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Objective To investigate the utility of an automatic deep learning (DL) method for segmentation of T2 maps in patients with idiopathic inflammatory myopathy (IIM) against healthy controls, and also the association of quantitative T2 values in patients with laboratory and pulmonary findings. Methods Structural MRI and T2 mapping of bilateral thigh muscles from patients with IIM and healthy volunteers were segmented using dedicated software based on a pre-trained convolutional neural network. Incremental and federated learning were implemented for continuous adaptation and improvement. Muscle T2 values derived from DL segmentation were compared between patients and healthy controls, and T2 values of patients were further analyzed with serum muscle enzymes, and interstitial lung disease (ILD) which was diagnosed and graded based on chest HRCT. Results Overall, 64 patients (27 patients with dermatomyositis, 29 with polymyositis, and 8 with antisynthetase syndrome (ASS)) and 10 healthy controls were included. By using DL-based muscle segmentation, T2 values generated from T2 maps accurately differentiated patients from those of controls (p < 0.001) with a cutoff value of 36.4 ms (sensitivity 96.9%, and specificity 100%). In patients with IIM, muscle T2 values positively correlated with all the serum muscle enzymes (all p < 0.05). ILD score of patients with ASS was markedly higher than that of those without ASS (p = 0.011), while dissociation between the severity of muscular involvement and ILD was observed (p = 0.080). Conclusion Automatic DL could be used to segment thigh muscles and help quantitatively assess muscular inflammation of IIM through T2 mapping. Key Points • Muscle T2 mapping automatically segmented by deep learning can differentiate IIM from healthy controls. • T2 value, an indicator of active muscle inflammation, positively correlates with serum muscle enzymes. • T2 mapping can detect muscle disease in patients with normal muscle enzyme levels.

Funder: Chronic Disease Research Foundation; doi: http://dx.doi.org/10.13039/100011721, Funder: Zoe Global Ltd, Multiple studies across global populations have established the primary symptoms characterising Coronavirus Disease 2019 (COVID-19) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID, and the extent and length of time for which they are elevated after COVID-19, could not be examined. We analysed individual symptom prevalences and characterised patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups ('no COVID-19', 'COVID-19 in last 12 weeks', 'COVID-19 > 12 weeks ago'), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the 'COVID-19 in last 12 weeks' and 'no COVID-19' groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the 'COVID-19 > 12 weeks ago' and 'no COVID-19' groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services.

In the data-driven artificial intelligence paradigm, models heavily rely on large amounts of training data. However, factors like sampling distribution imbalance can lead to issues of bias and unfairness in healthcare data. Sensitive attributes, such as race, gender, age, and medical condition, are characteristics of individuals that are commonly associated with discrimination or bias. In healthcare AI, these attributes can play a significant role in determining the quality of care that individuals receive. For example, minority groups often receive fewer procedures and poorer-quality medical care than white individuals in US. Therefore, detecting and mitigating bias in data is crucial to enhancing health equity. Bias mitigation methods include pre-processing, in-processing, and post-processing. Among them, Reweighting (RW) is a widely used pre-processing method that performs well in balancing machine learning performance and fairness performance. RW adjusts the weights for samples within each (group, label) combination, where these weights are utilized in loss functions. However, RW is limited to considering only a single sensitive attribute when mitigating bias and assumes that each sensitive attribute is equally important. This may result in potential inaccuracies when addressing intersectional bias. To address these limitations, we propose M3Fair, a multi-level and multi-sensitive-attribute reweighting method by extending the RW method to multiple sensitive attributes at multiple levels. Our experiments on real-world datasets show that the approach is effective, straightforward, and generalizable in addressing the healthcare fairness issues., 4 pages, 1 table, Beijing Health Data Science Summit 2023

Background: There are many reconstruction methods after sternal tumor resection, but the method that LARS mesh combines with bone-cement has not been reported.Case report: A 54-year-old female patient and a 55-year-old male patient admitted to our department all presented with sternum masses, but neither presented with respiratory disorders. In women with limited manubrium sternum lesions, we resected the manubrium sternum completely. In men with sternal lesions, we removed part of the sternum and part of the sternocostal joint. The patients recovered well after surgery, and there were no respiratory complications and no tumor recurrence during the 1-year follow-up respectively.Conclusion: We report two cases of sternal defect repair using LARS mesh combined with bone cement. This method is safe and stable, and can achieve satisfactory results.

In conventional plasmonic media and plasmonic metamaterials, such as metallic wire mesh, longitudinal mode of electromagnetic wave manifests itself in frequency overlapping transverse modes, which impedes clear observation of longitudinal-mode-specific physical effects. Through interlacing two sets of wire meshes, an ideal band for longitudinal mode is achieved ranging from zero frequency to plasma frequency where transverse modes are completely forbidden. The unique spectral separation of modes facilitates the observation of pure longitudinal mode and related plasmonic effects in bulk medium. We report the first experiment of anomalous optical transmission, induced solely by electromagnetic longitudinal mode resonance, below plasma frequency in the wire mesh medium.

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g., combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g., smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and electromagnetic power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyzes the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.

We study the dispersions of the guided modes in the continuous uniaxial crystal slab waveguide and engineer their degeneracies through dielectric anisotropy. By switching the uniaxial positivity and negativity, we can obtain distinctive nodal types, point and line, for the lowest degeneracy in frequency. The mirror symmetry protections, Mx and My, are pointed out, and the degeneracy properties are intuitively analyzed through comparing the approximate slopes of the guided modes. Our results reveal a link between the lowest nodal types and the positivity/negativity of the uniaxial crystal, and provide a new approach to regulate the topology of degeneracy in two-dimensional photonic bands.

The origin of ferromagnetism in epitaxial strained LaCoO3-x films has been a long controversial hitherto. Here, we investigated the magnetic behavior of a series of oxygen vacancies ordered LaCoO3-x films on different substrates. Obvious ferromagnetism was observed in perovskite LaCoO3/LSAT and LaCoO3/STO films, while LaCoO3/LAO films show weak ferromagnetism behavior. Meanwhile, LaCoO2.67 films exhibit antiferromagnetic behavior. An unexpected low-temperature ferromagnetism phenomenon with a Curie temperature of ~83 K and a saturation magnetization of ~1.2 μB/Co was discovered in15-nm-thick LaCoO2.5/LSAT thin films, which is probably related to the interface CoO6 octahedral rotation pattern change. Meanwhile, the observed ferromagnetism gradually disappears as the thickness of the film increases, indicating a tensile strain relaxation. Analysis suggests that the rotation and rhombohedral distortion of the CoO6 octahedron weakened the crystal field splitting and promoted the generation of the ordered high-spin state of Co2+, thus super-exchange effect between Co2+ (HS), Co2+ (LS), and Co2+ (HS) produced a low-temperature ferromagnetic behavior. However, compressive-strained LaCoO2.5 film on LaAlO3 substrate shows normal anti-ferromagnetism behavior. These results demonstrate both oxygen vacancies and tensile strain are correlated with the emergent magnetic properties in epitaxial LaCoO3-x films and provides a new perspective to regulate the magnetic properties of transition oxide thin films.

We study the Wannier-Stark (WS) localization in one-dimensional amplitude-chirped lattices with the $j$th onsite potential modulated by a function $Fj\cos(2\pi \alpha j)$, where $F$ is the external field with a period determined by $\alpha=p/q$ ($p$ and $q$ are co-prime integers). In the Hermitian (or non-Hermitian) systems with real (or imaginary) fields, we can obtain real (or imaginary) WS ladders in the eigenenergy spectrum. In most cases with $q \geq 2$, there are multiple WS ladders with all the eigenstates localized in the strong field limit. However, in the lattices with $q=4$, the energy-dependent localization phenomenon emerges due to the competition between spatially periodic and linearly increasing behaviors in the onsite potential. About half the number of eigenstates are gathered at the band center and can extend over a wide region or even the full range of the lattice, even when the field becomes very strong. Moreover, in the non-Hermitian lattices with odd $q$, some of the WS ladders become doubly degenerate, where the eigenstates are evenly distributed at two neighboring sites in a wide regime of field strength. Our work opens an avenue for exploring WS localization in both Hermitian and non-Hermitian amplitude-chirped lattices., Comment: 6 pages, 6 figures

Additional file 3: Table1. Advantages and disadvantages of biomaterials for neural tissue regeneration.

This paper investigates limited-budget consensus design and analysis problems of general high-order multiagent systems with intermittent communications and switching topologies. The main contribution of this paper is that the tradeoff design between the energy consumption and the consensus performance can be realized while achieving leaderless or leader-following consensus, under constraints of limited budgets and intermittent communications. Firstly, a new intermittent limited-budget consensus control protocol with a practical trade-off design index is proposed, where the total budget of the whole multiagent system is limited. Then, leaderless limited-budget consensus design and analysis criteria are derived, in which the matrix variables of linear matrix inequalities are determined according to the total budget and the practical trade-off design parameters. Meanwhile, an explicit formulation of the consensus function is derived to describe the consensus state trajectory of the whole system. Moreover, a new two-stage transformation strategy is utilized for leader-following cases, by which the dynamics decomposition of leaderless and leader-following cases can be converted into a unified framework, and sufficient conditions of the leader-following limited-budget consensus design and analysis are determined via those of the leaderless cases. Finally, numerical simulations are given to illustrate theoretical results.

In this paper, we introduce the notions of crossed module of associative conformal algebras, 2-term strongly homotopy associative conformal algebras, and discuss the relationship between them and the 3-th Hochschild cohomology of associative conformal algebras. We classify the non-abelian extensions by introducing the non-abelian cohomology. We show that non-abelian extensions of an associative conformal algebra can be viewed as Maurer-Cartan elements of a suitable differential graded Lie algebra, and prove that the Deligne groupoid of this differential graded Lie algebra corresponds one to one with the non-abelian cohomology. Based on this classification, we study the inducibility of a pair of automorphisms about a non-abelian extension of associative conformal algebras, and give the fundamental sequence of Wells in the context of associative conformal algebras. Finally, we consider the extensibility of a pair of derivations about an abelian extension of associative conformal algebras, and give an exact sequence of Wells type., 35 pages, comments are welcome

In this paper, we develop a cohomology theory of a left-symmetric conformal algebra and study its some applications. We define the cohomology of a left-symmetric conformal algebra, and then give an isomorphism between the cohomology spaces of the left-symmetric conformal algebra and its sub-adjacent Lie conformal algebra. As applications of the cohomology theory, we study linear deformations, formal $1$-parameter deformations, $T^*$-extensions of a left-symmetric conformal algebra respectively and obtain some properties., 16pages

This article is based on the use of GE combined with longitudinal lag time to quantify cardiac MRI screening for amyloidosis autologous thousand-cell transplantation, combined with clinical routine risk stratification, method for risk assessment of patients with amyloidosis and monitor the patient’s evaluation of the efficacy after treatment. Cardiac involvement with systemic amyloidosis is of great significance for both treatment and prognosis assessment, and is essential for quantitative and qualitative diagnosis or objectively providing prognostic value. In summary, myocardial amyloidosis needs to be studied before heart failure. It is recommended that patients undergo routine cardiac MRI examination to comprehensively evaluate cardiac morphology, function, risk stratification, prognosis, and treatment guidance. Diagnosis based on a single modality has been replaced by a comprehensive multi-modality method, and there is sufficient evidence to show the potential value of cardiac. However, with the continuous improvement of quality and value in the medical field, the field of cardiac will inevitably develop. The predicted and baseline indexes of myocardial strain predicted cardiac remission were 0.96 and 0.79, respectively. When the predictive value of clinical routine indicators and cardiac indicators is analyzed using blood response as the evaluation standard, the reduction in end-diastolic volume/body surface area (P = 0.031) can predict complete haematological remission. Folded cross-validation test shows that the end-diastolic volume/body surface area reduction and the baseline index IgG combined with myocardial strain predict AUC of complete blood remission of 0.78 and 0.76, respectively. This study will also continue to follow up and increase the sample size to verify the current conclusions.

Objective: This study aimed to evaluate the intervention effect of curcumin in myocardial infarction rodent models.Methods: A systematic retrieval of relevant studies on curcumin intervention in rats or mice myocardial infarction models was conducted, and the data were extracted. The outcome indicators included biochemical blood indicators, such as creatine kinase (CK), creatine kinase isoenzyme (CK-MB), malondialdehyde (MDA), lactate dehydrogenase (LDH) and superoxide dismutase (SOD), as well as cardiac tissue structure indicators, such as left ventricular weight to body weight ratio (LVW/BW), apoptosis index, left ventricular end-diastolic dimension (LVEDD), left ventricular end-systolic diameter (LVESD), and myocardial infarction area, and hemodynamic indexes, such as systolic blood pressure (SBP), diastolic blood pressure (DBP), left ventricular end-diastolic pressure (LVEDP), left ventricular ejection fraction (LVEF), left ventricular fractional shortening (LVFS), maximum rate of left ventricular pressure rise (+dp/dtmax), and maximum rate of left ventricular pressure decline (–dp/dtmax). These results were then analyzed by meta-analysis. Studies were evaluated for methodological quality using the syrcle’s bias risk tool.Results: A total of 24 studies were included in the meta-analysis. The quality assessment of included studies revealed that the evidence was low quality and none of studies was judged as having a low risk of bias across all domains. The results revealed that curcumin could reduce CK-MB, CK, LDH, and MDA levels. They also revealed that it could lower SBP, DBP, LVEDP, LVW/BW, apoptosis index, LVEDD, LVESD, and myocardial infarction area and increase LVEF, LVFS, +dp/dtmax, and–dp/dtmax. However, it had no significant impact on the heart rate and the levels of SOD in the models.Conclusion: Curcumin alleviates myocardial injury and oxidative stress in myocardial infarction rodent models in terms of blood biochemistry indicators, improves the diastolic and systolic capacity of the ventricle in terms of hemodynamic indexes, and reduces the necrosis and apoptosis of cardiomyocytes in terms of tissue structure. The methodological quality of the studies was low and additional research is warranted.

The frequency of, and risk factors for, long COVID are unclear among community-based individuals with a history of COVID-19. To elucidate the burden and possible causes of long COVID in the community, we coordinated analyses of survey data from 6907 individuals with self-reported COVID-19 from 10 UK longitudinal study (LS) samples and 1.1 million individuals with COVID-19 diagnostic codes in electronic healthcare records (EHR) collected by spring 2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for 12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic general and mental health, overweight/obesity, and asthma were associated with prolonged symptoms in both LS and EHR data, but findings for other factors, such as cardio-metabolic parameters, were inconclusive.

The frequency of, and risk factors for, long COVID are unclear among community-based individuals with a history of COVID-19. To elucidate the burden and possible causes of long COVID in the community, we coordinated analyses of survey data from 6907 individuals with self-reported COVID-19 from 10 UK longitudinal study (LS) samples and 1.1 million individuals with COVID-19 diagnostic codes in electronic healthcare records (EHR) collected by spring 2021. Proportions of presumed COVID-19 cases in LS reporting any symptoms for 12+ weeks ranged from 7.8% and 17% (with 1.2 to 4.8% reporting debilitating symptoms). Increasing age, female sex, white ethnicity, poor pre-pandemic general and mental health, overweight/obesity, and asthma were associated with prolonged symptoms in both LS and EHR data, but findings for other factors, such as cardio-metabolic parameters, were inconclusive.

Inspired by the complexity and diversity of biological neurons, a quadratic neuron is proposed to replace the inner product in the current neuron with a simplified quadratic function. Employing such a novel type of neurons offers a new perspective on developing deep learning. When analyzing quadratic neurons, we find that there exists a function such that a heterogeneous network can approximate it well with a polynomial number of neurons but a purely conventional or quadratic network needs an exponential number of neurons to achieve the same level of error. Encouraged by this inspiring theoretical result on heterogeneous networks, we directly integrate conventional and quadratic neurons in an autoencoder to make a new type of heterogeneous autoencoders. Anomaly detection experiments confirm that heterogeneous autoencoders perform competitively compared to other state-of-the-art models.

Graphical Abstract

A neural network with the widely-used ReLU activation has been shown to partition the sample space into many convex polytopes for prediction. However, the parameterized way a neural network and other machine learning models use to partition the space has imperfections, \textit{e}.\textit{g}., the compromised interpretability for complex models, the inflexibility in decision boundary construction due to the generic character of the model, and the risk of being trapped into shortcut solutions. In contrast, although the non-parameterized models can adorably avoid or downplay these issues, they are usually insufficiently powerful either due to over-simplification or the failure to accommodate the manifold structures of data. In this context, we first propose a new type of machine learning models referred to as Manifoldron that directly derives decision boundaries from data and partitions the space via manifold structure discovery. Then, we systematically analyze the key characteristics of the Manifoldron such as manifold characterization capability and its link to neural networks. The experimental results on 4 synthetic examples, 20 public benchmark datasets, and 1 real-world application demonstrate that the proposed Manifoldron performs competitively compared to the mainstream machine learning models. We have shared our code in \url{https://github.com/wdayang/Manifoldron} for free download and evaluation.

Magnetic resonance imaging plays an essential role in clinical diagnosis by acquiring the structural information of biological tissue. Recently, many multi-contrast MRI super-resolution networks achieve good effects. However, most studies ignore the impact of the inappropriate foreground scale and patch size of multi-contrast MRI, which probably leads to inappropriate feature alignment. To tackle this problem, we propose the Flexible Alignment Super-Resolution Network (FASR-Net) for multi-contrast MRI Super-Resolution. The Flexible Alignment module of FASR-Net consists of two modules for feature alignment. (1) The Single-Multi Pyramid Alignment(S-A) module solves the situation where low-resolution (LR) images and reference (Ref) images have different scales. (2) The Multi-Multi Pyramid Alignment(M-A) module solves the situation where LR and Ref images have the same scale. Besides, we propose the Cross-Hierarchical Progressive Fusion (CHPF) module aiming at fusing the features effectively, further improving the image quality. Compared with other state-of-the-art methods, FASR-net achieves the most competitive results on FastMRI and IXI datasets. Our code will be available at \href{https://github.com/yimingliu123/FASR-Net}{https://github.com/yimingliu123/FASR-Net}.

We define a cup product on the Hochschild cohomology of an associative conformal algebra $A$, and show the cup product is graded commutative. We define a graded Lie bracket with the degree $-1$ on the Hochschild cohomology $\HH^{\ast}(A)$ of an associative conformal algebra $A$, and show that the Lie bracket together with the cup product is a Gerstenhaber algebra on the Hochschild cohomology of an associative conformal algebra. Moreover, we consider the Hochschild cohomology of split extension conformal algebra $A\hat{\oplus}M$ of $A$ with a conformal bimodule $M$, and show that there exist an algebra homomorphism from $\HH^{\ast}(A\hat{\oplus}M)$ to $\HH^{\ast}(A)$.

In this paper, we study the Batalin-Vilkovisky structure on the Hochschild cohomology of quantum zigzag algebras $A_{q}$ of type $\widetilde{\mathbf{A}}_{1}$. We first calculate the dimensions of Hochschild homology groups and Hochschild cohomology groups of $A_{q}$. Based on these computations, we determine the Hochschild cohomology ring of $A_{q}$, and give the Batalin-Vilkovisky operator and the Gerstenhaber bracket on Hochschild cohomology ring of $A_{q}$ explicitly.

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The traditional methods for preparing expanded graphite (EG) often require harsh conditions and take a long time resulting in a high-cost and severe environmental pollution. A simple, energy-saving and efficient route for preparing EG was developed, in which flake graphite was exfoliated with K2S2O8 under concentrated H2SO4 at 80 oC for a few minutes. The microstructures, morphology and functional groups of the EG were characterized by XRD, SEM, FT-IR and Raman spectroscopy, and the electrical conductivity was measured by a four-point probe method. Results indicated that the flake graphite transformed into a worm-like structure after expansion with slight damage to the graphite sheets. A maximum expanded volume of 150 mL/g was obtained under the optimal conditions of 80 oC for 5 min with mass ratios of graphite to K2S2O8 of 1:7 and graphite to concentrated H2SO4 of 1:20. The electrical conductivity of the flexible graphite film prepared by rolling from the optimized EG reached 5.47×104 S/m. The mild oxidation and oxygen released by the decomposition of K2S2O8 under the acidic conditions are responsible for the efficiency of the method, which is promising for the mass production of EG due to its simplicity, low cost and low environmental impact.

Fermented meat products have a long history in China. These products exhibit a characteristic unique flavor, compact meat quality, clear color, long shelf life and wide variety and are easy to transport. During the processing and storage of fermented meat products, microorganisms are present and exhibit diverse characteristics. Microorganisms can accelerate the degradation of proteins and fats to produce flavor compounds, inhibit the growth and reproduction of heterozygous bacteria, and reduce the content of chemical pollutants. This paper reviews the microbial diversity of Chinese ham, sausage, preserved meat, pressed salted duck, preserved fish and air-dried meat and provides analyses of the microbial compositions of various products. Due to the differences in raw materials, technology, auxiliary materials, and fermentation technology, the microbial species found in various fermented meat products in China are different. However, most fermented meat products in China are subjected to pickling and fermentation, so their microbial compositions also have similarities. Microorganisms in fermented meat products mainly include staphylococci, lactobacilli, micrococci, yeasts, and molds. The study of microbial diversity is of great significance for the formation of quality flavor and the safety control of fermented meat products, and it provides some theoretical reference for the study of fermented meat products in China.

Twisted moir\'e superlattices (TMSs) are fascinating materials with exotic physical properties. Despite tremendous studies on electronic, photonic and phononic TMSs, it has never been witnessed that TMSs can exhibit higher-order band topology. Here, we report on the experimental observation of higher-order topological states in acoustic TMSs. By introducing moir\'e twisting in bilayer honeycomb lattices of coupled acoustic resonators, we find a regime with designed interlayer couplings where a sizable band gap with higher-order topology emerges. This higher-order topological phase host unique topological edge and corner states, which can be understood via the Wannier centers of the acoustic Bloch bands below the band gap. We confirm experimentally the higher-order band topology by characterizing the edge and corner states using acoustic pump-probe measurements. With complementary theory and experiments, our study opens a pathway toward band topology in TMSs., Comment: 4 figures

Topological phases of matter lie at the heart of physics, connecting elegant mathematical principles to real materials that are believed to shape future electronic and quantum computing technologies. To date, studies in this discipline have almost exclusively been restricted to single-gap band topology because of the Fermi-Dirac filling effect. Here, we theoretically analyze and experimentally confirm a novel class of multi-gap topological phases, which we will refer to as non-Abelian topological semimetals, on kagome geometries. These unprecedented forms of matter depend on the notion of Euler class and frame charges which arise due to non-Abelian charge conversion processes when band nodes of different gaps are braided along each other in momentum space. We identify such exotic phenomena in acoustic metamaterials and uncover a rich topological phase diagram induced by the creation, braiding and recombination of band nodes. Using pump-probe measurements, we verify the non-Abelian charge conversion processes where topological charges of nodes are transferred from one gap to another. Moreover, in such processes, we discover symmetry-enforced intermediate phases featuring triply-degenerate band nodes with unique dispersions that are directly linked to the multi-gap topological invariants. Furthermore, we confirm that edge states can faithfully characterize the multi-gap topological phase diagram. Our study unveils a new regime of topological phases where multi-gap topology and non-Abelian charges of band nodes play a crucial role in understanding semimetals with inter-connected multiple bands., 22 + 19 pages, 5+11 figures. With regard to references, please note that this concerns a version submitted to the journal in February 2021

In order to quantitatively characterize the ability of PVD(physical vapor deposition) film sensors to detect cracks in metallic structures, the process parameters applied to LY12-CZ aluminium alloys were first optimized using orthogonal tests, and coin shape, 1mm concentric dual ring shape, 0.5mm concentric tricyclic shape PVD film sensors were prepared on three groups of specimen with central hole using these parameters. Subsequently, the on-line monitoring experiment of fatigue cracks was carried out under laboratory conditions, the potential output signals of the PVD film sensors and microscope observations were compared and analysed. Finally, the probability of detection curves of all kinds of PVD thin-film sensors and PVD film sensor in different shapes were plotted separately using the improved crack size separation method and binomial distribution detection model. PVD thin-film sensors have 93.56% detection probability for cracks with length greater than 0.99mm at 95% confidence level. Compared to coin-shaped thin-film sensors, concentric ring shape film sensors are more sensitive to cracks smaller than 0.5mm, and the sensors with finer channel width have the higher probability of detection on small size cracks.

Yinian Zhang,1,2,* Hua-Teng Dong,3,* Lei Duan,1,2 Liang Niu,1,2 Guo-Qiang Yuan,1,2 Jun-Qiang Dai,1,2 Bo-Ru Hou,1,2 Ya-Wen Pan1,2 1Department of Neurosurgery and Laboratory of Neurosurgery, Lanzhou University Second Hospital, Lanzhou 730030, People’s Republic of China; 2Institute of Neurology, Lanzhou University, Lanzhou 730030, People’s Republic of China; 3Department of Pediatric Neurology, Gansu Provincial Maternity and Child-Care Hospital, Lanzhou 730050, People’s Republic of China *These authors contributed equally to this work Objectives: Despite the availability of effective antiepileptic drugs, epileptic patients still suffer from intractable seizures and adverse events. Better control of both seizures and fewer side effects is needed in order to enhance the patient’s quality of life. We performed the present study with an attempt to explore the effect that HDAC4 gene silencing would have on epilepsy simulated by model rats. Furthermore, the study made additional analysis on the relativity of the HDAC4 gene in regard to its relationship with the gamma-aminobutyric acid (GABA) signaling pathway. Materials and methods: Tremor rats were prepared in order to establish the epilepsy model. The rats would go on to be treated with si-HDAC4 in order to identify roles of the HDAC4 in levels of GABAARα1, GABAARα4, GAD65, GAT-1, and GAT-3. Finally, both electroencephalogram behavior and cognitive function of the rats following the treatment of si-HDAC4 were observed. Results: Levels of the GABAARα1 and GABAARα4 showed an evident increase, while GAD65, GAT-1, and GAT-3 displayed a decline in the epilepsy rats treated with the aforementioned si-HDAC4 when compared with the epilepsy rats. After injection of si-HDAC4, the epilepsy rats presented with a reduction in seizure degree, latency and duration of seizure, amount of scattered epileptic waves, and occurrence of epilepsy, with an improvement in their cognitive function. Conclusion: The study highlighted the role that HDAC4 gene silencing played in easing the cases of epilepsy found in the model rats. This was shown to have occurred through the upregulation of both GABAARα1 and GABAARα4 levels, as well as in the downregulation of GAD65, GAT-1, and GAT-3 levels. The evidence provided shows that the HDAC4 gene is likely to present as a new objective in further experimentation in the treatment of epilepsy. Keywords: epilepsy, HDAC4, gene silencing, GABA receptor, GABA transporter, seizures

The economic operation optimization of microgrid is an important research topic in the power system. Therefore, this paper proposes a surrogate model particle swarm optimization algorithm based on the global-local search mechanism. Firstly, aiming at the problem that the statistical information of Kriging model is difficult to guarantee the prediction accuracy, the dynamic transformation is carried out to enhance the robustness of the model; secondly, the global-local search mechanism is introduced to make the algorithm fully explore the fitness landscape near the Kriging model after quickly locating the current optimal particle position, so as to achieve the balance of convergence quality and convergence efficiency. The proposed method has been tested on numerous benchmark test functions from two test suites, and the results show that the proposed algorithm has more advantages than other comparison algorithms in optimization accuracy. Finally, simulations are carried out in two operating modes of microgrid islanding and grid-connected, which has verified the effectiveness of the proposed method.

Additional file 1.

Mianning ham, a traditional Chinese dry-cured ham, is protected by national geographical indications. To understand the surface and internal flavor composition and microbial community structure of Mianning ham, solid phase microextraction-gas chromatography (SPME-GC-MS) technology and Illumina high-throughput sequencing were utilized. The results showed that a total of 60 flavor substances were identified in the hams. Forty-nine kinds of flavorings were identified on the surface, including 14 aldehydes, 6 ketones, 10 alcohols, 5 esters, 7 hydrocarbons, 5 acids, and 2 other compounds. Thirty-six kinds of internal flavorings were identified, including 13 aldehydes, 4 ketones, 6 alcohols, 3 esters, 5 hydrocarbons, 4 acids and 1 other type. Decanal (34.91 μg/g) was the most prevalent compound on the surface, followed by n-hexanol (24.99 μg/g), n-hexanal (20.20 μg/g), and n-octyl (16.14 μg/g). n-Hexanal (20.74 μg/g) was the most common compound internally, followed by non-aldehyde (5.70 μg/g), 1-octene-3-alcohol (3.54 μg/g), and inverse-2-octenal (2.77 μg/g). Penicillium lanosum, Penicillium nalgiovense, Debaryomyces hansenii, Staphylococcus equorum, and Erwinia tasmaniensis were isolated from the surfaces of the hams by the traditional culture method. By Illumina high-throughput sequencing, three fungal phyla were identified. Ascomycota was the dominant phylum followed by Basidiomycota. At the genus level, 11 fungi were identified, of which Aspergillus was the dominant fungus, followed by Penicillium and Wallemia. These findings provide fundamental knowledge regarding the microorganisms and flavor compounds in Mianning ham, which will help industrial processors develop effective strategies for standardizing quality parameters.

Twisted moir�� superlattices (TMSs) are fascinating materials with exotic physical properties. Despite tremendous studies on electronic, photonic and phononic TMSs, it has never been witnessed that TMSs can exhibit higher-order band topology. Here, we report on the experimental observation of higher-order topological states in acoustic TMSs. By introducing moir�� twisting in bilayer honeycomb lattices of coupled acoustic resonators, we find a regime with designed interlayer couplings where a sizable band gap with higher-order topology emerges. This higher-order topological phase host unique topological edge and corner states, which can be understood via the Wannier centers of the acoustic Bloch bands below the band gap. We confirm experimentally the higher-order band topology by characterizing the edge and corner states using acoustic pump-probe measurements. With complementary theory and experiments, our study opens a pathway toward band topology in TMSs., 4 figures

Additional file 2.

Liang C, Sun W, He H, et al. Int J Nanomedicine.2018;13:209–220. The authors have advised due to an error at the time offigure assembly, Figure 6B on page 217 is incorrect. Thecorrect Figure 6 is shown below. The authors apologize for this error and advise it does notaffect the results of the paper. Read the original article

With the rise of social networks, information on the internet is no longer solely organized by web pages. Rather, content is generated and shared among users and organized around their social relations on social networks. This presents new challenges to information retrieval systems. On a social network search system, the generation of result sets not only needs to consider keyword matches, like a traditional web search engine does, but it also needs to take into account the searcher's social connections and the content's visibility settings. Besides, search ranking should be able to handle both textual relevance and the rich social interaction signals from the social network. In this paper, we present our solution to these two challenges by first introducing a social retrieval mechanism, and then investigate novel deep neural networks for the ranking problem. The retrieval system treats social connections as indexing terms, and generates meaningful results sets by biasing towards close social connections in a constrained optimization fashion. The result set is then ranked by a deep neural network that handles textual and social relevance in a two-tower approach, in which personalization and textual relevance are addressed jointly. The retrieval mechanism is deployed on Facebook and is helping billions of users finding postings from their connections efficiently. Based on the postings being retrieved, we evaluate our two-tower neutral network, and examine the importance of personalization and textual signals in the ranking problem., 8 pages, 8 figures

Additional file 2. Brain volumetry quantified by different automatic segmentation tools on multiple scanners.

The data describes a study of producing CO from CO2 electrochemical reduction with high efficiency by using binary copper-indium catalyst, which is a supplymentary to a paper on ACS Appl. Mater. Interfaces ( DOI: 10.1021/acsami.9b16862 )

Supplemental material, Supp_Material_cIMT_and_CSVD_cognitive_function20200623 for Carotid intima–media thickness relative to cognitive impairment in dialysis patients, and their relationship with brain volume and cerebral small vessel disease by Ke Zheng, Yujun Qian, Tiaye Lin, Fei Han, Hui You, Xixi Tao, Bo Hou, Jing Yuan, Haiyun Wang, Dingding Zhang, Ke Lv, Feng Feng, Yicheng Zhu and Xuemei Li in Therapeutic Advances in Chronic Disease

This study assesses the sustainability of rice farming through the perspectives of farmer attributes and land ecosystem – sub-categorized as the socio-economic profile of farmers, resources, constraints, investments, and its economic contribution to the economic pursuits of families of farmers. It also proposes a program which can improve rice production in Bulacan, Philippines, and similar contexts. This study discusses the identified rice farming constraints such as inadequate capital, high cost of labor, inadequate supply of farm inputs, poor marketing outlet, high cost of pesticides, high cost of fertilizer, issues on land tenure system, ignorance on the existing rice farming programs of the government, poor storage facilities, high cost of transportation, pests and diseases, and climate change. The contributions of rice farming to the economic pursuits of families of farmers are analyzed in terms of their gross profit, savings, and family living expenditures such as food, clothing, recreation, personal item, health care, education, utilities, transportation, dwelling maintenance, and appliances/furniture. Lastly, the suggestions for sustainable and human health facilitating rice farming in developing countries are discussed.

Additional file 1. Sample case for calculating the CV of volumetric data from different scanners in a single subject.

Electrolytic capacitor is widely selected as output capacitor in DC-DC converter, while it has limited reliability. Monitoring the equivalent series resistance (ESR) is an effective method to diagnostic the output capacitor. In this paper, an online monitoring scheme of ESR is present for discontinuous conduction mode (DCM) Buck converters. Based on the output ripple voltage, the model of ESR is established. By sampling the output ripple voltage, the ESR is calculated using the sampled values. The proposed method reduces the current measurement and avoids the change of converter topology. The simulation and experimental results verify the effectiveness of the method.

Background Mitral regurgitation (MR) has a severe impact on hemodynamics and induces severe structural changes in the left atrium. Atrial remodeling is known to alter excitability and conduction in the atrium facilitating atrial fibrillation and atrial flutter. PMVR is a feasible and highly effective procedure to reduce MR in high‐risk patients, which are likely to suffer from atrial rhythm disturbances. So far, electroanatomical changes after PMVR have not been studied. Hypothesis In the current study, we investigated changes in surface electrocardiograms (ECGs) of patients undergoing PMVR for reduction of MR. Methods We evaluated 104 surface ECGs from patients in sinus rhythm undergoing PMVR. P wave duration, P wave amplitude, PR interval, QRS duration, QRS axis, and QT interval were evaluated before and after PMVR and at follow‐up. Results We found no changes in QRS duration, QRS axis, and QT interval after successful PMVR. However, P wave duration, amplitude, and PR interval were significantly decreased after reduction of MR through PMVR (P

The food-traceability system is considered to be one of the main measures to fundamentally prevent food-safety problems. It is of great value to study consumer demand for traceable food and market simulations that can adjust the production and supply structure of traceable food and promote traceable market development. Having sampled and interviewed 2,121 consumers in China, consumer preferences for traceable pork with different levels of safety information, and the respective market share of traceable pork with different product profiles were investigated using conjoint value analysis and the randomized first choice method. Results showed that Chinese consumers prioritized the certification of a traceable-pork safety-information attribute. Furthermore, consumers were willing to pay extra costs in order to obtain traceable safety information. However, this additional expenditure should account for no more than 30% of the price of ordinary pork, or consumer demand for safe pork decreases. Results of a market simulation also identified a type of traceable pork that had an optimal combination of attributes and met the needs of Chinese consumers. Consequently, the government should gradually promote a multilevel traceable-food market system in China by developing a combination of a certification mechanism and traceability system, and increasing financial subsidies for the construction of the traceability system.

A crack monitoring technique is desired to ensure the safety and reliability of metallic structures. In the present study, a conductive film sensor was presented to monitor structural cracks in metal structures in real-time based on the electrical potential method. First, a Ti/TiN film sensor was prepared on the fatigue critical portion of a 2A12-T4 aluminum alloy specimen by vacuum ion plating technology, which allows firm integration with the metal surface. A finite element model (FEM) of the Ti/TiN film sensor was then constructed and the changes in the output of the sensor along with corresponding changes in crack propagation were discussed. The results indicated that the Ti/TiN film sensor has high sensitivity to cracks and it is feasible to monitor structural surface cracks using the sensor. Finally, crack monitoring experiments were carried out based on the Ti/TiN film sensor. Experimental results showed that the output potential curve of the Ti/TiN film sensor contained several regions, which corresponded to plastic deformation accumulation, crack propagation, and sensor failure, respectively. Therefore, the information on the origination and propagation of structural cracks can be gained through analyzing changes in slope of the output potential values of the Ti/TiN film sensor with respect to time.DOI: http://dx.doi.org/10.5755/j01.ms.21.4.9623

The inhibitory effect of resveratrol on the growth of gastric cancer cells through downregulation of the Wnt/β-catenin signaling pathway were studied. First we determined the effective concentration of resveratrol on the growth and proliferation of MGC-803 gastric cancer cells. Methylthiazolyl tetrazolium assay showed that resveratrol significantly inhibited the proliferation of MGC-803 cells in a dose-dependent manner. Resveratrol induced apoptotic morphological changes in MGC-803 cells. Reverse transcription-polymerase chain reaction and western blot analysis showed that resveratrol downregulated the expression of three important components of the Wnt signaling pathway, β-catenin, c-myc, and cyclin D1, at the mRNA and protein levels. Overall, resveratrol inhibits the growth of MGC-803 cells by inhibiting the Wnt signaling pathway. This study provides a new idea and direction for the antitumor mechanism of resveratrol.