Ce1-xMnxVO4 with Improved Activity for Low-Temperature Catalytic Reduction of NO with NH3.

Novel Ce1-xMnxVO4 catalysts prepared via modified hydrothermal synthesis were used in selective catalytic reduction of NO using NH3 (NH3-SCR). The Ce1-xMnxVO4 catalysts displayed optimum NO removal efficiency at 250 oC. Physicochemical properties including crystal type, morphology, particle size, elemental composition, BET surface area, chemical bond, and valence state were studied by XRD, TEM, EDS, N2 adsorption-desorption, Raman spectroscopy, and XPS.

Multimodal machine learning enables AI chatbot to diagnose ophthalmic diseases and provide high-quality medical responses.

Chatbot-based multimodal AI holds promise for collecting medical histories and diagnosing ophthalmic diseases using textual and imaging data. This study developed and evaluated the ChatGPT-powered Intelligent Ophthalmic Multimodal Interactive Diagnostic System (IOMIDS) to enable patient self-diagnosis and self-triage. IOMIDS included a text model and three multimodal models (text + slit-lamp, text + smartphone, text + slit-lamp + smartphone).

Relationship between functional structures and horizontal connections in macaque inferior temporal cortex.

Horizontal connections in anterior inferior temporal cortex (ITC) are thought to play an important role in object recognition by integrating information across spatially separated functional columns, but their functional organization remains unclear. Using a combination of optical imaging, electrophysiological recording, and anatomical tracing, we investigated the relationship between stimulus-response maps and patterns of horizontal axon terminals in the macaque ITC. In contrast to the "like-to-like" connectivity observed in the early visual cortex, we found that horizontal axons in ITC do not preferentially connect sites with similar object selectivity.

Tailorable biosensors for real-time monitoring of stress distribution in soft biomaterials and living tissues.

Visualizing mechanical stress distribution in soft and live biomaterials is essential for understanding biological processes and improving material design. However, it remains challenging due to their complexity, dynamic nature, and sensitivity requirements, necessitating innovative techniques. Since polysaccharides are common in various biomaterials, a biosensor integrating a Förster resonance energy transfer (FRET)-based tension sensor module and carbohydrate-binding modules (FTSM-CBM) has been designed for real-time monitoring of the stress distribution of these biomaterials.

A multi-domain feature fusion epilepsy seizure detection method based on spike matching and PLV functional networks.

The identification of spikes, as a typical characteristic wave of epilepsy, is crucial for diagnosing and locating the epileptogenic region. The traditional seizure detection methods lack spike features and have low sample richness. This paper proposes a seizure detection method with spike-based phase locking value (PLV) functional brain networks and multi-domain fused features.

Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions.

As people's material living standards continue to improve, the types and quantities of household garbage they generate rapidly increase. Therefore, it is urgent to develop a reasonable and effective method for garbage classification. This is important for resource recycling and environmental improvement and contributes to the sustainable development of production and the economy.

Prediction of Pharmacoresistance in Drug-Naïve Temporal Lobe Epilepsy Using Ictal EEGs Based on Convolutional Neural Network.

Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis.

Low Neutralization of SARS-CoV-2 Omicron BA5248, XBB15 and JN1 by Homologous Booster and Breakthrough Infection.

Immunity against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can be induced through either infection with the virus or vaccination, providing protection against reinfection or reducing the risk of severe clinical outcomes. In this study, we recruited 172 volunteers who received different vaccination regimens, including 124 individuals who had recovered from breakthrough infections caused by the Omicron variant (27 with 2 doses, 49 with 3 doses, and 48 with 4 doses) and 48 healthy donors who did not experience breakthrough infections (all of whom received a fourth dose during the infection wave). We measured neutralizing antibody levels against Omicron BA.

Laboratory-Engineered Glioblastoma Organoid Culture and Drug Screening.

Glioblastoma (GBM) is described as a group of highly malignant primary brain tumors and stands as one of the most lethal malignancies. The genetic and cellular characteristics of GBM have been a focal point of ongoing research, revealing that it is a group of heterogeneous diseases with variations in RNA expression, DNA methylation, or cellular composition. Despite the wealth of molecular data available, the lack of transferable pre-clinic models has limited the application of this information to disease classification rather than treatment stratification.

Missing value replacement in strings and applications.

Missing values arise routinely in real-world sequential (string) datasets due to: (1) imprecise data measurements; (2) flexible sequence modeling, such as binding profiles of molecular sequences; or (3) the existence of confidential information in a dataset which has been deleted deliberately for privacy protection. In order to analyze such datasets, it is often important to replace each missing value, with one or more letters, in an efficient and effective way. Here we formalize this task as a combinatorial optimization problem: the set of constraints includes the of the missing value (i.

Optimized Photochromic Performance of Spiropyran through Incorporation into Hydrogen-Bonded Organic Frameworks and Applications in Anticounterfeiting and Information Encryption.

Photostimulus-responsive fluorescent materials are promising for anticounterfeiting and UV printing due to rapid response and simple preparation. In this paper, we propose a novel strategy to prepare photostimulus-responsive materials SP@HOF-olefin by integrating the photochromic molecule spiropyran (SP) with postsynthetic modified hydrogen-bonded organic frameworks (HOF-olefin). Compared to SP@HOF, the composites SP@HOF-olefin exhibit enhanced photochromic properties, such as a fast response speed, pronounced color contrast, and exceptional fatigue resistance.

A machine learning model the prediction of athlete engagement based on cohesion, passion and mental toughness.

Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them.

Using monitoring and simulation to analyze the failure characteristics of multizone landslides controlled by faults: a case study.

Slopes influenced by multiple faults are prone to large-scale landslides triggered by multi-regional failures. Understanding the failure process and sequence is essential for the sustainable development of mining operations. This paper presents a method combining InSAR monitoring and numerical simulation to analyze the failure processes of slopes affected by multiple faults.

Downregulation of the Phosphatase PHLPP1 Contributes to NNK-induced Malignant Transformation of Human Bronchial Epithelial Cells (HBECs).

Cigarette smoking (CS) is one of the greatest health concerns, which can cause lung cancer. 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), a tobacco-specific nitrosamine, and has been well-documented for its carcinogenic activity in both epidemiological and laboratory studies. PH domain leucine-rich repeat protein phosphatase 1 (PHLPP1) and phosphatase and tensin homolog (PTEN) are two well-known phosphatase tumor suppressors that have been reported to be downregulated in human lung cancer tissues.

Spectrum Sensing in Very Low SNR Environment Using Multi-Scale Temporal Correlation Perception with Residual Attention.

Spectrum sensing is recognized as a viable strategy to alleviate the scarcity of spectrum resources and to optimize their usage. In this paper, considering the time-varying characteristics and the dependence on various timescales within a time series of samples composed of in-phase (I) and quadrature (Q) component signals, we propose a multi-scale time-correlated perceptual attention model named MSTC-PANet. The model consists of multiple parallel temporal correlation perceptual attention (TCPA) modules, enabling us to extract features at different timescales and identify dependencies among features across various timescales.

A Complete Coverage Path Planning Algorithm for Lawn Mowing Robots Based on Deep Reinforcement Learning.

This paper introduces Re-DQN, a deep reinforcement learning-based algorithm for comprehensive coverage path planning in lawn mowing robots. In the fields of smart homes and agricultural automation, lawn mowing robots are rapidly gaining popularity to reduce the demand for manual labor. The algorithm introduces a new exploration mechanism, combined with an intrinsic reward function based on state novelty and a dynamic input structure, effectively enhancing the robot's adaptability and path optimization capabilities in dynamic environments.

Based on the Geometric Characteristics of Binocular Imaging for Yarn Remaining Detection.

The automated detection of yarn margins is crucial for ensuring the continuity and quality of production in textile workshops. Traditional methods rely on workers visually inspecting the yarn margin to determine the timing of replacement; these methods fail to provide real-time data and cannot meet the precise scheduling requirements of modern production. The complex environmental conditions in textile workshops, combined with the cylindrical shape and repetitive textural features of yarn bobbins, limit the application of traditional visual solutions.

An X-Band Class-J GaN MMIC Power Amplifier with Well-Designed In-Band Output Power Flatness.

This paper presents an X-band high-power GaN MMIC power amplifier (PA). To balance efficiency, output power, and saturated power flatness, the load-line theory is employed to analyze and validate the power variation trends within an extended continuous Class B/J (CCBJ) impedance space. Theoretical constant power contours are plotted within this space.

Generating a Full Cycle of Alternative Current Using a Triboelectric Nanogenerator for Energy Harvesting.

The triboelectric nanogenerator (TENG) has emerged as a promising technology for efficiently converting ambient mechanical energy into electrical energy. Among various designs, the disk-based rotational TENG has demonstrated significant potential, as it can continuously harvest energy in a sliding mode via a grating mechanism. However, horizontal mechanical energy is more common than rotational energy in many practical applications.

Modeling of historical and future changes in temperature and precipitation in the Panj River Basin in Central Asia under the CMIP5 RCP and CMIP6 SSP scenarios.

This study examines the complexities of climate modeling, specifically in the Panj River Basin (PRB) in Central Asia, to evaluate the transition from CMIP5 to CMIP6 models. The research aimed to identify differences in historical simulations and future predictions of rainfall and temperature, examining the accuracy of eight General Circulation Models (GCMs) used in both CMIP5 (RCP4.5 and 8.

Machine learning empowered coherent Raman imaging and analysis for biomedical applications.

In situ and in vivo visualization and analysis of functional, endogenous biomolecules in living systems have generated a pivotal impact in our comprehension of biology and medicine. An increasingly adopted approach involves the utilization of molecular vibrational spectroscopy, which delivers notable advantages such as label-free imaging, high spectral density, high sensitivity, and molecule specificity. Nonetheless, analyzing and processing the intricate, multi-dimensional imaging data to extract interpretable and actionable information poses a fundamental obstacle.

Systematic dissection of pleiotropic loci and critical regulons in excitatory neurons and microglia relevant to neuropsychiatric and ocular diseases.

Advancements in single-cell multimodal techniques have greatly enhanced our understanding of disease-relevant loci identified through genome-wide association studies (GWASs). To investigate the biological connections between the eye and brain, we integrated bulk and single-cell multiomic profiles with GWAS summary statistics for eight neuropsychiatric and five ocular diseases. Our analysis uncovered five latent factors explaining 61.

A new polymer with rich carbonyl delocalized π-conjugated structure for high-performance aqueous zinc ion batteries.

The development of sustainable and clean energy has become a top priority, driven by global carbon peaking and carbon neutrality targets. Organics are widely used in aqueous zinc ion batteries (AZIBs) due to their environmental friendliness, high structural designability, and safety. However, organic materials often face some challenges, including high solubility, low specific capacity, and unclear mechanism, which hinder its further applications.

Unraveling the role of Ta in the phase transition of Pb(TaSe) using temperature-dependent Raman spectroscopy.

Phase engineering strategies in two-dimensional transition metal dichalcogenides (2D-TMDs) have garnered significant attention due to their potential applications in electronics, optoelectronics, and energy storage. Various methods, including direct synthesis, pressure control, and chemical doping, have been employed to manipulate structural transitions in 2D-TMDs. Metal intercalation emerges as an effective technique to modulate phase transition dynamics by inserting external atoms or ions between the layers of 2D-TMDs, altering their electronic structure and physical properties.

A CRISPR-Cas and Argonaute-Driven Two-Factor Authentication Strategy for Information Security.

The escalating growth in computing power and the advent of quantum computing present a critical threat to the security of modern cryptography. Two-factor authentication strategies can effectively resist brute-force attacks to improve the security of access control. Herein, we proposed a two-factor and two-authentication entity strategy based on the trans-cleavage activity of CRISPR-Cas and the "dual-step" sequence-specific cleavage of Argonaute.