Search Results (3,029)

Background/objectives: Understanding the immune landscape in cervical cancer is critical to the development of improved therapeutics. This study investigated the immune microenvironment in early-stage cervical cancer with a focus on B and T cell immune aggregates, i.e., lymphoid aggregates (LAs) and tertiary lymphoid structures (TLSs). Methods: Using multispectral imaging, we interrogated a cohort of patients with clinical stage I squamous or adenocarcinoma of the cervix with a focus on T and B cell spatial location and organization. Despite early-stage disease, recurrence was common at 37%, highlighting the need to identify patients at high risk for recurrence. Results: We demonstrated that high CD8+ T cell infiltration correlated significantly with improved overall survival (OS), particularly in patients with adenocarcinoma histology. CD8+ T cells colocalized with B cells, suggesting the formation of a more sophisticated cellular neighborhood, i.e., TLS, which has prognostic benefit in other solid tumors. CXCL13, a chemokine associated with TLS formation, correlated with improved recurrence-free survival. The combination of high CXCL13 and lymphoid structures correlated with improved OS. However, most immune structures in cervical cancer were lymphoid aggregates (LAs) that lack features of more developed TLS, such as high endothelial venules (HEVs) and germinal centers (GCs), highlighting a lack of full immune activation in this microenvironment. Validation in The Cancer Genome Atlas (TCGA) cohort illustrated similar trends in survival. Conclusion: Collectively, this work demonstrates the prognostic significance of immune infiltration and eventual TLS induction in early cervical cancer and presents potential future therapeutic targets. Full article

Plant awareness, which refers to the ability to notice, value, and understand the importance of plants, has emerged as a significant research field, particularly considering the growing concerns about sustainability and biodiversity loss. Acknowledging the crucial role of plants in sustaining life on Earth and human well-being, several studies highlight the need for educational interventions that can meaningfully enhance plant awareness. In this context, the present study aims to design, implement, and evaluate a Teaching–Learning Sequence (TLS) with university students in a Pedagogical Department. The TLS was grounded in the principles of transformative learning, an educational approach focused not merely on the transmission of knowledge but on fostering deep, personal shifts in learners’ perceptions and attitudes. To assess its impact, the Plant Awareness Disparity Index (PAD-I) was used before and after the implementation, supported by systematic observations and focus group discussions. Results indicate that the TLS effectively enhanced specific dimensions of plant awareness, particularly relative interest between plants and animals and attitudes toward plants. These findings position transformative learning as a promising pedagogical framework for promoting plant awareness in higher education and pave the way for its future application in earlier educational levels. Full article

Background: To identify the radiomics features of both granulomas and tumorlets (TL) and to assess the potential role of radiomics in differentiating these two diseases. Methods: From 2013 to 2021, ninety patients who had undergone lung surgery and pre-operative chest CT evaluation, with pathologically proven granulomas or TL, were retrospectively enrolled. Two radiologists, in consensus, manually segmented the lesions on CT images. Radiomic features were then automatically extracted from these segmentations using dedicated software. The performance of CT radiomics features in differentiating TL from granulomas was tested by receiver operating characteristic curves and the areas under the curve (AUCs), calculating sensitivity and specificity. Results: The final population consisted of 55 patients (38 female; mean age 64 ± 14 years), 32 with TL and 23 with granulomas. Significant differences were found in 16/107 radiomic features: 3 Shape, 1 First Order, 2 Grey Level Co-occurrence Matrix (GLCM), 2 Gray Level Dependence Matrix (GLDM), 4 Grey Level Run Length Matrix (GLRLM), and 4 Gray Level Size Zone Matrix (GLSZM). Flatness and Long Run High Gray Level Emphasis showed the best performances in discriminating TL from granulomas (AUC: 0.903; sensitivity: 100%; specificity: 80%; and AUC: 0.896; sensitivity: 92.3%; specificity: 76.5%; respectively; both p < 0.001). Conclusions: Radiomics may be a non-invasive imaging tool for characterization of small lung nodules, differentiating granulomas from TL, and may play a role in preventing TL growth and its possible malignant evolution, avoiding delayed diagnosis. Full article

Accurate individual tree inventories are fundamental to urban forest management, yet automated delineation from Terrestrial Laser Scanning (TLS) data remains a challenge. This study presents a two-stage hybrid framework that combines a domain-adapted deep learning model (TreeLA-Net) with a geometric algorithm (SEGR) to solve this issue, aiming to reduce the need for instance-level annotations. TreeLA-Net first generates semantic labels, outperforming the baseline RandLA-Net by 2.5 percentage points in overall accuracy. Subsequently, SEGR leverages these priors to achieve a tree detection rate of 92.0% on our primary study site. To assess the framework’s transferability, an external validation was conducted on a new, independent site, where the model, without retraining, yielded a recall of 81.5%. These findings suggest that the framework is not strictly overfitted and possesses generalization capabilities. The proposed approach is offered as a potential tool to support data-driven urban forest management, particularly for automated tree mapping and inventory. We hope that this study may contribute to ongoing efforts to develop robust methods for characterizing complex urban forest structures. Full article

This study assessed elemental exposure and health risks in 35 prepared livestock and poultry dishes from Zhejiang Province using inductively coupled plasma mass spectrometry (ICP-MS). Aluminum (Al) showed the highest concentrations, while strontium (Sr) and barium (Ba) were moderate; other elements (molybdenum (Mo), chromium (Cr), lead (Pb), cadmium (Cd), thallium (Tl), cobalt (Co), arsenic (As)) were low; and nickel (Ni) was undetected. All dishes complied with GB 2762-2022 limits. Although seven dishes showed mild-to-moderate single-factor contamination, Nemerow indices confirmed safe levels (P_c < 0.7). Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) indicated that processing methods drove contamination profiles, with deep-fried products accumulating higher metal levels than stir-fried or boiled ones. While non-carcinogenic risks were acceptable for adults, children showed higher susceptibility with Total Target Hazard Quotients (TTHQ) values nearly double those of adults, exceeding safety thresholds in certain dishes primarily due to As and Cr. Carcinogenic risks for hexavalent chromium (Cr(VI)) and inorganic arsenic (iAs) were acceptable (1 × 10⁻⁶ to 1 × 10⁻⁴) for 32 dishes. After speciation-based recalibration, the remaining three dishes also fell within safe limits. Overall, exposure risks are low, though specific deep-fried products warrant monitoring. Full article

While ensuring the accuracy of encrypted malicious traffic detection, improving model training speed remains a challenge. In order to solve this challenge, we propose CNNRes-DIndRNN for detecting encrypted malicious traffic classification. This model uses 1D-CNN to capture local feature relationships between data and IndRNN to capture their global dependency relationships. This method uses Zeek (version 7.0.0) to filter TLS datasets and NetTiSA to build time-series features that help models identify malicious behaviors. Combine time-series and encrypted features, then encode them with XLNet to improve model learning ability and speed training. In the final step, the encoded data is fed into CNNRes-DIndRNN. The results on five datasets including CTU-13 and MCFP showed that CNNRes-DIndRNN achieved 99.81% accuracy in binary classification and 99.67% in multi-class classification. These results represent improvements of 0.50–7.78% (binary) and 0.93–12.26% (multi-class) over all baseline methods. In performance comparisons, CNNRes-DIndRNN achieved the fastest training and testing times. It achieves the best comprehensive performance while maintaining high recognition accuracy. Full article

Understanding life history parameters is key to assessing demography, biological productivity, and extinction risk of fishes. Age and growth analyses in chondrichthyan fishes (sharks, rays, and ghost sharks) is primarily undertaken through counting vertebral band pairs. For rare, threatened, and protected species such as river sharks (Carcharhinidae; Glyphis), obtaining sufficient vertebrae samples may not be possible. Here we use a very small sample size, selective size-class sampling, back-calculation techniques, and a Bayesian hierarchical model that accounts for repeated measures to provide age and growth information for the Speartooth Shark Glyphis glyphis from which comprehensive sampling is not possible. Ten individuals were selectively sampled from the Adelaide River, Northern Territory, Australia. Bayesian length-at-age models using a combination of informative and uninformative priors in a multi-model framework were applied to the observed and back-calculated data with the sexes combined. Band pair counts produced age estimates of 0–11 years and suggest that age at maturity is possibly >12 years. Most model parameter estimates for length-at-birth (L₀) and asymptotic length (L_∞) were biologically plausible. The Gompertz growth function, applied through a Bayesian hierarchical approach to back-calculated data, provided the best fitting and most biologically appropriate length-at-age parameters: L_∞ = 229.5 cm TL ± (14.6 SE), g_Gom = 0.16 yr⁻¹ ± (0.01 SE), and L₀ = 58.2 cm TL ± (1.4 SE). The results presented here are the first study to apply Bayesian methods to back-calculated length-at-age data while accounting for repeated measures. Full article

The pulp and paper mill industry in Corner Brook, Newfoundland and Labrador, Canada produces 150 Mg/day of pulp and paper mill sludge (PPMS) with a high moisture content (70–80%). Instead of the current practice of burning, PPMS may be repurposed as vermicompost. However, the optimum population density of Eisenia fetida to maximize the bioconversion process and its influence on population dynamics are largely unknown. The current study aimed at determining how stocking densities affect the vermicomposting time, vermicompost quality, and population dynamics of E. fetida. By using three stocking densities—1.13 g (TL), 2.04 g (TM), and 3.01 g (TH)—the E. fetida per kg of PPMS and the quality of the vermicompost were determined by chemical analysis followed by a germination test and bioassay on Raphanus sativus seedlings. The total vermicompost produced in TL (66.3%) and TM (68.8%) made the bioconversion process quicker in 60 days. The addition of more E. fetida (TH) delayed the process of vermicomposting by up to 90 days (p < 0.003). Overall, 0.87 (TM) E. fetida/L of PPMS was found to be the optimum population density for obtaining the best quantity and quality of vermicompost. The highest earthworm biomass was harvested in TL, followed by TM and TH, as 3.2, 1.3, and 0.9-fold, respectively, compared to the introduced biomass in 60 days (p < 0.008). The mean growth rate (2.6 mg/worm/day), biomass gain (3.49 mg/g), and reproduction rate (3.9 cocoon/worm) were also significantly higher (p < 0.023) in TL compared to TM and TH in 60 days. Therefore, the present study shows the importance of using an optimum stocking density to maximize the bioconversion process in PPMS, especially in cooler regions. Full article

Although cookies introduced as session authentication tokens in Hypertext Transfer Protocol (HTTP) resolve its stateless limitation, their static nature introduces vulnerabilities to cross-site scripting (XSS) attacks. Attackers exploit unfiltered user input to inject malicious scripts into web applications, enabling theft of user cookies for session hijacking. While HTTP Secure (HTTPS) employs Transport Layer Security (TLS) to encrypt communications, it remains susceptible to client-side script injection vulnerabilities that bypass TLS protections. Current cookie session hijacking protections focus on credential security but remain vulnerable to link-layer attacks. To address this challenge, we propose a novel Cookie Authentication Scheme against XSS Attacks (CAXSS) for HTTPS. The CAXSS scheme uses signatures to the messages exchanged by the original HTTPS protocol to achieve mutual identity authentication. Specifically, clients authenticate cookies using digital signatures based on Elliptic Curve Cryptography (ECC), while servers reject unsigned cookies. This approach ensures that only legitimate clients can generate valid cookie credentials, thwarting unauthorized cookie reuse. The results of security analysis and performance evaluations demonstrate that the CAXSS scheme is secure and effective. Full article

Background and Objectives: Hyperleukocytosis in acute myeloid leukemia (AML) is life-threatening, often complicated by leukostasis, tumor lysis syndrome (TLS), and disseminated intravascular coagulation (DIC), with very high early mortality. Leukapheresis (LA) can rapidly reduce circulating blast burden, but its effect on survival and prognostic relevance of disease markers remains unclear. Materials and Methods: We retrospectively analyzed 74 adult AML patients with WBC > 100 × 10⁹/L treated at the University Clinical Center of Serbia between 2014 and 2024: 28 received LA plus cytoreduction (LA group), and 46 received cytoreduction alone (non-LA group). We evaluated 15-, 30-, and 90-day mortality and overall survival (OS), and assessed clinical, laboratory, and immunophenotypic predictors using Cox regression, with separate subgroup analyses. Results: Patients in the LA group had significantly higher baseline leukocyte counts and LDH (p = 0.18 and p = 0.024, respectively). Although LA resulted in a median 34% reduction in WBC, there was no statistically significant difference in early mortality: 15-day survival was 68% vs. 76% (HR 0.70, p = 0.423), 30-day survival 50% vs. 65% (HR 0.62, p = 0.197), and 90-day survival 39.3% vs. 41.3% (HR 0.85, p = 0.604). Median OS was similarly poor, about 1 month in the LA group compared to 2 months in the non-LA (HR 0.73). Across all patients, ECOG PS ≥2, elevated LDH, TLS, and DIC were the strongest indicators of early death. In the LA group, elevated LDH and increased peripheral blood (PB) monocyte count predicted 15-day mortality (p = 0.021 and p = 0.031, respectively), but lost significance by day 90. In non-LA patients, CD25 positivity (p = 0.034) and DIC (p = 0.045) predicted 15-day death. By day 90, CD25 expression (p = 0.048) remained prognostic, while PB blast percentage (p = 0.045) and PB monocyte count (p = 0.017) emerged as additional adverse prognostic predictors in the non-LA group. In multivariate analysis, higher PB blast percentage, CD25 positivity, and ECOG PS ≥ 2 independently predicted poorer OS. Conclusions: Although LA did not reduce early mortality in the entire cohort, the loss of prognostic significance of elevated LDH, high PB blast percentage, PB monocyte burden, and CD25 expression in the LA group may suggest that the intervention can attenuate the impact of biologically aggressive disease. Full article

Nanocrystalline diamond (NCD) films were synthesized by microwave plasma chemical vapor deposition (MPCVD) from a CH₄/Ar mixture on seedless p-type Si(111) substrates at 100–400 °C. Crystallinity was evaluated by X-ray diffraction (Cu Kα); bonding by Raman spectroscopy and X-ray photoelectron spectroscopy (XPS); morphology and thickness by scanning electron microscopy (SEM); defect states by thermoluminescence (TL). SEM shows continuous films with uniform thickness. XRD displays a broad (111) reflection near 2θ = 44°. Raman and XPS reveal temperature-dependent bonding: between 300 and 400 °C, the sp³ fraction increases relative to sp². TL glow curves show peaks at 157 °C and 270 °C, indicating electron-trap centers. These results demonstrate hydrogen-free and seedless NCD growth at low substrate temperatures, supporting potential electronic and dosimetry applications requiring a low thermal load. Full article

The emergence of quantum computing threatens the security of classical cryptographic algorithms such as RSA and ECC. Post-quantum cryptography (PQC) offers mathematically secure alternatives, but migration is a complex, multi-year undertaking. Unlike past transitions (AES, SHA-2, TLS 1.3), PQC migration requires larger parameter sizes, hybrid cryptographic schemes, and unprecedented ecosystem coordination. This paper presents a structured expert synthesis of migration timelines, based on analysis of migration dependencies, historical precedents, and industry engagement. We analyze migration timelines for small, medium, and large enterprises, considering infrastructure upgrades, personnel availability, budget constraints, planning quality, and inter-enterprise synchronization. We argue that realistic timelines extend well beyond initial optimistic estimates: 5–7 years for small enterprises, 8–12 years for medium enterprises, and 12–15+ years for large enterprises under baseline assumptions. PQC migration is not a siloed technical upgrade but a global synchronization exercise, deeply intertwined with Zero Trust Architecture and long-term crypto-agility. These timelines are contextualized against expected arrival windows for fault-tolerant quantum computers (FTQC), projected between 2028 and 2033. We further analyze the “Store Now, Decrypt Later” threat model, crypto-agility frameworks, and provide comprehensive risk mitigation strategies for enterprises navigating this unprecedented cryptographic transition. Full article

The Macao rammed earth wall is a typical representative of cultural heritage in hot-humid regions. However, the spatial differentiation mechanisms of its surface deterioration remain unclear. This study, taking the Old Wall in Macao as a case, combined field investigation with terrestrial laser scanning (TLS) and thermal imaging to systematically reveal the spatial distribution patterns of surface pathologies and their hydrological driving mechanisms. Based on structural separations and deterioration characteristics, the wall was divided into three adjacent sections for comparative analysis. The main conclusions are as follows: (1) Quantitative analysis showed the section with a gentler slope (77%) experienced significant flatness deterioration due to uneven settlement, promoting internal water penetration that triggered severe undercutting (35% of its surface area); (2) The other two sections maintained steep slopes (86%) that promoted surface runoff, which combined with adjacent building drainage led to significant biological colonization (68% in the section most affected by nearby temple drainage); (3) Thermal imaging verified the correlation between water infiltration cores and temperature-flatness anomalies, enabling construction of a coupled “geometry-hydrology-pathology” model that elucidates the complete causal chain from foundation settlement to surface pathology. This study provides a theoretical basis and technical support for the differentiated protection of rammed earth heritage in hot-humid environments. Full article

Accurate and efficient forest inventory methods are crucial for monitoring forest ecosystems, assessing carbon stocks, and supporting sustainable forest management. Traditional field-based techniques, which rely on manual measurements such as diameter at breast height (DBH) and tree height (TH), remain labour-intensive and time-consuming. In this study, we introduce and validate a fully open-source, low-cost terrestrial laser scanning system (LCA-TLS) built from commercially available components and based on the Livox Avia sensor. With a total cost of €2050, the system responds to recent technological developments that have significantly reduced hardware expenses while retaining high data quality. This trend has created new opportunities for broadening access to high-resolution 3D data in ecological research. The performance of the LCA-TLS was assessed under controlled and field conditions and benchmarked against three reference devices: the RIEGL VZ-1000 terrestrial laser scanner, the Stonex X120GO handheld mobile laser scanner, and the iPhone 15 Pro Max structured-light device. The LCA-TLS achieved high accuracy for estimating DBH (RMSE: 1.50 cm) and TH (RMSE: 0.99 m), outperforming the iPhone and yielding results statistically comparable to the Stonex X120GO (DBH RMSE: 1.32 cm; p > 0.05), despite the latter being roughly ten times more expensive. While the RIEGL system produced the most accurate measurements, its cost exceeded that of the LCA-TLS by a factor of about 30. The hardware design, control software, and processing workflow of the LCA-TLS are fully open-source, allowing users worldwide to build, modify, and apply the system with minimal resources. The proposed solution thus represents a practical, cost-effective, and accessible alternative for 3D forest inventory and LiDAR-based ecosystem monitoring. Full article

This study aims to investigate the impact of strategic drivers, specifically IT & Business Strategy Alignment (IT-BSA), Transglobal Leadership (TL), and Product Innovation (PI), on the adoption of Green Supply Chain Management (GSCM) and its subsequent effect on Sustainable Performance (SP). A key objective is to examine the moderating role of Risk Management (RM) in the relationship between these drivers and GSCM. This research employs a quantitative methodology, utilizing survey data collected from 216 middle and top Indonesian oil and gas managers. The hypothesized relationships were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that IT-BSA, TL, and PI are significant positive GSCM antecedents. Furthermore, GSCM has a strong, positive impact on SP. The results confirm that RM significantly and positively moderates the influence of all three strategic drivers on GSCM adoption. These findings provide a clear managerial roadmap, highlighting that an active risk management framework is critical for translating internal capabilities into effective sustainability practices, thereby enhancing a firm’s competitive advantage and long-term performance. Full article