Browse Articles

An efficient algorithm for pedestrian fall detection in various image degradation scenarios based on YOLOv8n

Optimizing the axis ratio of elliptical PCM encasement for enhanced thermal performance in radiant floor heating systems

Association between exposure to volatile organic compounds and atherogenic index of plasma in NHANES 2011–2018

Effectiveness of drone-based thermal sensors in optimizing controlled environment agriculture performance under arid conditions

Abstract Controlled environmental agriculture (CEA), integrated with internet of things and wireless sensor network (WSN) technologies, offers advanced tools for real-time monitoring and assessment of microclimate and plant health/stress. Drone applications have emerged as transformative technology with significant potential for CEA. However, adoption and practical implementation of such technologies remain limited, particularly in arid regions. Despite their advantages in agriculture, drones have yet to gain widespread utilization in CEA systems. This study investigates the effectiveness of drone-based thermal imaging (DBTI) in optimizing CEA performance and monitoring plant health under arid conditions. Several WSN sensors were deployed to track microclimatic variations within the CEA environment. A novel method was developed for assessing canopy temperature (Tc) using thermocouples and DBTI. The crop water stress index (CWSI) was computed based on Tc extracted from DBTI. Findings revealed that DBTI effectively distinguished between all treatments, with Tc detection exhibiting a strong correlation (R2 = 0.959) with sensor-based measurements. Results confirmed a direct relationship between CWSI and Tc, as well as a significant association between soil moisture content and CWSI. This research demonstrates that DBTI can enhance irrigation scheduling accuracy and provide precise evapotranspiration (ETc) estimates at specific spatiotemporal scales, contributing to improved water and food security.

River floating object detection with transformer model in real time

Oncological outcomes of breast-conserving surgery versus mastectomy following neoadjuvant chemotherapy in a contemporary multicenter cohort

Abstract To evaluate local recurrence (LR), distant recurrence (DR) and death in non-metastatic patients undergoing breast-conserving surgery (BCS) or mastectomy following current neoadjuvant chemotherapy (NAC) regimens. Patients submitted to NAC in 2013–2023 were evaluated (n = 365; mastectomy: 165; BCS: 200). More mastectomy patients were over 70 years old (12.7% versus 7%; p = 0.02) and had T4b tumors (16.4% versus 4.5%; p = 0.0003), whereas more BCS patients had node-negative axilla (42% versus 31.5%; p = 0.02). After a mean follow-up of 65 months (range: 4-124), LR and DR were similar in the mastectomy and BCS groups (4.8% versus 5.0%; p = 0.95 and 10.9% versus 9%; p = 0.58, respectively). More deaths occurred in the mastectomy group (8.5% versus 3%; p = 0.03). Ten-year LR-free survival was higher in the BCS group (98.5% versus 95%; HR: 3.41; 1.09–10.64; p = 0.03), while 10-year DR-free survival was similar in both groups (91% BCS versus 89% mastectomy, HR: 1.25; 0.65–2.42; p = 0.4). Overall survival was better in the BCS group (97% versus 91.5%; HR: 2.62; 1.06–6.69; p = 0.03). Estimated 10-year disease-free survival, stratified according to tumor stage, showed no significant difference except for T4 disease, for which the risk was greater in the mastectomy group (94.5% versus 81.8%; HR: 2.86, 1.54–5.30, p = 0.0008). In the multivariate analysis, T3/T4 staging (OR: 4.37, 1.03–21.91; p = 0.04) and axillary dissection (OR: 5.11, 1.14–35.52; p = 0.04) were associated with LR in the BCS group. In this cohort of patients receiving contemporary NAC, BCS proved to be a safe alternative to mastectomy following treatment with NAC, even in cases of locally advanced BC.

The impact of vestibular-autonomic blood pressure responses derived from the head-up Tilt test on benign paroxysmal positional vertigo recurrence

Role of raw Ilmenite nanoparticles in Rhodamine B degradation using peroxymonosulfate and graphitic carbon nitride

Exploiting adaptive neuro-fuzzy inference systems for cognitive patterns in multimodal brain signal analysis

Adaptive damage analysis method for ultimate bearing capacity of steel truss structures with box section

Multi-objective collaborative optimization of active distribution network operation based on improved particle swarm optimization algorithm

Robust control of a compliant manipulator with reduced dynamics and sliding perturbation observer

A galactose-based auto-expression system improves T7-inducible protein production in Escherichia coli

Leading report on the molecular prevalence of emerging pathogens Hepatozoon sp. and Lankesterella sp. in the blood samples of seven wild lizard species

In vivo deletion of a GWAS-identified Myb distal enhancer acts on Myb expression, globin switching, and clinical erythroid parameters in β-thalassemia

Development and usability of the “Cognitive Evergreenland” app to engage individuals at high risk of dementia in lifestyle interventions

Effectiveness of machine learning methods in detecting grooming: a systematic meta-analytic review

Abstract This study presents a systematic review (SR) and meta-analysis (MA) on the use of machine learning (ML) methods for detecting online grooming, a form of manipulation and child sexual abuse. The SR identified 33 studies from IEEE, Web of Science, Scopus, Springer, PubMed, and Google Scholar databases, and 11 ML methods were meta-analyzed for accuracy (ACC), precision (P), recall (R), and $$\hbox {F}_1$$ Score (F1). Multilayer Perceptron (MLP) demonstrated the highest accuracy (ACC=92%, p<0.001) and precision (P=81%, p<0.001), excelling in capturing complex, nonlinear patterns essential for analyzing nuanced online interactions. Support Vector Machine (SVM), with an ACC of 88% (p<0.001), achieved a balanced performance, characterized by high precision (P=86%, p<0.001), recall (R=74%, p<0.001), and the highest F1 score (0.79). SVM emerges as an effective algorithm, providing a robust balance across all metrics, emphasizing its adaptability and reliability in detecting nuanced grooming behaviors. This study is pioneering in meta-analyzing ML methods applied to the effectiveness in detecting grooming. The results highlight the efficacy of certain algorithms and contribute to the identification of online predators. A crucial aspect of cybersecurity for preventing child sexual abuse.

The prevalence and risk of allergic rhinitis in psoriasis patients: a systematic review and meta-analysis

Effect of Mn content on the corrosion behavior and biocompatibility of biodegradable Zn-Mn alloys

Novel immune drug combination induces tumour microenvironment remodelling and reduces the dosage of anti-PD-1 antibody

Abstract Immune checkpoint inhibitors (ICIs) are effective in clinical settings; however, they present immune-related adverse effects and financial burden. Although dose reduction of ICIs may mitigate these limitations, it could compromise therapeutic efficacy. Using two adjuvants (poly(I:C) and LAG-3-Ig) combined with three neoantigen peptides (Comb), we examined whether Comb could enhance the efficacy of reduced dose of αPD-1 monoclonal antibody (RD-αPD-1 mAb), which has limited efficacy. In a murine colorectal cancer model using an MC38 cell line, Comb addition to RD-αPD-1 mAb enhanced treatment efficacy. Analysis of the tumour microenvironment (TME) in mice treated with Comb using flow cytometry and single-cell RNA sequencing revealed decreased macrophages with highly expressing immunosuppressive genes and increased plasmacytoid dendritic cells with highly expressing antigen-presenting genes. A potent infiltration of CD8 + tumour-infiltrating lymphocytes (TILs) with an effector profile was only observed in RD-αPD-1 mAb with Comb. Additionally, single-cell T cell receptor repertoire analysis underscored an oligoclonal expansion of CD8 + TILs following treatment with RD-αPD-1 mAb with Comb. This novel immune drug combination may be a promising strategy for reducing αPD-1 mAb dosage while preserving antitumour efficacy through modulating the TME.