Browse Articles

Detection method of subgrade settlement for the road of ART in coastal tidal flat area based on Vehicle-mounted binocular stereo vision technology

Study on indoor thermal environment and energy consumption of traditional dwellings of ethnic minorities in Sichuan plateau

Abstract In this paper, field tests, questionnaire surveys, and DesignBuilder were used to analyse the indoor thermal environment and energy consumption of traditional houses in a traditional ethnic minority village of Western Sichuan Plateau of China, The results showed that during the summer test period, the outdoor temperature range was 9.3–7.8 °C and the relative humidity range was 53.5–67.4%, while the indoor temperature range of the tested room was 13.3–2.3 °C, and the relative humidity range was 69.1–83.0%. The humidity is high, and the thermal environment does not meet the requirement of local standard. Therefore, corresponding energy-saving optimization measures are proposed. In the winter heating building model data, compared with the heat load before optimization, the energy saving reaches about 56.5%. In addition, the carbon emissions and economic suitability of different heating methods were evaluated. Electric heating, coal-fired heating and biomass heating have payback periods of 11 years, 24 years and 6 years respectively. With perspective focusing on the special regional and ethnic characteristics of the plateau, this research aims to promote energy conservation and sustainable development of local traditional buildings of ethnic minorities, and help improve the living environment of the Sichuan Plateau. In the future, a long-term monitoring mechanism can be established to continuously track residential buildings after the adoption of optimization measures to evaluate the actual effect of these measures.

Automated multi-class MRI brain tumor classification and segmentation using deformable attention and saliency mapping

Research on the performance of the SegFormer model with fusion of edge feature extraction for metal corrosion detection

Explainable AI analysis for smog rating prediction

Social isolation and risk of mortality in middle-aged and older adults with arthritis: a prospective cohort study of four cohorts

A hybrid slime mold enhanced convergent particle swarm optimizer for parameter estimation of proton exchange membrane fuel cell

Amplitude and frequency encoding result in qualitatively distinct informational landscapes in cell signaling

Mathematical study of silicate and oxide networks through Revan topological descriptors for exploring molecular complexity and connectivity

The impacts of technological overlap on international collaboration in China’s green innovation endeavors

Sex-specific trends in the global burden and risk factors of atrial fibrillation and flutter from 1990 to 2021

A novel simultaneous monitoring method for surface roughness and tool wear in milling process

Heartbeat evoked potentials reflect interoceptive awareness during an emotional situation

Shikimic acid protects against doxorubicin-induced cardiotoxicity in rats

Abstract Doxorubicin (DOX) is used to treat a variety of malignancies; however, its cardiotoxicity limits its effectiveness. Shikimic acid (SA) showed several promising biomedical applications. This study investigated the protective effect of SA on DOX-induced cardiotoxicity in male rats. The ADMETlab 2.0 web server was used to predict the pharmacokinetic properties of SA. Molecular docking studies were conducted using AutoDock Vina. Fifty male rats were divided into 4 groups (n = 10); G1 was a negative control; G2 was injected with 4 mg/kg of DOX intraperitoneally (i.p.) once a week for a month; G3 was gavaged by 1/10 of SA LD50 (280 mg/kg) daily for a month, and G4 was injected with DOX as in G2 and with SA as in G3. After a month, hematological, biochemical, molecular, and histopathological investigations were assessed. The results showed that SA treatment led to significant amelioration of the DOX-induced cardiotoxicity in rats by restoring hematological, biochemical, inflammatory biomarkers, antioxidant gene expression, and cardiac histopathological alterations. Importantly, the impact of SA treatment against DOX-promoted cardiac deterioration is by targeting the Nrf-2/Keap-1/HO-1/NQO-1 signaling pathway, which in turn induces the antioxidant agents. These findings suggest that SA treatment could potentially mitigate cardiac toxicity during DOX-based chemotherapy.

Enhancing the shelf life of natural scale inhibitors using bio preservatives

Abstract One of the key challenges in using natural extracts for water treatment is their biodegradability and susceptibility to microbial spoilage, which can limit storage and long-term effectiveness. This study investigates the scale inhibition capabilities of an aqueous extract of Salvia rosmarinus sp through electrochemical measurements, conductivity tests, and morphological examination. Additionally, two natural substances, Rhamnolipid and Chitosan, were evaluated as bio-preservatives to prevent mold growth and enhance the shelf life of the rosemary extract. The reasons for selecting these specific bio-preservatives include their known antimicrobial properties, antioxidant effects, environmental benefits, and suitability for the intended application. For 24 weeks, we conducted a microbial examination and assessed the anti-scaling performance of the extract in combination with the bio-preservatives. The results demonstrate that rosemary extract significantly inhibits CaCO3 scale precipitation, attributed to the presence of carboxylate and hydroxyl groups which effectively chelate cations and disturb the normal crystal growth of the scales. Additionally, the rosemary extract-chitosan mixture exhibits superior antimicrobial and anti-scaling performance compared to the rosemary extract–rhamnolipids combination over six months. It can be concluded that a 1:2 ratio of chitosan to rosemary extract provides an effective eco-friendly scale inhibitor and reduces the growth of pathogenic bacteria and fungi with an extended shelf life. In this context, biosurfactants and polysaccharides present beneficial properties that offer sustainable and biological alternatives to conventional chemical biocides.

Real-time vs. static ultrasound-guided needle cricothyroidotomy: a randomized crossover simulation trial

Green forage impacts on the DNA methylation in the ruminal wall of Italian mediterranean dairy buffaloes

Porcine milk small extracellular vesicles modulate peripheral blood mononuclear cell proteome in vitro

Position-context additive transformer-based model for classifying text data on social media

Abstract In recent years, the continuous increase in the growth of text data on social media has been a major reason to rely on the pre-training method to develop new text classification models specially transformer-based models that have proven worthwhile in most natural language processing tasks. This paper introduces a new Position-Context Additive transformer-based model (PCA model) that consists of two-phases to increase the accuracy of text classification tasks on social media. Phase I aims to develop a new way to extract text characteristics by paying attention to the position and context of each word in the input layer. This is done by integrating the improved word embedding method (the position) with the developed Bi-LSTM network to increase the focus on the connection of each word with the other words around it (the context). As for phase II, it focuses on the development of a transformer-based model based primarily on improving the additive attention mechanism. The PCA model has been tested for the implementation of the classification of health-related social media texts in 6 data sets. Results showed that performance accuracy was improved by an increase in F1-Score between 0.2 and 10.2% in five datasets compared to the best published results. On the other hand, the performance of PCA model was compared with three transformer-based models that proved high accuracy in classifying texts, and experiments also showed that PCA model overcame the other models in 4 datasets to achieve an improvement in F1-score between 0.1 and 2.1%. The results also led us to conclude a direct correlation between the volume of training data and the accuracy of performance as the increase in the volume of training data positively affects F1-Score improvement.

Potent targeted larvicidal activities of marine-derived Bacillus sp. bacterial extracts on mosquito vectors