ABSTRACT
Electroencephalography (EEG)-based applications in brain-computer interfaces (BCIs), neurological disease diagnosis, rehabilitation, etc., rely on supervised approaches such as classification that requires given labels. However, with the ever-increasing amount of EEG data, incomplete or incorrectly labeled or unlabeled EEG data are increasing. It likely degrades the performance of supervised approaches. In this work, we put forward a novel unsupervised exploratory EEG analysis solution by clustering based on low-dimensional prototypes in latent space that are associated with the respective clusters. Having the prototype as a baseline of each cluster, a compositive similarity is defined to act as the critic function in clustering, which incorporates similarities on three levels. The approach is implemented with a Generative Adversarial Network (GAN), termed W-SLOGAN, by extending the Stein Latent Optimization for GANs (SLOGAN). The Gaussian Mixture Model (GMM) is utilized as the latent distribution to adapt to the diversity of EEG signal patterns. The W-SLOGAN ensures that images generated from each Gaussian component belong to the associated cluster. The adaptively learned Gaussian mixing coefficients make the model remain effective in dealing with an imbalanced dataset. By applying the proposed approach to two public EEG or intracranial EEG (iEEG) epilepsy datasets, our experiments demonstrate that the clustering results are close to the classification of the data. Moreover, we present several findings that were discovered by intra-class clustering and cross-analysis of clustering and classification. They show that the approach is attractive in practice in the diagnosis of the epileptic subtype, multiple labelling of EEG data, etc.
Subject(s)
Brain-Computer Interfaces , Electroencephalography , Electroencephalography/methods , Humans , Cluster Analysis , Epilepsy/diagnosis , Epilepsy/physiopathology , Algorithms , Signal Processing, Computer-Assisted , Neural Networks, ComputerABSTRACT
BACKGROUND: We aimed to evaluate the diagnostic capabilities of Chinese laboratories for inherited metabolic disorders (IMDs) using gas chromatography-mass spectrometry (GC-MS) on urine samples. Meanwhile, based on the result of the pilot external quality assessment (EQA) scheme, we hope to establish a standardized and reliable procedure for future EQA practice. METHODS: We recruited laboratories that participated in the EQA of quantitative analysis of urinary organic acids with GC-MS before joining the surveys. In each survey, a set of five real urine samples was distributed to each participant. The participants should analyze the sample by GC-MS and report the "analytical result", "the most likely diagnosis", and "recommendation for further tests" to the NCCL before the deadline. RESULTS: A total of 21 laboratories participated in the scheme. The pass rates were 94.4% in 2020 and 89.5% in 2021. For all eight IMDs tested, the analytical proficiency rates ranged from 84.7% - 100%, and the interpretational performance rate ranged from 88.2% - 97.0%. The performance on hyperphenylalaninemia (HPA), 3-methylcrotonyl-CoA carboxylase deficiency (MCCD), and ethylmalonic encephalopathy (EE) samples were not satisfactory. CONCLUSIONS: In general, the participants of this pilot EQA scheme are equipped with the basic capability for qualitative organic acid analysis and interpretation of the results. Limited by the small size of laboratories and samples involved, this activity could not fully reflect the state of clinical practice of Chinese laboratories. NCCL will improve the EQA scheme and implement more EQA activities in the future.
Subject(s)
Metabolic Diseases , Phenylketonurias , Humans , Quality Control , Laboratories , Metabolic Diseases/diagnosis , China , Quality Assurance, Health CareABSTRACT
Gait recognition, which aims at identifying individuals by their walking patterns, has achieved great success based on silhouette. The binary silhouette sequence encodes the walking pattern within the sparse boundary representation. Therefore, most pixels in the silhouette are under-sensitive to the walking pattern since the sparse boundary lacks dense spatial-temporal information, which is suitable to be represented with dense texture. To enhance the sensitivity to the walking pattern while maintaining the robustness of recognition, we present a Complementary Learning with neural Architecture SearcH (CLASH) framework, consisting of walking pattern sensitive gait descriptor named dense spatial-temporal field (DSTF) and neural architecture search based complementary learning (NCL). Specifically, DSTF transforms the representation from the sparse binary boundary into the dense distance-based texture, which is sensitive to the walking pattern at the pixel level. Further, NCL presents a task-specific search space for complementary learning, which mutually complements the sensitivity of DSTF and the robustness of the silhouette to represent the walking pattern effectively. Extensive experiments demonstrate the effectiveness of the proposed methods under both in-the-lab and in-the-wild scenarios. On CASIA-B, we achieve rank-1 accuracy of 98.8%, 96.5%, and 89.3% under three conditions. On OU-MVLP, we achieve rank-1 accuracy of 91.9%. Under the latest in-the-wild datasets, we outperform the latest silhouette-based methods by 16.3% and 19.7% on Gait3D and GREW, respectively.
ABSTRACT
BACKGROUND: Arthroscopic bipolar radiofrequency energy (bRFE) is a common method for minimally invasive treatment of cartilage injuries. The benefits of bRFE are still controversial, and its safety has become the focus of attention. OBJECTIVE: This study aimed to reveal the effects of energy setting and recovery period on the efficacy and safety of bRFE. METHODS: The New Zealand white rabbit knee cartilage injury model was established, and bRFE was used to treat the cartilage with different energy settings, including 20 W and 40 W, and recovery periods of 0 and 1 month. By observing the immediate and late results on damaged cartilage, along with chondrocyte apoptosis, the effects of energy setting and recovery period on the efficacy and safety of bRFE were accessed. RESULTS: The pathological conditions, surface profile and chondrocyte viability in the bRFE treatment group produced greater late effects and were significantly better than those in the model group. Nevertheless, bRFE produced a timely injury that resulted in an increased rate of apoptosis (p < 0.05), which was alleviated in subsequent recovery (p < 0.05). CONCLUSIONS: bRFE can effectively trim and improve the cartilage lesion area, and reduce cracks. Although bRFE produced timely chondrocyte damage, this was alleviated on subsequent recovery. Therefore, bRFE with appropriate energy is beneficial to the recovery of cartilage damage, proper attention should be paid to the recovery period.
Subject(s)
Cartilage, Articular , Rabbits , Animals , Cartilage, Articular/injuries , Cartilage, Articular/pathology , Cartilage, Articular/surgery , ChondrocytesABSTRACT
Herein, the coating of MnO2 nanomaterials on the surface of aluminum honeycomb was carried out to meet the requirements of high air velocity, low pressure drop and high activity in ozone removal scenarios. A commercially readily available waterborne silica sol mixed with waterborne acrylate latex was creatively utilized as the binder. A series of coating samples were prepared by spray coating method and evaluated focusing on their adhesion strength and catalytic activity towards ozone decomposition in an air duct at room temperature, by varying MnO2/binder mass ratio and number of sprayings. It was found that the adhesion strength of the catalytic coatings on the aluminum honeycomb increased with the increase of binder mass ratio, but the increased binder made the catalyst particles closely packed, resulting in reduced exposure of active sites and decrease of ozone conversion. Accordingly, catalyst slurry with 81.8 wt.% MnO2 in dry coating and spraying times of two were determined as the optimal process parameters. As-prepared aluminum honeycomb filter with MnO2 layer of 50 µm thickness achieved ozone conversion of 29.3%±1.7% under conditions of air velocity 3.0 m/sec, relative humidity â¼50%, room temperature (26°C) and initial ozone concentration of 200 ppbV. This filter can be well adaptable to indoor air purification equipment operating at high air velocity with low wind resistance.
Subject(s)
Aluminum , Ozone , Manganese Compounds , Oxides , TemperatureABSTRACT
Trace heavy metals exist in drinking water, having great adverse effects on human health and making it a huge challenge to remove. Herein, novel materials have been prepared by a simple and green method using single- (polydopamine (PDA) or 2,3-dimercaptopropanesulfonic sodium (DMPS)) (PDA-OACF or DMPS-OACF) and two-component (PDA and DMPS) (DMPS-PDA-OACF) functionalized activated carbon fibers pretreated by hydrogen peroxide for the removal of trace heavy metals. The as-prepared DMPS-OACF (7.5,20) under DMPS addition of 7.5 mg and sonication time of 20 min retained large specific surface area, micro-mesoporous structure and rich functional groups and showed better adsorption performance for trace lead and mercury. It also exhibited wide applicable ranges of pH (3.50-10.50) and concentration (50-1136 µg L-1), rapid adsorption kinetics, and excellently selective removal performance for trace lead. The maximum lead adsorption capacity reached 16.03 mg g-1 when the effluent lead concentration met World Health Organization (WHO) standard and the adsorbent can be regenerated by EDTA solution. The fitting results of adsorption kinetics and isotherm models revealed that the lead adsorption process was multi-site adsorption on heterogeneous surfaces and chemical adsorption. The excellent adsorption properties for trace heavy metals were attributed that the sulfur/oxygen/nitrogen-containing functional groups boosted diffusion and adsorption by electrostatic attraction and coordination, suggesting that DMPS-OACF (7.5,20) has great application potential in the removal of trace heavy metals.
Subject(s)
Drinking Water , Metals, Heavy , Trace Elements , Water Pollutants, Chemical , Humans , Lead , Charcoal/chemistry , Carbon Fiber , Water Pollutants, Chemical/analysis , Metals, Heavy/analysis , Adsorption , Kinetics , Hydrogen-Ion ConcentrationABSTRACT
AIMS: Alpha-thalassaemia is one of the most common monogenic disorders worldwide. Due to high guanine-cytosine (GC) content and high mutation diversity in α-globin gene cluster, deletional and non-deletional mutations were usually separately detected with different methods. The aim of this study was to develop a novel one-step method for α-thalassaemia genotyping. METHODS: A multiplex symmetric PCR melting curve strategy was designed for one-step α-thalassaemia genotyping. Based on this strategy, a novel method was developed to simultaneously detect four common deletional (-α3.7 , -α4.2 , _ _SEA , --THAI ) and five common non-deletional (αCD30(-GAG)α, αCD31(G>A)α, αWSα, αQSα, αCSα) α-thalassaemia mutations in a closed-tube reaction. This method was also evaluated by double-blind detection of 235 genotype-known samples and 1630 clinical samples. RESULTS: All nine α-thalassaemia mutations could be accurately identified by this novel method within 3 hours. The evaluation results also showed a 100% concordance with comparison methods. CONCLUSIONS: This method is rapid, accurate, low-cost and easy to operate, which can be used for molecular screening and genetic diagnosis of α-thalassaemia in clinical practice. The multiplex symmetric PCR melting curve strategy designed in this study can also provide an effective approach to the method development for high GC content templates and multiple mutations.
Subject(s)
alpha-Thalassemia , Humans , alpha-Thalassemia/diagnosis , alpha-Thalassemia/genetics , Genotype , Mutation , Multiplex Polymerase Chain Reaction , alpha-Globins/geneticsABSTRACT
The development of superhydrophobic adsorbents for the capture of trace volatile organic compounds (VOCs) from humid indoor air is still a challenge. Herein, we reported the formation of a granular zinc-based metal-organic gel, i.e., ZIF-412(gel) by optimizing the synthesis conditions. The thermally stable xerogel exhibited high surface area (1008 m2/g), hydrophobicity, and viscosity for self-depositing on the substrate such as non-woven fibers. Dynamic adsorption experiments under various humidity conditions demonstrated as-synthesized ZIF-412(gel) owned excellent VOC (hexanal) adsorption performance with adsorption capacity higher than commercial activated carbon and some water-stable MOFs including ZIF-8, ZIF-67, MIL-101(Cr) and ZIF-414. ZIF-412(gel) could be regenerated at temperature as low as 358 K without obvious loss in adsorption capacity. The adsorption mechanism of hexanal over ZIF-412(gel) is also simulated by Grand canonical Monte Carlo (GCMC).
ABSTRACT
The removal and recovery of volatile organic compounds (VOCs) are widely used in many industrials. Unfortunately, most conventional porous materials not only have low VOCs uptake, but also need to be regenerated at relatively high temperature. Metal-organic frameworks (MOFs) have great potential for the removal and recovery of VOCs as their record-breaking gas adsorption capacity, easy regeneration, tunable pore structure and functional groups. Whereas, powdered MOFs are hardly implemented in industrial fields owing to their low bulk density and high pressure drop. Exploring a green method to prepare granular MOFs for the removal and recovery of VOCs is still a challenge. Herein, we report the room temperature green synthesis of a stable Fe-based MOF monolith by using water as the solvent without applying high pressure and chemical binders. The static and dynamic experiments show that the optimized centimeter-scale monolith has high porosity and mechanical strength, and exhibits much better adsorption performance for representative aromatic VOCs (benzene, toluene and p-xylene), than commercial activated carbon and activated carbon fiber under the same conditions. Remarkably, as-synthesized monolith can be rapidly regenerated at lower temperature. These results clearly demonstrate the advantages of MOF monoliths in removing and recovering VOCs, and also provide new insight into the effects of drying temperature, washing and centrifugation procedures on MOF shaping.
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Type 2 diabetes mellitus (T2DM) occurs that cannot effectively use the insulin. Insulin Resistance (IR) is a significant characteristic of T2DM which is also an essential treatment target in blood glucose regulation to prevent T2DM and its complications. Bile acids (BAs) are one group of bioactive metabolites synthesized from cholesterol in liver. BAs play an important role in mutualistic symbiosis between host and gut microbiota. It is shown that T2DM is associated with altered bile acid metabolism which can be regulated by gut microbiota. Simultaneously, BAs also reshape gut microbiota and improve IR and T2DM in the bidirectional communications of the gut-liver axis. This article reviewed the findings on the interaction between BAs and gut microbiota in improving T2DM, which focused on gut microbiota and its debinding function and BAs regulated gut microbiota through FXR/TGR5. Meanwhile, BAs and their derivatives that are effective for improving T2DM and other treatments based on bile acid metabolism were also summarized. This review highlighted that BAs play a critical role in the glucose metabolism and may serve as therapeutic targets in T2DM, providing a reference for discovering and screening novel therapeutic drugs.
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Loss of respiratory functions impairs Candida albicans colonization of host tissues and virulence in a murine model of candidiasis. Furthermore, it is known that respiratory inhibitors decrease mannan synthesis and glucan exposure and thereby promotes phagocytosis. To understand the impact of respiratory proteins of C. albicans on host innate immunity, we characterized cell wall defects in three mitochondrial complex I (CI) null mutants (nuo1Δ, nuo2Δ and ndh51Δ) and in one CI regulator mutant (goa1Δ), and we studied the corresponding effects of these mutants on phagocytosis, neutrophil killing and cytokine production by dendritic cells (DCs). We find that reductions of phosphopeptidomannan (PPM) in goa1Δ, nuo1Δ and phospholipomannan (PLM) in nuo2Δ lead to reductions of IL-2, IL-4, and IL-10 but increase of TNF-α in infected DCs. While PPM loss is a consequence of a reduced phospho-Cek1/2 MAPK that failed to promote phagocytosis and IL-22 production in goa1Δ and nuo1Δ, a 30% glucan reduction and a defective Mek1 MAPK response in ndh51Δ lead to only minor changes in phagocytosis and cytokine production. Glucan exposure and PLM abundance seem to remain sufficient to opsonize neutrophil killing perhaps via humoral immunity. The diversity of immune phenotypes in these mutants possessing divergent cell wall defects is further supported by their transcriptional profiles in each infected murine macrophage scenario. Since metabolic processes, oxidative stress-induced senescence, and apoptosis are differently affected in these scenarios, we speculate that during the early stages of infection, host immune cells coordinate their bioactivities based upon a mixture of signals generated during host-fungi interactions.
Subject(s)
Candida albicans , Interleukin-10 , Animals , Candida albicans/genetics , Cytokines/metabolism , Dendritic Cells , Electron Transport Complex I/metabolism , Glucans/metabolism , Interleukin-10/metabolism , Interleukin-2/metabolism , Interleukin-4/metabolism , Macrophages/metabolism , Mannans , Mice , Phagocytosis , Tumor Necrosis Factor-alpha/metabolismABSTRACT
Modern methods mainly regard lane detection as a problem of pixel-wise segmentation, which is struggling to address the problems of efficiency and challenging scenarios like severe occlusions and extreme lighting conditions. Inspired by human perception, the recognition of lanes under severe occlusions and extreme lighting conditions is mainly based on contextual and global information. Motivated by this observation, we propose a novel, simple, yet effective formulation aiming at ultra fast speed and the problem of challenging scenarios. Specifically, we treat the process of lane detection as an anchor-driven ordinal classification problem using global features. First, we represent lanes with sparse coordinates on a series of hybrid (row and column) anchors. With the help of the anchor-driven representation, we then reformulate the lane detection task as an ordinal classification problem to get the coordinates of lanes. Our method could significantly reduce the computational cost with the anchor-driven representation. Using the large receptive field property of the ordinal classification formulation, we could also handle challenging scenarios. Extensive experiments on four lane detection datasets show that our method could achieve state-of-the-art performance in terms of both speed and accuracy. A lightweight version could even achieve 300+ frames per second(FPS). Our code is at https://github.com/cfzd/Ultra-Fast-Lane-Detection-v2.
ABSTRACT
Gait recognition aims at identifying the pedestrians at a long distance by their biometric gait patterns. It is inherently challenging due to the various covariates and the properties of silhouettes (textureless and colorless), which result in two kinds of pair-wise hard samples: the same pedestrian could have distinct silhouettes (intra-class diversity) and different pedestrians could have similar silhouettes (inter-class similarity). In this work, we propose to solve the hard sample issue with a Memory-augmented Progressive Learning network (GaitMPL), including Dynamic Reweighting Progressive Learning module (DRPL) and Global Structure-Aligned Memory bank (GSAM). Specifically, DRPL reduces the learning difficulty of hard samples by easy-to-hard progressive learning. GSAM further augments DRPL with a structure-aligned memory mechanism, which maintains and models the feature distribution of each ID. Experiments on two commonly used datasets, CASIA-B and OU-MVLP, demonstrate the effectiveness of GaitMPL. On CASIA-B, we achieve the state-of-the-art performance, i.e., 88.0% on the most challenging condition (Clothing) and 93.3% on the average condition, which outperforms the other methods by at least 3.8% and 1.4%, respectively.
ABSTRACT
To achieve efficient and selective trace heavy metals removal from drinking water, a low-cost purification material polydopamine/activated carbon fibers (PDA/H-ACF) was successfully prepared by polymerizing dopamine on the surface of activated carbon fibers pretreated with hydrogen peroxide. The morphology, phase, surface functional groups, specific surface, and pore size distribution of the as-prepared sample were analyzed using FESEM, XPS, BET and pore size distribution test (PST), and FTIR, and orthogonal experiments were used to investigate the influences of concentration of H2O2, pretreatment time, and reflux temperature on trace lead removal. The results showed that the sample pretreated under optimized conditions could produce different pore structures, and the content of functional group -COOH obviously increased. After further modification by polydopamine, the contents of -NH-, -NH2, and -OH functional groups on the surface obviously enhanced, which were beneficial to increase adsorption site and promote trace lead removal. The effluent lead concentration decreased from initial 150 to 3.18 ppb within 5 min, meeting the requirement of NSF International Standard/American National Standard for Drinking Water Treatment Units (NSF/ANSI 53-2020) (5 ppb). The isothermal adsorption process and adsorption kinetics could be well-fitted by the Langmuir isotherm and pseudo-second-order kinetics model, indicating that the adsorption process of trace lead by PDA/H-ACF belonged to monolayer and chemical adsorption. Moreover, the as-prepared PDA/H-ACF also showed superior trace lead adsorption performance in the presence of high concentration competitive metal ions, in a wide pH range and in tap water, and therefore had good application prospect in the field of drinking water purification.
Subject(s)
Drinking Water , Water Pollutants, Chemical , Water Purification , Adsorption , Carbon Fiber , Charcoal , Hydrogen Peroxide , Hydrogen-Ion Concentration , Indoles , Kinetics , Lead , Polymers , Water Pollutants, Chemical/analysisABSTRACT
The COVID-19 pandemic has led to the closure of schools around the world. When children study online, parents are concerned about the impact of increased screen time on their children's physical and mental health. This poster reports results from a qualitative study of Chinese preteens' Internet use and parental mediation during the COVID-19 pandemic. Through interviews with eight parents of primary school students aged from 10 to 12, we found several problems with preteens' Internet use, posing challenges for parental mediation. Parents have adopted stricter restrictive mediation strategies to reduce the impact of Internet addiction and implemented co-use strategies to help preteens adapt to online learning.
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The emission of pollutants from building decoration and furbishing materials associated with unpleasant odors is the main reason for complaints relating to poor quality indoor air. Currently, few studies have focused on the identification of odorants and the quantification of emissions from these building materials. Here, we summarize the analytical methods available for the study of indoor odorants and evaluate existing understanding of odorants from nine kinds of building materials, namely plaster board, wood-based materials, linoleum, carpets, plastics, rubber, artificial leather, paints, and adhesives. The possible odor-causing compounds emitted by these different materials and their odor threshold values are identified. Finally, suggestions are proposed for future research and control measures to minimize indoor odor pollution. Overall, olfactometry is the most important tool for odor analysis desite the non-standardized application of the technique when used in the assessment of odor emissions from building materials. In addition, there are large differences in the reported patterns of odorant emissions from building materials, although oxidized substances such as aldehydes, ketones, and acids are frequently identified in association with the aging of the materials via processes such as oxidation and ozone degradation over time.
Subject(s)
Air Pollution, Indoor , Ozone , Air Pollution, Indoor/analysis , Construction Materials , Odorants/analysis , OlfactometryABSTRACT
High-capacity image steganography, aimed at concealing a secret image in a cover image, is a technique to preserve sensitive data, e.g., faces and fingerprints. Previous methods focus on the security during transmission and subsequently run a risk of privacy leakage after the restoration of secret images at the receiving end. To address this issue, we propose a framework, called Multitask Identity-Aware Image Steganography (MIAIS), to achieve direct recognition on container images without restoring secret images. The key issue of the direct recognition is to preserve identity information of secret images into container images and make container images look similar to cover images at the same time. Thus, we introduce a simple content loss to preserve the identity information, and design a minimax optimization to deal with the contradictory aspects. We demonstrate that the robustness results can be transferred across different cover datasets. In order to be flexible for the secret image restoration in some cases, we incorporate an optional restoration network into our method, providing a multitask framework. The experiments under the multitask scenario show the effectiveness of our framework compared with other visual information hiding methods and state-of-the-art high-capacity image steganography methods. The code is available at https://github.com/jiabaocui/MIAIS.
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Non-alcoholic fatty liver disease (NAFLD) and alcoholic fatty liver disease (AFLD) are the most prevalent metabolic liver diseases globally. Due to the complex pathogenic mechanisms of NAFLD and AFLD, no specific drugs were approved at present. Lipid accumulation, oxidative stress, insulin resistance, inflammation, and dietary habits are all closely related to the pathogenesis of NAFLD and AFLD. However, the mechanism that promotes disease progression has not been fully elucidated. Meanwhile, the gut microbiota and their metabolites also play an important role in the pathogenesis and development of NAFLD and AFLD. This article comparatively reviewed the shared and specific signaling pathways, clinical trials, and potential intervention effectors of NAFLD and AFLD, revealing their similarities and differences. By comparing the shared and specific molecular regulatory mechanisms, this paper provides mutual reference strategies for preventing and treating NAFLD, AFLD, and related metabolic diseases. Furthermore, it provides enlightenment for discovering novel therapies of safe and effective drugs targeting the metabolic liver disease.
ABSTRACT
Porous carbon materials with chemical and thermal stability and high porosity have been widely used for volatile organic compound (VOC) purification. Designing granular carbon with remarkable adsorption capacity and rapid regeneration is of great significance for the capture of VOCs from high humidity air. Herein, a series of N-doped granular carbons were synthesized by direct carbonization of metal-organic gel (MOG). The N-doped granular carbons (C700 and C700K) feature high surface area, hierarchical pore, and abundant N,O multifunctional groups. The toluene adsorption capacity of C700K is highly improved (9.0 mmol/g toluene at P/P0 = 0.1) in comparison with MOG (4.81 mmol/g toluene at P/P0 = 0.1). The toluene breakthrough time of C700K is over 4 times longer than that of MOG at wet conditions (60% RH, 298 K), also much longer than that of widely used carbon materials, zeolites, and representative MOFs, including BPL activated carbon, coconut shell activated carbon, carbosieve, ZSM-5, and MIL-101(Cr). Furthermore, the N-doped granular carbons also exhibit excellent hydrophobicity and can be regenerated rapidly. The internal pore channel and desorption kinetics reveal that the effective diffusion length plays a critical role in the regeneration rate.