A coordinated adaptive multiscale enhanced spatio-temporal fusion network for multi-lead electrocardiogram arrhythmia detection.

The multi-lead electrocardiogram (ECG) is widely utilized in clinical diagnosis and monitoring of cardiac conditions. The advancement of deep learning has led to the emergence of automated multi-lead ECG diagnostic networks, which have become essential in the fields of biomedical engineering and clinical cardiac disease diagnosis. Intelligent ECG diagnosis techniques encompass Recurrent Neural Networks (RNN), Transformers, and Convolutional Neural Networks (CNN). While CNN is capable of extracting local spatial information from images, it lacks the ability to learn global spatial features and temporal memory features. Conversely, RNN relies on time and can retain significant sequential features. However, they are not proficient in extracting lengthy dependencies of sequence data in practical scenarios. The self-attention mechanism in the Transformer model has the capability of global feature extraction, but it does not adequately prioritize local features and cannot extract spatial and channel features. This paper proposes STFAC-ECGNet, a model that incorporates CAMV-RNN block, CBMV-CNN block, and TSEF block to enhance the performance of the model by integrating the strengths of CNN, RNN, and Transformer. The CAMV-RNN block incorporates a coordinated adaptive simplified self-attention module that adaptively carries out global sequence feature retention and enhances spatial-temporal information. The CBMV-CNN block integrates spatial and channel attentional mechanism modules in a skip connection, enabling the fusion of spatial and channel information. The TSEF block implements enhanced multi-scale fusion of image spatial and sequence temporal features. In this study, comprehensive experiments were conducted using the PTB-XL large publicly available ECG dataset and the China Physiological Signal Challenge 2018 (CPSC2018) database. The results indicate that STFAC-ECGNet surpasses other cutting-edge techniques in multiple tasks, showcasing robustness and generalization.

Atomic Evolution Mechanism and Suppression of Edge Threading Dislocations in Nitride Remote Heteroepitaxy.

The majority of dislocations in nitride epilayers are edge threading dislocations (TDs), which diminish the performance of nitride devices. However, it is extremely difficult to reduce the edge TDs due to the lack of available slip systems. Here, we systematically investigate the formation mechanism of edge TDs and find that besides originating at the coalescence boundaries, these dislocations are also closely related to geometrical misfit dislocations at the interface. Based on this understanding, we propose a novel strategy to reduce the edge TD density of the GaN epilayer by nearly 1 order of magnitude via graphene-assisted remote heteroepitaxy. The first-principles calculations confirm that the insertion of graphene dramatically reduces the energy barrier required for interfacial sliding, which promotes a new strain release channel. This work provides a unique approach to directly suppress the formation of edge TDs at the source, thereby facilitating the enhanced performance of photoelectronic and electronic devices.

Cell recognition based on features extracted by AFM and parameter optimization classifiers.

Intelligent technology can assist in the diagnosis and treatment of disease, which would pave the way towards precision medicine in the coming decade. As a key focus of medical research, the diagnosis and prognosis of cancer play an important role in the future survival of patients. In this work, a diagnostic method based on nano-resolution imaging was proposed to meet the demand for precise detection methods in medicine and scientific research. The cell images scanned by AFM were recognized by cell feature engineering and machine learning classifiers. A feature ranking method based on the importance of features to responses was used to screen features closely related to categorization and optimization of feature combinations, which helps to understand the feature differences between cell types at the micro level. The results showed that the Bayesian optimized back propagation neural network has accuracy rates of 90.37% and 92.68% on two cell datasets (HL-7702 & SMMC-7721 and GES-1 & SGC-7901), respectively. This provides an automatic analysis method for identifying cancer cells or abnormal cells, which can help to reduce the burden of medical or scientific research, decrease misjudgment and promote precise medical care for the whole society.

High-quality AFM image acquisition of living cells by modified residual encoder-decoder network.

Atomic force microscope enables ultra-precision imaging of living cells. However, atomic force microscope imaging is a complex and time-consuming process. The obtained images of living cells usually have low resolution and are easily influenced by noise leading to unsatisfactory imaging quality, obstructing the research and analysis based on cell images. Herein, an adaptive attention image reconstruction network based on residual encoder-decoder was proposed, through the combination of deep learning technology and atomic force microscope imaging supporting high-quality cell image acquisition. Compared with other learning-based methods, the proposed network showed higher peak signal-to-noise ratio, higher structural similarity and better image reconstruction performances. In addition, the cell images reconstructed by each method were used for cell recognition, and the cell images reconstructed by the proposed network had the highest cell recognition rate. The proposed network has brought insights into the atomic force microscope-based imaging of living cells and cell image reconstruction, which is of great significance in biological and medical research.

Research on Evolution of Relevant Defects in Heavily Mg-Doped GaN by H Ion Implantation Followed by Thermal Annealing.

This study focuses on the heavily Mg-doped GaN in which the passivation effect of hydrogen and the compensation effect of nitrogen vacancies (VN) impede its further development. To investigate those two factors, H ion implantation followed by thermal annealing was performed on the material. The evolution of relevant defects (H and VN) was revealed, and their distinct behaviors during thermal annealing were compared between different atmospheres (N2/NH3). The concentration of H and its associated yellow luminescence (YL) band intensity decrease as the thermal annealing temperature rises, regardless of the atmosphere being N2 or NH3. However, during thermal annealing in NH3, the decrease in H concentration is notably faster compared to N2. Furthermore, a distinct trend is observed in the behavior of the blue luminescence (BL) band under N2 and NH3. Through a comprehensive analysis of surface properties, we deduce that the decomposition of NH3 during thermal annealing not only promotes the out-diffusion of H ions from the material, but also facilitates the repair of VN on the surface of heavily Mg-doped GaN. This research could provide crucial insights into the post-growth process of heavily Mg-doped GaN.

The study on mechanical model considering optimal self-adaption in the bottleneck area.

It aims to solve the problem that the evacuation state of pedestrians depicted by the traditional social force model in a crowded multiexit scenario has a relatively large difference with the actual state, especially the 'optimal path' considered by the self-driving force is the problem of shortest path, and the multiexit evacuation mode depicted by the 'herd behavior' is the local optimum problem. Through in-depth analysis of actual evacuation data of pedestrians and causes of problem, a new crowd evacuation optimization model is established in order to effectively improve the simulation accuracy of crowd evacuation in a multi-exit environment. The model obtains the direction of motion of pedestrians using a field model, fully considers the factors such as exit distance, distribution of pedestrians and regional crowding degree, makes a global optimization for the self-driving force in the social force model using a centralized and distributed network model, and makes a local optimization for it using an elephant herding algorithm, so as to establish a new evacuation optimization method for optimal self-adaption in the bottleneck area. The performance status is compared between the improved social force model and the new model by experiments, and the key factors that affect the new model are analyzed in an in-depth manner. The results show that the new model can optimize the optimal path choice at the early stage of evacuation and improve the evacuation efficiency of pedestrians at the late stage, so as to ensure relatively even distribution of pedestrians at each exit, and also make the simulated evacuation process be more real; and the improvement in overall evacuation efficiency is greater when the number of pedestrians to be evacuated is larger. Therefore, the new model provides a method to solve the phenomenon of disorder in overall pedestrian evacuation due to excessive crowd density during the process of multi-exit evacuation.

Quasi van der Waals Epitaxy of Single Crystalline GaN on Amorphous SiO2/Si(100) for Monolithic Optoelectronic Integration.

The realization of high quality (0001) GaN on Si(100) is paramount importance for the monolithic integration of Si-based integrated circuits and GaN-enabled optoelectronic devices. Nevertheless, thorny issues including large thermal mismatch and distinct crystal symmetries typically bring about uncontrollable polycrystalline GaN formation with considerable surface roughness on standard Si(100). Here a breakthrough of high-quality single-crystalline GaN film on polycrystalline SiO2/Si(100) is presented by quasi van der Waals epitaxy and fabricate the monolithically integrated photonic chips. The in-plane orientation of epilayer is aligned throughout a slip and rotation of high density AlN nuclei due to weak interfacial forces, while the out-of-plane orientation of GaN can be guided by multi-step growth on transfer-free graphene. For the first time, the monolithic integration of light-emitting diode (LED) and photodetector (PD) devices are accomplished on CMOS-compatible SiO2/Si(100). Remarkably, the self-powered PD affords a rapid response below 250 µs under adjacent LED radiation, demonstrating the responsivity and detectivity of 2.01 × 105 A/W and 4.64 × 1013 Jones, respectively. This work breaks a bottleneck of synthesizing large area single-crystal GaN on Si(100), which is anticipated to motivate the disruptive developments in Si-integrated optoelectronic devices.

Determining the degree of chromosomal instability in breast cancer cells by atomic force microscopy.

Chromosomal instability (CIN) is a source of genetic variation and is highly linked to the malignance of cancer. Determining the degree of CIN is necessary for understanding the role that it plays in tumor development. There is currently a lack of research on high-resolution characterization of CIN and the relationship between CIN and cell mechanics. Here, a method to determine CIN of breast cancer cells by high resolution imaging with atomic force microscopy (AFM) is explored. The numerical and structural changes of chromosomes in human breast cells (MCF-10A), moderately malignant breast cells (MCF-7) and highly malignant breast cells (MDA-MB-231) were observed and analyzed by AFM. Meanwhile, the nuclei, cytoskeleton and cell mechanics of the three kinds of cells were also investigated. The results showed the differences in CIN between the benign and cancer cells. Also, the degree of structural CIN increased with enhanced malignancy of cancer cells. This was also demonstrated by calculating the probability of micronucleus formation in these three kinds of cells. Meanwhile, we found that the area of the nucleus was related to the number of chromosomes in the nucleus. In addition, reduced or even aggregated actin fibers led to decreased elasticities in MCF-7 and MDA-MB-231 cells. It was found that the rearrangement of actin fibers would affect the nucleus, and then lead to wrong mitosis and CIN. Using AFM to detect chromosomal changes in cells with different malignancy degrees provides a new detection method for the study of cell carcinogenesis with a perspective for targeted therapy of cancer.

Phosphor-free micro-pyramid InGaN-based white light-emitting diode with a high color rendering index on a ß-Ga2O3 substrate.

We demonstrate the InGaN/GaN-based monolithic micro-pyramid white (MPW) vertical LED (VLED) grown on (-201)-oriented ß-Ga2O3 substrate by selective area growth. The transmission electron microscopy (TEM) reveals an almost defect-free GaN pyramid structure on (10-11) sidewalls, including stacked dual-wavelength multi-quantum wells (MQWs). From the electroluminescence (EL) spectra of the fabricated MPW VLED, a white light emission with a high color rendering index (CRI) of 97.4 is achieved. Furthermore, the simulation shows that the light extraction efficiency (LEE) of the MPW VLED is at least 4 times higher compared with the conventional planar LED. These results show that the MPW VLED grown on ß-Ga2O3 has great potential for highly efficient phosphor-free white light emission.

ß-Ga2O3 Air-Channel Field-Emission Nanodiode with Ultrahigh Current Density and Low Turn-On Voltage.

Field-emission nanodiodes with air-gap channels based on single ß-Ga2O3 nanowires have been investigated in this work. With a gap of ∼50 nm and an asymmetric device structure, the proposed nanodiode achieves good diode characteristics through field emission in air at room temperature. Measurement results show that the nanodiode exhibits an ultrahigh emission current density, a high enhancement factor of >2300, and a low turn-on voltage of 0.46 V. More impressively, the emission current almost keeps constant over a wide range (8 orders of magnitude) of air pressures below 1 atm. Meanwhile, the fluctuation in field-emission current is below 8.7% during long-time monitoring, which is better than the best reported field-emission device based on ß-Ga2O3 nanostructures. All of these results indicate that ß-Ga2O3 air-gapped nanodiodes are promising candidates for vacuum electronics that can also operate in air.

Optimal drug regimens for improving ALP biochemical levels in patients with primary biliary cholangitis refractory to UDCA: a systematic review and Bayesian network meta-analysis.

BACKGROUND: Up to 40% of UDCA-treated patients do not have an adequate clinical response. Farnesoid X receptor agonists, peroxisome proliferator-activated receptor agonists, and fibroblast growth factor 19 analogs were developed as adjunctive therapy. The aim of this network meta-analysis was to compare the efficacy of these drugs as add-on therapy for patients with primary biliary cholangitis (PBC) refractory to UDCA in improving ALP levels. METHODS: We searched PubMed, Embase, Web of Science, and the Cochrane Library for eligible studies until 1 December 2023. Randomized controlled trials, cohort studies, and case-control studies comparing the efficacy of different combination treatments and UDCA monotherapy in UDCA-refractory PBC patients were included in the analysis. Cumulative probability was used to rank the included treatments. RESULTS: A total of 23 articles were eligible for our network meta-analysis. In terms of improving ALP levels, In terms of improving ALP biochemical levels, bezafibrate combined with UDCA (MD 104.49, 95% CI 60.41, 161.92), fenofibrate combined with UDCA (MD 87.81, 95% CI (52.34, 129.79), OCA combined with UDCA (MD 65.21, 95% CI 8.99, 121.80), seladelpar combined with UDCA (MD 117.39, 95% CI 19.97, 213.95), elafibranor combined with UDCA (MD 140.73, 95% CI 74.34, 209.98), saroglitazar combined with UDCA (MD 132.09, 95% CI 13.99, 247.04) was more effective than UDCA monotherapy. Elafibranor in combination with UDCA was the most likely (32%) to be the optimal drug regimen. CONCLUSION: As second-line therapy for UDCA-refractory PBC, PPAR agonists were more effective than any other drugs with other mechanisms in improving ALP biochemical levels, with elafibranor being the best.

Wafer-Scale Transferrable GaN Enabled by Hexagonal Boron Nitride for Flexible Light-Emitting Diode.

Epitaxy growth and mechanical transfer of high-quality III-nitrides using 2D materials, weakly bonded by van der Waals force, becomes an important technology for semiconductor industry. In this work, wafer-scale transferrable GaN epilayer with low dislocation density is successfully achieved through AlN/h-BN composite buffer layer and its application in flexible InGaN-based light-emitting diodes (LEDs) is demonstrated. Guided by first-principles calculations, the nucleation and bonding mechanism of GaN and AlN on h-BN is presented, and it is confirmed that the adsorption energy of Al atoms on O2 -plasma-treated h-BN is over 1 eV larger than that of Ga atoms. It is found that the introduced high-temperature AlN buffer layer induces sufficient tensile strain during rapid coalescence to compensate the compressive strain generated by the heteromismatch, and a strain-relaxation model for III-nitrides on h-BN is proposed. Eventually, the mechanical exfoliation of single-crystalline GaN film and LED through weak interaction between multilayer h-BN is realized. The flexible free-standing thin-film LED exhibits ≈66% luminescence enhancement with good reliability compared to that before transfer. This work proposes a new approach for the development of flexible semiconductor devices.

Use of Atomic Force Microscopy in UVB-Induced Chromosome Damage Provides Important Bioinformation for Cell Damage Assessment.

The chromosomal structure derived from UVB-stimulated HaCaT cells was detected by atomic force microscopy (AFM) to evaluate the effect of UVB irradiation. The results showed that the higher the UVB irradiation dose, the more the cells that had chromosome aberration. At the same time, different representative types of chromosome structural aberrations were investigated. We also revealed damage to both DNA and cells under the corresponding irradiation doses. It was found that the degree of DNA damage was directly proportional to the irradiation dose. The mechanical properties of cells were also changed after UVB irradiation, suggesting that cells experienced a series of chain reactions from inside to outside after irradiation. The high-resolution imaging of chromosome structures by AFM after UVB irradiation enables us to relate the damage between chromosomes, DNA, and cells caused by UVB irradiation and provides specific information on genetic effects.

Lattice modulation strategies for 2D material assisted epitaxial growth.

As an emerging single crystals growth technique, the 2D-material-assisted epitaxy shows excellent advantages in flexible and transferable structure fabrication, dissimilar materials integration, and matter assembly, which offers opportunities for novel optoelectronics and electronics development and opens a pathway for the next-generation integrated system fabrication. Studying and understanding the lattice modulation mechanism in 2D-material-assisted epitaxy could greatly benefit its practical application and further development. In this review, we overview the tremendous experimental and theoretical findings in varied 2D-material-assisted epitaxy. The lattice guidance mechanism and corresponding epitaxial relationship construction strategy in remote epitaxy, van der Waals epitaxy, and quasi van der Waals epitaxy are discussed, respectively. Besides, the possible application scenarios and future development directions of 2D-material-assisted epitaxy are also given. We believe the discussions and perspectives exhibited here could help to provide insight into the essence of the 2D-material-assisted epitaxy and motivate novel structure design and offer solutions to heterogeneous integration via the 2D-material-assisted epitaxy method.

Plasmon-enhanced deep ultraviolet Micro-LED arrays for solar-blind communications.

Localized surface plasmon resonance (LSPR)-enhanced deep ultraviolet (DUV) Micro-light emitting diodes (Micro-LEDs) using Al nanotriangle arrays (NTAs) are reported for improving the -3 dB modulation bandwidth. Through self-assembled nanospheres, the high-density Al NTAs arrays are transferred into the designated p-AlGaN region of the Micro-LEDs, realizing the effect of LSPR coupling. A 2.5-fold enhancement in photoluminescence (PL) intensity is demonstrated. Combined with the PL intensity ratio at 300 K and 10 K, internal quantum efficiency (IQE) may be increased about 15-20% by the plasmonic effect and the carrier lifetime decreases from 1.15 ns to 0.82 ns, suggesting that LSPR accelerates the spontaneous emission rate. Resulting from the improvement of the IQE, the electroluminescence intensity of Micro-LED arrays with LSPR is obviously increased. Meanwhile, the -3 dB bandwidth of 6 × 6 Micro-LED arrays is increased from 180 MHz to 300 MHz at a current density of 200 A/cm2. A potential way is proposed to further increase both the IQE and the modulation bandwidth of DUV Micro-LEDs.

Cell recognition based on atomic force microscopy and modified residual neural network.

Cell recognition methods are in high demand in cell biology and medicine, and the method based on atomic force microscopy (AFM) shows a great value in application. The difference in mechanical properties or morphology of cells has been frequently used to detect whether cells are cancerous, but this detection method cannot be a general means for cancer cell detection, and the traditional artificial feature extraction method also has its limitations. In this work, we proposed an analytic method based on the physical properties of cells and deep learning method for recognizing cell types. The residual neural network used for recognition was modified by multi-scale convolutional fusion, attention mechanism and depthwise separable convolution, so as to optimize feature extraction and reduce operation costs. In the method, the collected cells were imaged by AFM, and the processed images were analyzed by the optimized convolutional neural network. The recognition results of two groups of cells (HL-7702 and SMMC-7721, SGC-7901 and GES-1) by this method show that the recognition rate of dataset with the combination of cell surface morphology, adhesion and Young's modulus is higher, and the recognition rate of the dataset with optimal resolution is higher. Our study indicated that the recognition of physical properties of cells using deep learning technology can serve as a universal and effective method for the automated analysis of cell information.

A wearable gloved sensor based on fluorescent Ag nanoparticles and europium complexes for visualized assessment of tetracycline in food samples.

The abuse of tetracycline antibiotics leads to accumulating residues in the human body, seriously affecting human health. Establishing a sensitive, efficient, and reliable method for qualitative and quantitative detection of tetracycline (TC) is necessary. This study integrated silver nanoclusters and europium-based materials into the same nano-detection system to construct a visual and rapid TC sensor with rich fluorescence color changes. The nanosensor has the advantages of a low detection limit (10.5 nM), high detection sensitivity, fast response, and wide linear range (0-30 µM), which can meet the analysis requirements of different types of food samples. In addition, portable devices based on paper and gloves were designed. Through the smartphone's chromaticity acquisition and calculation analysis application (APP), the real-time rapid visual intelligent analysis of TC in the sample can be realized, which guides the intelligent application of multicolor fluorescent nanosensors.

Quasi-van der Waals Epitaxy of a Stress-Released AlN Film on Thermally Annealed Hexagonal BN for Deep Ultraviolet Light-Emitting Diodes.

The heteroepitaxy of high-quality aluminum nitride (AlN) with low stress is essential for the development of energy-efficient deep ultraviolet light-emitting diodes (DUV-LEDs). In this work, we realize that quasi-van der Waals epitaxy growth of a stress-released AlN film with low dislocation density on hexagonal boron nitride (h-BN)/sapphire suffered from high-temperature annealing (HTA) treatment and demonstrate its application in a DUV-LED. It is revealed that HTA effectively improves the crystalline quality and surface morphology of monolayer h-BN. Guided by first-principles calculations, we demonstrate that h-BN can enhance lateral migration of Al atoms due to the ability to lower the surface migration barrier (less than 0.14 eV), resulting in the rapid coalescence of the AlN film. The HTA h-BN is also proved to be efficient in reducing the dislocation density and releasing the large strain in the AlN epilayer. Based on the low-stress and high-quality AlN film on HTA h-BN, the as-fabricated 290 nm DUV-LED exhibits 80% luminescence enhancement compared to that without h-BN, as well as good reliability with a negligible wavelength shift under high current. These findings broaden the applications of h-BN in favor of III-nitride and provide an opportunity for further developing DUV optoelectronic devices on large mismatched heterogeneous substrates.

Principles for 2D-Material-Assisted Nitrides Epitaxial Growth.

Beyond traditional heteroepitaxy, 2D-materials-assisted epitaxy opens opportunities to revolutionize future material integration methods. However, basic principles in 2D-material-assisted nitrides' epitaxy remain unclear, which impedes understanding the essence, thus hindering its progress. Here, the crystallographic information of nitrides/2D material interface is theoretically established, which is further confirmed experimentally. It is found that the atomic interaction at the nitrides/2D material interface is related to the nature of underlying substrates. For single-crystalline substrates, the heterointerface behaves like a covalent one and the epilayer inherits the substrate's lattice. Meanwhile, for amorphous substrates, the heterointerface tends to be a van der Waals one and strongly relies on the properties of 2D materials. Therefore, modulated by graphene, the nitrides' epilayer is polycrystalline. In contrast, single-crystalline GaN films are successfully achieved on WS2 . These results provide a suitable growth-front construction strategy for high-quality 2D-material-assisted nitrides' epitaxy. It also opens a pathway toward various semiconductors heterointegration.

Transdermal and lateral effective diffusivities for drug transport in stratum corneum from a microscopic anisotropic diffusion model.

This paper presents a computational model of molecular diffusion through the interfollicular stratum corneum. Specifically, it extends an earlier two-dimensional microscopic model for the permeability in two ways: (1) a microporous leakage pathway through the intercellular lipid lamellae allows slow permeation of highly hydrophilic permeants through the tissue; and (2) the model yields explicit predictions of both lateral (D‾‖sc) and transdermal (D‾⊥sc) effective (average, homogenized) diffusivities of solutes within the tissue. We present here the mathematical framework for the analysis and a comparison of the predictions with experimental data on desorption of both hydrophilic and lipophilic solutes from human stratum corneum in vitro. Diffusion in the lipid lamellae is found to make the effective diffusivity highly anisotropic, with the predicted ratio D‾‖sc/D‾⊥sc ranging from 34 to 39 for fully hydrated skin and 150 to more than 1000 for partially hydrated skin. The diffusivities and their ratio are in accord with both experimental data and the results of mathematical analyses performed by others.