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Graphene oxide (GO)-based humidity sensors are attracting widespread attention due to their high responsivity and low cost. However, GO-based humidity sensors generally suffer from slow response and recovery as well as poor stability. Here, we report a flexible resistive humidity sensor based on a MoS2/GO composite film that was fabricated by mixing different volumes of MoS2 and GO dispersions with adjustable volume ratios. The MoS2/GO composite film has been used as a sensing layer on screen-printed interdigital electrodes. The results show that the best device performance was achieved at a dispersion volume of 0.05 mL with a MoS2/GO volume ratio of 5 : 1, featuring a high responsivity (â¼98%), a fast response/recovery time (1.3/12.1 s), excellent stability and low cost. Furthermore, the humidity sensor exhibits good linearity over a wide humidity range (33%RH-98%RH) at room temperature (25 °C) and can be fabricated easily and feasibly. The application of the humidity sensors we prepared in human respiration detection and human fingertip proximity detection has been demonstrated. These findings indicate the great potential of the MoS2/GO composite in developing next generation high-performance humidity sensors.
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Background: Vascular cognitive impairment (VCI) manifests in memory impairment, mental slowness, executive dysfunction, behavioral changes, and visuospatial abnormalities, significantly compromising the quality of daily life for patients and causing inconvenience to caregivers. Neuroimaging serves as a crucial approach to evaluating the extent, location, and type of vascular lesions in patients suspected of VCI. Nevertheless, there is still a lack of comprehensive bibliometric analysis to discern the research status and emerging trends concerning VCI neuroimaging. Objective: This study endeavors to explore the collaboration relationships of authors, countries, and institutions, as well as the research hotspots and frontiers of VCI neuroimaging by conducting a bibliometric analysis. Methods: We performed a comprehensive retrieval within the Core Collection of Web of Science, spanning from 2000 to 2023. After screening the included literature, CiteSpace and VOSviewer were utilized for a visualized analysis aimed at identifying the most prolific author, institution, and journal, as well as extracting valuable information from the analysis of references. Results: A total of 1,024 publications were included in this study, comprising 919 articles and 105 reviews. Through the analysis of keywords and references, the research hotspots involve the relationship between neuroimaging of cerebral small vessel disease (CSVD) and VCI, the diagnosis of VCI, and neuroimaging methods pertinent to VCI. Moreover, potential future research directions encompass CSVD, functional and structural connectivity, neuroimaging biomarkers, and lacunar stroke. Conclusion: The research in VCI neuroimaging is constantly developing, and we hope to provide insights and references for future studies by delving into the research hotspots and frontiers within this field.
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Sharding blockchain is a technology designed to improve the performance and scalability of traditional blockchain systems. However, due to its design, communication between shards depends on shard leaders for transmitting information, while shard members are unable to detect communication activities between shards. Consequently, Byzantine nodes can act as shard leaders, engaging in malicious behaviors to disrupt message transmission. To address these issues, we propose the Cross shard leader accountability protocol (CSLAP), which is based on the two-phase atomic commit protocol (2PC). CSLAP employs byzantine broadcast/byzantine agreement (BB/BA) for Byzantine fault tolerance to generate cross-shard leader re-election certificates, thereby reducing the impact of shard leaders on inter-shard communication. It also uses Round-robin mechanism to facilitate leader re-election. Moreover, we demonstrate that CSLAP maintains the security and liveness of sharding transactions while providing lower communication latency. Finally, we conducted an experimental comparison between CSLAP and other cross-shard protocols. The results indicate that CSLAP exhibits superior performance in reducing communication latency.
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This paper delves into enhancing the performance of ScAlN-based Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) through the implementation of Polydimethylsiloxane (PDMS) acoustic lenses. The PMUT, encapsulated in PDMS, underwent thorough characterization through the utilization of an industry-standard hydrophone calibration instrument. The experimental results showed that the ScAlN-based PMUT with the PDMS lenses achieved an impressive sensitivity of -160 dB (re: 1 V/µPa), an improvement of more than 8 dB compared to the PMUT with an equivalent PDMS film. There was a noticeable improvement in the -3 dB main lobe width within the frequency response when comparing the PMUT with PDMS encapsulation, both with and without lenses. The successful fabrication of high-performance PDMS lenses proved instrumental in significantly boosting the sensitivity of the PMUT. Comprehensive performance evaluations underscored that the designed PMUT in this investigation surpassed its counterparts reported in the literature and commercially available transducers. This encouraging outcome emphasizes its substantial potential for commercial applications.
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In this study, we propose a method for optimizing the design of CMUT sensors using genetic algorithms. Existing CMUT sensors face frequency response and sensitivity limitations, necessitating optimization to enhance their sensing performance. Traditional optimization methods are often intricate and time-consuming and may fail to yield the optimal solution. Genetic algorithms, which simulate the biological evolution process, offer advantages in global optimization and efficiency, making them widely utilized in the optimization design of Microelectromechanical Systems (MEMS) devices. Based on the theoretical framework and finite element model of CMUT sensors, we propose a CMUT array element optimization design method based on genetic algorithms. The optimization and validation results demonstrate that we have successfully designed a broadband CMUT array element consisting of four microelements with a 1-2 MHz frequency range. Compared with a randomly arranged array element, the optimized array shows a 63.9% increase in bandwidth and a 7.5% increase in average sensitivity within the passband. Moreover, the sensitivity variance within the passband is reduced by 50.2%. Our proposed method effectively optimizes the design of high sensitivity CMUT sensors with the desired bandwidth, thereby offering significant reference value for the optimization design of CMUT sensors.
Subject(s)
Clavicle , Fracture Fixation, Internal , Fractures, Bone , Fractures, Malunited , Printing, Three-Dimensional , Humans , Clavicle/injuries , Clavicle/surgery , Clavicle/diagnostic imaging , Fracture Fixation, Internal/methods , Fractures, Malunited/surgery , Fractures, Malunited/diagnostic imaging , Fractures, Bone/surgery , Fractures, Bone/diagnostic imaging , Recurrence , Male , Adult , Treatment Outcome , FemaleABSTRACT
Real-time DOA (direction of arrival) estimation of surface or underwater targets is of great significance to the research of marine environment and national security protection. When conducting real-time DOA estimation of underwater targets, it can be difficult to extract the prior characteristics of noise due to the complexity and variability of the marine environment. Therefore, the accuracy of target orientation in the absence of a known noise is significantly reduced, thereby presenting an additional challenge for the DOA estimation of the marine targets in real-time. Aiming at the problem of real-time DOA estimation of acoustic targets in complex environments, this paper applies the MEMS vector hydrophone with a small size and high sensitivity to sense the conditions of the ocean environment and change the structural parameters in the adaptive adjustments system itself to obtain the desired target signal, proposes a signal processing method when the prior characteristics of noise are unknown. Theoretical analysis and experimental verification show that the method can achieve accurate real-time DOA estimation of the target, achieve an error within 3.1° under the SNR (signal-to-noise ratio) of the X channel of -17 dB, and maintain a stable value when the SNR continues to decrease. The results show that this method has a very broad application prospect in the field of ocean monitoring.
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OBJECTIVE: To investigate the impact of the combination of CICARE (C - Connect, I - Introduce, C - Communicate, A - Ask, R - Respond, E - Exit) communication model and traditional Chinese medicine (TCM) poultice on muscle strength and depression levels in patients. METHODS: Patients were divided into three groups: basic treatment group, basic treatment + TCM poultice group, and combined treatment group. Conventional rehabilitation therapy, TCM poultice external application, and the combination of both with the CICARE communication model were applied in the respective groups. Muscle strength (AMA muscle strength grading scale), self-care abilities (Barthel Index), depression symptoms (Hamilton Depression Rating Scale), neurological deficit status (NIHSS score) and serum inflammatory factor levels were assessed at admission, 3 weeks, and 8 weeks of treatment. RESULTS: After 3 and 8 weeks of treatment, the combined treatment group had higher AMA muscle strength scores and improved Barthel Index scores compared to other groups (p < 0.05). Depressive symptoms also improved significantly in the combined treatment group, with lower HDRS scores at 3 and 8 weeks (p < 0.05). After 8 weeks, IL-1, IL-6, and hs-CRP levels decreased in all groups, with the combined treatment group showing the lowest levels (p < 0.05). NIHSS scores decreased significantly in all groups post-intervention, with the combined treatment group showing the greatest improvement (p < 0.05). CONCLUSION: The integration of CICARE communication model with TCM poultice shows notable benefits in enhancing muscle strength, daily living self-care abilities, reducing depression, neurological impairment, and inflammatory factors in post-stroke hemiplegia patients.
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This paper presents the design and development of a high-resolution 3D ultrasound imaging system based on a 1 × 256 piezoelectric ring array, achieving an accuracy of 0.1 mm in both ascending and descending modes. The system achieves an imaging spatial resolution of approximately 0.78 mm. A 256 × 32 cylindrical sensor array and a digital phantom of breast tissue were constructed using the k-Wave toolbox. The signal is acquired layer by layer using 3D acoustic time-domain simulation, resulting in the collection of data from each of the 32 layers. The 1 × 256 ring array moves on a vertical trajectory from the chest wall to the nipple at a constant speed. A data set was collected at intervals of 1.5 mm, resulting in a total of 32 data sets. Surface rendering and volume rendering algorithms were used to reconstruct 3D ultrasound images from the volume data obtained via simulation so that the smallest simulated reconstructed lesion had a diameter of 0.3 mm. The reconstructed three-dimensional image derived from the experimental data exhibits the contour of the breast model along with its internal mass. Reconstructable dimensions can be achieved up to approximately 0.78 mm. The feasibility of applying the system to 3D breast ultrasound imaging has been demonstrated, demonstrating its attributes of resolution, precision, and exceptional efficiency.
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Bats are associated with the circulation of most mammalian filoviruses (FiVs), with pathogenic ones frequently causing deadly hemorrhagic fevers in Africa. Divergent FiVs have been uncovered in Chinese bats, raising concerns about their threat to public health. Here, we describe a long-term surveillance to track bat FiVs at orchards, eventually resulting in the identification and isolation of a FiV, Dehong virus (DEHV), from Rousettus leschenaultii bats. DEHV has a typical filovirus-like morphology with a wide spectrum of cell tropism. Its entry into cells depends on the engagement of Niemann-Pick C1, and its replication is inhibited by remdesivir. DEHV has the largest genome size of filoviruses, with phylogenetic analysis placing it between the genera Dianlovirus and Orthomarburgvirus, suggesting its classification as the prototype of a new genus within the family Filoviridae. The continuous detection of viral RNA in the serological survey, together with the wide host distribution, has revealed that the region covering southern Yunnan, China, and bordering areas is a natural circulation sphere for bat FiVs. These emphasize the need for a better understanding of the pathogenicity and potential risk of FiVs in the region.
Subject(s)
Chiroptera , Filoviridae , Animals , Phylogeny , China , MammalsABSTRACT
BACKGROUND: The extracellular matrix (ECM) and cancer-associated fibroblasts (CAFs) play major roles in tumor progression, metastasis, and the poor response of many solid tumors to immunotherapy. CAF-targeted chimeric antigen receptor-T cell therapy cannot infiltrate ECM-rich tumors such as osteosarcoma. METHOD: In this study, we used RNA sequencing to assess whether the recently invented membrane-anchored and tumor-targeted IL-12-armed (attIL12) T cells, which bind cell-surface vimentin (CSV) on tumor cells, could destroy CAFs to disrupt the ECM. We established an in vitro model of the interaction between osteosarcoma CAFs and attIL12-T cells to uncover the underlying mechanism by which attIL12-T cells penetrate stroma-enriched osteosarcoma tumors. RESULTS: RNA sequencing demonstrated that attIL12-T cell treatment altered ECM-related gene expression. Immunohistochemistry staining revealed disruption or elimination of high-density CAFs and ECM in osteosarcoma xenograft tumors following attIL12-T cell treatment, and CAF/ECM density was inversely correlated with T-cell infiltration. Other IL12-armed T cells, such as wild-type IL-12-targeted or tumor-targeted IL-12-T cells, did not disrupt the ECM because this effect depended on the engagement between CSV on the tumor cell and its ligand on the attIL12-T cells. Mechanistic studies found that attIL12-T cell treatment elevated IFNγ production on interacting with CSV+ tumor cells, suppressing transforming growth factor beta secretion and in turn upregulating FAS-mediated CAF apoptosis. CAF destruction reshaped the tumor stroma to favor T-cell infiltration and tumor inhibition. CONCLUSIONS: This study unveiled a novel therapy-attIL12-T cells-for targeting CAFs/ECM. These findings are highly relevant to humans because CAFs are abundant in human osteosarcoma.
Subject(s)
Bone Neoplasms , Cancer-Associated Fibroblasts , Osteosarcoma , Animals , Humans , Interleukin-12 , Heterografts , Osteosarcoma/therapy , Cell Membrane , Extracellular Matrix , Disease Models, Animal , Bone Neoplasms/therapy , Cell- and Tissue-Based TherapySubject(s)
Bone Cements , Osteomyelitis , Humans , Internal Fixators , Osteomyelitis/surgery , Printing, Three-Dimensional , Tibia/surgeryABSTRACT
Cadmium (Cd) contamination in paddy soil threatens rice growth and food safety, enriching manganese (Mn) in rice seedlings is expected to reduce Cd uptake by rice. The effects of 250 µM Mn-treated seedlings on reducing Cd uptake of four rice genotypes (WYJ21, ZJY1578, HHZ, and HLYSM) planted in 0.61 mg kg-1 Cd-contaminated soil, were studied through the hydroponic and pot experiments. The results showed that the ZJY1578 seedling had the highest Mn level (459 µg plant-1), followed by WYJ21 (309 µg plant-1), and less Mn accumulated in the other genotypes. The relative expression of OsNramp5 (natural resistance-associated macrophage protein) was reduced by 42.7 % in ZJY1578 but increased by 23.3 % in HLYSM. The expressions of OsIRT1 (iron-regulated transporter-like protein) were reduced by 24.0-56.0 % in the four genotypes, with the highest reduction in ZJY1578. Consequently, a greater reduction of Cd occurred in ZJY1578 than that in the other genotypes, i.e., the root and shoot Cd at the tillering were reduced by 27.8 % and 48.5 %, respectively. At the mature stage, total Cd amount and distribution in the shoot and brown rice were also greatly reduced in ZJY1578, but the inhibitory effects were weakened compared to the tillering stage. This study found various responses of Cd uptake and transporters to Mn-treated seedlings among rice genotypes, thus resulting in various Cd reductions. In the future, the microscopic transport processes of Cd within rice should be explored to deeply explain the genotypic variation.
Subject(s)
Oryza , Seedlings , Seedlings/genetics , Oryza/genetics , Cadmium/toxicity , Manganese , Genotype , SoilABSTRACT
Breast cancer histopathological image automatic classification can reduce pathologists workload and provide accurate diagnosis. However, one challenge is that empirical datasets are usually imbalanced, resulting in poorer classification quality compared with conventional methods based on balanced datasets. The recently proposed bilateral branch network (BBN) tackles this problem through considering both representation and classifier learning to improve classification performance. We firstly apply bilateral sampling strategy to imbalanced breast cancer histopathological image classification and propose a meta-adaptive-weighting-based bilateral multi-dimensional refined space feature attention network (MAW-BMRSFAN). The model is composed of BMRSFAN and MAWN. Specifically, the refined space feature attention module (RSFAM) is based on convolutional long short-term memories (ConvLSTMs). It is designed to extract refined spatial features of different dimensions for image classification and is inserted into different layers of classification model. Meanwhile, the MAWN is proposed to model the mapping from a balanced meta-dataset to imbalanced dataset. It finds suitable weighting parameter for BMRSFAN more flexibly through adaptively learning from a small amount of balanced dataset directly. The experiments show that MAW-BMRSFAN performs better than previous methods. The recognition accuracy of MAW-BMRSFAN under four different magnifications still is higher than 80% even when unbalance factor is 16, indicating that MAW-BMRSFAN can make ideal performance under extreme imbalanced conditions.
Subject(s)
Breast Neoplasms , Humans , Female , Breast Neoplasms/diagnostic imaging , Breast/diagnostic imaging , Diagnosis, Computer-Assisted/methodsABSTRACT
A novel breast ultrasound tomography system based on a circular array of capacitive micromechanical ultrasound transducers (CMUT) has broad application prospects. However, the images produced by this system are not suitable as input for the training phase of the super-resolution (SR) reconstruction algorithm. To solve the problem, this paper proposes an improved medical image super-resolution (MeSR) method based on the sparse domain. First, we use the simultaneous algebraic reconstruction technique (SART) with high imaging accuracy to reconstruct the image into a training image in a sparse domain model. Secondly, we denoise and enhance the contrast of the SART images to obtain improved detail images before training the dictionary. Then, we use the original detail image as the guide image to further process the improved detail image. Therefore, a high-precision dictionary was obtained during the testing phase and applied to filtered back projection SR reconstruction. We compared the proposed algorithm with previously reported algorithms in the Shepp Logan model and the model based on the CMUT background. The results showed significant improvements in peak signal-to-noise ratio, entropy, and average gradient compared to previously reported algorithms. The experimental results demonstrated that the proposed MeSR method can use noisy reconstructed images as input for the training phase of the SR algorithm and produce excellent visual effects.
Subject(s)
Breast , Ultrasonography, Mammary , Ultrasonography, Mammary/methods , Algorithms , Humans , Female , Breast/diagnostic imagingABSTRACT
BACKGROUND: Seeking positive and comprehensive rehabilitation methods after stroke is an urgent problem to be solved, which is very important to improve the dysfunction of stroke. The aim of this study was to investigate the effects of motor imagery-based brain-computer interface training (MI-BCI) on upper limb function and attention in stroke patients with hemiplegia. METHODS: Sixty stroke patients with impairment of upper extremity function and decreased attention were randomly assigned to the control group (CR group) or the experimental group (BCI group) in a 1:1 ratio. Patients in the CR group received conventional rehabilitation. Patients in the BCI group received 20 min of MI-BCI training five times a week for 3 weeks (15 sessions) in addition to conventional rehabilitation. The primary outcome measures were the changes in Fugl-Meyer Motor Function Assessment of Upper Extremities (FMA-UE) and Attention Network Test (ANT) from baseline to 3 weeks. RESULTS: About 93% of the patients completed the allocated training. Compared with the CR group, among those in the BCI group, FMA-UE was increased by 8.0 points (95%CI, 5.0 to 10.0; P < 0.001). Alert network response time (32.4ms; 95%CI, 58.4 to 85.6; P < 0.001), orienting network response (5.6ms; 95%CI, 29.8 to 55.8; P = 0.010), and corrects number (8.0; 95%CI, 17.0 to 28.0; P < 0.001) also increased in the BCI group compared with the CR group. Additionally, the executive control network response time (- 105.9ms; 95%CI, - 68.3 to - 23.6; P = 0.002), the total average response time (- 244.8ms; 95%CI, - 155.8 to - 66.2; P = 0.002), and total time (- 122.0ms; 95%CI, - 80.0 to - 35.0; P = 0.001) were reduced in the BCI group compared with the CR group. CONCLUSION: MI-BCI combined with conventional rehabilitation training could better enhance upper limb motor function and attention in stroke patients. This training method may be feasible and suitable for individuals with stroke. TRIAL REGISTRATION: This study was registered in the Chinese Clinical Trial Registry with Portal Number ChiCTR2100050430(27/08/2021).
Subject(s)
Brain-Computer Interfaces , Stroke Rehabilitation , Stroke , Humans , Stroke Rehabilitation/methods , Hemiplegia/etiology , Recovery of Function/physiology , Electroencephalography/methods , Stroke/complications , Upper ExtremityABSTRACT
INTRODUCTION: To explore the diagnostic value of spatiotemporal image correlation (STIC) for different types of fetal conotruncal defects (CTDs). METHODS: The clinical data and STIC images of 174 fetuses with CTDs diagnosed via prenatal ultrasound were analyzed retrospectively. RESULTS: Among the 174 cases of CTDs, 58 were tetralogy of Fallot (TOF); 30, transposition of great arteries (TGA) (D-TGA, 23 cases; cc-TGA, 7 cases); 26, double outlet of the right ventricle (DORV); 32, persistent arterial trunk (PTA) (type A1, 15 cases; type A2, 11 cases; type A3, 5 cases; type A4, 1 case); and 28, pulmonary atresia (PA) (ventricular septal defect, 24 cases; ventricular septal integrity, 4 cases). Among the cases, 156 were complicated with complex congenital intracardiac and extracardiac malformations. The abnormal display rate of the four-chamber view of two-dimensional echocardiography was low. The display rate of the permanent arterial trunk was the highest (90.6%) in STIC imaging. CONCLUSIONS: STIC imaging can be used in the diagnosis of different types of CTDs, especially in persistent arterial trunks, and thus has great value for the clinical treatment and prognosis of these defects.
Subject(s)
Double Outlet Right Ventricle , Heart Defects, Congenital , Transposition of Great Vessels , Pregnancy , Female , Humans , Retrospective Studies , Ultrasonography, Prenatal/methods , Prenatal Diagnosis , Transposition of Great Vessels/diagnostic imaging , FetusABSTRACT
The design of a highly effective isopropanol gas sensor with high response and trace detection capability is extremely important for environmental surveillance and human health. Here, novel flower-like PtOx@ZnO/In2O3 hollow microspheres were prepared by a three-step approach. The hollow structure was composed of an In2O3 shell inside and layered ZnO/In2O3 nanosheets outside with PtOx nanoparticles (NPs) on the surface. Meanwhile, the gas sensing performances of the ZnO/In2O3 composite with different Zn/In ratios and PtOx@ZnO/In2O3 composites were evaluated and compared systematically. The measurement results indicated that the ratio of Zn/In affected the sensing performance and the ZnIn2 sensor presented a higher response, which was then modified with PtOx NPs to further enhance its sensing property. The Pt@ZnIn2 sensor exhibited outstanding isopropanol detection performance with ultrahigh response values under 22 and 95% relative humidity (RH). In addition, it also showed a rapid response/recovery speed, good linearity, and low theoretical limit of detection (LOD) regardless of being under a relatively dry or ultrahumid atmosphere. The enhancement of isopropanol sensing properties might be ascribed to the unique structure of PtOx@ZnO/In2O3, heterojunctions between the components, and catalytic effect of Pt NPs.
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With advances in new materials and technologies, there has been increasing research focused on flexible sensors. However, in most flexible pressure sensors made using new materials, it is challenging to achieve high detection sensitivity across a wide pressure range. Although traditional silicon-based sensors have good performance, they are not formable and, because of their rigidity and brittleness, they are not suitable for fitting with soft human skin, which limits their application in wearable devices to collect various signals. Silicon nanomembranes are ultra-thin, flexible materials with excellent piezoresistive properties, and they can be applied in various fields, such as in soft robots and flexible devices. In this study, we developed a flexible pressure sensor based on the use of silicon nanomembranes (with a thickness of only 340 nm) as piezoresistive units, which were transferred onto a flexible polydimethylsiloxane (PDMS) substrate. The flexible pressure sensor operated normally in the range of 0-200 kPa, and the sensitivity of the sensor reached 0.0185 kPa-1 in the low-pressure range of 0-5 kPa. In the high-pressure range of 5-200 kPa, the sensitivity of the sensor was maintained at 0.0023 kPa-1. The proposed sensor exhibited a fast response and excellent long-term stability and could recognize human movements, such as the bending of fingers and wrist joints, while maintaining a stable output. Thus, the developed flexible pressure sensor has promising applications in body monitoring and wearable devices.