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The daily operations of large hydropower stations on rivers induce frequent variations in downstream water levels and flow velocities, resulting in unsteady and complex hydraulic characteristics at the confluence of the main stream and its tributaries, which adversely affect navigation safety. The continuity and momentum equations, along with the RNG k-ϵ turbulence model and the VOF model, were employed to simulate the river flow process at the confluence under unsteady flow conditions. The simulated results for water levels and velocity vector fields are in good agreement with experimental data. Variations in hydraulic characteristics, including water level, flow velocity, and longitudinal gradient at the confluence of the main stream and its tributaries, were analysed. The results indicated that the water level at the confluence decreases when the tributary merges with the main stream. As the confluence ratio increases, fluctuations in the water level at the confluence decrease. However, an increase in the staggered period results in greater fluctuations in the water level within this region. Moreover, a crescent-shaped high-speed flow region is formed at the confluence of the tributary and the main stream. As the unsteady flow discharge of the main stream increases, the relative area of this region correspondingly enlarges, reaching its maximum at peak discharge, and subsequently gradually diminishes as the discharge decreases. Based on these simulation data, a Long Short-Term Memory (LSTM) model was developed to effectively predict water levels and flow velocities, providing a more convenient and accurate method for obtaining real-time information on confluence areas than traditional mathematical and statistical approaches. This study provides novel insights into predicting flow characteristics in confluence areas, thereby offering a basis for formulating navigation safety plans.

Abstract Chinese traditional music, a vital expression of Chinese cultural heritage, possesses both a profound emotional resonance and artistic allure. This study sets forth to refine and analyze the acoustical features essential for the aesthetic recognition of Chinese traditional music, utilizing a dataset spanning five aesthetic genres. Through recursive feature elimination, we distilled an initial set of 447 low-level physical features to a more manageable 44, establishing their feature-importance coefficients. This reduction allowed us to estimate the quantified influence of higher-level musical components on aesthetic recognition, following the establishment of a correlation between these components and their physical counterparts. We conducted a comprehensive examination of the impact of various musical elements on aesthetic genres. Our findings indicate that the selected 44-dimensional feature set could enhance aesthetic recognition. Among the high-level musical factors, timbre emerges as the most influential, followed by rhythm, pitch, and tonality. Timbre proved pivotal in distinguishing between the JiYang and BeiShang genres, while rhythm and tonality were key in differentiating LingDong from JiYang, as well as LingDong from BeiShang.

Spin‐orbital angular momentum conversion (SOC) of light has found applications in classical and quantum optics. However, the existing SOC elements suffer severe restrictions on broadband integrated applications at miniature scales, due to bulky configurations, single function, and failing to control the dispersion. Herein, a high‐efficiency broadband achromatic method for independently and elaborately engineering the dispersion and the SOC of light based on a cascaded metasurface device is proposed. The metadevice is capable of efficiently decoupling the SOC from the modulation of dispersion with high‐broadband focusing efficiency up to 75%. For the proof of concept, the generation of high‐efficiency achromatic‐focused and spin‐controlled optical vortices with switchable topological charge (lσ=+1=1 and lσ=−1=2) is successfully demonstrated. The presence of achromatically and highly concentrated optical vortices with tunable photonic angular momentum using spin as an optical knob makes the proposed ultracompact and multifunctional metadevice a promising platform for optical micromanipulation at nanoscale dimensions.

Background: Recently, the utilization of sugar as a cryoprotectant has garnered significant attention. Sucrose and trehalose, as non-permeable cryoprotectants, can effectively regulate the osmotic pressure inside and outside cells while maintaining cell membrane stability during cryopreservation. Furthermore, it has been observed that monosaccharides sugars, particularly fructose, exhibit superior efficacy in preserving the quality of frozen substances as compared to disaccharides and trisaccharides sugars. Nevertheless, there is currently limited research assessing the cryopreservation effects of sucrose, trehalose, and fructose. The objective of this experiment is to identify the best cryoprotectant between sucrose, trehalose, and fructose for intact rat ovaries. Methods: Intact ovaries with blood vessels were obtained from 20 adult Lewis female rats and divided accordingly into four groups: control (non-vitrified), sucrose, fructose, and trehalose. The ovarian samples were subjected to a stepped cryoprotectant exposure and subsequently follicular histological analysis using light and electron microscopy. Ovarian cell apoptosis was evaluated by BCL2-Associated X (BAX) immunohistochemistry and Terminal Deoxynucleotidyl Transferase-Mediated Deoxyuridine Triphosphate nick End-Labeling (TUNEL) analyses. Results: The sucrose and the trehalose groups preserved the ovarian histological structure better than the fructose group. Additionally, there was no statistical difference in the total follicle number between the sucrose and trehalose groups, but the percentage of apoptotic cells in the trehalose group was significantly lower than that of the sucrose group (p < 0.01). Conclusions: Sucrose and trehalose perfusion protocols preserved the ovarian histology. However, the least apoptotic changes were observed in the trehalose group. The study suggested that trehalose would be a well-applied cryoprotectant in the cryopreservation of intact rat ovaries.

Abstract Artificial intelligence has been a research highlight in recent years. Therefore, quantitative analysis about human perception has been of great concern, for instance, affective computing based on music or picture materials. As music is one of the main art forms of auditory aesthetics, its quantitative studies related to aesthetic perception show great potential. This study proposed the evaluation method of aesthetic categories for Chinese traditional music. According to this method, a dataset with aesthetic‐emotional multi‐annotation was established. The dataset was composed of 500 clips of Chinese traditional music, and it consisted of five aesthetic categories. The distribution characteristics of different aesthetic categories in the emotional dimension space were analysed. Furthermore, by extracting corresponding acoustical features, we tested the accuracy of different classifiers for aesthetic classification. The results showed that the highest accuracy was 65.37% by logistic regression. This work provided a data foundation for the quantitative research and aesthetics computation of Chinese traditional music. The database also can be used for the research of cross‐cultural music perception.

A case study of the complex interplay of electrodes surface potentials and reactants oxidation potentials for photofuel cell (PFC) operation is highlighted. Cyclic voltammetry (CV) reveals that InN/InGaN quantum dots (QDs) are active for H2O2 and water oxidation in the light. InGaN nanowires (NWs) are active for H2O2 oxidation in the light and dark. In H2O2 PFC operation, high performance is achieved for InN/InGaN QDs in the light. NWs operate with lower performance in the light and dark. Similarly, with glucose as biofuel, the NWs are active in the light and dark, the QDs only in the light. All results are explained by the surface states on the c-plane QDs and m-plane NW sidewalls, the oxidation potentials of H2O2, water and glucose, and the catalytic activity of the QDs.

Many electrical equipment malfunction text messages are collected during power system operation and maintenance procedures. These texts usually contain crucial information for maintenance and condition monitoring. Because these power system malfunction texts are characterized by multidomain vocabularies, complex-syntactic structures, and long sentences, it is challenging to for automated systems to capture their semantic meaning and essential information. To address this issue, we propose a hybrid natural language processing (hybrid-NLP) algorithm to extract entities that represent electrical equipment. This algorithm is composed of a dictionary-based method, a language technology platform (LTP) tool, and the bidirectional encoder representations from a transformers-conditional random field (BERT-CRF) model. Significantly, the softmax output layer of the bidirectional encoder representations from the transformers (BERT) model is replaced by the conditional random field (CRF) algorithm to strengthen the contextual relationships between words and thus solve the local optimization of the preferred word label. The effectiveness of the proposed hybrid-NLP method is verified on a realistic dataset. Moreover, a statistical analysis is conducted to provide a reference for the operation and maintenance of power systems.

Optical analog computing has natural advantages of parallel computation, high speed and low energy consumption over traditional digital computing. To date, research in the field of on-chip optical analog computing has mainly focused on classical mathematical operations. Despite the advantages of quantum computing, on-chip quantum analog devices based on metasurfaces have not been demonstrated so far. In this work, based on a silicon-on-insulator (SOI) platform, we illustrated an on-chip quantum searcher with a characteristic size of 60 × 20 μm2. We applied classical waves to simulate the quantum search algorithm based on the superposition principle and interference effect, while combining it with an on-chip metasurface to realize modulation capability. The marked items are found when the incident waves are focused on the marked positions, which is precisely the same as the efficiency of the quantum search algorithm. The proposed on-chip quantum searcher facilitates the miniaturization and integration of wave-based signal processing systems.

Music emotion recognition is increasingly becoming important in scientific research and practical applications. Due to the differences in musical characteristics between Western and Chinese classical music, it is necessary to investigate the distinctions in music emotional feature sets to improve the accuracy of cross-cultural emotion recognition models. Therefore, a comparative study on emotion recognition in Chinese and Western classical music was conducted. Using the V-A model as an emotional perception model, approximately 1000 pieces of Western and Chinese classical excerpts in total were selected, and approximately 20-dimension feature sets for different emotional dimensions of different datasets were finally extracted. We considered different kinds of algorithms at each step of the training process, from pre-processing to feature selection and regression model selection. The results reveal that the combination of MaxAbsScaler pre-processing and the wrapper method using the recursive feature elimination algorithm based on extremely randomized trees is the optimal algorithm. The harmonic change detection function is a culturally universal feature, whereas spectral flux is a culturally specific feature for Chinese classical music. It is also found that pitch features are more significant for Western classical music, whereas loudness and rhythm features are more significant for Chinese classical music.

The heterostructuring and doping concepts have proved to obtain a novel n-InGaN/p-Cu2O nanowire (NW) photoanode by strong enhancement of the photocurrent compared to a bare InGaN NW photoanode in solar water splitting. The large photocurrent is due to the maximized photocarrier separation and hole transfer to the surface in the depletion zone of the p–n heterojunction established by the p-Cu2O layer, forming a thin, uniform shell-layer around the n-InGaN NW core by electrodeposition. For sufficiently thin Cu2O layers, the upward energy band bending in the depletion zone extends up to the surface for optimized hole transport and surface reaction. Thick Cu2O layers on top of the InGaN NWs act as common photocathodes. The functional InGaN/Cu2O heterostructure core-shell NW photoanode is chemically self-stabilized at positive applied voltage by a thin CuO surface layer. Final deposition of the earth-abundant NiOOH co-catalyst boosts the photocurrent of the InGaN/Cu2O/NiOOH complete NW photoanode into the competitive mA/cm2 range.

Photonic integrated circuits (PICs) have garnered increasing attention because of their high efficiency in information processing. Recently, lithium niobate on insulator (LNOI) has become a new platform for PICs with excellent properties. Several tunable devices such as on-chip tunable devices that utilize the electric-optic effect of LN have been reported. However, an on-chip electrically tunable beam modulator that can focus or deflect the wave has not yet been developed. In this study, we designed an electrically tunable LNOI metasurface for on-chip optical beam manipulation. With a carefully designed local phase profile, we realized the tunable focusing and reflection functions on the chip. As the bias voltage varies, the focusing length can be shifted up to 19.9 μm (~13λ), whereas the focusing efficiency remains greater than 72%. A continuously tunable deflection can also be achieved efficiently within a range of 0–45°. The beam modulator enhances the ability to manipulate light on LNOI chips, which is expected to promote the development of integrated on-chip photonics.

We present a basic, comprehensive study of the electrocatalytic activity of epitaxial InN/InGaN quantum dots (QDs) by cyclic voltammetry, electrochemical impedance spectroscopy, linear sweep voltammetry and capacitance-voltage measurements, using the ferro/ferricyanide redox probe. Key is the direct proof of the dependence of the catalytic activity on the QD structural properties and of the existence and overall tunability of high positive surface charge on the QDs being in origin of the catalytic activity together with the zero-dimensional electronic properties. This fundamental assessment paves the way to fine-tuning the artificial QD structure as efficient catalyst to further boost the performance of biosensors and photoanodes for solar hydrogen generation. Keywords: Quantum dots, InN, InGaN, Catalysis

We demonstrate an all-solid-state potentiometric sensor constructed from solid-state InN/InGaN sensing- and reference electrodes with the epitaxial InN/InGaN layers directly grown on Si substrates. The sensor, evaluated in KCl aqueous solution, exhibits super-Nernstian sensitivity of −78 mV/decade with good linearity for concentrations of 0.01–1 M, which is the physiologically relevant range. Good stability and re-usability are demonstrated by a long-time drift below 0.2 mV h−1 and standard deviation of 8 mV for repeated measurements over 10 d. These properties fulfil the requirements for compact, robust and highly sensitive all-solid-state sensors and sensor arrays. [ABSTRACT FROM AUTHOR]

We introduce cyclic voltammetry (CV) with dissolved, chemically stable electrolytes as a sensitive, non-destructive and fast method for the analysis of the surface morphology of InGaN epitaxial layers and nanostructures grown on silicon. The surface area is probed by the electric double layer capacitance (EDLC) formed upon attachment of ions in solution under close-to-equilibrium conditions. The dynamics of the measured EDLC as a function of scan rate characterizes the nano-scale surface morphology. The dynamics of the measured EDLC follows a power law dependence on the scan rate. The exponent clearly correlates with the RMS surface roughness at the nano/atomic scale deduced from atomic force microscopy. CV is thus complementary to other established methods for the morphological analysis of epitaxial layers in general. [ABSTRACT FROM AUTHOR]