Search Results (434)

Background: Fiberoptic bronchoscopy (FOB) is a procedure routinely performed in clinical practice for both diagnostic and therapeutic purposes. FOB frequently impairs respiratory function, which may exacerbate respiratory failure. Currently, conventional oxygen therapy (COT) is the most commonly used form of respiratory support; however, non-invasive ventilation (NIV) and high-flow nasal cannula (HFNC) are being used increasingly. The optimal settings and indications for NIV and HFNC in patients with respiratory acidosis undergoing FOB have not yet been determined. Methods: This is a prospective, multicenter, randomized controlled trial including two parallel study populations defined by the indication for bronchoscopy and the type of respiratory acidosis. Therapeutic FOB (Study 1): Patients with decompensated type 2 respiratory failure (pH < 7.35 and PaCO₂ > 45 mmHg) will be randomized to receive one of four methods of respiratory support during bronchoscopy: COT, NIV, HFNC, or invasive mechanical ventilation (IMV) (n = 315). Diagnostic FOB (Study 2): Patients with chronic respiratory acidosis (pH ≥ 7.35, PaCO₂ > 45 mmHg, and/or HCO₃⁻ > 27 mmol/L) will be randomized to receive COT, NIV, or HFNC during bronchoscopy (n = 210). Before FOB, patients in both groups will undergo arterial blood gas (ABG) analysis. During FOB, vital signs will be continuously monitored, including SpO₂, FiO₂, TcCO₂, ECG, and heart rate. After FOB, ABG analysis will be repeated, and study endpoints and complications, if any, will be recorded. The planned study period is from April 2026 to April 2029. Results: Based on the study results, we aim to evaluate the effectiveness and safety of different respiratory support strategies during flexible bronchoscopy, with the primary objective of comparing the rate of treatment failure among COT, HFNC, NIV, and IMV. Treatment failure is defined as the need for endotracheal intubation, premature termination of the procedure, or escalation of respiratory support. Additionally, we aim to identify the optimal NIV and HFNC settings, as well as complication rates in both study groups. Conclusions: The results of this study will help define the role of optimal respiratory support in patients with respiratory acidosis undergoing FOB, potentially leading to a shorter time from admission to diagnosis, better tolerance of the procedure, and faster recovery afterward. Full article

Background/Objectives: In the school setting, high-intensity interval training (HIIT) has emerged as a time-efficient strategy to improve children’s physical fitness; however, different implementation modalities have not been compared. The aim of this study was to compare the effects of an individual versus paired HIIT protocol based on functional bodyweight exercises on physical fitness-related and anthropometric outcomes in primary school children. Methods: Sixty-one children (11.6 ± 0.3 years) participated in a 10-week experimental study with three parallel groups: individual HIIT (EG1, n = 21), paired HIIT (EG2, n = 20), and a control group (CG, n = 20). Although both HIIT groups performed the same bodyweight functional exercises, in EG2 the exercises required coordinated movement between the partners. The HIIT protocol was integrated into the warm-up of Physical Education (PE) classes twice per week (Tabata-type protocol; 8 × 20 s/10 s/≤8 min per session). Body composition, muscular strength, and cardiorespiratory fitness (estimated VO₂max) were assessed at pre- and post-test, along with a rating of perceived exertion (1–10 scale) and enjoyment/motivation (1–5 scale) across several sessions (1, 7 and 14). Data were analyzed using pre-post comparisons, ANOVA, and ANCOVA models adjusted for baseline values. Results: Body fat percentage decreased in all groups. The individual HIIT group showed within-group improvements in VO₂max (+5.3%, p < 0.001), handgrip strength (+10.1%, p = 0.003), and standing long jump (+4.1%, p = 0.033), with moderate-to-large effect sizes, whereas the paired HIIT group showed smaller and statistically non-significant changes. Between-group comparisons suggested a tendency toward greater improvements in VO₂max and handgrip strength in the individual HIIT group compared with the paired group, although the overall ANOVA for VO₂max was not statistically significant. Perceived exertion declined over time in the paired group but remained relatively stable in the individual group. Conclusions: A low-volume HIIT program performed individually was associated with improvements in several physical fitness outcomes in schoolchildren. In contrast, paired execution showed smaller and mostly non-significant changes, together with a progressive reduction in perceived intensity. Full article

Securing IoT networks presents fundamental challenges rooted in hardware constraints: firmware is often non-upgradeable and every security boundary is fixed at manufacture. Machine learning-based intrusion detection offers a scalable response, yet nearly all published systems assume clean training data and clean inference conditions. Production IoT environments satisfy neither assumption. Sensors degrade, packets drop, and adversaries deliberately corrupt telemetry streams to evade detection. The framework described here is built around that reality. The proposed framework is distinguished from prior work by four design decisions. First, three encoding branches, a residual DNN, a 1D-CNN, and a BiLSTM, are run in parallel and are fused by concatenation, each capturing structural patterns in tabular traffic data that the others miss. Second, a dual-view consistency loss trains the model under simultaneous feature masking and Gaussian noise, penalizing prediction divergence between two independently corrupted views of the same sample. Third, we introduce entropy-weighted attention: rather than fixed learned weights, per-feature importance is adjusted dynamically from information entropy measured across training batches, giving higher-entropy features stronger influence because they carry more discriminative variation. Fourth, branch-dropout regularization randomly silences entire branches during training, forcing each to develop independently useful representations instead of co-adapting. Class imbalance is handled through severity-aware loss weighting which scales contributions by the operational cost of missing each attack category, not purely by inverse frequency. On UNSW-NB15, the full model achieves 99.99% accuracy, 100% precision, 99.97% recall, and a false-negative rate of 2.65 × 10⁻⁴—the lowest across all compared architectures. Full article

We construct a connection-theoretic framework for parallel transport of spectral components along parameter families of signals on the similarity group $\tilde{G}=\mathbb{R}\times \mathrm{SO}\left(2\right)$. Let ${\left\{f_t\right\}}_{t\in I}$ be a signal family that evolves under a $C^1$ group trajectory. The frequency support of the associated scale-rotation transforms produces three Hilbert subbundles over the parameter interval, and the trajectory velocity induces a covariant derivative on each subbundle. The standard spectral viewpoint treats transformation behavior at individual parameter values. Our formulation instead organizes the propagation of spectral components along the entire parameter path and provides closed-form transport operators together with error bounds on each subbundle. We derive three explicit parallel transport formulas. On the equivariant subbundle the transport is an exact isometric translation. On the coupled subbundle, the transport combines log-scale translation with a phase factor $e^{i{n}_0\Delta \theta }$. On the invariant subbundle, the transport is approximate, with the quantitative bound $\parallel {\mathsf{\Pi }}^{\mathrm{inv}}F-F\parallel \le \epsilon |\Delta \tau |\parallel F\parallel$, where ${\mathsf{\Pi }}^{\mathrm{inv}}$ denotes the parallel transport operator on that subbundle. We introduce the notion of non-parallelism rate as a pointwise measure of deviation from parallel evolution, and we prove that cumulative deviation along the path is bounded by the path integral of this quantity. The bound separates into two parts. One part is controlled by trajectory estimation error and reflects geometric mismatch. The other part is controlled by intrinsic appearance variation and reflects non-geometric drift. We also show that regularity transfers from the signal family to the spectral sections, and we establish a discrete transport theorem whose finite-sum error bounds recover the continuous estimates in the small-step limit. The framework provides a quantitative geometric tool for multi-scale feature evolution under continuous scale-rotation transformations. Full article

Background/Objectives: Testicular cancer accounts for approximately 1% of all male malignancies, with an incidence ranging from 1 to 10 per 100,000 men and it predominantly affects young individuals, with nearly 60% of cases diagnosed between 15 and 35 years of age. In recent decades, the incidence of testicular cancer has markedly increased, paralleling a global rise in male infertility rates. Although chemotherapy is known to adversely affect fertility, the extent to which the tumor itself and its different histological subtypes impact semen quality remains incompletely understood. The aim of this study was to evaluate semen parameters in men diagnosed with testicular cancer prior to oncological treatment and to assess the possible association between tumor histology and semen quality. Methods: This retrospective study included data from 284 men diagnosed with testicular cancer who underwent semen cryopreservation prior to surgery, chemotherapy, or radiotherapy. Data were collected between January 2016 and June 2022 at the Maternal and Child Department of the University of Naples Federico II. Histopathological classification was available for 278 patients and revealed the following distribution: 59% (165/278) classic seminoma, 14.7% (41/278) seminomatous mixed germ cell tumors, 13.3% (37/278) non-seminomatous mixed germ cell tumors, and 12.6% (35/278) non-seminomatous germ cell tumors. Results: No significant association was observed between tumor histology and abnormal semen parameters. According to World Health Organization (WHO) reference values, semen parameters in patients with testicular cancer were predominantly distributed between the 5th and 25th percentiles. Microscopic semen analysis revealed significantly lower sperm concentration, total motility, and normal morphology in cancer patients (p < 0.001; p < 0.001; and p < 0.002, respectively). Logistic regression analysis showed a significant association between age and testicular cancer risk (p < 0.001), with a negative coefficient indicating that the likelihood of developing the disease decreases with increasing age. Additionally, patients with seminoma were significantly older than those with non-seminomatous tumors: on average, 4.07 years older than those with pure non-seminoma (p = 0.007) and 5.60 years older than those with mixed non-seminoma (p < 0.001). No statistically significant age differences were observed among non-seminomatous subtypes. Conclusions: These findings underscore the importance of systematic semen evaluation in young men diagnosed with testicular cancer and highlight the critical role of fertility preservation strategies in the comprehensive management of these patients. Full article

Background: Prostate cancer remains a significant global health burden, yet current diagnostic reliance on PSA screening is heavily hampered by limited specificity and high rates of overdiagnosis. Methods: To address this clinical bottleneck, we utilized a highly sensitive Complete360^®-MyMeta targeted-metabolomics platform to perform high-resolution profiling of 43 metabolites across the carnitine, polyamine, and methylation networks in plasma from a discovery cohort of all-stage (I–IV) PCa patients and healthy controls. Results: Our analysis identified 28 significantly altered metabolites (p < 0.05), revealing profound systemic metabolic reprogramming characterized by the depletion of circulating TML and putrescine, alongside the elevation of L-acetylcarnitine and sarcosine. These systemic shifts are consistent with a localized tumoral “metabolic sink”, wherein upregulated mitochondrial TML import via the SLC25A45 transporter actively fuels fatty acid oxidation, while parallel androgen signaling drives massive polyamine synthesis. Translating these mechanistic insights into a clinical tool, we developed a multivariable diagnostic signature utilizing mathematically stable bipartite metabolic ratios. An optimized, cross-validated model combining L-acetylcarnitine/TML and sarcosine/putrescine effectively mitigated physiological noise to achieve robust diagnostic separation, yielding an area under the curve (AUC) of 0.99. Conclusions: Ultimately, this study provides a discovery-phase proof-of-concept for the SLC25A45-TML axis as a mechanistically grounded, stage-independent liquid biopsy, offering a rational, non-invasive framework to significantly improve PCa detection. Full article

We proposed a bilateral parallel offset jet model that enables jet vectoring control without the need for an active high-pressure secondary flow. Flow characteristics, including deflection force, wall pressure distribution, and flow structures, were investigated. The evolutions of key flow structures during jet deflection were investigated, including the passive secondary flow, the shear layer, the boundary layer, and the separation bubble. By analyzing the formation, dissipation, and interactions of the key flow structures, as well as their relationship with pressure characteristics, the mechanism of the jet deflection control was further deduced. The fundamental driving force of the jet deflection stems from the unbalanced pressure difference on either side of the jet, and the valve can control the flow rate of passive secondary flow, thereby altering the near-wall pressure on its side and further generating a pressure that propels the jet to deflect. For walls of different lengths, at a moderate wall length, where L* = 1.5, with the valve controlling the passive secondary flow, a maximum jet vectoring angle of 6.4° can be continuously achieved at a low Reynolds number. Within the range where 20% < δ_v < 100%, the nonlinear error of jet vectoring control is 5.7%. At a short wall length, where L* = 0.5, the driving force generated by the valve to deflect the jet is insufficient, and the maximum vector angle is 0.3°. For longer walls, the impact of the jet against the trailing edge of the wall obstructs jet deflection; therefore, extending the wall is not conducive to jet vectoring control. Featuring a non-expanding wall structure, the bilateral parallel offset jet model provides a new thrust vectoring control scheme characterized by a compact afterbody, no need for a high-pressure secondary air source, and a simple structure. Full article

Recent advances in lifetime modeling have led to several extensions of classical distributions, among which the extended inverted Kumaraswamy lifetime model, known as the exponentiated generalized inverted Kumaraswamy model, represents a significant innovation. In parallel, progressive Type-II censoring frameworks have garnered growing attention for their adaptability and relevance across various applied disciplines, including medical, engineering, and social sciences. Driven by this motivation, the present study focuses on the problem of parameter estimation for the proposed lifetime model under a progressive Type-II censoring scheme. Both Bayesian and non-Bayesian frameworks are utilized to estimate the model parameters, reliability function, and hazard rate. Furthermore, interval estimation is conducted by constructing confidence and Bayesian credible intervals for these measures. Assuming independent gamma priors, Bayes estimators are derived under both symmetric and asymmetric loss functions to account for different decision-making perspectives. In addition, conditional and Bayesian predictive analyses are developed within a two-sample prediction framework, and their associated prediction intervals are constructed. The efficiency and robustness of the proposed estimation and prediction methodologies are thoroughly evaluated through an extensive simulation study conducted under various sample sizes and censoring schemes. To further demonstrate the model’s practical relevance, real-world medical and engineering datasets are analyzed, highlighting the applicability and effectiveness of the proposed distribution in empirical contexts. Full article

Unlike natural images, remote sensing images have unique characteristics such as high spatial resolution, complex textures, and strong directional features. Their content often contains many man-made targets with clear directional structures, such as buildings, roads, and bridges. It also contains complex ground object boundaries. However, most existing image compression methods are designed for natural images. They typically use square convolution kernels and local receptive fields. As a result, they struggle to effectively capture the rich directional structures in remote sensing images and model global context information. This limits compression efficiency and the fidelity of key information. To address this challenge, this paper proposes a novel remote sensing image compression algorithm. The algorithm uses a multi-scale asymmetric convolution block that combines sampling convolution, parallel one-dimensional horizontal and vertical convolutions, and two-dimensional square convolution. This helps the model better capture directional objects and multi-scale features. In addition, we also propose a multi-scale non-local attention module. It models global dependencies with a linear computational complexity. This helps improve the ability to retain key information. The experimental results demonstrate that compared with the baseline model, the proposed algorithm achieves a 0.40 dB improvement in BD-PSNR and a 10.27% reduction in BD-Rate, while also delivering superior subjective visual quality. These results confirm the effectiveness of our approach for remote sensing image compression. Full article

This study investigates the enhancement of hydrogen production efficiency in water electrolysis through the application of external magnetic fields. A series of controlled experiments were conducted using four distinct electrode materials—stainless steel (SS), low-carbon steel (LCS), titanium (Ti), and platinum-plated titanium (Ti/Pt)—to identify the optimal configuration for maximizing gas output. The research evaluated the influence of electrolyte concentration (KOH), current density, and magnetic field intensity ranging from 0 to 1800 G. Our findings indicate that the application of a 200 G magnetic field leads to a notable 6% increase in the rate of gas production compared to non-magnetized conditions. Specifically, a magnetic field oriented parallel to the electrode plates outperformed a perpendicular orientation by approximately 5%, a phenomenon attributed to the Lorentz force facilitating ionic mass transfer and gas bubble detachment. Furthermore, the integration of ion-exchange and proton-exchange membranes (MC-3470 and N-117) effectively isolated the anodic and cathodic products, elevating hydrogen purity from 67.4% to approaching 100% without compromising electrolysis efficiency. These results demonstrate that the strategic coupling of moderate magnetic fields with optimized electrode configurations provides a promising pathway for improving the efficiency and cleanliness of hydrogen production, which is essential for its role as a sustainable energy carrier. Full article

Non-insulated heat exchangers in gas-to-gas service lose substantial energy to the surroundings. This study evaluates Al₂O₃ and ZnO ceramic coatings (200 $\mathsf{\mu }$m) as passive thermal retention layers on the inner surface of the outer tube in a copper double-pipe heat exchanger, using 3D CFD simulations verified for internal consistency against Log Mean Heat Transfer Rate analytical solutions. Six cases were modelled: three coating conditions across parallel-flow and counter-flow configurations under laminar conditions ($R{e}_i\approx 525$, $R{e}_o\approx 192$) with air as the working fluid. The coating elevates the outer tube inner wall temperature $T_3$, increasing the convective driving force to the cold fluid while suppressing ambient dissipation. In parallel flow, Al₂O₃ increases the net inter-fluid heat transfer rate by 35.7% and reduces ambient losses by 81.4%; ZnO achieves 30.9% and 70.4%, respectively. In counter-flow, Al₂O₃ yields a 26.6% enhancement and 73.2% loss reduction. The coated parallel-flow configuration outperforms the uncoated counter-flow baseline. Thermal circuit analysis shows that Al₂O₃ superiority arises from its higher conductivity (40 vs. 19 W m⁻¹ K⁻¹), which sustains a higher equilibrium $T_3$ and a heat partition ratio of 11.84 versus 7.17 for ZnO. These results show that a single ceramic coating layer can recover a large fraction of the thermal energy lost through non-insulated walls, offering a low-cost, retrofit-compatible pathway to improve the energy efficiency of gas-to-gas heat exchangers in HVAC, building energy recovery, and industrial process heat applications. Full article

We propose a monolithically integrated optical frequency comb (OFC) generation platform on thin-film lithium niobate (TFLN), featuring cascaded dual-drive Mach–Zehnder modulators (DDMZM) and a ${\mathrm{S}\mathrm{i}}_3{\mathrm{N}}_4$-assisted spot size converter (SSC). To capture microscopic mode mismatches and spatial phase accumulation often overlooked in idealized scalar simulations, we establish a multi-physics co-simulation framework integrating finite-difference time-domain (FDTD) analysis with macroscopic transmission modeling. Based on this framework, the cascaded modulator architecture generates 25 highly stable comb lines with a dense 2 GHz spacing and an envelope flatness within 2 dB. Tolerance analysis indicates that the comb generation is highly resilient to typical manufacturing and environmental variations, including thermal bias drift, RF phase mismatch, and half-wave voltage ($V_{\pi }$) dispersion. Furthermore, physical-layer modeling shows that the integrated SSC reduces fiber-to-chip coupling loss to 0.55 dB per facet, preserving the necessary optical power budget. To validate the platform’s viability as a multi-wavelength continuous-wave source for spatial-division multiplexed (SDM) interconnects, a parallel transmission over a 20 km standard single-mode fiber is modeled. Using a digital signal processing (DSP)-free 10 Gb/s non-return-to-zero (NRZ) scheme, the 25-channel system maintains a worst-case bit error rate strictly below the forward error correction (FEC) threshold. This work offers a practical, physics-based evaluation framework for high-density co-packaged optics (CPO). Full article

Financial time series forecasting remains a persistent challenge due to the non-stationary nature, inherent noise, and multi-scale temporal dependencies present in market data. This paper presents MSTFNet, a multi-scale temporal fusion network that combines dilated causal convolutions with a frequency-enhanced sparse attention mechanism for improved financial prediction. The proposed architecture consists of three core components: a multi-scale dilated causal convolution module that extracts temporal patterns across different time horizons through parallel convolutional branches with varying dilation rates, a frequency-enhanced sparse attention mechanism that leverages Fast Fourier Transform to identify dominant periodic components and modulate attention weights accordingly, and an adaptive scale fusion gate that learns to dynamically combine representations from multiple temporal scales. Extensive experiments conducted on three public financial datasets (S&P 500, CSI 300, and NASDAQ Composite) spanning the period from January 2015 to December 2024 show two key results. First, consistent with near-efficient markets, the random-walk benchmark (${\widehat{y}}_{t+1}=y_t$) outperforms all the data-driven models on level-error metrics (MAE, RMSE, MAPE, and $R^2$), establishing the martingale as the binding lower bound on point-prediction error. Second, MSTFNet achieves the highest directional accuracy (DA) across all three indices—56.3% on the S&P 500 versus 50.0% for the martingale—representing a 6.3 percentage-point improvement that generates positive pre-cost returns in a trading strategy backtest. Among the eight data-driven baselines (LSTM, GRU, TCN, Transformer, Autoformer, FEDformer, PatchTST, and iTransformer), MSTFNet also achieves the lowest MAE, reducing it by 13.6% relative to the strongest data-driven baseline (iTransformer) on the S&P 500. These results confirm that integrating multi-scale temporal modeling with frequency-domain guidance extracts a real, if modest, directional signal from financial time series. Full article

Prostate cancer (PCa) remains one of the most prevalent urological malignancies worldwide, with early and accurate diagnosis being critical for improving patient outcomes. Traditional screening approaches, such as digital rectal examination and prostate-specific antigen (PSA) testing, have long served as frontline tools; however, their limited specificity and sensitivity contribute to high rates of false positives, unnecessary biopsies, and overtreatment. Recent UK guidelines and international consensus increasingly question the role of PSA-based population screening, advocating for risk-stratified pathways and multiparametric MRI as first-line investigations. In parallel, advances in molecular biology have identified promising cancer-specific biomarkers, such as prostate cancer antigen 3 (PCA3) and transmembrane protease serine 2 (TMPRSS2:ERG), that outperform PSAs in terms of specificity and prognostic value. These developments have catalysed innovation in biosensor technologies, enabling rapid, cost-effective, and non-invasive detection of single and multiplex biomarkers in urine and serum. Electrochemical and optical affinity-based biosensors offer transformative potential for the development of personalised point-of-care platforms and diagnostics, reducing the reliance on invasive procedures and improving clinical decision-making. The latter can be augmented with artificial intelligence (AI) tools. This review critically examines the limitations of PSAs, synthesises evidence on novel biomarkers and imaging-led strategies, and evaluates the design, performance, and translational challenges of biosensor-based assays. Furthermore, it outlines future directions, including standardisation, large-scale clinical validation, and integration of multiplex biosensors with AI for precision diagnostics. By bridging molecular insights with engineering innovations, these approaches promise to redefine PCa screening and enable accurate, patient-centred care. Full article

Biological E’s BEVAC^® is a recombinant DNA hepatitis B vaccine that has been used in India for more than a decade in routine early-life immunization and has recently been prequalified by the World Health Organization (WHO). This multicentre, single-blind, parallel-group, randomized phase IV trial, conducted at seven study sites in India, compared the immunogenicity and safety of BEVAC^® with a licensed comparator vaccine (GeneVac-B^®, Serum Institute of India Pvt. Ltd, Pune, India.) in healthy term neonates and infants. Participants received three 0.5 mL doses administered intramuscularly at birth (within 24 h), 6 weeks of age, and 14 weeks of age. The primary endpoint was seroprotection (anti-HBs IgG ≥10 mIU/mL) at 28 days after the third dose (Day 126), compared using a non-inferiority margin of −10%. Secondary endpoints included safety and tolerability outcomes through Day 126. A total of 468 neonates were randomized (234 per group), of whom 44% were female. At Day 126, seroprotection rates were 98.2% (95% CI: 95.39, 99.50) with BEVAC^® and 99.1% (95% CI: 96.78, 99.89) with the comparator; the between-group difference was −0.9% (95% CI: −3.09, 1.24), meeting the prespecified non-inferiority criterion. Solicited adverse events within 7 days after any dose occurred in 29.1% (95% CI: 23.3, 35.3) of BEVAC^® recipients and 35.0% (95% CI: 28.9, 41.5) of comparator recipients, most commonly pyrexia, injection-site pain, and swelling; all were mild-to-moderate. No serious adverse events were reported. BEVAC^® demonstrated non-inferior immunogenicity to the licensed comparator and a comparable safety profile. Full article