incorrect composition-phase diagrams that complicate further steps. Here, we leverage data mining techniques along with domain expertise to handle these issues. In this paper, we introduce an incremental phase mapping approach based on binary peak representations using a new threshold based fuzzy dissimilarity measure. The proposed approach first applies an incremental phase computation algorithm on discrete binary peak representation of XRD samples, followed by hierarchical clustering or manual merging of similar pure phases to obtain the final composition-phase diagram. We evaluate our method on the composition space of two ternary alloy systems- Co-Ni-Ta and Co-Ti-Ta. Our results are verified by domain scientists and closely resembles the manually computed ground-truth composition-phase diagrams. The proposed approach takes us closer towards achieving the goal of complete end-to-end automated XRD analysis., Accepted and presented at the International Workshop on Domain-Driven Data Mining (DDDM) as a part of the SIAM International Conference on Data Mining (SDM 2021). Contains 11 pages and 5 figures

We propose an end-to-end music mixing style transfer system that converts the mixing style of an input multitrack to that of a reference song. This is achieved with an encoder pre-trained with a contrastive objective to extract only audio effects related information from a reference music recording. All our models are trained in a self-supervised manner from an already-processed wet multitrack dataset with an effective data preprocessing method that alleviates the data scarcity of obtaining unprocessed dry data. We analyze the proposed encoder for the disentanglement capability of audio effects and also validate its performance for mixing style transfer through both objective and subjective evaluations. From the results, we show the proposed system not only converts the mixing style of multitrack audio close to a reference but is also robust with mixture-wise style transfer upon using a music source separation model.

Diamine-appended Mg2(dobpdc) (dobpdc4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) metal-organic frameworks are a promising class of CO2 adsorbents, although their stability to SO2─a trace component of industrially relevant exhaust streams─remains largely untested. Here, we investigate the impact of SO2 on the stability and CO2 capture performance of dmpn-Mg2(dobpdc) (dmpn = 2,2-dimethyl-1,3-propanediamine), a candidate material for carbon capture from coal flue gas. Using SO2 breakthrough experiments and CO2 isobar measurements, we find that the material retains 91% of its CO2 capacity after saturation with a wet simulated flue gas containing representative levels of CO2 and SO2, highlighting the robustness of this framework to SO2 under realistic CO2 capture conditions. Initial SO2 cycling experiments suggest dmpn-Mg2(dobpdc) may achieve a stable operating capacity in the presence of SO2 after initial passivation. Evaluation of several other diamine-Mg2(dobpdc) variants reveals that those with primary,primary (1°,1°) diamines, including dmpn-Mg2(dobpdc), are more robust to humid SO2 than those featuring primary,secondary (1°,2°) or primary,tertiary (1°,3°) diamines. Based on the solid-state 15N NMR spectra and density functional theory calculations, we find that under humid conditions, SO2 reacts with the metal-bound primary amine in 1°,2° and 1°,3° diamine-appended Mg2(dobpdc) to form a metal-bound bisulfite species that is charge balanced by a primary ammonium cation, thereby facilitating material degradation. In contrast, humid SO2 reacts with the free end of 1°,1° diamines to form ammonium bisulfite, leaving the metal-diamine bond intact. This structure-property relationship can be used to guide further optimization of these materials for CO2 capture applications.

A short history of teacher education reform in China after 1978.

While previous research using transcranial magnetic stimulation (TMS) suggest that cerebellum (CB) influences the neuroplastic response of primary motor cortex (M1), the role of different indirect (I) wave inputs in M1 mediating this interaction remains unclear. The aim of this study was to assess how CB influences neuroplasticity of early and late I-wave circuits. 22 young adults (22 ± 2.7 years) participated in 3 sessions in which I-wave periodicity repetitive transcranial magnetic stimulation (iTMS) was applied over M1 during concurrent application of cathodal transcranial direct current stimulation over CB (tDCSCB). In each session, iTMS either targeted early I-waves (1.5 ms interval; iTMS1.5), late I-waves (4.5 ms interval; iTMS4.5), or had no effect (variable interval; iTMSSham). Changes due to the intervention were examined with motor evoked potential (MEP) amplitude using TMS protocols measuring corticospinal (MEP1mV) excitability and the strength of CB-M1 connections (CBI). In addition, we indexed I-wave activity using short-interval intracortical facilitation (SICF) and low-intensity single-pulse TMS applied with posterior-anterior (MEPPA) and anterior-posterior (MEPAP) current directions. Following both active iTMS sessions, there was no change in MEP1mV, CBI or SICF (all P > 0.05), suggesting that tDCSCB broadly disrupted the excitatory response that is normally seen following iTMS. However, although MEPAP also failed to facilitate after the intervention (P > 0.05), MEPPA potentiated following both active iTMS sessions (both P < 0.05). This differential response between current directions suggests that the disruptive effects of CB modulation on M1 plasticity may be selectively mediated by AP-sensitive circuits (also likely recruited with MEP1mV, CBI, and SICF).

Biodegradable polymeric materials have become the most attractive research interest in recent years and are gradually widely used in various fields in the case of environmental pollution. In this paper, binary blends, mainly including varying contents of polyglycolic acid (PGA) and poly(vinyl alcohol) (PVA), were prepared via a melt compounding strategy. The ethylene-methyl acrylate-glycidyl methacrylate (EMA-GMA) was employed as the compatibilizer to improve the compatibility between the PGA and PVA and the polyolefin elastomer (POE) was used as toughening agent. The anti-compression property and water-soluble ability of the blends were particularly studied to explore their potential application in an oil/gas exploitation field. Special attentions were paid to the evolution of the water-soluble ability of PGAX with the PVA concentration. Furthermore, isothermal shear measurement and thermogravimetric analysis were performed to evaluate the thermal stability of PGA and PGA blends (PGAX) during melt processing. The results showed that the incompatibility between PGA and PVA largely deteriorated the mechanical property, i.e., anti-compression strength, leading to fragile characteristics under a lower compressive load for the PGAX samples with varied contents of PVA. The presence of PVA and EMA-GMA greatly enhanced the viscoelasticity of the PGA melt, showing an increased storage modulus and viscosity at a low shear frequency; however, the thermal instability of PGAX was intensified owing to the greater ease of thermal degradation of PVA than that of PGA. Meanwhile, the water-soluble ability of PGAX was improved due to the high water dissolution of PVA, which played the role as a sacrificial material. The purpose of this work is to pursue an effective modification for PGA processing and application via melt blending.

In this paper, we first extend the finite distortion problem from the bounded domains in $\mathbb{R}^2$ to the closed genus-zero surfaces in $\mathbb{R}^3$ by the stereographic projection. Then we derive a theoretical foundation for spherical equiareal parameterizations between a simply connected closed surface $\mathcal{M}$ and a unit sphere $\mathbb{S}^2$ via minimizing the total area distortion energy on $\overline{\mathbb{C}}$. Provided we determine the minimizer of the total area distortion energy, the minimizer composed with the initial conformal map determines the equiareal map between the extended planes. Taking the inverse stereographic projection, we can derive the equiareal map between $\mathcal{M}$ and $\mathbb{S}^2$. The total area distortion energy can be rewritten into the sum of Dirichlet energies associated with the southern and northern hemispheres, respectively, and can be decreased by alternatingly solving the corresponding Laplacian equations. Based on this foundational theory, we develop a modified stretch energy minimization for the computation of the spherical equiareal parameterization between $\mathcal{M}$ and $\mathbb{S}^2$. In addition, under some mild conditions, we verify that our proposed algorithm has asymptotically R-linear convergence or forms a quasi-periodic solution. Numerical experiments on various benchmarks validate the assumptions for convergence always hold and indicate the efficiency, reliability and robustness of the developed modified stretch energy minimization.

Velocity of the acoustic signal generated by partial discharge (PD) in the transformer is considerably affected by temperature. Because of thermosiphon effect, the internal temperature of the transformer gradually decreases from the top to the bottom, which leads the acoustic signal to propagate faster in the upper part of the transformer. Besides, due to the complex internal structure of the transformer, it is difficult for the acoustic signal to propagate from the PD source to the sensor along a straight line. In order to further enhance the accuracy of PD localization results, this paper proposes a correction-iteration method with considering the influence of the insulation oil temperature rise and the internal structure of the transformer. Based on the coordinate of the PD source calculated in the last iteration, more accurate results of the next iteration can be estimated. Effectiveness of the proposed method is verified by simulations and experiments, and the obtained results indicate that the localization error is positively correlated with temperature rise. Compared with other present localization methods, such as the Newton's method, the genetic algorithm and the imperial competitive algorithm, the PD localization results estimated by the proposed correction-iteration method are more accurate.

In this paper, we first derive a theoretical basis for spherical conformal parameterizations between a simply connected closed surface $\mathcal{S}$ and a unit sphere $\mathbb{S}^2$ by minimizing the Dirichlet energy on $\overline{\mathbb{C}}$ by stereographic projection. The Dirichlet energy can be rewritten as the sum of the energies associated with the southern and northern hemispheres and can be decreased under an equivalence relation by alternatingly solving the corresponding Laplacian equations. Based on this theoretical foundation, we develop a modified Dirichlet energy minimization with nonequivalence deflation for the computation of the spherical conformal parameterization between $\mathcal{S}$ and $\mathbb{S}^2$. In addition, under some mild conditions, we verify the asymptotically R-linear convergence of the proposed algorithm. Numerical experiments on various benchmarks confirm that the assumptions for convergence always hold and indicate the efficiency, reliability and robustness of the developed modified Dirichlet energy minimization., 29 pages

The Exa.TrkX project presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise for similar reconstruction tasks in the LHC. Graphs describing particle interactions are formed by treating each detector hit as a node, with edges describing the relationships between hits. We utilise a multihead attention message passing network which performs graph convolutions in order to label each node with a particle type. We previously demonstrated promising performance for our network. Using Delaunay triangulation as edge-forming technique, we tested different truth labeling schemes (a "full" version where each particle type is its own category, and a "simple" one that merges some of the categories by similar topologies), as well as different versions with or without edges connecting hits across planes (referred to as 3D and 2D networks, respectively). We found that the best accuracy is achieved by the 2D network, although the 3D network provides higher label consistency across planes. In this presentation, in addition to reviewing the network properties and goals, we will demonstrate further improvements in various aspects of the work. These include changes to the merging of categories for the simple truth labeling, the addition of an attention mechanism for 3D edges, and optimization of hyper parameters. After these additions, we will discuss further steps and assess the readiness of the network for usage in real-life neutrino experiments.

Differential diagnosis of brain metastases subtype and primary central nervous system lymphoma (PCNSL) is necessary for treatment decisions. The application of machine learning facilitates the classification of brain tumors, but prior investigations into primary lymphoma and brain metastases subtype classification have been limited.To develop a machine-learning model to classify PCNSL, brain metastases with primary lung and non-lung origin.Retrospective.A total of 211 subjects with pathologically confirmed PCNSL or brain metastases (training cohort 168 and testing cohort 43).A 3.0 T axial contrast-enhanced T1-weighted spin-echo inversion recovery sequence (T1WI-CE), axial T2-weighted fluid-attenuation inversion recovery sequence (T2FLAIR) ASSESSMENT: Several machine-learning models (support vector machine, random forest, and K-nearest neighbors) were built with least absolute shrinkage and selection operator (LASSO) using features from T1WI-CE, T2FLAIR, and clinical. The model with the highest performance in the training cohort was selected to differentiate lesions in the testing cohort. Then, three radiologists conducted a two-round classification (with and without model reference) using images and clinical information from testing cohorts.Five-fold cross-validation was used for model evaluation and calibration. Model performance was assessed based on sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC).Twenty-five image features were selected by LASSO analysis. Random forest classifier was selected for its highest performance on the training set with an AUC of 0.73. After calibration, this model achieved an accuracy of 0.70 on the testing set. Accuracies of all three radiologists improved under model reference (0.49 vs. 0.70, 0.60 vs. 0.77, 0.58 vs. 0.72, respectively).The random forest model based on conventional MRI and clinical data can diagnose PCNSL and brain metastases subtypes (lung and non-lung origin). Model classification can help foster the diagnostic accuracy of specialists and streamline prognostication workflow.4 TECHNICAL EFFICACY: Stage 2.

Smart biomaterials combined with stem cell-based therapeutic strategies have brought innovation in the field of bone tissue regeneration. However, little is known about precartilaginous stem cells (PCSCs), which can be used as seed cells and incorporated with bioactive scaffolds for reconstructive tissue therapy of bone defects. Herein, iron oxide nanoparticles (IONPs) were employed to modulate the fate of PCSCs, resulting in the enhanced osteogenic differentiation potential both in vitro and in vivo. PCSCs were isolated from the ring of La-Croix extracted from polydactylism patient and identified through immunohistochemically staining using anti-FGFR-3 antibodies. Potential toxicity of IONPs toward PCSCs was assessed through cell viability, proliferation, and attachment assay, and the results demonstrated that IONPs exhibited excellent biocompatibility. After that, the effects of IONPs on osteogenic differentiation of PCSCs were evaluated and enhanced ALP activity, formation of mineralized nodule, and osteogenic-related genes expressions could be observed upon IONPs treatment. Moreover, in vivo bone regeneration assessment was performed using rabbit femur defects as a model. A novel methacrylated alginate and 4-arm poly (ethylene glycol)-acrylate (4A-PEGAcr)-based interpenetrating polymeric printable network (IPN) hydrogel was prepared for incorporation of IONPs-labeled PCSCs, where 4A-PEGAcr was the common component for three-dimensional (3D) printing. The implantation of IONPs-labeled PCSCs significantly accelerated the bone formation process, indicating that IONPs-labeled PCSCs could endow current scaffolds with excellent osteogenic ability. Together with the fact that the IONPs-labeled PCSCs-incorporated IPN hydrogel (PCSCs-hydrogels) was biosafety and printable, we believed that PCSCs-hydrogels with enhanced osteogenic bioactivity could enrich the stem cell-based therapeutic strategies for bone tissue regeneration.

Current-induced spin-orbit torque (SOT) is regarded as a promising mechanism for driving neuromorphic behavior in spin-orbitronic devices. In principle, the strong SOT in heavy metal-based magnetic heterostructure is attributed to the spin-orbit coupling (SOC)-induced spin Hall effect (SHE) and/or the spin Rashba-Edelstein effect (SREE). Recently, SOC-free mechanisms such as the orbital angular momentum (OAM)-induced orbital Hall effect (OHE) and/or the orbital Rashba-Edelstein effect (OREE) have been proposed to generate sizable torques comparable to those from the conventional spin Hall mechanism. In this work, we show that the orbital current can be effectively generated by the nitrided light metal Cu. The overall damping-like SOT efficiency, which consists of both the spin and the orbital current contributions, can be tailored from ~ 0.06 to 0.4 in a Pt/Co/CuNx magnetic heterostructure by tuning the nitrogen doping concentration. Current-induced magnetization switching further verifies the efficacy of such orbital current with a critical switching current density as low as Jc ~ 5 x 10^10 A/m2. Most importantly, the orbital-current-mediated memristive switching behavior can be observed in such heterostructures, which reveals that the gigantic SOT and efficient magnetization switching are the tradeoffs for the applicable window of memristive switching. Our work provides insights into the role of orbital current might play in SOT neuromorphic devices and paves a new route for making energy-efficient spin-orbitronic devices.

Liver diseases seriously endanger people’s physical health, especially liver cancer, and its morbidity and mortality have increased year by year. The reason why liver cancer is difficult to cure is that in addition to the low lethality of cancer drugs to cancer cells, another important factor is that the drugs do not have liver targeting, and there is no way to efficiently deliver anti-cancer drugs to the liver lesions. Hepatocytes can specifically recognize galactose, therefore the galactosyl liver-targeted drug carrier can deliver the drug to the liver in a targeted manner, so that the drug can be directed to the liver, reduce the dose and times of drug administration, reduce toxic side effects, and reduce the adverse reactions of patients, which is of great significance for the treatment of liver cancer. In this thesis, paclitaxel long-circulating nano-liposomes targeting liver cancer constructed with galactose as raw materials can improve the pharmacokinetics and tissue distribution of traditional formulations of paclitaxel, and enhance the safety and tumor suppressive effect of paclitaxel in vivo.

An accurate assessment of the damp status of oil-impregnated paper (OIP) bushings is crucial for the power industry to make informed decisions on the maintenance and replacement schedule of bushings. This article proposes a hybrid of the convolutional neural network (CNN) and the hidden Markov model (HMM) for estimating the damp status (i.e., moisture level and moisture source) of bushings especially when nonuniform moisture distribution exhibits in the bushing. First, simulation models of moisture diffusion and frequency-domain spectroscopy (FDS) of the OIP bushing were constructed using the finite element modeling (FEM) approach. Then, CNN was employed to extract informative features from FDS results of the OIP bushing, which is sensitive to both concentrations and sources of moisture. Finally, HMMs were further utilized as a strong stability tool to recognize the damp status of OIP bushings. The proposed method was implemented to identify the bushing damp status using both simulation data and real-life measurements. Identification results demonstrate that the proposed method has high accuracy in determining the moisture level and moisture source of the OIP bushing insulation.

Timely repair of fused silica damage ensures the stable operation of high-power laser systems. In the traditional repair process, the material nearby the damaged area is gradually ablated with CO2 or femtosecond laser. Subsequently, homogenization and residual stress removal are required because of the microcracks and thermal accumulation generated with the ablation. As a result, the repair efficiency is greatly restricted. In this paper, a new method using in-volume, selective femtosecond laser-induced etching to repair the damage of fused silica is proposed. The region irradiated by femtosecond laser becomes more susceptible to the etching solution due to its constitutive characteristics having undergone chemical restructuring. In this way, material nearby the damaged area transparent to the laser radiation is modified locally inside the volume. A femtosecond laser is used to scan the damaged area with a 3D hollow trajectory. The applicable modification of fused silica occurs when the single pulse energy is approximately 2 μJ to 5 μJ, the repetition frequency is approximately 200 kHz to 500 kHz, and the scanning speed is approximately 10 mm/s. Then, the etching solution reacts quickly along the 3D profile of the modified path, and the damaged area is removed as a whole piece. This method can greatly reduce the workload of repair, and the etching process of fused silica is carried out synchronously. So, the etching efficiency is not affected by the number of damage points. In addition, the weak reaction between the etching solution and the substrate could homogenize the interface. It provides an efficient way to repair the surface damage of fused silica.

Additional file 1: Figure S1. (A) Differentiation of mitochondria-related genes in A172 TMZ resistance cells (A172-R) with shSOD2 or shControl is shown in the heatmap graphs. A total of 84 genes was assessible from the assay. Among them, however, only 71 of the items were found in the database of mitochondria-related genes according to MitoCarta 2.0. (B) The correlation between SH3GLB1 and SOD2 was also shown in TCGA-GBM dataset and the 14 paired patients. (C) Nine cases showing expression of SH3GLB1 in the paired primary- and recurrent-tissues using IHC staining (100x and 400x magnification). (D) Kaplan-Meier curves of TCGA-GBMLGG (GBM and low-grade glioma) database showed higher SH3GLB1 levels caused poor survival. Figure S2. Ingenuity Pathway Analysis was applied for analysis of the major mitochondria-related molecular and cellular functional alterations in the transcriptome data from 14 RNA-seq data from paired recurrent and treatment-naïve high-grade glioma samples. As shown in the figure, sample numbers of down- (left column) or up-regulated (right column) genes. In each grid, the color is determined by the rank percentile, and the number represents sample that fulfills the criteria. The levels and significance of the genes ratio from CGGA glioma database (recurrent versus primary) are also shown aside. Note that none of the genes in complex II had CGGA database significance better than **, and the genes in complex V and CoQ synthesis was not higher in the resistant groups in the 14 paired samples. ***p < 0.001, **p < 0.01, *p < 0.05, NS: not significant. NA: data not available. Figure S3. (A) Five naïve glioblastoma tumor samples were used for single-cell transcriptome and were sorted into nine clusters according to their gene expression (Fig. 2A). The heatmap graph shows the common related genes of GBM and tumor-initiating cells among the clusters. Note that clusters 3, 7, 8, and 9 are identified as immunocytes because of the presence of the markers such as CD3E/G, GZMA, ITGAM, ITGAX. (B) The clusters reclassified by the studies of Neftel et al. (Cell, 2019) were divided into four cellular states. Figure S4. (A) Cell metabolic phenotype profile were measured using Seahorse Analyzer (OCR and ECAR). (B) The individual OCR parameters were measured using the indicated reagents and plotted in Fig. 5B, with the statistic graphs showing the parameters of maximal respiration, spare respiratory capacity, and nonmitochondrial respiration. (C) The parental cells transfected with SH3GLB1-overexpressing vector were stained with a JC-1 dye, showing the enhanced fluorescent ratio. Figure S5. (A) IACS-010759 effect to cell density for 72 hours of the parental cells with or without SH3GLB1 overexpression are shown in the bar graph. (B) IACS-010759 effect to cell density for 72 hours of the resistant cells with or without SH3GLB1 knockdown are shown in the bar graph. (*P < 0.05) Figure S6. (A) The U87MG-R luciferase-carrying cells (U87MG-R-luc-EGFP) were transfected with shSH3GLB1 used in animal experiment. SOD2 levels did not be affected by SH3GLB1 deficiency. (B) The tumor volume was measured at Day 20 and Day 23 according to the National Cancer Institute formula. (C) The body weight was recorded at the indicated day as the statistic graph. (*P < 0.05) (D) The image shows the tumor extracted from euthanized mice (scale bar = 1 cm) (E) The SH3GLB1 expression in the tissue using an IHC staining is shown (scale bar = 200 μm). (F) The body weight was recorded and shown in the statistical graph. Figure S7. Kaplan-Meier curves of GBM database from CGGA showed the survival of the indicated subunits genes of OXPHOS complex. Figure S8. A172 or A172-R cells are used in the results including roles of SH3GLB1 on Sp1 promoter, Sp1 expression, 36 autophagy levels, OXPHOS levels, cell density and OCR analysis. Figure S9. Pt#5 or Pt#5-R cells are used in the results including roles of SH3GLB1 on Sp1 promoter, Sp1 expression, autophagy levels, OXPHOS levels, cell density and OCR analysis.

Supplemental material, sj-doc-1-taj-10.1177_20406223221102750 for A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy by Zhe Qian, Houji Wu, Yihua Wu, Wei Liao, Tao Yu, Xuwen Xu, Jie Peng and Shaohang Cai in Therapeutic Advances in Chronic Disease

The volumetric stretch energy has been widely applied to the computation of volume-/mass-preserving parameterizations of simply connected tetrahedral mesh models. However, this approach still lacks theoretical support. In this paper, we provide the theoretical foundation for volumetric stretch energy minimization (VSEM) to compute volume-/mass-preserving parameterizations. In addition, we develop an associated efficient VSEM algorithm with guaranteed asymptotic R-linear convergence. Furthermore, based on the VSEM algorithm, we propose a projected gradient method for the computation of the volume/mass-preserving optimal mass transport map with a guaranteed convergence rate of $\mathcal{O}(1/m)$, and combined with Nesterov-based acceleration, the guaranteed convergence rate becomes $\mathcal{O}(1/m^2)$. Numerical experiments are presented to justify the theoretical convergence behavior for various examples drawn from known benchmark models. Moreover, these numerical experiments show the effectiveness and accuracy of the proposed algorithm, particularly in the processing of 3D medical MRI brain images., Comment: 26 pages

This report describes fossils recovered from Ganxian Cave in 2008 and 2018 by the Natural History Museum and Anthropology Museum of Guangxi. The cave sedimentary fill yielded rich mammalian fossils consisting mainly of isolated teeth of medium- to large-sized mammals (Primates, Proboscidea, Perissodactyla, Carnivora, Rodentia, Artiodactyla) of typical ‘Ailuropoda-Stegodon’ fauna, (e.g. Stegodon orientalis, Ailuropoda baconi, Pongo weidenreichi, Tapirus sinensis, Megatapirus augustus, Crocuta ultima), and more numerous extant species belonging to 28 taxa in total. The biochronological age of the fauna agreed with the age estimates obtained using Uranium–series and coupled ESR/U-series dating. Collectively, these results indicate a Ganxian fossil age range of 168.9 ± 2.4 ka to 362 ± 78 ka and establish Ganxian Cave as one of the most precisely dated Middle Pleistocene fossil sites in southern China. Comparison of Ganxian fauna with Pleistocene fossil records of the well-documented faunas of southern China and southeast Asia indicates that the Asian elephant (Elephas maximus) probably first appeared in Ganxian Cave. Paleoenvironmental reconstruction-based analysis of the large mammalian fossil assemblage from Ganxian Cave indicates that during the late Middle Pleistocene, the habitat consisted mainly of forests with some open areas and the climate was warm and humid.

Additional information for simulation and fabrication details

Additional file 1: Figure 1. (A) IHC staining of LRIG2 in OS tissues and Para-cancerous tissues (100× and 400×). (B) The images of the original blots of the relative expression of LRIG2 protein in OS cell lines (MG63, 143B, HOS and U2) compared with human osteoblast cell line hFOB1.19. (C) TCGA database analyzes the 5-year survival prognosis of LRIG2 in sarcoma patients. Figure 2. (A) The original western blot images of knockout efficiency of LRIG2 gene of three different short hairpins. (B) The original blots images of silencing LRIG2 efficiency (HOS and 143B cells). Figure 3. (A) Original western blot images of the expression levels of various proteins after LRIG2 knockdown (HOS cell line). (B) Original western blot images of the expression levels of various proteins after LRIG2 knockdown (143B cell line). All the blots were cut prior to hybridization with antibodies. Figure 4. Silencing LRIG2 inhibits the growth of osteosarcoma spontaneous metastasis xenograft models. (A) Orthotopic osteosarcoma xenograft tumor models were established, the nude mice were euthanized after 4 weeks, orthotopic tumors dissected to obtain samples. (B) Tumor sizes were measured weekly and calculated using the following formula: V= (Length×Width^2/2). (C) Tumors were dissected and weighted. Figure 5. Silencing LRIG2 inhibits the growth of osteosarcoma xenograft tumor. LRIG2 stably transfected gene silencing were inoculated subcutaneously into the nude mice. The nude mice were euthanized after 5 weeks, subcutaneous tumors dissected to obtain samples (6 for control group and 6 for LRIG2- knockdown group). The relative mRNA expression levels of control group and LRIG2-knockdown group were detected by qRT-PCR.

Additional file 1 Supplemental Table 1. The correlation between IFT20 and GM130 protein in cancerous and adjacent tissues. Supplemental Fig. 1. The forest plot of Cox proportional hazard regression models with TNM stage included. To exclude collinearity, the three types' expressions of IFT20 and GM130 protein (IOD/area, rate of positive cells, and staining intensity score) were separately included in the model.

Additional file 1. Material and method details.

Current-induced spin-orbit torque (SOT) is regarded as a promising mechanism for driving neuromorphic behavior in spin-orbitronic devices. In principle, the strong SOT in heavy metal-based magnetic heterostructure is attributed to the spin-orbit coupling (SOC)-induced spin Hall effect (SHE) and/or the spin Rashba-Edelstein effect (SREE). Recently, SOC-free mechanisms such as the orbital angular momentum (OAM)-induced orbital Hall effect (OHE) and/or the orbital Rashba-Edelstein effect (OREE) have been proposed to generate sizable torques comparable to those from the conventional spin Hall mechanism. In this work, we show that the orbital current can be effectively generated by the nitrided light metal Cu. The overall damping-like SOT efficiency, which consists of both the spin and the orbital current contributions, can be tailored from ~ 0.06 to 0.4 in a Pt/Co/CuNx magnetic heterostructure by tuning the nitrogen doping concentration. Current-induced magnetization switching further verifies the efficacy of such orbital current with a critical switching current density as low as Jc ~ 5 x 10^10 A/m2. Most importantly, the orbital-current-mediated memristive switching behavior can be observed in such heterostructures, which reveals that the gigantic SOT and efficient magnetization switching are the tradeoffs for the applicable window of memristive switching. Our work provides insights into the role of orbital current might play in SOT neuromorphic devices and paves a new route for making energy-efficient spin-orbitronic devices.

Oil-impregnated paper (OIP) bushing is essential equipment in power substations, and moisture intrusion is one of the major faults during its operation. In this article, a method is proposed to diagnose the moisture intrusion fault by the hidden Markov model (HMM) and the shuffled frog-leaping algorithm (SFLA). First, HMM is employed to characterize the probabilistic relationship between the moisture states and frequency-domain spectroscopy (FDS). Then, SFLA is adopted to optimize the locatable results of moisture intrusion point (MIP) in the bushing. Next, extensive simulated data are used for parameter training in the HMM-SFLA model library, with cross-validation for optimal parameters’ configuration of HMM and SFLA. Finally, the proposed method was validated by experiment in laboratory and field measurements. The results show that the proposed method can effectively diagnose the MIP of OIP bushings.

In order to study the effect of pulse current treatment on the mechanical properties, microstructure and cutting performance of YG8 cemented carbide, experiments were carried out by using self-made pulse current treatment device to treat cemented carbide samples with different current densities (J = 5, 10 and 15 A·mm−2). After the treatment of pulse current, when the current density increased from 5 to 15 A·mm−2, the hardness of the sample was improved to HV 1605, HV 1629 and HV 1653 from HV 1574; the transverse rupture strengths of the sample were 2136, 2289 and 2364 MPa, which were all higher than that of the untreated sample (2062 MPa), increasing by 3.6%, 11.0% and 14.6%, respectively; the corresponding cutting performance was increased by 10.1%, 13.9% and 19.4%, compared to that of the untreated tool. The tool’s life was also improved. After the treatment of pulse current, pulse current provided the driving force for dislocation motion, making it more likely for the dislocation to multiply and slip, the dislocation density was increased, and the mechanical properties were significantly improved.

Frequency-domain dielectric spectrum (FDS) is an effective testing method to reflect the changes of internal insulation status of oil-impregnated paper (OIP) bushing. In field application, the results of FDS test can be both affected by aging defects and damp defects, then the internal insulation defects of OIP bushing cannot be diagnosed in detail, which is an issue of discrimination of multiclass classification. To solve this problem, a method to diagnose the internal insulation defects of OIP bushing is proposed based on multiclass least square support vector machines (LS-SVMs) optimized by cuckoo search (CS) algorithm. First, the multiclass LS-SVM parameters are optimized by the CS algorithm. Then, the training data set is used to train the multiclass LS-SVM model, and the test data set is used for model testing. The experimental results show that the proposed method can effectively diagnose the internal insulation defects in detail, i.e., aging defects and damp defects. In addition, in the proposed method, the CS algorithm is better than the genetic algorithm and particle swarm optimization algorithm, and the convergence rate of the CS algorithm is faster than the other two algorithms.

This study proposes a high-accuracy method of localising partial discharge (PD) for transformer fault diagnosis. This study aims to solve the problem of high-accuracy estimation of PD in transformers by detecting the acoustic signals. First, by combining the advantages of the differential evolution (DE) algorithm and the particle swarm optimisation (PSO) algorithm, the authors describe a hybrid DE-PSO algorithm that can maintain great diversity even at the later stage of calculation. For further accuracy, a cooperative localisation differential evolution-particle swarm optimization-correction-Newton's method (DPCN) algorithm based on the DE-PSO algorithm and Newton's method with consideration of corrected time difference of arrival values is proposed. The results of simulations and experiments show that the proposed algorithm has excellent performance with high accuracy and strong robustness, and it can meet the needs of field applications.