Search Results (1,931)

Defensive pessimism, an important emotion regulation and motivation strategy, has increasingly attracted scholarly attention in psychology. Recently, sensor-based methods have begun to supplement or replace traditional questionnaire surveys in personality research. However, current approaches for collecting vital signs data face several challenges, including limited monitoring durations, significant data deviations, and susceptibility to external interference. This paper proposes a novel approach using a NiCr/NiSi alloy film temperature sensor, which has a K-type structure and flexible piezoelectric pressure sensor to identify and predict defensive pessimism personality traits. Experimental results indicate that the Seebeck coefficients for K-, T-, and E-type thermocouples are approximately 41 μV/°C, 39 μV/°C, and 57 μV/°C, respectively, which align closely with national standards and exhibit good consistency across multiple experimental groups. Moreover, radial artery frequency experiments demonstrate a strong linear relationship between pulse rate and the intensity of external stimuli, where stronger stimuli correspond to faster pulse rates. Simulation experiments further reveal a high correlation between radial artery pulse frequency and skin temperature, and a regression model based on the physiological sensor data shows a good fit (p < 0.05). These findings verify the feasibility of using temperature and flexible piezoelectric pressure sensors to identify and predict defensive pessimism personality characteristics. Full article

Lactic acid bacteria (LAB) are central to food, feed, and health biotechnology, yet their genomes have long resisted rapid, precise manipulation. This review charts the evolution of LAB genome-editing strategies from labor-intensive RecA-dependent double-crossovers to state-of-the-art CRISPR and CRISPR-associated transposase systems. Native homologous recombination, transposon mutagenesis, and phage-derived recombineering opened the door to targeted gene disruption, but low efficiencies and marker footprints limited throughput. Recent phage RecT/RecE-mediated recombineering and CRISPR/Cas counter-selection now enable scar-less point edits, seamless deletions, and multi-kilobase insertions at efficiencies approaching model organisms. Endogenous Cas9 systems, dCas-based CRISPR interference, and CRISPR-guided transposases further extend the toolbox, allowing multiplex knockouts, precise single-base mutations, conditional knockdowns, and payloads up to 10 kb. The remaining hurdles include strain-specific barriers, reliance on selection markers for large edits, and the limited host-range of recombinases. Nevertheless, convergence of phage enzymes, CRISPR counter-selection and high-throughput oligo recombineering is rapidly transforming LAB into versatile chassis for cell-factory and therapeutic applications. Full article

pH is a critical parameter requiring precise monitoring across scientific, industrial, and biological domains. Fluorescent pH probes offer a powerful alternative to traditional methods (e.g., electrodes, indicators), overcoming limitations in miniaturization, long-term stability, and electromagnetic interference. By utilizing photophysical mechanisms—including intramolecular charge transfer (ICT), photoinduced electron transfer (PET), and fluorescence resonance energy transfer (FRET)—these probes enable high-sensitivity, reusable, and biocompatible sensing. This review systematically details recent advances, categorizing probes by operational pH range: strongly acidic (0–3), weakly acidic (3–7), strongly alkaline (>12), weakly alkaline (7–11), near-neutral (6–8), and wide-dynamic range. Innovations such as ratiometric detection, organelle-specific targeting (lysosomes, mitochondria), smartphone colorimetry, and dual-analyte response (e.g., pH + Al³⁺/CN⁻) are highlighted. Applications span real-time cellular imaging (HeLa cells, zebrafish, mice), food quality assessment, environmental monitoring, and industrial diagnostics (e.g., concrete pH). Persistent challenges include extreme-pH sensing (notably alkalinity), photobleaching, dye leakage, and environmental resilience. Future research should prioritize broadening functional pH ranges, enhancing probe stability, and developing wide-range sensing strategies to advance deployment in commercial and industrial online monitoring platforms. Full article

Originally introduced in the 1960s by DISA Elektronik as a calibration tunnel for hot-wire anemometers, the Type 55D41 has now been reengineered into a versatile and modern aerodynamic test platform. While retaining key legacy components, such as the converging nozzle and the 55D42 power unit, the upgraded system features a redesigned modular test section with optical-grade quartz windows. This enhancement enables compatibility with advanced flow diagnostics and visualization methods, including PTV, DIC, and schlieren imaging. The modernized facility maintains the precision and flow stability that made the original design widely respected, while expanding its functionality to meet the demands of contemporary experimental research. Its architecture supports the aerodynamic characterization of micro-scale static pressure probes used in aerospace, propulsion, and micro gas turbine applications. Special attention is given to assessing the influence of probe tip geometry (e.g., conical, ogive), port positioning, and stem interference on measurement accuracy. Full article

Background/Objectives: Viral respiratory infections have a significant impact on global health and the economy. While vaccines are effective in preventing infection, they might not be available or sufficient when used alone and must be complemented by specific therapeutic strategies. The development of new antiviral agents is increasingly important due to the continual emergence of novel respiratory pathogens. Previously we identified bovine lactoferrin (bLf)-derived tetrapeptides and peptidomimetics that showed potent in vitro activity against the influenza A virus in the picomolar range. Methods: Inspired by these results, in this study, we evaluated the antiviral potential of these compounds against HCoV-229E, a human coronavirus that can cause severe disease in immunocompromised individuals, using a compound repositioning approach. Results: Functional studies revealed that SK(N-Me)HS (3) interferes with viral entry and replication, while compound SNKHS (5) primarily blocks infection in the early stages. Biophysical analyses confirmed the occurrence of high-affinity binding to the viral spike protein, and computational studies suggested that the compounds target a region involved in conformational changes necessary for membrane fusion. Conclusions: These findings highlight these compounds as promising candidates for coronavirus entry inhibition and underscore the value of compound repurposing in antiviral development. Full article

This paper proposes a novel hierarchical control architecture that combines Model Predictive Control (MPC) with Explicit Model-Following Control (EMFC) to enable accurate and efficient trajectory tracking for quadrotor electric Vertical Takeoff and Landing (eVTOL) aircraft operating in urban environments. The approach addresses the challenges of strong nonlinear dynamics, multi-axis coupling, and stringent safety constraints by separating the planning task from the fast-response control task. The MPC layer generates constrained velocity and yaw rate commands based on a simplified inertial prediction model, effectively reducing computational complexity while accounting for physical and operational limits. The EMFC layer then compensates for dynamic couplings and ensures the rapid execution of commands. A high-fidelity simulation model, incorporating rotor flapping dynamics, differential collective pitch control, and enhanced aerodynamic interference effects, is developed to validate the controller. Four representative ADS-33E-PRF tasks—Hover, Hovering Turn, Pirouette, and Vertical Maneuver—are simulated. Results demonstrate that the proposed controller achieves accurate trajectory tracking, stable flight performance, and full compliance with ADS-33E-PRF criteria, highlighting its potential for autonomous urban air mobility applications. Full article

Multiband transmission is, nowadays, being implemented worldwide to increase the optical transport network capacity, mainly because it uses the already-installed single-mode fiber (SMF). The G.654E SMF, due to its attributes (e.g., low-loss, and large-effective area in comparison with the standard G.652 SMF), can also increase network capacity and can also be used for multiband (MB) transmission. Nevertheless, in MB transmission, power mode coupling arises when bands with wavelengths below the cut-off wavelength are used, inducing multipath interference (MPI). This work investigates the impact of the MPI, due to mode coupling from G.654E SMF, in the transmission reach of a C+L+S band transmission system. Our results indicate that for the S-band scenario, the band below the wavelength cut-off, an approximately 25% reach decrease is observed when the MPI/span increases to −26 dB/span, considering quadrature phase-shift keying (QPSK) signals with a 64 GBaud symbol rate. We also concluded that if the L-band were not above the wavelength cut-off, it would be much more affected than the S-band, with an approximately 52% reach decrease due to MPI impact. Full article

Sensing transparent objects has many applications in human daily life, including robot navigation and grasping. However, this task presents significant challenges due to the unpredictable nature of scenes that extend beyond/behind transparent objects, particularly the lack of fixed visual patterns and strong background interference. This paper aims to solve the transparent object segmentation problem by leveraging the intrinsic global modeling capabilities of transformer architectures. We design a Query Parsing Module (QPM) that innovatively formulates segmentation as a dictionary lookup problem, differing fundamentally from conventional pixel-wise mechanisms, e.g., via attention-based prototype matching, and a set of learnable class prototypes as query inputs. Based on QPM, we propose a high-performance transformer-based end-to-end segmentation model, Transparent Object Segmentation through Query (TOSQ). TOSQ’s encoder is based on the Segformer’s backbone, and its decoder consists of a series of QPM modules, which progressively refine segmentation masks by the proposed QPMs. TOSQ achieves state-of-the-art performance on the Trans10K-V2 dataset (76.63% mIoU, 95.34% Acc), with particularly significant gains in challenging categories like windows (+23.59%) and glass doors (+11.22%), demonstrating its superior capability in transparent object segmentation. Full article

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

Electrochemical biosensors are revolutionizing food testing by addressing critical limitations of conventional strategies that suffer from cost, complexity, and field-deployment challenges. Emerging fluorescence and Raman techniques, while promising, face intrinsic drawbacks like photobleaching and matrix interference in opaque or heterogeneous samples. In contrast, electrochemical biosensors leverage electrical signals to bypass optical constraints, enabling rapid, cost-effective, and pretreatment-free analysis of turbid food matrices. This review highlights their operational mechanisms, emphasizing nano-enhanced signal amplification (e.g., Au nanoparticles and graphene) and biorecognition elements (antibodies, aptamers, and molecularly imprinted polymers) for ultrasensitive assay of contaminants, additives, and adulterants. By integrating portability, scalability, and real-time capabilities, electrochemical biosensors align with global food safety regulations and sustainability goals. Challenges in standardization, multiplexed analysis, and long-term stability are discussed, alongside future directions toward AI-driven analytics, biodegradable sensors, and blockchain-enabled traceability, ultimately fostering precision-driven, next-generation food safety and quality testing. Full article

One of the persistent challenges in multispectral image analysis is the interference caused by dense cloud cover and its resulting shadows, which can significantly obscure surface features. This becomes especially problematic when attempting to monitor surface changes over time using satellite imagery, such as from Landsat-8. In this study, rather than simply masking visual obstructions, we aimed to investigate the role and influence of clouds within the spectral data itself. To achieve this, we employed Independent Component Analysis (ICA), a statistical method capable of decomposing mixed signals into independent source components. By applying ICA to selected Landsat-8 bands and analyzing each component individually, we assessed the extent to which cloud signatures are entangled with surface data. This process revealed that clouds contribute to multiple ICA components simultaneously, indicating their broad spectral influence. With this influence on multiple wavebands, we managed to configure a set of components that could perfectly delineate the extent and location of clouds. Moreover, because Landsat-8 lacks cloud-penetrating wavebands, such as those in the microwave range (e.g., SAR), the surface information beneath dense cloud cover is not captured at all, making it physically impossible for ICA to recover what is not sensed in the first place. Despite these limitations, ICA proved effective in isolating and delineating cloud structures, allowing us to selectively suppress them in reconstructed images. Additionally, the technique successfully highlighted features such as water bodies, vegetation, and color-based land cover differences. These findings suggest that while ICA is a powerful tool for signal separation and cloud-related artifact suppression, its performance is ultimately constrained by the spectral and spatial properties of the input data. Future improvements could be realized by integrating data from complementary sensors—especially those operating in cloud-penetrating wavelengths—or by using higher spectral resolution imagery with narrower bands. Full article

Iopamidol (IPM), as a typical recalcitrant emerging pollutant and precursor of iodinated disinfection by-products (I-DBPs), is unsuccessfully removed by conventional wastewater treatment processes. This study comprehensively evaluated the ozone/peracetic acid (O₃/PAA) process for IPM degradation, focusing on degradation kinetics, environmental impacts, transformation products, ecotoxicity, disinfection byproducts (DBPs), and microbial inactivation. The O₃/PAA system synergistically activates PAA via O₃ to generate hydroxyl radicals (^•OH) and organic radicals (CH₃COO^• and CH₃CO(O)O^•), achieving an IPM degradation rate constant of 0.10 min⁻¹, which was significantly higher than individual O₃ or PAA treatments. The degradation efficiency of IPM in the O₃/PAA system exhibited a positive correlation with solution pH, achieving a maximum degradation rate constant of 0.23 min⁻¹ under alkaline conditions (pH 9.0). Furthermore, the process demonstrated strong resistance to interference from coexisting anions, maintaining robust IPM removal efficiency in the presence of common aqueous matrix constituents. Furthermore, quenching experiments revealed ^•OH dominated IPM degradation in O₃/PAA system, while the direct oxidation by O₃ and R-O^• played secondary roles. Additionally, based on transformation products (TPs) identification and ECOSAR predictions, the primary degradation pathways were elucidated and the potential ecotoxicity of TPs was systematically assessed. DBPs analysis after chlorination revealed that the O₃/PAA (2.5:3) system achieved the lowest total DBPs concentration (99.88 μg/L), representing a 71.5% reduction compared to PAA alone. Amongst, dichloroacetamide (DCAM) dominated the DBPs profile, comprising > 60% of total species. Furthermore, the O₃/PAA process achieved rapid 5–6 log reductions of E. coli. and S. aureus within 3 min. These results highlight the dual advantages of O₃/PAA in effective disinfection and byproduct control, supporting its application in sustainable wastewater treatment. Full article

Real-time quality monitoring using molten pool images is a critical focus in researching high-quality, intelligent automated welding. To address interference problems in molten pool images under complex welding scenarios (e.g., reflected laser spots from spatter misclassified as porosity defects) and the limited interpretability of deep learning models, this paper proposes a multi-granularity spatiotemporal representation learning algorithm based on the hybrid enhancement of handcrafted and deep learning features. A MobileNetV2 backbone network integrated with a Temporal Shift Module (TSM) is designed to progressively capture the short-term dynamic features of the molten pool and integrate temporal information across both low-level and high-level features. A multi-granularity attention-based feature aggregation module is developed to select key interference-free frames using cross-frame attention, generate multi-granularity features via grouped pooling, and apply the Convolutional Block Attention Module (CBAM) at each granularity level. Finally, these multi-granularity spatiotemporal features are adaptively fused. Meanwhile, an independent branch utilizes the Histogram of Oriented Gradient (HOG) and Scale-Invariant Feature Transform (SIFT) features to extract long-term spatial structural information from historical edge images, enhancing the model’s interpretability. The proposed method achieves an accuracy of 99.187% on a self-constructed dataset. Additionally, it attains a real-time inference speed of 20.983 ms per sample on a hardware platform equipped with an Intel i9-12900H CPU and an RTX 3060 GPU, thus effectively balancing accuracy, speed, and interpretability. Full article

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants that continue to raise concern owing to their ability to accumulate in living organisms. In recent years, a growing body of research has shown that PFAS can exert their toxicity through disruption of both DNA integrity and epigenetic regulation. This includes changes in DNA methylation patterns, histone modifications, chromatin remodeling, and interference with DNA repair mechanisms. These molecular-level alterations can impair transcriptional regulation and cellular homeostasis, contributing to genomic instability and long-term biological dysfunction. In neural systems, PFAS exposure appears particularly concerning. It affects key regulators of neurodevelopment, such as BDNF, synaptic plasticity genes, and inflammatory mediators. Importantly, epigenetic dysregulation extends to non-coding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), which mediate post-transcriptional silencing and chromatin remodeling. Although direct evidence of transgenerational neurotoxicity is still emerging, animal studies provide compelling hints. Persistent changes in germline epigenetic profiles and transcriptomic alterations suggest that developmental reprogramming might be heritable by future generations. Additionally, PFAS modulate nuclear receptor signaling (e.g., PPARγ), further linking environmental cues to chromatin-level gene regulation. Altogether, these findings underscore a mechanistic framework in which PFAS disrupt neural development and cognitive function via conserved epigenetic and genotoxic mechanisms. Understanding how these upstream alterations affect long-term neurodevelopmental and neurobehavioral outcomes is critical for improving risk assessment and guiding future interventions. This review underscores the need for integrative research on PFAS-induced chromatin disruptions, particularly across developmental stages, and their potential to impact future generations. Full article

Appendage autotomy frequently occurs during the cultivation of Exopalaemon carinicauda, which severely impacts its survival and economic benefits. To investigate the molecular mechanism underlying appendage regeneration in E. carinicauda, this study presents a comparative transcriptome analysis on samples from different stages of appendage regeneration in individuals of the same family of E. carinicauda. A total of 6460 differentially expressed genes (DEGs) were identified between the samples collected at 0 h post-autotomy (D0) and those collected at 18 h post-autotomy (D18h). Additionally, 7740 DEGs were identified between D0 and 14 d post-autotomy (D14d), with 3382 DEGs identified between D18h and D14d. Among them, differentially expressed genes such as EcR, RXR, BMP1, and Smad4 are related to muscle growth or molting and may be involved in the regeneration process. qRT-PCR results revealed that EcBMPR2 was expressed at relatively high levels in the gonad and ventral nerve cord tissues and that the highest level of expression was detected in the regenerative basal tissue at 24 h post-autotomy. In situ hybridization results indicated strong signals of this gene in the cells at the wound site at 72 h post-autotomy. Following knockdown of EcBMPR2, the expression levels of both EcBMPR1B and EcSmad1 were significantly downregulated, and long-term interference with the EcBMPR2 gene resulted in a significantly slower appendage regeneration process compared to the control group. When the downstream transcription factor EcSmad1 was knocked down, the two receptor genes EcBMPR2 and EcBMPR1B were downregulated, whereas EcBMP7 was upregulated. After inhibiting the BMP signaling pathway, the degree of cell aggregation at the autotomy site in the experimental group was significantly lower than that in the control group, the wound healing rate was delayed, and the blastema regeneration time was prolonged from 5 d to 7 d. Collectively, these results indicate that the BMP signaling pathway plays a critical role in the early stages of appendage regeneration in E. carinicauda. This study provides important theoretical insights for understanding limb regeneration in crustaceans. Full article