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Abstract Potteries, one of the tools widely used by early humans, encapsulates rich historical information. Deep neural networks have been applied to analyzing pottery digital images, bypassing the need for intricate handcrafted features. However, existing models focus solely on pottery shape comparison, neglecting the analysis of their evolution across different historical periods. In this work, we propose a method based on deep learning to assist experts in identifying the evolutionary patterns of a given pottery type within their specified chronological divisions. First we train a convolutional neural network for pottery classification, extracting low and high level features that represent different ages of pottery samples. Next, we employ clustering algorithms to identify representative potteries for each historical period based on high level features. To facilitate intuitive comparisons across different ages, we use shallow features and compute cosine similarities between potteries, visualizing shape and decoration differences. This approach enhances understanding of pottery evolution patterns directly through visual analysis. The effectiveness and efficiency of our proposed method are evaluated by validating it on three distinct era division cases using data from the Dabagou and Miaozigou archaeological sites, which represent the Miaozigou culture and exhibit clear evolutionary patterns. Our method identifies representative artifacts for each era and uncovers their evolutionary patterns effectively and efficiently, achieving conclusions comparable to those of experts while significantly reducing time compared to traditional manual methods.

Purpose: Head injury criterion (HIC) companied by a rotation-based metric was widely believed to be helpful for head injury prediction in road traffic accidents. Recently, the Euro-New Car Assessment Program utilized a newly developed metric called diffuse axonal multi-axis general evaluation (DAMAGE) to explain test device for human occupant restraint (THOR) head injury, which demonstrated excellent ability in capturing concussions and diffuse axonal injuries. However, there is still a lack of comprehensive understanding regarding the effectiveness of using DAMAGE for Hybrid Ⅲ 50th percentile male dummy (H50th) head injury assessment. The objective of this study is to determine whether the DAMAGE could capture the risk of H50th brain injury during small overlap barrier tests. Methods: To achieve this objective, a total of 24 vehicle crash loading curves were collected as input data for the multi-body simulation. Two commercially available mathematical dynamic models, namely H50th and THOR, were utilized to investigate the differences in head injury response. Subsequently, a decision method known as simple additive weighting was employed to establish a comprehensive brain injury metric by incorporating the weighted HIC and either DAMAGE or brain injury criterion. Furthermore, 35 sets of vehicle crash test data were used to analyze these brain injury metrics. Results: The rotational displacement of the THOR head is significantly greater than that of the H50th head. The maximum linear and rotational head accelerations experienced by H50th and THOR models were (544.6 ± 341.7) m/s2, (2468.2 ± 1309.4) rad/s2 and (715.2 ± 332.8) m/s2, (3778.7 ± 1660.6) rad/s2, respectively. Under the same loading condition during small overlap barrier (SOB) tests, THOR exhibits a higher risk of head injury compared to the H50th model. It was observed that the overall head injury response during the small overlap left test condition is greater than that during the small overlap right test. Additionally, an equation was formulated to establish the necessary relationship between the DAMAGE values of THOR and H50th. Conclusion: If H50th rather than THOR is employed as an evaluation tool in SOB crash tests, newly designed vehicles are more likely to achieve superior performance scores. According to the current injury curve for DAMAGE and brain injury criterion, it is highly recommended that HIC along with DAMAGE was prioritized for brain injury assessment in SOB tests.

Objective: Researchers looked into the safety and effectiveness of blepharoplasty in conjunction with botulinum toxin type A for the treatment of periocular skin laxity. Methods: 92 patients who received treatment at our institution for periocular skin laxity were chosen as research subjects. Their admission time ranged from May 2020 to December 2022. Using various therapy modalities, the patients were split into two groups: an observational team (n = 46) and a controlling team (n = 46). They were respectively given blepharoplasty treatment intervention and botulinum toxin type A combined with blepharoplasty treatment intervention. Eyelid bags, crow's feet, skin radiance and aesthetic results, quality of life were analyzed before and after the intervention, and physician and patient’ satisfaction with the results were compared. Results: 95.65 % was the effective rate of the observed group, which was 71.74 % compared with the control group, and significantly increased (P

Abstract Inflammation and fibrosis often occur in the kidney after acute injury, resulting in chronic kidney disease and consequent renal failure. Recent studies have indicated that lymphangiogenesis can drive renal inflammation and fibrosis in injured kidneys. However, whether and how this pathogenesis affects the contralateral kidney remain largely unknown. In our study, we uncovered a mechanism by which the contralateral kidney responded to injury. We found that the activation of mineralocorticoid receptors and the increase in vascular endothelial growth factor C in the contralateral kidney after unilateral ureteral obstruction could promote lymphangiogenesis. Furthermore, mineralocorticoid receptor activation in lymphatic endothelial cells resulted in the secretion of myofibroblast markers, thereby contributing to renal fibrosis. We observed that this process could be attenuated by administering the mineralocorticoid receptor blocker eplerenone, which, prevented the development of fibrotic injury in the contralateral kidneys of rats with unilateral ureteral obstruction. These findings offer valuable insights into the intricate mechanisms underlying kidney injury and may have implications for the development of therapeutic strategies to mitigate renal fibrosis in the context of kidney disease.

Abstract DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts, such as using only one command line. In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to facilitate their own model development. DANCE is an open-source Python package that welcomes all kinds of contributions.

Abstract Silver sulfide thin film, with excellent thermoelectric properties, is few reported due to the complex and time‐consuming high‐temperature or high‐pressure synthesis process. Here, a fast ionic conductor n‐type Ag2S film with good crystallinity and uniform density is prepared by sputtering metal Ag films of different thicknesses on glass and then reacting in S precursor solution at low temperature. At 450 K, β‐Ag2S films can be obtained and underwent a phase transition from α‐Ag2S monoclinic, which had a significant effect on their electrical and thermal properties. The grain size of Ag2S films increases with the increase of film thickness. Before and after the phase transition, the carrier concentration and mobility cause obvious changes in the electrical properties of Ag2S. The carrier concentration of body‐centered cubic phase β‐Ag2S is about three orders of magnitude higher than that of monoclinic phase α‐Ag2S, and the mobility is also 2–3 times that of the latter. Especially, after the phase transition, the conductivity of β‐Ag2S rises exponentially from the zero conductivity of α‐Ag2S and increases with the increase of temperature. The Ag2S film shows the highest figure of merit of 0.83 ± 0.30 at 600 K from the sample with ∼1600 nm thickness, which is the highest record among Ag2S‐based thermoelectric materials reported so far.

Abstract This study identified four patterns of regional extreme precipitation events (REPEs) in Central Asia (CA) and their crucial synoptic systems and multiscale interactions. Four patterns with distinct spatial distributions were identified in: northern Kazakhstan, southern Xinjiang, western CA, and the Tianshan Mountains. Focusing on the three most frequent REPEs, the kinetic energy (KE) cross‐scale transfer from the basic‐to synoptic‐scale windows exhibited a zonal dipole, resulting in the development and enhancement of REPEs in northern Kazakhstan. The available potential energy (APE) cross‐scale transfer exhibited opposing patterns between the upper and lower troposphere, indicating baroclinic instability in the lower troposphere and barotropic instability of the basic flow in the upper troposphere. Both mechanisms enhanced the Central Asian vortices (CAVs) in southern Xinjiang and induced REPEs. Conversely, the energy budgets exhibited baroclinic instability of the basic flow throughout the entire region when the Tianshan Mountains REPEs occurred, providing energy for prevalent CAVs.

Abstract Topography is an important factor affecting soil erosion and is measured as a combination of the slope length and slope steepness (LS-factor) in erosion models, like the Chinese Soil Loss Equation. However, global high-resolution LS-factor datasets have rarely been published. Challenges arise when attempting to extract the LS-factor on a global scale. Furthermore, existing LS-factor estimation methods necessitate projecting data from a spherical trapezoidal grid to a planar rectangle, resulting in grid size errors and high time complexity. Here, we present a global 1-arcsec resolution LS-factor dataset (DS-LS-GS1) with an improved method for estimating the LS-factor without projection conversion (LS-WPC), and we integrate it into a software tool (LS-TOOL). Validation of the Himmelblau–Orlandini mathematical surface shows that errors are less than 1%. We assess the LS-WPC method on 20 regions encompassing 5 landform types, and R2 of LS-factor are 0.82, 0.82, 0.83, 0.83, and 0.84. Moreover, the computational efficiency can be enhanced by up to 25.52%. DS-LS-GS1 can be used as high-quality input data for global soil erosion assessment.

Abstract Two OR3 research vessel cruises were conducted at seven nearshore sites from north to south in the western coastal waters off Taiwan in May (late spring) and November (late autumn) 2019 in order to gain insights into the 2 °C difference in the tropical-subtropical fish fauna. Totally, 37 families, 72 genera, and 99 taxas were recorded for the 1809 fishes. Three fish assemblages, the North, South, and Fall-Zhuoshui River (ZRf) groups, were identified as eurythermal, stenothermal, and croaker communities. Their dominants, in rank order, were Tarphops oligolepis, Liachirus melanospilosa, Ostorhinchus fasciatus, and Trachinocephalus myops for the Northern eurythermal group, Arnoglossus tenuis, Eubleekeria splendens, and Ostorhinchus pleuron for the Southern stenothermal group, and Johnius taiwanensis, Chrysochir aureus, and Pennahia macrocephalus for the croaker-ZRf group. Their distribution was markedly correlated with the bottom water temperature, seafloor grain size, and concentration of suspended solids. The influence of a 2 °C difference on the tropical and subtropical demersal fish could indicate how rising temperatures due to climate change are shaping fish communities. The flatfish, Liachirus melanospilos, was distributed northward by 0.5oN and is suggested to be considered as an ecological indicator of the tropicalization of subtropical marine ecosystems in the future.

Abstract RNA-binding proteins play crucial roles in the regulation of gene expression, and understanding the interactions between RNAs and RBPs in distinct cellular conditions forms the basis for comprehending the underlying RNA function. However, current computational methods pose challenges to the cross-prediction of RNA-protein binding events across diverse cell lines and tissue contexts. Here, we develop HDRNet, an end-to-end deep learning-based framework to precisely predict dynamic RBP binding events under diverse cellular conditions. Our results demonstrate that HDRNet can accurately and efficiently identify binding sites, particularly for dynamic prediction, outperforming other state-of-the-art models on 261 linear RNA datasets from both eCLIP and CLIP-seq, supplemented with additional tissue data. Moreover, we conduct motif and interpretation analyses to provide fresh insights into the pathological mechanisms underlying RNA-RBP interactions from various perspectives. Our functional genomic analysis further explores the gene-human disease associations, uncovering previously uncharacterized observations for a broad range of genetic disorders.

Background: Platelets, a type of anucleated cell, play a crucial role in cardiovascular diseases (CVDs). Therefore, targeting platelet activation is essential for mitigating CVDs. Endogenous agonists, such as collagen, activate platelets by initiating signal transduction through specific platelet receptors, leading to platelet aggregation. Eugenol, primarily sourced from clove oil, is known for its antibacterial, anticancer, and anti-inflammatory properties, making it a valuable medicinal agent. In our previous study, eugenol was shown to inhibit platelet aggregation induced by collagen and arachidonic acid. We concluded that eugenol exerts a potent inhibitory effect on platelet activation by targeting the PLCγ2–PKC and cPLA2-TxA2 pathways, thereby suppressing platelet aggregation. In our current study, we found that eugenol significantly inhibits NF-κB activation. This led us to investigate the relationship between the NF-κB and cPLA2 pathways to elucidate how eugenol suppresses platelet activation. Methods: In this study, we prepared platelet suspensions from the blood of healthy human donors to evaluate the inhibitory mechanisms of eugenol on platelet activation. We utilized immunoblotting and confocal microscopy to analyze these mechanisms in detail. Additionally, we assessed the anti-thrombotic effect of eugenol by observing fluorescein-induced platelet plug formation in the mesenteric microvessels of mice. Results: For immunoblotting and confocal microscopy studies, eugenol significantly inhibited NF-κB-mediated signaling events stimulated by collagen in human platelets. Specifically, it reduced the phosphorylation of IKK and p65 and prevented the degradation of IκBα. Additionally, CAY10502, a cPLA2 inhibitor, significantly reduced NF-κB-mediated signaling events. In contrast, BAY11-7082, an IKK inhibitor, did not affect collagen-stimulated cPLA2 phosphorylation. These findings suggest that cPLA2 acts as an upstream regulator of NF-κB activation during platelet activation. Furthermore, both BAY11-7082 and CAY10502 significantly reduced the collagen-induced rise in intracellular calcium levels. In the animal study, eugenol demonstrated potential as an anti-thrombotic agent by significantly reducing platelet plug formation in fluorescein-irradiated mouse mesenteric microvessels. Conclusion: Our study uncovered a novel pathway in platelet activation involving the cPLA2-NF-κB axis, which plays a key role in the antiplatelet effects of eugenol. These findings suggest that eugenol could serve as a valuable and potent prophylactic or therapeutic option for arterial thrombosis.

Background: Vascular smooth muscle cell (VSMC) injury caused by the inflammatory response plays a key role in cardiovascular disease (CVD), and the vasoprotective effects of mineralocorticoid receptor blockers (MRBs) support the role of mineralocorticoid receptor (MR) activation. Methods: C57BL/6 mice and VSMCs isolated from rats were treated with aldosterone and esaxerenone. Caspase-1, GSDMD-N, IL-1β, and NR3C2 expression and DNA damage in aortic VSMCs were detected using immunohistochemistry, Western blotting, and TUNEL staining. Mitochondrial changes were detected by transmission electron microscopy (TEM). Reactive oxygen species (ROS), MitoTracker, JC-I, mitochondrial respiratory chain complexes I–V, and NR3C2 were detected using immunofluorescence and flow cytometry. Pyroptosis was detected with scanning electron microscopy (SEM). Results: After aldosterone treatment, the number of TUNEL-positive cells increased significantly, and the expression of caspase-1, GSDMD-N, and IL-1β increased. TEM revealed mitochondrial damage, and SEM revealed specific pyroptotic changes, such as cell membrane pore changes and cytoplasmic extravasation. Increased ROS levels and nuclear translocation of NR3C2 were also observed. These pyroptosis-related changes were reversed by esaxerenone. Conclusions: Aldosterone activates the MR and mediates mitochondrial damage, thereby inducing pyroptosis in VSMCs via the NLRP3/caspase-1 pathway. Esaxerenone inhibits MR activation and reduces mitochondrial damage and oxidative stress, thereby inhibiting pyroptosis.

The present study evaluated the antiseizure and neuroprotective effects of sodium houttuyfonate (SH), a derivative of Houttuynia cordata Thunb. (H. cordata), in a kainic acid (KA)- induced seizure rat model and its underlying mechanism. Sprague Dawley rats were administered normal saline, SH (50 or 100 mg/kg), or carbamazepine (300 mg/kg) by oral gavage for seven consecutive days before the intraperitoneal administration of KA (15 mg/kg). SH showed antiseizure effects at a dose of 100 mg/kg; it prolonged seizure latency and decreased seizure scores. SH also significantly decreased neuronal loss in the hippocampi of KA-treated rats, which was associated with the prevention of glutamate level increase, the upregulation of glutamate reuptake-associated proteins (excitatory amino acid transporters 1–3), glutamate metabolism enzyme glutamine synthetase, the downregulation of the glutamate synthesis enzyme glutaminase, and significant alterations in the expression of AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor) and NMDA (N-methyl-D-aspartic acid receptor) receptor subunits in the hippocampus. Furthermore, the effects of SH were similar to those of the antiseizure drug carbamazepine. Therefore, the results of the present study suggest that SH has antiseizure effects on KA-induced seizures, possibly through the prevention of glutamatergic alterations. Our findings suggest that SH is a potential alternative treatment that may prevent seizures by preserving the normal glutamatergic system.

Abstract Background To introduce a new and simple classification and management of coronary artery involvement in aortic dissection and report results. Methods Coronary artery involvement was classified into two types according to the integrity of coronary intima: simple lesion (type S) and complex lesion (type C). Complex lesions were treated by CABG and simple lesions were treated by ostial repair or reimplantation. Data were collected and analyzed retrospectively. Results From January 2010 to December 2019, 267 consecutive patients were enrolled in the study, and among them complex lesions occurred in 27 patients (11.1%) and simple lesions was found in 240 patients(89.9%). Eleven untreated vessels with simple lesion were found to be involved again in the same operation and treated by CABG. The two type groups had comparable operative mortality (type S vs. type C, 9.6% vs. 18.5%, P = 0.28). 221 patients received follow-up with a median duration of 52 months. The overall survival rates at 1, 5, and 10 years postoperatively were 88.9%, 85.7%, and 79.8% in type S group and 79.2%, 79.2%, and 79.2% in type C group, respectively (P = 0.47). For the patients who received CABG and survived at discharge, radiographic follow-up with a median duration of 28 (IQR 7-55.5) months showed the freedom from occlusion of vein graft at 1, 5, and 10 years postoperatively were 87.5%, 70.0%, 28.0%. Conclusions According to the new classification, two types of lesions could be treated by corresponding methods with satisfactory early and long-term results. Unrepaired coronary artery was at a risk of re-involvement. Vein graft onto arteries without atherosclerosis still had a high occlusion rate.

With the development of artificial intelligence and breakthroughs in deep learning, large-scale foundation models (FMs), such as generative pre-trained transformer (GPT), Sora, etc., have achieved remarkable results in many fields including natural language processing and computer vision. The application of FMs in autonomous driving holds considerable promise. For example, they can contribute to enhancing scene understanding and reasoning. By pre-training on rich linguistic and visual data, FMs can understand and interpret various elements in a driving scene, and provide cognitive reasoning to give linguistic and action instructions for driving decisions and planning. Furthermore, FMs can augment data based on the understanding of driving scenarios to provide feasible scenes of those rare occurrences in the long tail distribution that are unlikely to be encountered during routine driving and data collection. The enhancement can subsequently lead to improvement in the accuracy and reliability of autonomous driving systems. Another testament to the potential of FMs’ applications lies in world models, exemplified by the DREAMER series, which showcases the ability to comprehend physical laws and dynamics. Learning from massive data under the paradigm of self-supervised learning, world models can generate unseen yet plausible driving environments, facilitating the enhancement in the prediction of road users’ behaviors and the off-line training of driving strategies. In this paper, we synthesize the applications and future trends of FMs in autonomous driving. By utilizing the powerful capabilities of FMs, we strive to tackle the potential issues stemming from the long-tail distribution in autonomous driving, consequently advancing overall safety in this domain.

Among the 17 Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the 13th SDG is a call for action to combat climate change. Moreover, SDGs 14 and 15 claim the protection and conservation of life below water and life on land, respectively. In this work, we provide a literature-founded overview of application areas, in which computer audition – a powerful but in this context so far hardly considered technology, combining audio signal processing and machine intelligence – is employed to monitor our ecosystem with the potential to identify ecologically critical processes or states. We distinguish between applications related to organisms, such as species richness analysis and plant health monitoring, and applications related to the environment, such as melting ice monitoring or wildfire detection. This work positions computer audition in relation to alternative approaches by discussing methodological strengths and limitations, as well as ethical aspects. We conclude with an urgent call to action to the research community for a greater involvement of audio intelligence methodology in future ecosystem monitoring approaches.

Platelets play a vital role in the formation of dangerous arterial thrombosis. Platelets are activated by adhesive proteins or soluble agonists through their specific receptors. The receptor-mediated signaling pathways lead to common signaling events, which result in shape changes and inside–out signaling, leading fibrinogen binding to glycoprotein IIb/IIIa complex (integrin αIIbβ3). This interaction initiates integrin αIIbβ3-mediated outside-in signaling, subsequently culminating in granule secretion and aggregation. Myricetin is a flavonoid that occurs in a variety of plants. Although myricetin has been demonstrated to have several bioactive properties, its role in platelet activation has not been extensively studied. The present study demonstrated the ability of myricetin to inhibit platelet aggregation stimulated by collagen, thrombin, and U46619. Myricetin reduced the ATP-release, cytosolic Ca2+ mobilization, and P-selectin expression and the activation of PLCγ2/PKC, PI3K/Akt/GSK3β, and MAPK. Myricetin exerted a direct inhibitory effect on the activation of integrin αIIbβ3 by disrupting the binding between FITC-PAC-1 and the integrin. Moreover, myricetin suppressed integrin αIIbβ3-mediated outside–in signaling, such as integrin β3, Src, and Syk phosphorylation on immobilized fibrinogen. In animal studies, myricetin significantly prolonged the occlusion time of thrombotic platelet plug formation in mesenteric microvessels without extending bleeding time. This study concludes that myricetin is a natural integrin αIIbβ3 inhibitor and a novel antithrombotic agent.

The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Models (LLMs) have demonstrated exceptional capabilities in text understanding, generation, and knowledge inference, opening up exciting avenues for IR research. LLMs not only facilitate generative retrieval but also offer improved solutions for user understanding, model evaluation, and user-system interactions. More importantly, the synergistic relationship among IR models, LLMs, and humans forms a new technical paradigm that is more powerful for information seeking. IR models provide real-time and relevant information, LLMs contribute internal knowledge, and humans play a central role of demanders and evaluators to the reliability of information services. Nevertheless, significant challenges exist, including computational costs, credibility concerns, domain-specific limitations, and ethical considerations. To thoroughly discuss the transformative impact of LLMs on IR research, the Chinese IR community conducted a strategic workshop in April 2023, yielding valuable insights. This paper provides a summary of the workshop’s outcomes, including the rethinking of IR’s core values, the mutual enhancement of LLMs and IR, the proposal of a novel IR technical paradigm, and open challenges.

A major challenge in analyzing scRNA-seq data arises from challenges related to dimensionality and the prevalence of dropout events. Here the authors develop a deep graph learning method called scMGCA based on a graph-embedding autoencoder that simultaneously learns cell-cell topology representation and cluster assignments, outperforming other state-of-the-art models across multiple platforms.

Marine debris significantly influences the environment and economics of marine ecosystems. Measures to ban illegally discarded materials using monitoring techniques are expected to mitigate marine debris mismanagement. For example, derelict oyster farming rafts along the southwestern coast of Taiwan have been a source of marine debris pollution since the 1980s. An efficient inspection system is an urgent requirement for monitoring oyster farming areas and, is expected to implement control and surveillance measures for litter discarded from coastal fisheries. To address this issue, this study examined combinations of radio frequency identification (RFID), drone archiving, and onshore receiving systems to ascertain the positions of oyster rafts and their owners with digitally tagged labels. The results showed that the two proposed monitoring systems are feasible for use in marine environments. The RFID signals archived by the drone reached 100% of the 200 tags with a spatial bias ranging from 2.38 to 59.99 m. RFID-GPS hybrid tag signals received by the onshore station covered 100% of the 20 tags with spatial bias ranging from 1.27 to 10.47 m. The RFID-GPS hybrid system was confirmed as a feasible approach for monitoring oyster rafts within 3 km of the coast. The real-time (1 h intervals) position and attributes of each raft detected by the system indicated that our designed techniques enhance responsible fishery surveillance and management of coastal aquaculture worldwide.

Material exchange between oceans and currents is crucial for biogeochemical processes in marginal seas, such as the Kuroshio intrusion in the Luzon Strait, which contributes to nutrient and phytoplankton growth in the adjacent water. Therefore, it is necessary to understand changes in major current systems and their possible effects on marine ecology. In this study, we applied an edge-detection method to satellite-derived sea-surface temperature (SST) images to identify the SST front as the index of Kuroshio intrusion during 1985–2017. Chlorophyll-a (Chl-a) concentrations and geostrophic currents (determined from satellite observations after 1993) were examined by comparing long-term variations related to the Kuroshio front using empirical-mode decomposition analysis. The Kuroshio intrusion into the Luzon Strait gradually decreased after the 1990s, as did the Chl-a concentrations and current speed in the Strait. In contrast, the speed of the Kuroshio Current in the eastern Philippine tended to increase, indicating that the northward Kuroshio Current from the eastern Philippines became stronger, curtailing the westward intrusion of the branch current into the Luzon Strait. The speed of the Kuroshio Current correlated with the bifurcation of the North Equatorial Current (NEC), which is upstream of the Kuroshio Current starting from the southeast Philippines. Therefore, the NEC bifurcation latitude may have shifted more southward, which strengthened the water mass and current speed of the Kuroshio, resulting in decreased westward motion of the Kuroshio through the Luzon Strait. Consequently, the weakening Kuroshio intrusion may have caused a decreasing trend of biogeochemical processes in the South China Sea.

Vehicle (related particulate matter) emissions, including primary vehicle (related particulate matter) emissions, secondary nitrate, and road dust, have become an important source of fine particulate matter (PM _2.5 ) in many cities across the world. The relationship between vehicle emissions and PM _2.5 during vehicle restrictions has not yet been revealed using field observational data. To address this issue, a three-month field campaign on physical and chemical characteristics of PM _2.5 at hourly resolution was conducted in Lanzhou, an urban basin with a semi-arid climate. The Lanzhou municipal government implemented more strict vehicle restriction measure during the latter part of field campaign period. The concentration of nitrogen oxides (NO _x ) and PM _2.5 decreased by 15.6% and 10.6%, respectively during the strict vehicle restriction period. The daily traffic fluxes decreased by 11.8% due to the vehicle restriction measure. The vehicle emission reduction led to a decrease of 2.43 μ g·m ^−3 in PM _2.5 , including the decrease of primary vehicle emissions, secondary nitrate, and road dust. The contribution of vehicle emissions to PM _2.5 decreased by 9.0% based on the results derived from a positive matrix factorization model. The sources other than vehicle emissions increased by 0.2 μ g·m ^−3 . Combining all evidence from the observations, the reduction of vehicle emissions is almost equal to the observed reduction in PM _2.5 . A further extrapolation that 9.0% reduction in vehicle emissions led to the observed reduction in PM _2.5 (2.32 μg·m ^−3 ). This study clearly quantifies the vehicle restriction related PM _2.5 reduction using field observations. The results provide scientific support for the implementation of effective vehicle emission reduction measures.

Abstract Objective One-staged surgical treatment of aortic coarctation combined with cardiac anomalies is challenging. We aim to evaluate the feasibility of bilateral aortofemoral bypass technique in one-staged surgery treating coractation by comparing surgical outcomes with catheter intervention plus stent (hybrid). Methods Between January 2012 and December 2017, 50 patients underwent one-staged surgical procedures to treat coarctation and repair concomitant cardiac anomalies, like aortic root dilatation, cardiac valvular disease and so on. Among them, 30 patients underwent bilateral aortofemoral bypass and 20 patients underwent hybrid procedure to treat coarctation. We retrospectively analyzed the data of these patients and compared the early and late results. Results All the baseline clinical characteristics were comparable between groups except that the mean age of bypass group was 39.5 ± 14.0 years which was older than hybrid group (27.9 ± 8.5 years, P = 0.002). Technical success was achieved in all patients, with no hospital death or other severe complications. Immediately after surgery, in bypass and hybrid group, the mean upper-limb systolic blood pressure decreased from 159.4 to 119.7 mmHg and 148.4 to 111.6 mmHg, the median peak systolic gradient decreased from 68.0 to 10 mmHg and 46.5 to 10 mmHg respectively (P = 0.09). And the mean upper-lower limbs gradient decreased from 21.7 to 5.9 mmHg and 21.0 to 2.7 mmHg respectively (P = 0.104). The mean follow-up time was 76.92 ± 18.7 in bypass group and 85.4 ± 20.6 months in hybrid group. There were 4 late deaths in bypass group (one died of gastrointestinal bleeding, one died of pulmonary embolism and the other two died of heart failure caused by mechanical prosthetic valve dysfunction). The follow-up peak systolic gradient and other blood pressure parameters showed stable and no differences between two groups. Conclusions The bilateral aortofemoral bypass surgery is a safe and effective method which can be used in one-staged surgical strategy to treat coarctation complicated by cardiac anomalies and can be an alternative to the hybrid method.

Background/purpose: In this study we aimed to investigate the prevalence of abnormal nasality in patients with unilateral rhinosinusitis and their nasality outcomes following functional endoscopic sinus surgery (FESS). Methods: A total of 42 patients with unilateral chronic rhinosinusitis who underwent unilateral FESS between April 2016 and November 2017 were enrolled. Questionnaires on sinonasal symptoms and nasality were recorded. The change in the nasalance score of vowels [a], [i] [u], nasal consonant [m], 2 nasal syllable repetitions, and 2 Chinese sentences were measured. The patients were evaluated preoperatively, 6 months, and 12 months after the operation. The patients were divided into two groups, wide opening surgery and limited surgery, according to the severity of the disease. Results: Among 42 patients, the subjective reports showed that one-third of unilateral chronic rhinosinusitis (CRS) patients had abnormal nasality preoperatively and significant improvement following FESS. The Lund–Mackay score was significantly negatively correlated with preoperative nasalance of [i] and positively correlated with change of nasalance of [i]. The increase in the value of [i] is statistically significant (p = 0.01) following FESS. In the further subgroup analysis, the change in nasalance was significant in the wide opening surgery group, but not in the limited surgery group. Conclusion: Although only one side of the nasal airway was involved, one-third of the patients reported abnormal nasality. In patients with more disease severity who underwent wide opening surgery, the nasalance significantly increased 1 year after FESS. The increase in the objective nasalance score was corresponded to a significant improvement of subjective self-reported nasality assessment postoperatively.

Background: Cancer precision medicine is an effective strategy to fight cancers by bridging genomics and drug discovery to provide specific treatment for patients with different genetic characteristics. Although some public databases and modelling frameworks have been developed through studies on drug response, most of them only considered the ramifications of the drug on the cell line and the effects on the patient still require a huge amount of work to integrate data from various databases and calculations, especially concerning precision treatment. Furthermore, not only efficacy but also the adverse effects of drugs on patients should be taken into account during cancer treatment. However, the adverse effects as essential indicators of drug safety assessment are always neglected.Method: A holistic estimation explores various drugs’ efficacy levels by calculating their potency both in reversing and enhancing cancer-associated gene expression change. And a method for bridging the gap between cell culture and living tissue estimates the effectiveness of a drug on individual patients through the mappings of various cell lines to each person according to their genetic mutation similarities.Result: We predicted the efficacy of FDA-recommended drugs, taking into account both efficacy and toxicity, and obtained consistent results. We also provided an intuitive and easy-to-use web server called DBPOM (http://www.dbpom.net/, a comprehensive database of pharmaco-omics for cancer precision medicine), which not only integrates the above methods but also provides calculation results on more than 10,000 small molecule compounds and drugs. As a one-stop web server, clinicians and drug researchers can also analyze the overall effect of a drug or a drug combination on cancer patients as well as the biological functions that they target. DBPOM is now public, free to use with no login requirement, and contains all the data and code.Conclusion: Both the positive and negative effects of drugs during precision treatment are essential for practical application of drugs. DBPOM based on the two effects will become a vital resource and analysis platform for drug development, drug mechanism studies and the discovery of new therapies.

This study focuses on how butyrate alleviates CAC simulated by AOM-DSS through TLR2 signals and MDSCs, which is still unclear. Our results revealed that butyrate slowed tumorigenesis supported by remission of weight loss, survival index, DAI, pathological dysplasia, the number and size of tumors. Butyrate caused a reduction of proinflammatory factors such as IL-12, IL-6, and TNF-α as well as MDSCs that help tumor immune escape in TME. The up-regulation of TLR2/Myd88/ NF-κB in intestinal tissues of CAC was also significantly inhibited by butyrate. Besides, the inhibition of butyrate on the up -regulation of TLR2 caused by TLR2 agonist Pam3csk4 and DSS inflammatory injury in Caco-2 cells fully proved its anti-inflammatory effect through TLR2 signal pathway. So, the above results implied that by suppressing TLR2 signals, butyrate may decrease the production of IL-6, IL-12, and TNF-α to restrict the MDSCs conscription in TME and halt the CAC progression.

Abstract Myeloid-derived suppressor cells (MDSCs) are derived from bone marrow progenitor cells commonly, which is a heterogeneous cell group composed of immature granulocytes, dendritic cells, macrophages and early undifferentiated bone marrow precursor cells. Its differentiation and immunosuppressive function are regulated by complex network signals, but the specific regulation mechanisms are not yet fully understood. In this study, we found that in mouse of Lewis lung cancer xenograft, long non-coding RNA Snhg6 (lncRNA Snhg6) was highly expressed in tumor-derived MDSCs compared with spleen-derived MDSCs. LncRNA Snhg6 facilitated the differentiation of CD11b+ Ly6G− Ly6Chigh monocytic MDSCs (Mo-MDSCs) rather than CD11b+ Ly6G+ Ly6Clow polymorphonuclear MDSCs (PMN-MDSCs), but did not affect the immunosuppressive function of MDSCs. Notably, lncRNA Snhg6 could inhibit the expression of EZH2 by ubiquitination pathway at protein level rather than mRNA level during the differentiation of mouse bone marrow cells into MDSCs in vitro. EZH2 may be an important factor in the regulation of lncRNA Snhg6 to promote the differentiation of Mo-MDSCs. So what we found may provide new ideas and targets for anti-tumor immunotherapy targeting MDSCs.

Abnormal cell proliferation and epithelial-mesenchymal transition (EMT) are the essential events that induce cancer initiation and progression. A fundamental goal in cancer research is to develop an efficient method to detect mutational genes capable of driving cancer. Although several computational methods have been proposed to identify these key mutations, many of them focus on the association between genetic mutations and functional changes in relevant biological processes, but not their real causality. Causal effect inference provides a way to estimate the real induce effect of a certain mutation on vital biological processes of cancer initiation and progression, through addressing the confounder bias due to neutral mutations and unobserved latent variables. In this study, integrating genomic and transcriptomic data, we construct a novel causal inference model based on a deep variational autoencoder to identify key oncogenic somatic mutations. Applied to 10 cancer types, our method quantifies the causal effect of genetic mutations on cell proliferation and EMT by reducing both observed and unobserved confounding biases. The experimental results indicate that genes with higher mutation frequency do not necessarily mean they are more potent in inducing cancer and promoting cancer development. Moreover, our study fills a gap in the use of machine learning for causal inference to identify oncogenic mutations.

Renal fibrosis is the inevitable pathway of the progression of chronic kidney disease to end-stage renal disease, which manifests as progressive glomerulosclerosis and renal interstitial fibrosis. In a previous study, we observed severe interstitial fibrosis in the contralateral kidneys of 6-month unilateral ureteral obstruction (UUO) rats, which was accompanied by increased macrophage infiltration and phenotypic transformation; after eplerenone administration, these effects were reduced. Therefore, we hypothesized that this effect was closely related to mineralocorticoid receptor (MR) activation induced by the increased aldosterone (ALD) level. In this study, we used uninephrectomy plus continuous aldosterone infusion in mice to observe whether aldosterone induced macrophage-to-myofibroblast transition (MMT) and renal fibrosis and investigated the signaling pathways. Notably, aldosterone induced predominantly M1 macrophage-to-myofibroblast transition by activating MR and upregulating TGF-β1 expression, which promoted renal fibrosis. These effects were antagonized by the MR blocker esaxerenone. These findings suggest that targeting the MR/TGF-β1 pathway may be an effective therapeutic strategy for renal fibrosis.

Renal fibrosis is an inevitable process in the progression of chronic kidney disease (CKD). Angiogenesis plays an important role in this process. Vascular endothelial cells are involved in renal fibrosis by phenotypic transformation and secretion of extracellular matrix. Aldosterone stimulates mineralocorticoid receptor (MR) activation and induces inflammation, which is important for angiogenesis. Clinically, MR blockers (MRBs) have a protective effect on damaged kidneys, which may be associated with inhibition of angiogenesis. In this study, we used aldosterone-infused mice and found that aldosterone induced angiogenesis and that endothelial-mesenchymal transition (EndMT) in neovascular endothelial cells was involved in renal fibrosis. Notably, aldosterone induced inflammation and stimulated macrophages to secrete vascular endothelial growth factor (VEGF) A to regulate angiogenesis by activating MR, whereas EndMT occurred in response to transforming growth factor-β1 (TGF-β1) induction and participated in renal fibrosis. These effects were antagonized by the MRB esaxerenone. These findings suggest that reducing angiogenesis may be an effective strategy for treating renal fibrosis.

Abstract Background Panic disorder (PD) is thought to be related with deficits in emotion regulation, especially in cognitive reappraisal. According to the cognitive model, PD patients’ intrinsic and unconscious misappraisal strategies are the cause of panic attacks. However, no studies have yet been performed to explore the underlying neuromechanism of cognitive reappraisal that occur on an unconscious level in PD patients. Methods Twenty-six patients with PD and 25 healthy controls (HC) performed a fully-verified event-block design emotional regulation task aimed at investigating responses of implicit cognitive reappraisal during an fMRI scan. Participants passively viewed negatively valanced pictures that were beforehand neutrally, positively, or adversely portrayed in the task. Results Whole-brain analysis of fMRI data showed that PD patients exhibited less activation in the right dorsolateral prefrontal cortex (dlPFC) and right dorsomedial prefrontal cortex (dmPFC) compared to HC, but presented greater activation in parietal cortex when negative pictures were preceded by positive/neutral vs negative descriptions. Simultaneously, interactive effects of Group × Condition were observed in the right amygdala across both groups. Furthermore, activation in dlPFC and dmPFC was is negatively correlated to severity of anxiety and panic in PD when negative images were preceded by non-negative vs negative descriptions. Conclusions Emotional dysregulation in PD is likely the result of deficient activation in dlPFC and dmPFC during implicit cognitive reappraisal, in line with impaired automatic top-down regulation. Correlations between severity of anxiety and panic attack and activation of right dlPFC and dmPFC suggest that the failure to engage prefrontal region during implicit cognitive reappraisal might be associated wtih the severity of anxiety and panic; such functional patterns might be the target of possible treatments.

ObjectiveTo develop and validate a nomogram model to predict postoperative 30-day mortality in acute type A aortic dissection patients receiving total aortic arch replacement with frozen elephant trunk technique.MethodClinical data on 1,156 consecutive acute type A aortic dissection patients who got total aortic arch replacement using the frozen elephant trunk technique was collected from January 2010 to December 2020. These patients were divided into training and testing cohorts at random with a ratio of 7:3. To predict postoperative 30-day mortality, a nomogram was established in the training set using the logistic regression model. The novel nomogram was then validated in the testing set. The nomogram's calibration and discrimination were evaluated. In addition, we created four machine learning prediction models in the training set. In terms of calibration and discrimination, the nomogram was compared to these machine learning models in testing set.ResultsLeft ventricular end-diastolic diameter 4 h were independent predictors of the 30-day mortality. The nomogram based on these 6 predictors manifested satisfying calibration and discrimination. In testing set, the nomogram outperformed the other 4 machine learning models.ConclusionThe novel nomogram is a simple and effective tool to predict 30-day mortality rate for acute type A aortic dissection patients undergoing total aortic arch replacement with frozen elephant trunk technique.

Precursor regulation has been an effective strategy to improve carotenoid production and the availability of novel precursor synthases facilitates engineering improvements. In this work, the putative geranylgeranyl pyrophosphate synthase encoding gene (AlGGPPS) and isopentenyl pyrophosphate isomerase encoding gene (AlIDI) from Aurantiochytrium limacinum MYA-1381 were isolated. We applied the excavated AlGGPPS and AlIDI to the de novo β-carotene biosynthetic pathway in Escherichia coli for functional identification and engineering application. Results showed that the two novel genes both functioned in the synthesis of β-carotene. Furthermore, AlGGPPS and AlIDI performed better than the original or endogenous one, with 39.7% and 80.9% increases in β-carotene production, respectively. Due to the coordinated expression of the 2 functional genes, β-carotene content of the modified carotenoid-producing E. coli accumulated a 2.99-fold yield of the initial EBIY strain in 12 h, reaching 10.99 mg/L in flask culture. This study helped to broaden current understanding of the carotenoid biosynthetic pathway in Aurantiochytrium and provided novel functional elements for carotenoid engineering improvements.

Single image deblurring has achieved significant progress for natural daytime images. Saturation is a common phenomenon in blurry images, due to the low light conditions and long exposure times. However, conventional linear deblurring methods usually deal with natural blurry images well but result in severe ringing artifacts when recovering low-light saturated blurry images. To solve this problem, we formulate the saturation deblurring problem as a nonlinear model, in which all the saturated and unsaturated pixels are modeled adaptively. Specifically, we additionally introduce a nonlinear function to the convolution operator to accommodate the procedure of the saturation in the presence of the blurring. The proposed method has two advantages over previous methods. On the one hand, the proposed method achieves the same high quality of restoring the natural image as seen in conventional deblurring methods, while also reducing the estimation errors in saturated areas and suppressing ringing artifacts. On the other hand, compared with the recent saturated-based deblurring methods, the proposed method captures the formation of unsaturated and saturated degradations straightforwardly rather than with cumbersome and error-prone detection steps. Note that, this nonlinear degradation model can be naturally formulated into a maximum-a posterioriframework, and can be efficiently decoupled into several solvable sub-problems via the alternating direction method of multipliers (ADMM). Experimental results on both synthetic and real-world images demonstrate that the proposed deblurring algorithm outperforms the state-of-the-art low-light saturation-based deblurring methods.

Recently, deep learning-based methods are proposed for hyperspectral images (HSIs) denoising. Among them, unsupervised methods such as deep image prior (DIP)-based methods have received much attention because these methods do not require any training data. However, DIP-based methods suffer from the semiconvergence behavior, i.e., the iteration of DIP-based methods needs to terminate by referring to the ground-truth image at the optimal iteration point. In this article, we propose the spatial-spectral constrained deep image prior (S2DIP) for the HSI mixed noise removal. Specifically, we integrate the DIP, the spatial-spectral total variation regularization term, and the $\ell _1$-norm sparse term to respectively capture the deep prior of the clean HSI, the spatial-spectral local smooth prior of the clean HSI, and the sparse prior of noise. The proposed S2DIP jointly leverages the expressive power brought from the deep convolutional neural network without any training data and exploits the HSI and noise structures via hand-crafted priors. Thus, our method avoids the semiconvergence behavior of DIP-based methods. Meanwhile, our method largely enhances the HSI denoising ability of DIP-based methods. To tackle the corresponding model, we utilize the alternating direction multiplier method algorithm. Extensive experiments demonstrate that our method outperforms model-based and deep learning-based state-of-the-art HSI denoising methods.

BackgroundTo compare outcomes between sinus replacement (SR) and conservative repair (CR) for dissected roots with normal size.MethodsFrom October 2018 to April 2021, a prospective cohort study was carried out. Patients were assigned to two groups (SR group and CR group) according to whether they underwent sinus replacement. Propensity score matching was applied to adjust preoperative variables and Kaplan–Meier method was used for survival analysis.ResultsThree hundred and eighty-seven patients were enrolled. In the whole cohort, 18 patients (4.7%) died postoperatively. The operative mortality of SR group was comparable to CR group (3.2% vs. 6.0%, p = 0.192 before matching; 3.5% vs. 7.0%, p = 0.267 after matching) and the incidence of hemostasis management under restarted cardiopulmonary bypass for root bleeding was lower in SR group (1.6% vs. 7.0%, p = 0.002 before matching; 2.1% vs. 8.5%, p = 0.03 after matching). The median follow-up duration was 12 months. There were 3 reoperations in the CR group. The estimated cumulative event rate of reoperation was 1.1 % at 12 months and 1.6% at 24 months in CR group, with a trend of a lower rate in the SR group (log-rank p = 0.089 before matching, p = 0.075 after matching). There was one late death in each group. The estimated cumulative event rate of death was 3.8% at 12 months and 24 months in the SR group, and was 6.6% in the CR group with no significant difference (log-rank p = 0.218 before matching, p = 0.120 after matching). Aortic regurgitation significantly improved postoperatively and remained stable during follow-up.ConclusionsSinus replacement is a simple, safe, and effective technique for repairing severely dissected sinus with a comparable time spent in operation and excellent immediate and short-term results. It had the advantages of eliminating false lumen and avoiding aortic root bleeding.

Abstract Background Acute type A aortic dissection with a dissection flap extending into the sinus segment often involves the commissures and the coronary ostia. In most cases, the intimal flap must be retained in order to restore aortic valve competence and reconstruct the coronary ostia. Residual dissection flap has the potential risks of proximal bleeding and adverse effects on long-term durability. We established a novel technique to reconstruct the aortic root using a pericardial autograft and significantly reduce remnant dissection tissues. Case presentation A 50-year-old female was admitted to our center with acute anterior chest pain and backache lasting about 10 h. Computed tomographic (CT) scans showed type A aortic dissection, with both coronary ostia being involved. Doppler echocardiography showed moderate aortic insufficiency. The dissection intimal flap was removed to the normal aorta wall near the annulus at the noncoronary sinus, leaving a 5 mm rim of intimal flap near the commissures and coronary ostia. Using a pericardial patch as a new aortic wall to reconstruct the root while preserving the aortic adventitia to fix and strengthen the new pericardial aortic wall. Ascending aorta and total arch replacement combined with frozen elephant trunk procedure was performed at the same time. The patient got an uneventful postoperative course. Conclusion Aortic root repair with a pericardial autograft is a safe and effective technique to treat acute type A dissection involving the sinus. Using this technique, residual dissection tissues could be significantly reduced, which subsequently decreases the risk of proximal bleeding and hence increases long-term durability.

Abstract Background Nonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed. However, the performance of their use in EEG data analysis has not been fully compared. Here, we provide a comparison of four NMF algorithms in terms of accuracy of estimation, stability (repeatability of the results) and time complexity of algorithms with simulated data. In the practical application of NMF algorithms, stability plays an important role, which was an emphasis in the comparison. A Hierarchical clustering algorithm was implemented to evaluate the stability of NMF algorithms. Results In simulation-based comprehensive analysis of fit, stability, accuracy of estimation and time complexity, hierarchical alternating least squares (HALS) low-rank NMF algorithm (lraNMF_HALS) outperformed the other three NMF algorithms. In the application of lraNMF_HALS for real resting-state EEG data analysis, stable and interpretable features were extracted. Conclusion Based on the results of assessment, our recommendation is to use lraNMF_HALS, providing the most accurate and robust estimation.

In this study, the robust H∞ event-triggered team formation tracking control design of multi-VTOL-UAVs in networked system is investigated. To describe the realistic networked system and UAV model, the intrinsic continuous Wiener random fluctuation, discontinuous Poisson random fluctuations, external disturbances and time-varying delays of wireless network are formulated in the proposed nonlinear stochastic jump diffusion system structure. By combining the event-triggered multi-UAV dynamic models and reference model into an augmented system, the robust H∞ event-triggered multi-UAV networked team tracking problem can be transformed to a Hamilton-Jacobi inequality(HJI)-constraint optimization problem. Due to the difficulties in solving HJI-constraint optimization problem, for practical application, the T-S fuzzy techniques are adopted to efficiently approximate the nonlinear multi-UAVs system by a set of local linearized networked systems. Thus, the HJI-constraint optimization problem for the H∞ event-triggered robust formation team tracking control can be transformed to a linear matrix inequality(LMI)-constraint optimization problem and can be easily solved by the convex optimization techniques. Finally, a simulation example is given to validate the effectiveness of the proposed event-triggered robust H∞ team formation tracking control for the multi-VTOL-UAV system.

This paper investigates the adaptive finite-time tracking control problem for a class of switched nonlinear systems with unmodeled dynamics. In practical applications, switched systems usually possess unfavourable factors, such as unmeasured states and unmodeled dynamics both of which are taken into account in this paper. A dynamic signal defined with a special property is introduced in this paper to improve control performance while garanteeing stability of the controlled system. By designing an observer, a finite-time adaptive output-feedback tracking controller is constructed via the backstepping technique. Then, the finite-time stability problem of the considered systems is studied. It is shown that all the signals in the closed-loop system are semi-globally uniformly finite-time bounded (SGFUB), and the observer errors and tracking errors can be regulated to a small neighborhood of the origin by choosing appropriate parameters. It is noted that, the design process is less complex than some existing results on tackling control problems of nonlinear systems with unmodeled dynamics. In the example, the simulation result testifies the effectiveness of the proposed method.

BackgroundThe optimal arterial cannulation site for acute aortic dissection repair is unclear, especially for complex arch surgery. Axillary artery cannulation is widely accepted but adding femoral artery cannulation to it was considered to potentially improve perfusion and early outcomes. To clarify this point, a comparison of perioperative outcomes for these two different cannulation strategies was conducted regarding the pathological features of dissection.MethodsFrom January 2010 to December 2019, 927 consecutive patients underwent a total arch replacement combined with frozen elephant trunk for acute type A aortic dissection. The data, including detailed pathological features, were retrospectively collected and analyzed. Propensity score matching and multivariate logistic regression analysis were used for adjusting confounders that are potentially related to the outcome.ResultsA total of 523 patients (56.3%) accepted a dual arterial cannulation (DAC group), and 406 patients (43.7%) received a single axillary artery cannulation (SAC group). In total, 388 pairs of patients were well-matched. Whether before or after adjusting the preoperative characteristics by matching, there were no significant differences in operative mortality (6.7 vs. 5.4%, P = 0.420 before matching; 5.4 vs. 5.4%, P = 1 after matching), stroke (6.7 vs. 5.4%, P = 0.420 before matching; 6.4 vs. 5.2%, P = 0.435 after matching), spinal cord injury (5 vs. 5.7%, P = 0.640 before matching; 5.4 vs. 5.7%, P = 1. After matching), and acute renal failure requiring dialysis (13.8 vs. 9.6%, P =0.050 before matching; 12.6 vs. 9.5%, P = 0.174) between the two groups. Dual arterial cannulation was not an independent protective factor of operative mortality (odds ratio [OR] 1.01, 95% confidence interval [CI] 0.55–1.86), stroke (OR 1.17, 95% CI 0.65–2.11), spinal cord injury (OR 1.17, 95% CI 0.65–2.11), and acute renal failure requiring continuous renal replacement therapy (CRRT) (OR 1.24, 95% CI 0.78–1.97) after adjusting for confounding factors by multivariable logistic regression analysis. In the subgroup analysis, no advantage of dual arterial cannulation was found for a particular population.ConclusionsSingle axillary artery cannulation was competent in the complex arch repair for acute aortic dissection, presenting with a satisfactory result as dual arterial cannulation. Adding femoral artery cannulation was necessary when a sufficient flow volume could not be achieved by axillary artery cannulation or when a lower limb malperfusion existed.

This paper mainly takes Zhacun goldmine as the research object and carries out research on the metallogenic system and genesis of the deposit in the area. The research methods are as follows: according to the geological characteristics of the metallogenic mining area in the Zhacun goldmine, combined with the comparative analysis of the metallogenic age, alteration characteristics and lithology between the Zhacun goldmine and the Lianhuashan alkali rich rock mass, and the analysis of the isotopic data in the Zhacun goldmine, this paper demonstrates that the magmatic activity of the Lianhuashan quartz monzonite porphyry plays an important role in the mineralization of this area, which is both an important ore source and fluid source. It is also the main heat source driving the circulation of ore-forming fluid. On this basis, through the analysis of the metallogenic elements in the area, the metallogenic system model of Zhacun goldmine is constructed. It is considered that under the action of long-term horizontal compressive stress, the atmospheric precipitation infiltrated into the formation continued to penetrate along the fractures and fissures to deep crust and finally mixed with the magmatic water sealed in the thick formation. During this period, a series of shallow and ultrashallow porphyry mass intruded, providing heat source and part of the ore-forming materials and resulting in incomplete homogenization under high temperature and high pressure, which formed highly mineralized mixed water. Under the combined action of long-term compressive stress and various deep thermal dynamics, these mineral fluids migrated along the buried deep faults near the core of the duplex anticline to the upper part of the crust. When the metal elements in these ore fluids migrated over long distances to the nappe fault zone of the gold-bearing fracture zone, the gold began to precipitate, and the native gold and the coarse-grained pyrite and quartz formed at the same time or earlier started to fill the fracture zone along the fissures and accumulate into minerals. Then, through the analysis of metallogenic conditions, gold mineralization process, and genetic mechanism of the deposit, it is proposed that the genetic type of the ore deposit in this area is magmatic mesothermal-epithermal gold deposit. The establishment of metallogenic system model in Zhacun goldmine will provide theoretical and practical guidance for deep and peripheral prospecting prediction in the area, carry out targeted and reasonable prediction, and improve prospecting effectiveness.

Since the COronaVIrus Disease 2019 (COVID-19) outbreak, developing a digital diagnostic tool to detect COVID-19 from respiratory sounds with computer audition has become an essential topic due to its advantages of being swift, low-cost, and eco-friendly. However, prior studies mainly focused on small-scale COVID-19 datasets. To build a robust model, the large-scale multi-sound FluSense dataset is utilised to help detect COVID-19 from cough sounds in this study. Due to the gap between FluSense and the COVID-19-related datasets consisting of cough only, the transfer learning framework (namely CovNet) is proposed and applied rather than simply augmenting the training data with FluSense. The CovNet contains (i) a parameter transferring strategy and (ii) an embedding incorporation strategy. Specifically, to validate the CovNet's effectiveness, it is used to transfer knowledge from FluSense to COUGHVID, a large-scale cough sound database of COVID-19 negative and COVID-19 positive individuals. The trained model on FluSense and COUGHVID is further applied under the CovNet to another two small-scale cough datasets for COVID-19 detection, the COVID-19 cough sub-challenge (CCS) database in the INTERSPEECH Computational Paralinguistics challengE (ComParE) challenge and the DiCOVA Track-1 database. By training four simple convolutional neural networks (CNNs) in the transfer learning framework, our approach achieves an absolute improvement of 3.57% over the baseline of DiCOVA Track-1 validation of the area under the receiver operating characteristic curve (ROC AUC) and an absolute improvement of 1.73% over the baseline of ComParE CCS test unweighted average recall (UAR).

To avoid brittle fracture and plastic yielding of steel beam-to-column connections under earthquakes, a new beam-to-column connection of steel structures with all-steel buckling restrained braces (BRBs) is proposed. The all-steel BRB is connected to the steel beam and column members through pins to form a new connection system. Taking the T-shaped beam-to-column connection steel structure as the research object, two structural types with an all-steel BRB installed on one side (S-type) and two sides (D-type) are considered. Theoretical equations of the connection system’s initial stiffness and yield load are derived through the mechanical models. The yield load, main strain distribution, energy dissipation, and stiffness of the connection system are investigated through quasi-static tests to verify the connection system’s seismic performance. The tests revealed that the proposed new connection system is capable of achieving a stable hysteresis behavior. At the end of loading, the beam and column members are not damaged, and the plastic deformation is concentrated in the plastic energy dissipating replaceable BRB, and the beam and column basically remain elastic. The proposed equations approximately estimated the load response of the proposed connection system. The results show that the damage mode of this new connection system under seismic loading is BRB yielding, with an elastic response from the beam-column members.

In order to deal with the uncertainty of measurement noise, particularly for outlier types of multipath interference and non-line of sight (NLOS) reception, this paper proposes a novel method for processing the navigation states of the Global Positioning System (GPS) that combines the maximum correntropy criterion (MCC) and the interacting multiple model (IMM), with an extended Kalman Filter (EKF). Multipath mitigation is essential for increased positioning accuracy since multipath interference is one of the primary sources of errors. Nonlinear filtering with IMM configuration uses filter structural adaptation. In processing time-varying satellite signal standards for GPS navigation, it offers an alternative for creating the adaptive filter. A collection of switching models built on a method of multiple model estimation can be used to characterize the uncertainty of the noise. Even though most noise in real life is non-Gaussian, time-varying, and of fluctuating strength, the standard EKF operates effectively when the noise is Gaussian. The performance of EKF will drastically decline if the signals appear non-Gaussian. The underlying system disrupted by heavy-tailed, non-Gaussian impulsive sounds could be better since the EKF employs second-order statistical information. The MCC is a method for comparing two random variables based on higher-order signal statistics. The maximum correntropy-extended Kalman filter (MCEKF), which uses the MCC rather than the minimal mean square error (MMSE) as the optimization criterion, is used to enhance performance in non-Gaussian situations. Finally, a performance evaluation will be conducted to compare the effectiveness of the suggested strategy in improving positioning to alternative system designs.

Ongoing electroencephalography (EEG) signals are recorded as a mixture of stimulus-elicited EEG, spontaneous EEG and noises, which poses a huge challenge to current data analyzing techniques, especially when different groups of participants are expected to have common or highly correlated brain activities and some individual dynamics. In this study, we proposed a data-driven shared and unshared feature extraction framework based on nonnegative and coupled tensor factorization, which aims to conduct group-level analysis for the EEG signals from major depression disorder (MDD) patients and healthy controls (HC) when freely listening to music. Constrained tensor factorization not only preserves the multilinear structure of the data, but also considers the common and individual components between the data. The proposed framework, combined with music information retrieval, correlation analysis, and hierarchical clustering, facilitated the simultaneous extraction of shared and unshared spatio-temporal-spectral feature patterns between/in MDD and HC groups. Finally, we obtained two shared feature patterns between MDD and HC groups, and obtained totally three individual feature patterns from HC and MDD groups. The results showed that the MDD and HC groups triggered similar brain dynamics when listening to music, but at the same time, MDD patients also brought some changes in brain oscillatory network characteristics along with music perception. These changes may provide some basis for the clinical diagnosis and the treatment of MDD patients.