Effects of the sequential use of L1 and bilingual subtitles on incidental English vocabulary learning: A cognitive load perspective.

Aim: From the perspective of cognitive load theory, the present study examined the relative effectiveness of the sequential use of L1 and bilingual subtitles on incidental English vocabulary learning.

Methods: A total of 162 upper-intermediate Chinese learners of English as a foreign language watched an English clip in one of 4 subtitling conditions: L1-bilingual, bilingual-bilingual, L2-L2, and no subtitles.

Results: Results suggested a statistically significant advantage for the L1-bilingual condition over other conditions for word form and meaning recall.

Classification Prediction of Hydrocephalus After Intercerebral Haemorrhage Based on Machine Learning Approach.

In order to construct a clinical classification prediction model for hydrocephalus after intercerebral haemorrhage(ICH) to guide clinical treatment decisions, this paper retrospectively analyses the clinical data of 844 cases of ICH and hydrocephalus inpatients admitted to Yueyang People's Hospital from May 2019 to October 2022, of which 95 cases of hydrocephalus occurred after ICH and no hydrocephalus in 749 cases. The following indicators were compared between the two groups of patients: gender, age, Glasgow Coma Scale(GCS)score, whether the amount of bleeding was greater than 30 ml, whether it broke into the ventricle or not, modified Graeb score(MGS), modified Rankin Scale (MRS) score, whether surgery was performed or not, red blood cells, white blood cells, and platelets. After variable screening, the following six variables were selected: GCS score, MGS, MRS score, whether the bleeding volume was greater than 30 ml, whether it broke into the ventricle or not, and whether surgery was performed or not were modelled and analysed using logistic regression model and support vector machine model in machine learning.

Classifying crash causation patterns in 2-vehicle collisions between autonomous and conventional vehicles.

Objective: This study aims to investigate the causes of 2-vehicle collisions involving an autonomous vehicle (AV) and a conventional vehicle (CV). Prior research has primarily focused on the causes of crashes from the perspective of AVs, often neglecting the interactions with CVs.

Method: To address this limitation, the study proposes a classification framework for crash causation patterns in 2-vehicle collisions involving an AV and a CV, considering their interactions.

A novel lightweight deep learning based approaches for the automatic diagnosis of gastrointestinal disease using image processing and knowledge distillation techniques.

Background: Gastrointestinal (GI) diseases pose significant challenges for healthcare systems, largely due to the complexities involved in their detection and treatment. Despite the advancements in deep neural networks, their high computational demands hinder their practical use in clinical environments.

Objective: This study aims to address the computational inefficiencies of deep neural networks by proposing a lightweight model that integrates model compression techniques, ConvLSTM layers, and ConvNext Blocks, all optimized through Knowledge Distillation (KD).

Palladium Nanosheet Enables Synergistic Electrocatalytic Dehalogenation via Direct and Indirect Electron Transfer Mechanisms.

Electrocatalytic dehalogenation is a promising method for the remediation of chlorinated organic pollutants. The dehalogenation performance is controlled by catalytic activity, and the underlying electrocatalytic dehalogenation mechanisms need to be carefully investigated for guiding the design of catalyst. Here we report the preparation of a new Pd-based catalyst with a nanosheet structure (Pd NS) by a simple wet-chemical reduction method.

Pt@ZnCoO Microspheres as Peroxidase Mimics: Enhanced Catalytic Activity and Application for L-Cysteine Detection.

Compared to natural enzymes, the development of efficient artificial simulated enzymes, such as those based on bimetallic materials with high catalytic activity and good stability, is an important way until now. Herein, we employed ZnCoO microspheres as carriers to synthesize Pt-doped composites with different amounts using a one-pot method. The morphology and structure of the synthesized materials were characterized using XRD, SEM, BET, FT-IR, XPS, and Zeta potential techniques.

Tungsten Carbide/Tungsten Oxide Catalysts for Efficient Electrocatalytic Hydrogen Evolution.

Catalyzing hydrogen evolution reaction (HER) is a key process in high-efficiency proton exchange membrane water electrolysis (PEMWE) devices. To replace the use of Pt-based HER catalyst, tungsten carbide (WC) is one of the most promising non-noble-metal-based catalysts with low cost, replicable catalytic performance, and durability. However, the preparation access to scalable production of WC catalysts is inevitable.

On-site visual quantification of alkaline phosphatase activity in cells using a smartphone-based approach.

Alkaline phosphatase (ALP) is a critical biomarker associated with various physiological and pathological processes, making its detection essential for disease diagnosis and biomedical research. In this study, we developed a novel, simple, and portable visual quantification method for ALP activity in cells using an efficient CuZnS nanomaterial with peroxidase-like properties, integrated into a smartphone-based platform for enhanced usability. The CuZnS nanomaterial catalyzes the breakdown of H₂O₂, generating ·OH radicals that oxidize the colorless substrate TMB into blue oxTMB, which is subsequently reduced back to TMB by ascorbic acid (AA).

Inhibition of advanced glycation end-products in frozen-thawed and reheated pork by pigskin gelatin hydrolysates.

This study investigated the effects of pigskin gelatin hydrolysates (PGH, 4 %) as a cryoprotectant on the formation of advanced glycation end-products (AGEs) in pre-heated pork subjected to freeze-thaw cycles and subsequent reheating. During the freeze-thaw process, PGH significantly mitigated the increase in α-dicarbonyl precursors (α-DPs) and AGEs compared to the control group. Specifically, the levels of glyoxal and methylglyoxal decreased by 4.

A class of n-D Hamiltonian conservative chaotic systems with three-terminal memristor: Modeling, dynamical analysis, and FPGA implementation.

Memristors are commonly used to introduce various chaotic systems and can be used to enhance their chaotic characteristics. However, due to the strict construction conditions of Hamiltonian systems, there has been limited research on the development of memristive Hamiltonian conservative chaotic systems (MHCCSs). In this work, a method for constructing three-terminal memristors is proposed, and the three-terminal memristors are incorporated into the Hamiltonian system, resulting in the development of a class of n-D MHCCS.

A Time-Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen.

Structural damage identification based on structural health monitoring (SHM) data and machine learning (ML) is currently a rapidly developing research area in structural engineering. Traditional machine learning techniques rely heavily on feature extraction, where weak feature extraction can lead to suboptimal features and poor classification performance. In contrast, ML-based methods, particularly deep learning approaches like convolutional neural networks (CNNs), automatically extract relevant features from raw data, improving the accuracy and adaptability of the damage identification process.

Tumor-microenvironment-mediated second near-infrared light activation multifunctional cascade nanoenzyme for self-replenishing O/HO multimodal tumor therapy.

Developing a catalytic nanoenzyme activated by the tumor microenvironment (TME) shows excellent potential for in situ cancer treatment. However, the rational design of a cascade procedure to achieve high therapeutic efficiency remains challenging. In this study, the colorectal TME-responsive multifunctional cascade nanoenzyme CuO@MnO@glucose oxidase (GOx)@hyaluronic acid (HA) was developed to target in situ cancer starvation/chemodynamic therapy (CDT)/photothermal therapy (PTT).

Sensorless control of switched reluctance motor based on inductance characteristic point under magnetic saturation.

This paper presents a method of rotor position estimation for switched reluctance motors suitable for saturation. The effects of saturation as well as voltage changes are taken into account at the same time. It is based on the inductance in the unsaturated region.

Tumor detection on bronchoscopic images by unsupervised learning.

The diagnosis and early identification of intratracheal tumors relies on the experience of the operators and the specialists. Operations by physicians with insufficient experience may lead to misdiagnosis or misjudgment of tumors. To address this issue, a datasets for intratracheal tumor detection has been constructed to simulate the diagnostic level of experienced specialists, and a Knowledge Distillation-based Memory Feature Unsupervised Anomaly Detection (KD-MFAD) model was proposed to learn from this simulated experience.

Crowd counting in domain generalization based on multi-scale attention and hierarchy level enhancement.

In order to solve the problem of weak single domain generalization ability in existing crowd counting methods, this study proposes a new crowd counting framework called Multi-scale Attention and Hierarchy level Enhancement (MAHE). Firstly, the model can focus on both the detailed features and the macro information of structural position changes through the fusion of channel attention and spatial attention. Secondly, the addition of multi-head attention feature module facilitates the model's capacity to effectively capture complex dependency relationships between sequence elements.

Association between ambient temperature and increased total length of hospital stay of patients with cardiopulmonary disease in Hong Kong.

Background: While temperature extremes have been shown to be associated with an increased risk of hospital admissions, evidence of their impact on the length of hospital stay, which may capture the lingering effects of temperature extremes, is scarce.

Objectives: We aimed to evaluate the association between daily variation in ambient temperature and daily variation in daily total length of stay (daily TLOS), a composite measure encompassing the daily count of hospital admissions and their corresponding length of hospital stay among cardiopulmonary patients. Additionally, we quantified the burden of TLOS attributable to non-optimal temperatures among Hong Kong's older adult population.

Solve the cause, not the symptom: Managerial myopia and environmental investment preferences.

Corporate executives often favor short-term "end-of-pipe" solutions to comply with environmental regulations. In this study, we examine how managerial myopia influences corporate preferences for environmental investments, using data from listed Chinese firms between 2007 and 2021. Grounded in the upper-echelon and time orientation theories, this analysis reveals that managerial myopia discourages environmental investments, with a more pronounced impact on preventive measures compared to treatment-focused approaches.

Fatigue reliability assessment of rib-to-deck double-sided welded joints in orthotropic steel decks considering welding residual stress.

Fatigue cracking of rib-to-deck conventional single-sided welded joints is a prevalent issue in orthotropic steel decks (OSDs), significantly impacting their structural integrity and durability. Rib-to-deck innovative double-sided welded joints have the potential to enhance the fatigue resistance of OSD. However, Welding Residual Stresses (WRS) significantly influence the fatigue life of these joints, mandating its consideration in fatigue assessments.

Buried interface engineering towards stable zinc anodes for high-performance aqueous zinc-ion batteries.

The dendrite and corrosion issues still remain for zinc anodes. Interface modification of anodes has been widely used for stabilizing zinc anodes. However, it is still quite challenging for such modification to simultaneously suppress zinc dendrites and corrosion issues.

The synergistic effect induced by "Z-bond" between cations and anions achieving a highly reversible zinc anode.

Due to their high energy density, low cost, and environmental friendliness, aqueous zinc-ion batteries are considered a potential alternative to Li-ion batteries. However, dendrite growth and parasitic reactions of water molecules limit their practical applications. Herein, an ionic liquid additive, 1-butyl-3-methylimidazolium Bis(fluorosulfonyl)imide (BMImFSI), is introduced to regulate the electrical double layer (EDL).

Signal-on lateral flow immunoassays for rapid detection of tetrodotoxin in pufferfish.

Small-molecule biotoxins are frequently founded in grains, corns, peanuts, and different kinds of aquatic products, and they are harmful to human health. Lateral flow immunoassays (LFIAs) have been widely used for on-site detection of small-molecule biotoxins. However, most of the reported LFIAs approaches are signal-off type because each small-molecule biotoxin only has one antigen binding site due to the small size of the molecule.