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To overcome the low efficiency of overall water splitting, highly effective and stable catalysts are in urgent need, especially for the anode oxygen evolution reaction (OER). In this case, nickel selenides appear as good candidates to catalyze OER and other substitutable anodic reactions due to their high electronic conductivity and easily tunable electronic structure to meet the optimized adsorption ability. Herein, an interesting phase transition from the hexagonal phase of NiSe (H-NiSe) to the rhombohedral phase of NiSe (R-NiSe) induced by the doping of cobalt atoms is reported. The five-coordinated R-NiSe is found to grow adjacent to the six-coordinated H-NiSe, resulting in the formation of the H-NiSe/R-NiSe heterostructure. Further characterizations and calculations prove the reduced splitting energy for R-NiSe and thus the less occupancy in the t2g orbits, which can facilitate the electron transfer process. As a result, the Co2 -NiSe/NF shows a satisfying catalytic performance toward OER, hydrogen evolution reaction, and (hybrid) overall water splitting. This work proves that trace amounts of Co doping can induce the phase transition from H-NiSe to R-NiSe. The formation of less-coordinated species can reduce the t2g occupancy and thus enhance the catalytic performance, which might guide rational material design.
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A mid-infrared BaGa4Se7 optical parametric oscillator with high conversion efficiency and beam quality is demonstrated, which is pumped by a 2.79-µm electro-optically Q-switched Cr, Er:YSGG laser. A pulse energy of 3.5 mJ with a pulse width of 21 ns at 10 Hz is obtained in the range of 3.94-9.55 µm, and the beam quality factors are measured to be Mx2=5.0 and My2=4.6. The optical-to-optical conversion efficiency is 18.9%, and the slope efficiency is 31.6%, which is a 59% improvement on the best of the previously reported slope efficiencies for BaGa4Se7-based OPOs.
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We use ultrafast phase-contrast imaging to directly observethe cone-like terahertz (THz) Cherenkov wave generated by optical rectification of femtosecond laser pulses focused into bulk lithium niobate (LiNbO3) single crystals. The transverse imaging geometry allows the Cherenkov angle, THz wave velocity, and optical pump pulse group velocity to be measured. Furthermore, transition-like THz radiation generated by the femtosecond laser pulse at the air-crystal boundary is observed. The effect of optical pump pulse polarization on the generation of THz Cherenkov waves and transition-like radiation in LiNbO3 is also investigated.
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BACKGROUND: Ultrasound is considered a reliable, widely available, non-invasive, and inexpensive imaging technique for assessing and detecting the development phases of cancer; both in vivo and ex vivo, and for understanding the effects on cell cycle and viability after ultrasound treatment. METHODS: Based on the topological continuity characteristics, and that adjacent points or areas represent similar features, we propose a topological penalized convex objective function of sparse coding, to recognize similar cell phases. RESULTS: This method introduces new features using a deep learning method of sparse coding with topological continuity characteristics. Large-scale comparison tests demonstrate that the RAW can outperform SIFT GIST and HoG as the input features with this method, achieving higher sensitivity, specificity, F1 score, and accuracy. CONCLUSIONS: Experimental results show that the proposed topological sparse coding technique is valid and effective for extracting new features, and the proposed system was effective for cell recognition of microscopy images of theMDA-MB-231 cell line. This method allows features from sparse coding learning methods to have topological continuity characteristics, and the RAW features are more applicable for the deep learning of the topological sparse coding method than SIFT GIST and HoG.
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Microscopía por Video/métodos , Neoplasias/patología , Reconocimiento de Normas Patrones Automatizadas/métodos , Algoritmos , Línea Celular Tumoral , Supervivencia Celular , Humanos , Imagen de Lapso de Tiempo/métodosRESUMEN
Traditional differential expression genes (DEGs) identification models have limitations in small sample size datasets because they require meeting distribution assumptions, otherwise resulting high false positive/negative rates due to sample variation. In contrast, tabular data model based on deep learning (DL) frameworks do not need to consider the data distribution types and sample variation. However, applying DL to RNA-Seq data is still a challenge due to the lack of proper labeling and the small sample size compared to the number of genes. Data augmentation (DA) extracts data features using different methods and procedures, which can significantly increase complementary pseudo-values from limited data without significant additional cost. Based on this, we combine DA and DL framework-based tabular data model, propose a model TabDEG, to predict DEGs and their up-regulation/down-regulation directions from gene expression data obtained from the Cancer Genome Atlas database. Compared to five counterpart methods, TabDEG has high sensitivity and low misclassification rates. Experiment shows that TabDEG is robust and effective in enhancing data features to facilitate classification of high-dimensional small sample size datasets and validates that TabDEG-predicted DEGs are mapped to important gene ontology terms and pathways associated with cancer.
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Aprendizaje Profundo , RNA-Seq , Humanos , RNA-Seq/métodos , Perfilación de la Expresión Génica/métodos , Neoplasias/genética , Biología Computacional/métodos , Bases de Datos Genéticas , Regulación Neoplásica de la Expresión GénicaRESUMEN
Understanding the structure-activity relationship of catalysts and the reaction pathway is crucial for designing efficient, selective, and stable electrocatalytic systems. In situ vibrational spectroscopy provides a unique tool for decoding molecular-level factors involved in electrocatalytic reactions. Typically, spectra are recorded when the system reaches steady states under set potentials, known as steady-state measurements, providing static pictures of electrode properties at specific potentials. However, transient information that is crucial for understanding the dynamic of electrocatalytic reactions remains elusive. Thus, time-resolved in situ vibrational spectroscopies are developed. This mini review summarizes time-resolved in situ infrared and Raman techniques and discusses their application in electrocatalytic research. With different time resolutions, these time-resolved techniques can capture unique dynamic processes of electrocatalytic reactions, short-lived intermediates, and the surface structure revolution that would be missed in steady-state measurements alone. Therefore, they are essential for understanding complex reaction mechanisms and can help unravel important molecular-level information hidden in steady states. Additionally, improving spectral time resolution, exploring low/ultralow frequency detection, and developing operando time-resolved devices are proposed as areas for advancing time-resolved techniques and their further applications in electrocatalytic research.
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This article concentrates on the adaptive neural control approach of n -link flexible-joint electrically driven robots. The presented control method only needs to know the position and armature current information of the flexible-joint manipulator. An adaptive observer is designed to estimate the velocities of links and motors, and radial basis function neural networks are applied to approximate the unknown nonlinearities. Based on the backstepping technique and the Lyapunov stability theory, the observer-based neural control issue is addressed by relying on uplink-event-triggered states only. It is demonstrated that all signals are semi-globally ultimately uniformly bounded and the tracking errors can converge to a small neighborhood of zero. Finally, simulation results are shown to validate the designed event-triggered control strategy.
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A systemic investigation of the terahertz (THz) transmission of La0.67Ca0.33MnO3 film on the (001)-oriented NdGaO3 substrate under external magnetic field and low temperature have been performed. The significant THz absorption difference between the out-of-plane and the in-plane magnetic field direction is observed, which is consistent with the electrical transport measurement using the standard four-probe technique. Furthermore, we find that the complex THz conductivities can be reproduced in terms of the Drude Smith equation as the magnetic field is perpendicular to the film plane, whereas it deviates from this model when the in-plane magnetic field is applied. We suggest that such anisotropies in THz transport dynamics have close correspondences with the phase separation and anisotropic magnetoresistance effects in the perovskite-structured manganites. Our work demonstrates that the THz time-domain spectroscopy (TDS) can be an effective non-contact method for studying the magneto-transport properties of the perovskite-structured manganites.
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Thermoelectric conversion from low-grade heat to electricity is regarded as the highly reliable and environmentally friendly technology in energy-harvesting area. However, how to develop efficient thermoelectric materials using a simple fabrication method is still a critical challenge in thermoelectric community. Here, we first fabricate the high thermoelectric performance of Ca-doped AgSbSe2 with a hierarchical microstructure using a facile approach, namely, mechanical alloying (for only 30 min) and a quick hot-pressing method. The hierarchical microstructure, including point defects (atomic scale), dislocations, and nanoprecipitates (nanoscale) as well as grain boundaries (microscale), strongly scatters phonons with comparable sizes without deterioration of carrier mobility. Because of the higher carrier concentration of nanostructured AgSbSe2 than that of coarse-grain AgSbSe2, power factor can also be improved slightly after nanostructuring. Ca doping further optimizes the carrier concentration and creates the point-defect scattering of phonons, leading to the ultralow lattice thermal conductivity â¼0.27 W m-1 K-1 at 673 K and thus largely improving the peak ZT up to 1.2. The high thermoelectric performance in combination with a facile fabrication method highlights AgSbSe2-based materials as robust thermoelectric candidates for energy harvesting.
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A tunable diode laser (TDL) was used to measure hydrogen chloride (HCl) spectra at 5747 cm(-1) (1.74 µm) and temperatures of 25-950 °C in a quartz cell. The purpose was to evaluate the capability of monitoring HCl concentration under pyrohydrolysis conditions using a near-infrared (NIR) laser. These conditions are characterized by 20-40% HCl, 2-40% H2O, and the presence of metal chloride vapors at temperatures of 600-1000 °C. Spectral peak area measurements of HCl-N2 mixtures at atmospheric pressure and a path length of 8.1 cm showed linear absorption behavior between concentrations of 5-95% and temperatures of 25-950 °C. Results from the addition of 2-40% water (H2O) indicate that the HCl peak area relationships are not affected for temperatures of 350-950 °C. Evaporating NiCl2 within the cell did not show spectral interference effects with HCl between 650 and 850 °C. The results from this work indicate that a near-infrared optical sensor is capable of measuring high HCl concentrations at high temperatures in the presence of high H2O content during pyrohydrolysis process conditions.