Henan University

The miniaturization of electronics and increased power density pose significant challenges, including short circuits, electromagnetic interference (EMI) and heat accumulation. Developing electrically insulative materials that integrate EMI shielding and heat...

Dual‐band photodetectors have huge potential for application in secure optical communication, multicolor imaging, and logical operation. However, the majority of currently documented dual‐band photodetectors suffer from high energy consumption and poor photoresponse performance; especially, the dual‐band photodetectors targeted at the UV region have yet not been reported. In this study, for the first time, a self‐powered UV dual‐band photodetector based on Cs3BiCl6/GaN heterojunction is designed and fabricated through a dual‐source co‐evaporation technique. Experiments and theoretical simulations confirm that the unique dual‐band absorption characteristics of Cs3BiCl6 and the strong surface‐charge recombination near the Cs3BiCl6 surface are the primary factors enabling the achievement of UV dual‐band photodetection. Importantly, owing to the well‐matched energy band alignment of Cs3BiCl6 and GaN, the photodetectors exhibit ultra‐high Ion/Ioff ratio (1 × 10⁷), large specific detectivity (1.23 × 10¹² Jones), and ultrafast response speed (τr/τf = 28 µs/190 µs). Finally, utilizing the UV dual‐band characteristics of the fabricated device, the logical operation and encrypted photo‐communication applications are successfully demonstrated. The obtained results suggest that the lead‐free perovskite Cs3BiCl6 is potentially an attractive candidate for the manufacture of high‐performance UV dual‐band photodetectors that can be employed in advanced encryption technology.

In China, the acquisition of English by native Xishuangbanna Dai speakers is a typical example of third language (L3) learning. However, previous studies primarily focus on L3 teaching, and cross-linguistic influence, particularly at the phonological level, is under-researched. The present study selected the English vowel /ɑː/ and the English consonants /b/ and /d/, which are similar to Dai and Mandarin, as target sounds. To examine the cross-linguistic data differences, both the values of the voice onset time (VOT) of the target consonants and the F1/F2 values of the target vowels were extracted from the recorded wordlist in the phonetic experiment, and Kruskal–Wallis tests, Mann–Whitney U tests, and the Euclidean distance of the relevant data were conducted using SPSS. The VOT values of L3 English were found to differ significantly from standard English, in that they shifted from negative to positive, approaching those of standard Mandarin. A significant negative correlation between the number of foreign languages known by the participants and the VOT values was observed. The F1 and F2 values of L3 English also differed significantly from standard English, with a lower and more forward tongue position among the three languages. The smallest vowel space distance existed between English and standard Mandarin. These findings support the second language (L2) Status Factor Model, thereby validating both the progressive and regressive transfer paths, and they also highlight the impact of multilingualism on phonological transfer. Thus, this study offers practical implications for the instruction of English phonology and the practice of interpreting.

It is more attractive to develop effective strategies to reduce sugar intake without compromising food quality with the rising prevalence of obesity and diabetes around the world. Due to its high cost, tagatose has not been widely adopted as a sucrose substitute in toast bread. In the present research, five types of toast containing different proportions (0%, 4%, 8%, 12%, and 16%) of tagatose with sweetness similar to that of sucrose were prepared. The effects of tagatose on microstructural, textural, physicochemical, nutritional, and sensory properties and in vitro digestion were evaluated using techniques such as Fourier transform infrared spectroscopy (FT‐IR), scanning electron microscopy (SEM), rheological test, textural profile assay (TPA), and gas chromatography–mass spectrometry (GC–MS) analysis. The results indicated that after the substitution of tagatose for sucrose, the water‐holding capacities of the dough were increased, whereas the specific volume of toast was decreased from 4.74 to 3.01 mL/g (p < 0.05), and the acidity of toast was increased from 1.92 to 2.69°T (p < 0.05). The content of flavor substances, especially alcohols, in the toast was significantly increased by the addition of tagatose. However, the glycemic index (GI) of toast was decreased from 94.39 to 67.96 (p < 0.05). Overall, the addition of 12% or more tagatose will significantly reduce the GI of toasted bread and enrich the flavor, but it will lead to a decrease in specific volume and an increase in acidity. Tagatose is a promising alternative sweetener with low calorie.

Staphylococcus (S.) aureus and its increasing antimicrobial resistance pose a significant challenge to global health. The rapid emergence of antibiotic resistance and the risks associated with chemical preservatives are major global concerns. Consequently, there is an important issue of developing effective control strategies in the food industry. This study aimed to determine the prevalence of S. aureus isolated from dairy products in Egypt. Additionally, antimicrobial resistance profiling was assessed. Finally, the potential use and sensory attributes of essential oils, such as olive and black seed oils, along with D-amino acids as antimicrobial additives in Domiati cheese under osmotic stress, were evaluated for controlling methicillin-resistant S. aureus. A total of 150 dairy samples were examined, including 30 samples each of raw milk, ultra-heat-treated (UHT) milk, Karish cheese, Domiati cheese and frozen dairy dessert. The results revealed that 32% of the examined samples were positive for S. aureus, with more than 70% of the isolates exhibiting multidrug resistance to tetracycline, erythromycin and oxacillin. Molecular characterisation showed that 23 and 7 isolates harboured the enterotoxin genes sea and seb, respectively. Furthermore, 72 and 4 isolates carried the nuc and mecA genes, respectively. Among the 10 examined D-amino acids, D-tryptophan (40 mM) demonstrated the most potent antibacterial activity. Our study also revealed, for the first time, the significant inhibitory effect of D-tryptophan on methicillin-resistant S. aureus (MRSA) in contaminated cheese. The number of MRSA cells treated with olive and black seed oils (1%) and Dtryptophan (40 mM) was significantly reduced by 2 to 5 log cfu/g in cheese (P < 0.05). The used natural additives improved overall acceptability and other sensory attributes of the cheese. The combination of essential oils and D-tryptophan presents a promising eco-friendly solution for controlling S. aureus contamination in the food industry

Metal halide perovskite solar cells (PSCs) are promising as the next‐generation photovoltaic technology. However, the inferior stability under various temperatures remains a significant obstacle to commercialization. Here, a heat‐triggered dynamic self‐healing framework (HDSF) is implemented to repair defects at grain boundaries caused by thermal variability, enhancing PSCs' temperature stability. HDSF, distributed at the grain boundaries and surface of the perovskite film, stabilizes the perovskite lattice and releases the perovskite crystal stress through the dynamic exchange reaction of sulfide bonds. The resultant PSCs achieved a power‐conversion efficiency (PCE) of 26.32% (certified 25.84%) with elevated temperature stability, retaining 88.7% of the initial PCE after 1000 h at 85 °C. In a variable temperature cycling test (between −40 and 80 °C), the HDSF‐treated device retained 87.6% of its initial PCE at −40 °C and 92.6% at 80 °C after 160 thermal cycles. This heat‐triggered dynamic self‐healing strategy could significantly enhance the reliability of PSCs in application scenarios.

With the development of the industrial internet of things, an increasing number of intelligent terminal devices are being deployed in mining operations. However, due to the surge in network traffic and the limited availability of computational resources, these terminal devices face challenges in meeting high-performance requirements such as low transmission latency and low energy consumption. To address this issue, this paper proposes a method that combines partial offloading with collaborative mobile edge computing (MEC). This approach leverages device-to-device communication to partition computational tasks into multiple subtasks, offloading some of them to collaborative devices or MEC servers for execution. This not only alleviates the computational burden on MEC servers but also makes full use of the idle computing resources of terminal devices, thereby enhancing resource utilization efficiency. Given the limited computational capacity of terminal devices, this paper optimizes the offloading decision-making process between terminal devices and MEC servers. By introducing weighted coefficients for latency and energy consumption, the proposed method ensures that task completion latency does not exceed a predefined threshold while minimizing the overall system cost. The problem is formulated as a multi-objective optimization problem, which is solved using a two-layer alternating optimization framework. In the upper layer, an improved genetic algorithm (IGA) based on heuristic rules is employed to generate an offloading decision population, while the lower layer utilizes the deep deterministic policy gradient (DDPG) algorithm to optimize the offloading strategy and the weighted coefficients for latency and energy consumption. To evaluate the effectiveness of the proposed method, we compare it with five baseline algorithms: the improved grey wolf optimizer metaheuristic algorithm, the traditional genetic algorithm, the binary offloading decision mechanism, the partial non-cooperative mechanism, and the fully local execution mechanism. Simulation results demonstrate that the proposed IGA-DDPG algorithm achieves significant improvements over these baseline methods. Specifically, under various experimental scenarios, IGA-DDPG reduces latency by an average of 24.5%, decreases energy consumption by 26.3%, and lowers overall system cost by 44.6%. Moreover, the algorithm consistently ensures a 100% task completion rate under different system configurations.

Video salient object detection is all about identifying the most salient object from a video sequence and segmenting the exact region of that object. Most video salient object detection methods have low performance and low efficiency, and there is much room for improvement. We found that some existing methods consider the advantages of spatial and temporal modalities, but do not fully explore the complementarity between different modalities, which may lead to poor performance of the model when dealing with complex scenes. To cope with the above problems, this paper proposes a novel end-to-end spatiotemporal information cooperative interaction network (SICINet) for salient object detection in video. The network consists of three key modules: cross-modal feature supplementation (CFS), cross-guidance enhancement (CGE), and refinement-adaptive fusion (RAF). Specifically, we propose the CFS module to enable spatiotemporal features to complement each other to facilitate discriminative feature learning, and to learn cross-modal feedback features to ensure the comprehensiveness of salient information in the subsequent fusion stage. In addition, considering that spatiotemporal information can be mutually constrained, we designed the CIE module to use the rough prediction maps of spatiotemporal modalities to bootstrap each other’s multilevel features to filter the unimodal redundant information. Finally, we introduce the RAF module to refine the input features using spatial attention and achieve adaptive weighting fusion by learning the channel weights. Experimental evaluations on four publicly available datasets show that our proposed method is robust under various challenging scenarios (e.g., multiple objects, dynamic foregrounds) and performs more favorably than current state-of-the-art methods.

U2 small nuclear ribonucleoprotein auxiliary factor 1 (U2AF1) gene is a pivotal splicing factor frequently mutated in various malignancies, including myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML). U2AF1 plays a critical role in the recognition and processing of 3ʹ splice sites during pre-mRNA splicing, thereby contributing to the regulation of gene expression and the generation of protein diversity. However, how U2AF1 contributes to the formation and regulation of different categories of chimeric RNAs remains elusive. In this study, we aimed to elucidate the involvement of U2AF1 in chimeric RNA formation and its regulatory impact on different categories of chimeric RNA. Employing knockdown and overexpression strategies in leukemia and esophageal cancer cell lines, we conducted paired-end RNA sequencing following U2AF1 knockdown to assess transcriptomic alterations and their influence on alternative splicing patterns. Subsequently, we utilized the SOAPfuse algorithm to detect and characterize chimeric RNAs from the paired-end RNA sequencing data. Our findings unveiled significant changes in the landscape of chimeric RNA upon U2AF1 knockdown, highlighting its critical role in chimeric RNA formation. This study provides novel insights into how U2AF1 mediates chimeric RNA formation and regulates distinct categories of chimeric RNA within leukemia cell lines. Thereby highlighting its potential as a biomarker for leukemia and other malignancies, promising avenues for future diagnostic and therapeutic developments.

In the field of valleytronics, significant advancements have been made in valley manipulation in linear optical processes. However, the exploration of relevant nonlinearity is crucial for developing coherent optical sources and signal processing in on-chip photonic devices, yet it remains relatively underexplored. Here we demonstrate all-optical valley regulation by leveraging nonlinear parametric scattering processes within monolayer transition metal dichalcogenides embedded in a semiconductor microcavity. Specifically, by utilizing three excitation laser beams (signal, pump, and idler lasers), we observe that the signals from both valleys can be synchronously amplified or suppressed by adjusting the phase of the pump laser. Remarkably, we can independently and effectively control the signals from each valley, with the amplification or suppression of either valley being regulated by the degree of circular polarization or phase difference between circularly polarized components of the pump laser. These advancements in all-optical valley manipulation deepen the understanding of nonlinear optical processes and thus facilitate their potential applications in opto-valleytronic devices.

Electrochromic smart windows with dynamic photothermal management can enhance living comfort and reduce building energy consumption. However, they usually suffer from low selectivity and optical modulation in visible (VIS) and near‐infrared (NIR) regions owing to the coupled mechanism restriction. Here, the reversible deposition and ion adsorption in WO3//MnO2‐based smart windows are decoupled using a hybrid electrolyte, realizing their independent and efficient VIS–NIR regulation. The Cu²⁺/Mn²⁺ ions in the hybrid electrolyte enhance proton adsorption on the WO3 surface while impeding proton insertion, imparting state‐of‐the‐art NIR regulation to the WO3 electrode. Moreover, the synergy of protons and Cu²⁺/Mn²⁺ ions facilitates reversible MnO2 electrodeposition on the electrode, triggering independent tuning of VIS light with an optical modulation of 94%. The outdoor test and simulation reveal that the smart window achieves cooling at 5–10 °C, an energy savings of 73.2 MJ m⁻² and a reduction of 14.4 kg of CO2 emissions per square meter of the building annually. This work would contribute to energy‐saving and emission‐reduction solutions in widespread applications.

This study significantly contributes to the existing body of knowledge by examining the long- and short-run effects of terms of trade components (TOT computer & communication, TOT fuel, TOT food, and TOT goods), capital, labour force, stock trade, and investment on U.S. economic growth from 1980 to 2021 using the Autoregressive Distributed Lag (ARDL) model. The findings of terms of trade (TOT) reveal that TOT computer & communication and TOT food are primarily export-oriented components, whereas TOT fuel and TOT goods are predominantly import-oriented components. However, the findings of the unit root test reveal that all variables are stationary at the first difference I(1). The ARDL bounds test confirms the existence of a long-run relationship between the dependent and independent variables. Long-run analysis indicates that TOT fuel and TOT food negatively affect economic growth, while TOT goods and TOT computers & communication positively contribute to it. Additionally, capital, labour force, and investment are found to be key drivers of U.S. economic growth. The Error Correction Model (ECM) results show an 87% adjustment rate from short-run to long-run equilibrium, signifying a gradual convergence toward equilibrium. The time-varying Granger Causality test demonstrates that GDP causally impacts terms of trade in computer and communication products, goods, labour force, gross capital, and stock trade. Furthermore, impulse response analysis reveals a stable and positive upward trend in GDP's effect on TOT goods, TOT computer & communication, and TOT food, while TOT fuel exhibits a downward trend. The study recommends that policymakers invest in the technological sector to reduce reliance on fuel imports, enhance international trade, and thereby promote sustained economic growth.

Diabetic foot ulcers (DFUs) are a complex mixture of neuropathy, peripheral arterial disease, and infection, where excessive reactive oxygen species (ROS) exacerbates inflammation and impairs healing. Therefore, there is an urgent need to design a hydrogel dressing with a ‘lever’ function to balance ROS levels in the wound to achieve both antimicrobial and anti‐inflammatory effects on DFUs. In this study, we synthesised ROS‐responsive diselenide liposomes loaded with a pro‐skin healing factor (ergothioneine (ET)), thrombin, and a sonosensitizer (HMME) and constructed nanocomposite ‘lever’ hydrogels modulated by ultrasound (US). During early infection, sonodynamic therapy (SDT) under US generates bactericidal ROS, cleaving diselenide bonds to release ET and thrombin. Upon US cessation, thrombin/fibrinogen forms an in situ gel, while ET scavenges residual ROS and promotes M2 macrophage polarization in later stages. In addition, the potential immunomodulatory mechanisms of the nanocomposite ‘lever’ hydrogels were investigated via RNA sequencing. In conclusion, the novel nanocomposite ‘lever’ hydrogels effectively achieved a balance between ROS production and annihilation during different stages of wound repair while providing antibacterial and anti‐inflammatory properties to promote neovascularisation and improve diabetic peripheral neuropathy. In conclusion, by precisely controlling ROS levels across wound‐healing phases, this strategy offers a promising solution for refractory DFUs.