Biomimetic Electrochemical Sensor Based on Single-Atom Nickel Laccase Nanoenzyme for Quercetin Detection.

Laccase, a member of the copper oxidase family, has been used as a green catalyst in the environmental and biochemical industries. However, laccase nanoenzymes are limited to materials with copper as the active site, and noncopper laccase nanoenzymes have been scarcely reported. In this study, inspired by the multiple copper active sites of natural laccase and the redox Cu2+/Cu+ electron transfer pathway, a novel nitrogen/nickel single-atom nanoenzyme (N/Ni SAE) with high laccase-like activity was prepared by inducing Ni and dopamine precipitation through a controllable water/ethanol interface reaction. Compared with that of laccase, the laccase activity simulated by N/Ni SAE exhibited excellent stability and reusability. The N/Ni SAE exhibited a higher efficiency toward the degradation of 2,4-dichlorophenol, hydroquinone, bisphenol A, and p-aminobenzene. In addition, a sensitive electrochemical biosensor was constructed by leveraging the laccase-like activity of N/Ni SAE; this sensor offered unique advantages in terms of catalytic activity, selectivity, stability, and repeatability. Its detection ranges for quercetin were 0.01-0.1 and 1.0-100 µM, and the detection limit was 3.4 nM. It was also successfully used for the quantitative detection of quercetin in fruit juices. Therefore, the single-atom biomimetic nanoenzymes prepared in this study promote the development of a new electrochemical strategy for the detection of various bioactive molecules and show great potential for practical applications.

Integrated physical-layer secure visible light communication and positioning system based on polar codes.

Visible light communication (VLC) with physical-layer security can provide information-theoretic security for the optical wireless channel based on the characteristics of the channel instead of encryption algorithms and secret keys at application layer. Since precise location information of communication parties is crucial for estimating channel states and designing secure communication schemes, this paper proposes an integrated visible light communication and positioning system which provides triple functionalities of high-accuracy indoor positioning, physical-layer secure visible light communication, and flicker mitigation illumination. A heterogeneous signal hybrid line coding scheme is proposed for the transmitter to converge the high-speed communication data signals and the low-speed positioning data signals, and a hybrid heterogeneous signal extraction scheme is proposed for the receiver to separate the hybrid heterogeneous signals with a high-bandwidth photodetector and a low-pass complementary metal-oxide-semiconductor (CMOS) image sensor. Based on the positioning information and the communication scheme, a polar codes-based forward error correction coding scheme is designed to achieve physical-layer security and transmission reliability simultaneously. Numerical results show that the proposed system can reach a secrecy code rate of 0.76 for a single-input single-output indoor VLC channel and a transmission efficiency of 0.38 without perceivable flicker. Experimental results show that the proposed system can achieve an average positioning accuracy of 3.35 cm and decrease the bit error rate of a legitimate receiver to a near error-free level (lower than 10-7) while keeping the bit error rate of an eavesdropper at 0.4887 (nearly 0.5) with a transmission data rate of 1 Mbps, resulting in near-zero suppression of the eavesdropped information and a high secrecy capacity of 0.9994.

Local attention and long-distance interaction of rPPG for deepfake detection.

With the development of generative models, abused Deepfakes have aroused public concerns. As a defense mechanism, face forgery detection methods have been intensively studied. Remote photoplethysmography (rPPG) technology extract heartbeat signal from recorded videos by examining the subtle changes in skin color caused by cardiac activity. Since the face forgery process inevitably disrupts the periodic changes in facial color, rPPG signal proves to be a powerful biological indicator for Deepfake detection. Motivated by the key observation that rPPG signals produce unique rhythmic patterns in terms of different manipulation methods, we regard Deepfake detection also as a source detection task. The Multi-scale Spatial-Temporal PPG map is adopted to further exploit heartbeat signal from multiple facial regions. Moreover, to capture both spatial and temporal inconsistencies, we propose a two-stage network consisting of a Mask-Guided Local Attention module (MLA) to capture unique local patterns of PPG maps, and a Temporal Transformer to interact features of adjacent PPG maps in long distance. Abundant experiments on FaceForensics + + and Celeb-DF datasets prove the superiority of our method over all other rPPG-based approaches. Visualization also demonstrates the effectiveness of the proposed method.

Comparison of crop productivity, economic benefit and environmental footprints among diversified multi-cropping systems in South China.

Diversified multi-cropping system with high productivity and low environmental costs is crucial for the development of sustainable agriculture in different regions. However, the information on this practice has still been limited in the South China. This study compared different diversified multi-cropping systems including peanut-rice-fallow (P-R-F), peanut-rice-ryegrass (P-R-R), soybean-rice-ryegrass (S-R-R), feed corn-rice-milk vetch (FC-R-M), sweet corn-rice-milk vetch (SC-R-M) and zucchini -rice-milk vetch (Z-R-M), with the conventional double-rice system (CK). A newly proposed agricultural environmental footprint index (EFI) framework was introduced to quantify the comprehensive environmental costs of different systems. Results indicated that the annual productivities of P-R-R and FC-R-M rotation systems significantly increased by 39.91 % and 25.06 %, respectively, compared to the CK. The economic benefits of P-R-R and FC-R-M were 53.71 % and 16.67 % higher than the CK, respectively, with significant differences. The EFIs based on unit farmland area, crop productivity and economic benefit of the P-R-R and FC-R-M systems were 17.07 %-40.68 % lower than the CK, respectively, showing the lower environmental costs. Therefore, the P-R-R and FC-R-M were recommended as alternatives of double-rice cropping in the South China. In addition, the results indicated that the fertilization and irrigation practices were the key points for improving the rotation systems. This study provided valuable information for the transition of rice-based cropping system in South China. It was also a reference for the development of sustainable agriculture in the world's subtropical agricultural system.

Multidisciplinary collaboration for the successful treatment of a giant hepatic solitary fibrous tumor protruding into the thorax: A case report.

Solitary fibrous tumors (SFTs) are composed of spindle cells and collagen fibers, and these form rare mesenchymal tumors. SFTs are most frequently observed in intrathoracic sites; however, they may also occur in extrathoracic sites, such as the liver. Unlike the hepatic SFTs (HSFTs) reported in the literature, the SFT detailed in the present case report was a large tumor that originated from the liver, with a dumbbell-shaped growth through the diaphragm into the right thoracic cavity. This posed substantial challenges in both diagnosis and treatment. Thus, the present report outlines the findings of a multidisciplinary team meeting that was used to discuss and develop an optimal and personalized treatment strategy for the patient. Transhepatic arterial embolization was performed to block the major arterial blood supply to the tumor in order to reduce its size. Subsequently, the tumor was fully resected, following the collaboration of the experienced hepatobiliary and thoracic surgeons. Following surgery, the abdominal distension experienced by the patient ceased, and no tumor recurrence was detected at the 1-year follow-up. In conclusion, due to limited previous reports of HSFT treatment using multidisciplinary collaboration, the present study outlined the treatment used for this specific tumor type, and the corresponding literature was reviewed.

FERGCN: facial expression recognition based on graph convolution network.

Due to the problems of occlusion, pose change, illumination change, and image blur in the wild facial expression dataset, it is a challenging computer vision problem to recognize facial expressions in a complex environment. To solve this problem, this paper proposes a deep neural network called facial expression recognition based on graph convolution network (FERGCN), which can effectively extract expression information from the face in a complex environment. The proposed FERGCN includes three essential parts. First, a feature extraction module is designed to obtain the global feature vectors from convolutional neural networks branch with triplet attention and the local feature vectors from key point-guided attention branch. Then, the proposed graph convolutional network uses the correlation between global features and local features to enhance the expression information of the non-occluded part, based on the topology graph of key points. Furthermore, the graph-matching module uses the similarity between images to enhance the network's ability to distinguish different expressions. Results on public datasets show that our FERGCN can effectively recognize facial expressions in real environment, with RAF-DB of 88.23%, SFEW of 56.15% and AffectNet of 62.03%.

Worldwide Trends of Research on Periprosthetic Osteolysis: A Bibliometric Study Based on VOSviewer.

BACKGROUND: Due to the increasing number of joint arthroplasty operations, surgeons have begun to devote more attention to the problem of periprosthetic osteolysis. In recent years, numerous studies have focussed on periprosthetic osteolysis, but there have been no relevant bibliometric studies. METHODS: We searched the Web of Science database for relevant articles concerning periprosthetic osteolysis published from 1965 to 2021. The following data were extracted: authors' name, article title, publication journal, impact factor (IF) of the journal in the publication year, keywords, topic of the article, publication country/region, the sum of times cited, H-index and funding sources. VOSviewer and Excel 2019 were used to conduct the bibliometric study and visualise the analysis. RESULTS: A total of 1255 publications were included. In all selected articles, "orthopaedics" became the dominant topic (662 of 1255, 52.75%). The most productive years were 2018 and 2019, with a total of 83 publications. The Journal of Arthroplasty published the most articles on periprosthetic osteolysis (110 publications). The United States of America published the most articles (525, 41.83%). The latest keywords "continuous intramedullary infusion", "erythromycin", "autophagy", "bone-resorbing cells" and "proinflammatory cytokines" both appeared in five articles in 2017. CONCLUSION: This bibliometric study showed that there is a growing trend in published articles related to periprosthetic osteolysis. Journal of Arthroplasty was the top productive journal on periprosthetic osteolysis. The United States of America dominates studies of periprosthetic osteolysis. "Continuous intramedullary infusion", "erythromycin", "autophagy", "bone-resorbing cells" and "proinflammatory cytokines" may be new research hotspots in the field of periprosthetic osteolysis.

Clinical and radiological outcomes in three-dimensional printing assisted revision total hip and knee arthroplasty: a systematic review.

BACKGROUND: This study investigates whether three-dimensional (3D) printing-assisted revision total hip/knee arthroplasty could improve its clinical and radiological outcomes and assess the depth and breadth of research conducted on 3D printing-assisted revision total hip and knee arthroplasty. METHODS: A literature search was carried out on PubMed, Web of Science, EMBASE, and the Cochrane Library. Only studies that investigated 3D printing-assisted revision total hip and knee arthroplasty were included. The author, publication year, study design, number of patients, patients' age, the time of follow-up, surgery category, Coleman score, clinical outcomes measured, clinical outcomes conclusion, radiological outcomes measured, and radiological outcomes conclusion were extracted and analyzed. RESULTS: Ten articles were included in our review. Three articles investigated the outcome of revision total knee arthroplasty, and seven investigated the outcome of revision total hip arthroplasty. Two papers compared a 3D printing group with a control group, and the other eight reported 3D printing treatment outcomes alone. Nine articles investigated the clinical outcomes of total hip/knee arthroplasty, and eight studied the radiological outcomes of total hip/knee arthroplasty. CONCLUSION: 3D printing is being introduced in revision total hip and knee arthroplasty. Current literature suggests satisfactory clinical and radiological outcomes could be obtained with the assistance of 3D printing. Further long-term follow-up studies are required, particularly focusing on cost-benefit analysis, resource availability, and, importantly, the durability and biomechanics of customized prostheses using 3D printing compared to traditional techniques.

[Distribution and drug resistance of pathogens causing periprosthetic infections after hip and knee arthroplasty].

OBJECTIVE: To study the distribution and drug resistance of pathogens causing periprosthetic infections after hip and knee arthroplasty, and to formulate prevention and treatment strategies for drug-resistant bacteria. METHODS: The data of 146 cases of periprosthetic infection after primary hip and knee arthroplasty from 2010 to 2015 were collected, including 111 cases of periprosthetic infection after hip arthroplasty and 35 cases of periprosthetic infection after knee arthroplasty. The culture positive rate, pathogenic bacteria composition and drug resistance rate were counted over the years, and the change trend of pathogen distribution and drug resistance was analyzed. RESULTS: One hundredand eight strains of pathogenic bacteria were detected in 146 cases, and the positive rate of culture was 73.97%. Gram positive bacteria accounted for 55.48%, Staphylococcus epidermidis and Staphylococcus aureus accounted for 25.34% and 15.07% respectively. Gram negative bacteria accounted for 13.01%, including Enterobacter cloacae, Pseudomonas aeruginosa and Escherichia coli. There were 4 cases of Mycobacterium tuberculosis infection and mixed infection. The results of culture over the years showed that the constituent ratio of Gram positive bacteria had an increasing trend, fluctuating from 39.13% to 76.47%. The results of drug sensitivity showed that the pathogens were highly resistant to ß-lactams, quinolones, clindamycin and gentamicin, and the drug resistance rate was increasing, but it was still sensitive to rifampicin, nitrofurantoin, tigecycline, linezolid and vancomycin. CONCLUSION: Gram positive bacteria are the main pathogens of periprosthetic infection, and the proportion is increasing gradually.The pathogens have high resistance to many kinds of antibiotics, and the resistance rate is still increasing. To strengthen the monitoring of the distribution and drug resistance of pathogenic bacteria is helpful to grasp its change trend and formulate targeted prevention and control strategies.

Optimizing a dual-frequency and phase modulation method for SSVEP-based BCIs.

OBJECTIVE: The design of the stimulation paradigm plays an important role in steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) studies. Among various stimulation designs, the dual-frequency paradigm in which two frequencies are used to encode one target is of importance and interest. However, because the number of possible frequency combinations is huge, the existing dual-frequency modulation paradigms failed to optimize the encoding towards the best combinations. Thus, this work aiming at designing a new dual-frequency and phase modulation paradigm with the best combinations stimuli. APPROACH: This study proposed a dual-frequency and phase modulation method, which can achieve a large number of targets by making different combinations of two frequencies and an initial phase. This study also designed a set of methods for quickly optimizing the stimulation codes for the dual-frequency and phase modulation method. MAIN RESULTS: An online 40-class BCI experiment with 12 subjects obtained an accuracy of 96.06[Formula: see text]4.00% and an averaged information transfer rate (ITR) of 196.09[Formula: see text]15.25 bits min-1, which were much higher than the existing dual-frequency modulation paradigms. Moreover, an offline simulation with a public dataset showed that the optimization method was also effective for optimizing the single-frequency and phase modulation paradigm. SIGNIFICANCE: These results demonstrate the high performance of the proposed dual-frequency and phase modulation method and the high efficiency of the optimization method for designing SSVEP stimulation paradigms. In addition, the coding efficiency of the optimized dual-frequency and phase modulation paradigm is higher than that of the single-frequency and phase modulation paradigm, and it is expected to further realize the BCI paradigm with a large amount of targets.

Thermally Stable Poly(vinylidene fluoride) for High-Performance Printable Piezoelectric Devices.

Piezoelectric polymers, such as poly(vinylidene fluoride) (PVDF) and its copolymers, can achieve large strains and high work density under external electrical fields. These materials are highly desirable in the development of electronic devices and intelligent structures. Here, we demonstrate that dehydrofluorination (DHF) can provide a versatile chemical modification of the PVDF homopolymer that yields thermally stable ferroelectricity. The DHF process significantly increases the fraction of planar chain conformation in the PVDF and results in higher piezoelectric coupling with a wider processing temperature range, compared to traditionally processed PVDF. The efficacy of DHF in promoting planar chain conformation is demonstrated through molecular simulation and further proven by experimental characterization. The induced piezoelectric phases by DHF were able to be preserved through high temperature treatments up to 200 °C. The dehydrofluorinated PVDF exhibits improved electromechanical coupling with a high piezoelectric strain coefficient of d31 = 25.12 ± 1.13 pC/N, which can be further improved to 35.12 ± 0.69 pC/N by common mechanical drawing. This high piezoelectric voltage coefficient leads to an excellent actuation and energy harvesting behavior with a power density of 21.96 mW/cm3 in a flexible undrawn PVDF energy harvester, which is 3.13 times higher than conventionally drawn PVDF. The versatile and scalable method for preparing PVDF polymers with high piezoelectric coupling will enable new manufacturing processes not currently compatible with PVDF homopolymers.

[Study on a quantitative analysis method for pulse signal by modelling its waveform in time and space domain].

In order to quantitatively analyze the morphology and period of pulse signals, a time-space analytical modeling and quantitative analysis method for pulse signals were proposed. Firstly, according to the production mechanism of the pulse signal, the pulse space-time analytical model was built after integrating the period and baseline of pulse signal into the analytical model, and the model mathematical expression and its 12 parameters were obtained for pulse wave quantification. Then, the model parameters estimation process based on the actual pulse signal was presented, and the optimization method, constraints and boundary conditions in parameter estimation were given. The spatial-temporal analytical modeling method was applied to the pulse waves of healthy subjects from the international standard physiological signal sub-database Fantasia of the PhysioNet in open-source, and we derived some changes in heartbeat rhythm and hemodynamic generated by aging and gender difference from the analytical models. The model parameters were employed as the input of some machine learning methods, e.g. random forest and probabilistic neural network, to classify the pulse waves by age and gender, and the results showed that random forest has the best classification performance with Kappa coefficients over 98%. Therefore, the space-time analytical modeling method proposed in this study can effectively quantify and analyze the pulse signal, which provides a theoretical basis and technical framework for some related applications based on pulse signals.

Potential roles of dietary flavonoids from Citrus aurantium L. var. amara Engl. in atherosclerosis development.

Dietary consumption of flavonoids correlated positively with lower risk of cardiovascular disease. However, the precise roles of flavonoids from the blossoms of Citrus aurantium Linn variant amara Engl (CAVA) in atherosclerosis (AS) are still poorly understood. This study aimed to find novel flavonoid-type skeletons with protection against AS. Total flavonoids (CAVAF), homoeriodictyol (HE) and hesperetin-7-O-ß-d-glucopyranoside (HG) were isolated from the blossoms of Citrus aurantium Linn variant amara Engl. by chromatography. Their suppressive effects on lipopolysaccharide (LPS)-induced inflammatory responses and ox-LDL-induced foam cell formation were systematically and comparatively investigated using macrophage RAW264.7 cells. HE was more powerful than HG in inhibiting LPS-induced production of nitric oxide (NO), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), interleukin-1 beta (IL-1ß) and gene expression in RAW264.7 cells. HE and HG showed different responses to extracellular signal-regulated kinases (ERK), c-Jun N-terminal kinases (JNK), P38, P65, IκBα, IκKα/ß phosphorylation, and nuclear factor-kappa B (NF-κB) nuclear translocation. HE and HG also differentially decreased oxidized low-density lipoprotein (ox-LDL)-induced foam cell formation by regulating peroxisome proliferator-activated receptor-gamma (PPARγ), phospholipid ATP-binding cassette transporter A1 (ABCA1), phospholipid ATP-binding cassette transporter G1 (ABCG1), scavenger receptor class B type I (SRB1), scavenger receptor class A type I (SRA1) and cluster of differentiation 36 (CD36) expression at gene and protein levels in RAW264.7 cells. HG showed weaker potential than HE in preventing AS development. Their chemical differences might partially explain the discrepancy in their bioactivity. In conclusion, HE and HG might be developed into novel therapeutic agents against inflammation and AS-associated diseases.

Constructing an Associative Memory System Using Spiking Neural Network.

Development of computer science has led to the blooming of artificial intelligence (AI), and neural networks are the core of AI research. Although mainstream neural networks have done well in the fields of image processing and speech recognition, they do not perform well in models aimed at understanding contextual information. In our opinion, the reason for this is that the essence of building a neural network through parameter training is to fit the data to the statistical law through parameter training. Since the neural network built using this approach does not possess memory ability, it cannot reflect the relationship between data with respect to the causality. Biological memory is fundamentally different from the current mainstream digital memory in terms of the storage method. The information stored in digital memory is converted to binary code and written in separate storage units. This physical isolation destroys the correlation of information. Therefore, the information stored in digital memory does not have the recall or association functions of biological memory which can present causality. In this paper, we present the results of our preliminary effort at constructing an associative memory system based on a spiking neural network. We broke the neural network building process into two phases: the Structure Formation Phase and the Parameter Training Phase. The Structure Formation Phase applies a learning method based on Hebb's rule to provoke neurons in the memory layer growing new synapses to connect to neighbor neurons as a response to the specific input spiking sequences fed to the neural network. The aim of this phase is to train the neural network to memorize the specific input spiking sequences. During the Parameter Training Phase, STDP and reinforcement learning are employed to optimize the weight of synapses and thus to find a way to let the neural network recall the memorized specific input spiking sequences. The results show that our memory neural network could memorize different targets and could recall the images it had memorized.

Isolation of Aramid Nanofibers for High Strength and Toughness Polymer Nanocomposites.

The development of nanoscale reinforcements that can be used to improve the mechanical properties of a polymer remains a challenge due to the long-standing difficulties with exfoliation and dispersion of existing materials. The dissimilar chemical nature of common nanofillers (e.g., carbon nanotubes, graphene) and polymeric matrix materials is the main reason for imperfect filler dispersion and, consequently, low mechanical performance of their composites relative to theoretical predictions. Here, aramid nanofibers that are intrinsically dispersible in many polymers are prepared from commercial aramid fibers (Kevlar) and isolated through a simple, scalable, and low-cost controlled dissolution method. Integration of the aramid nanofibers in an epoxy resin results in nanocomposites with simultaneously improved elastic modulus, strength, and fracture toughness. The improvement of these two mutually exclusive properties of nanocomposites is comparable to the enhancement of widely reported carbon nanotube reinforced nanocomposites but with a cost-effective and more feasible method to achieve uniform and stable dispersion. The results indicate the potential for aramid nanofibers as a new class of reinforcements for polymers.