Search Results (2,338)

Distributed radar networks have emerged as a key technology in remote sensing and surveillance due to their high transmission power and robustness against node failures. When performing coherent beamforming with multiple radars, frequency and phase deviations introduced by independent oscillators lead to a decrease in transmission power. This paper proposes an optimized diffuse Kalman filter (ODKF) for the frequency and phase synchronization. Specifically, each radar locally estimates its frequency and phase, then shares this information with neighboring nodes, which are used for incremental update and diffusion update to adjust local estimates. To further reduce synchronization errors, we incorporate a self-feedback strategy in the diffusion step, in which each node balances its own estimate with neighbor information by optimizing the diagonal weights in the diffusion matrix. Numerical simulations demonstrate the superior performance of the proposed method in terms of mean squared deviation (MSD) and convergence speed. Full article

Background/Objectives: White matter (WM) structural changes have been found in patients with chronic spinal pain (CSP). In these patients, pain neuroscience education followed by cognition-targeted exercise therapy (i.e., the Modern Pain Neuroscience Approach (MPNA)) was shown to be more effective than biomedically-focused education followed by symptom-contingent exercise therapy for improving clinical outcomes. The present study examined whether an MPNA, compared to biomedically-focused treatment, can change WM structure in regions of interest and whether potential WM structural changes are associated with clinical improvements in patients with CSP. Methods: Patients with CSP were randomized into an experimental (MPNA) or control (biomedically-focused) treatment group. Diffusion-weighted Magnetic Resonance Images were acquired pre-treatment, post-treatment, and at 1-year follow-up. WM structure was assessed using diffusion tensor imaging in 8 WM regions of interest, and linear mixed models assessed differences between groups in response to treatment. Results: No significant treatment x time interaction effects were found; however, significant main effects of time were found in 7 WM tracts. Significant main effects of time revealed increased fractional anisotropy (FA), decreased mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in the cingulum hippocampus, and decreased RD and MD in the superior cerebellar peduncle at 1-year follow-up compared to baseline. In contrast, decreased FA and/or increased MD, AD, or RD values were found in other WM tracts (e.g., anterior corona radiata) from pre-treatment to 1-year follow-up. Greater reduction in kinesiophobia was moderately correlated with a smaller decrease in RD in the superior cerebellar peduncle at 1-year follow-up compared to baseline. No other significant associations were found between WM structural changes and clinical improvements. Conclusions: In conclusion, in patients with CSP, regional WM structure changed over time irrespective of prescribed treatment (timespan of 12 months). Further research, including Neurite Orientation Dispersion and Density Imaging and a healthy control group, allowing for a more specific examination of WM microstructural changes in response to multimodal treatment in patients with CSP, is warranted. Full article

The pursuit of electrochemical carbon dioxide reduction reaction (CO₂RR) as a means of energy generation and mitigation of global warming is of considerable interest. In this study, a novel RuO₂-incorporated SnO₂-fabricated glassy carbon electrode (GCE) with a Nafion binder was used for the electrochemical reduction of CO₂ in an aqueous alkaline imidazole medium. The electrode fabrication process involved the drop-casting method, where RuO₂.SnO₂ was incorporated onto the surface of the GCE. Electrochemical studies demonstrated that the GCE-RuO₂.SnO₂ electrode facilitated CO₂ reduction at −0.58 V vs. the reversible hydrogen electrode (RHE) via a diffusion-controlled pathway with the transfer of two electrons. Importantly, the first electron transfer step was identified as the rate-determining step (RDS). A Tafel slope of 144 mV dec⁻¹ confirmed the association of two-electron transfer kinetics with CO₂RR. Moreover, the standard rate constant (k_o) and formal potential (E°′) were evaluated as 2.89 × 10⁻⁵ cm s⁻¹ and 0.0998 V vs. RHE, respectively. Kinetic investigations also reveal that the deprotonation and electron release steps took place simultaneously in the CO₂RR. Based on the reported results, the GCE-RuO₂.SnO₂ electrode could be a promising candidate for CO₂ reduction, applicable in renewable energy generation. Full article

Background and Objectives: Acute respiratory distress syndrome (ARDS) is a severe form of acute lung injury with high mortality, characterized by hypoxemic respiratory failure and diffuse lung damage. Despite advancements in care, no definitive biomarkers have been established for ARDS diagnosis and prognostic stratification. Soluble receptor for advanced glycation end-products (sRAGE), a marker of alveolar epithelial injury, has shown promise as a prognostic indicator in ARDS. This study evaluates sRAGE’s utility in predicting 28-day mortality. Materials and Methods: A retrospective cohort study was conducted at a tertiary care ICU in Serbia from January 2021 to June 2023. Adult patients meeting the Berlin definition of ARDS were included. Exclusion criteria included pre-existing chronic respiratory diseases and prolonged mechanical ventilation before diagnosis. Serum sRAGE levels were measured within 48 h of ARDS diagnosis using enzyme-linked immunosorbent assay (ELISA). Clinical severity scores, laboratory markers, and ventilatory parameters were recorded. Logistic regression and survival analyses were used to assess the prognostic value of sRAGE for 28-day mortality. Results: A cohort of 121 patients (mean age 55.5 years; 63.6% male) was analyzed. Non-survivors exhibited higher median sRAGE levels than survivors (5852 vs. 4479 pg/mL, p = 0.084). The optimal sRAGE cut-off for predicting mortality was >16,500 pg/mL (sensitivity 30.4%, specificity 86.9%). Elevated sRAGE levels were associated with greater disease severity and an increased risk of 28-day mortality in ARDS patients, highlighting its potential as a prognostic biomarker. The main findings, while indicative of a trend toward higher sRAGE levels in non-survivors, did not reach statistical significance. Conclusions: The main findings, while indicative of a trend toward higher sRAGE levels in non-survivors, did not reach statistical significance (p = 0.084). sRAGE demonstrates potential as a prognostic biomarker in ARDS and has moderate correlation with 28-day mortality. Integrating sRAGE with other biomarkers could enhance risk stratification and guide therapeutic decisions. The retrospective design limits the ability to establish causation, underscoring the need for multicenter prospective studies. Full article

Pressure-retarded osmosis (PRO) is a process that allows the production of mechanical energy from the chemical potential difference between two solutions of different concentrations separated by a semi-permeable membrane. One of the main obstacles for this technology to be commercially competitive is the difference between the theoretical power density and the experimental power density due to negative factors like ICP. Analytical models facilitate the analysis of the relationships between system parameters and thus facilitate the optimization of components. In general, PRO has traditionally been explained through the solution–diffusion model, where the flow of water through the membrane depends on a diffusivity factor, the concentration gradient, and the hydraulic pressure gradient. This paper focuses on developing a modified solution–diffusion model that includes means to control the ICP through rotational kinetic energy. An energy balance method for obtaining a solution diffusion-based model is explained, and an analytical model is obtained. Finally, said model is verified through simulations with parameters reported in the literature to obtain insight on the required dimensions for a prototype. It was found that a turning radius of 0.5 m and an angular speed of less than 3000 rev/min could generate enough kinetic energy to compensate for ICP losses in a PRO scenario. Also, the results suggest that bigger concentration differences could benefit more of this technology, as they require almost the same energy as smaller concentration differences but allow for more energy extraction. Full article

Water interacting with clay minerals—such as kaolinite, montmorillonite, and pyrophyllite—fundamentally governs their geotechnical and environmental functions, thereby influencing parameters such as retention, transport, and stability. Understanding the effects of temperature on water behavior within clay mineral interlayers is critical for predicting the performance of clay–water systems under dynamic environmental conditions. This study performed molecular dynamics simulations to investigate the structural, dynamical, and mechanical properties of interlayer water in three representative clay minerals over a temperature range of 298.15–363.15 K. Our analyses focused on mean squared displacement (MSD), density profiles, hydrogen bond dynamics, and stress distributions, thereby revealing the interaction between water structuring and thermal fluctuations. Results indicated distinct temperature-dependent changes in water diffusion and hydrogen bond stability, with montmorillonite consistently exhibiting enhanced water retention and steadier hydrogen bonding networks across the studied temperature spectrum. Density profiles highlighted pronounced confinement effects at lower temperatures that gradually diminish with increasing thermal energy. Concurrently, the stress distributions revealed the mechanical responses of clay–water interfaces, highlighting the interplay between thermal motion of water molecules and their interactions with the clay surfaces. These findings offer valuable insights into how temperature regulates water behavior in clay mineral interlayers and provide a foundation for advancing predictive modeling and the design of engineered systems in water-rich, thermally variable environments. Full article

This study aims to achieve in situ-formed pure Ti and Ti6Al4V coatings on 316L stainless steel through hot pressing and examine their wear and corrosion properties thoroughly in two simulated body fluids: physiological serum (0.9% NaCl) and Hanks’ solution. The sintering and diffusion bonding process was conducted at 1050 °C under a uniaxial pressure of 40 MPa for 30 min in a vacuum environment of 10⁻⁴ mbar. Following sintering, in situ-formed pure Ti and Ti6Al4V coatings, approximately 1000 µm thick, were produced on 316L substrates approximately 3000 µm in thickness. The mean hardness of 316L substrates, pure Ti, and Ti6Al4V coatings are around 165 HV, 170 HV, and 420 HV, respectively. The interface of the stainless steel substrate and the pure Ti and Ti6Al4V coatings exhibited no microstructural defects, while the interface exhibited significantly higher hardness values (ranging from 600 to 700 HV). The coatings improved corrosion resistance in both electrolytes compared to the 316L substrate. Wet wear tests revealed reduced friction coefficients in 0.9% NaCl relative to Hanks’ solution, highlighting the chemical interactions between the material surface and the electrolyte type and the significance of tribocorrosion in biocoatings. Full article

Laser active imaging systems can remedy the shortcomings of visible light imaging systems in difficult imaging circumstances, thereby attaining clear images. However, laser images exhibit significant modal discrepancy in contrast to the visible image, impeding human perception and computer processing. Consequently, it is necessary to translate laser images to visible images across modalities. Existing cross-modal image translation algorithms are plagued with issues, including difficult training and color bleeding. In recent studies, diffusion models have demonstrated superior image generation and translation abilities and been shown to be capable of generating high-quality images. To achieve more accurate laser-visible image translation, we designed an improved diffusion model, called DCLTV, which limits the randomness of diffusion models by means of dual-condition control. We incorporated the Brownian bridge strategy to serve as the first condition control and employed interpolation-based conditional injection to function as the second condition control. We also established a dataset comprising 665 pairs of laser-visible images to compensate for the data deficiency in the field of laser-visible image translation. Compared to five representative baseline models, namely Pix2pix, BigColor, CT2, ColorFormer, and DDColor, the proposed DCLTV achieved the best performance in terms of both qualitative and quantitative comparisons, realizing at least a 15.89% reduction in FID and at least a 22.02% reduction in LPIPS. We further validated the effectiveness of the dual conditions in DCLTV through ablation experiments, achieving the best results with an FID of 154.74 and an LPIPS of 0.379. Full article

Clinical and mycological data are essential for the optimal management of patients with Candida vaginitis (CV), particularly in cases of (i) azole-resistant C. albicans vaginitis, (ii) recurrent CV, and (iii) CV in pregnant women. The present retrospective single-center study investigated the antifungal activity of six commonly used antifungals against randomly selected vaginal isolates recovered from 68 pregnant women in Adana, Türkiye, including C. albicans, petite C. glabrata, non-petite C. glabrata, and C. krusei, using the disk diffusion method at pH 4 and 7. Furthermore, the antifungal activities of fluconazole and itraconazole were also assessed using the broth microdilution method. For all isolates, the mean inhibition zone diameters were narrower for itraconazole and ketoconazole and larger for miconazole at pH 4 than pH 7 (p < 0.05). For nystatin, zone diameters were wider in C. albicans and petite C. glabrata at pH 4 (p < 0.001 and p < 0.001). Remarkably, clotrimazole was more active at pH 4 than at pH 7, except against non-petite C. glabrata isolates. Based on the broth microdilution results, the resistance rate was higher at pH 4 than at pH 7 in all isolates. Candida glabrata petite isolates exhibited MIC values 2 to 5 times higher than those of the non-petite isolates for both fluconazole and itraconazole. This study highlights the potent activity of topical antifungals (miconazole, nystatin, and clotrimazole) for the treatment of CV in pregnant women and highlights the need to identify petite and non-petite mutants of vaginal C. glabrata isolates to obtain more reliable data and for antifungal susceptibility testing prior to decision-making. The results of the two antifungal susceptibility methods were compared for C. albicans and C. glabrata isolates, and the reliability of the disk diffusion test was discussed. Full article

When exploring interactions between Christianity and other religions in East Asia, the place given to the shamanic tradition remains ambiguous and marginal. This article analyzes the religious encounters between shamanism and Christianity in East Asia through specific and representative case studies. This article is divided into three main parts. Section 1 introduces the core terms “shamanism” and “diffusionism”, explaining their general meanings and the specific ways they are used in this study, and provides a regional overview of the cases analyzed in this paper. Sections 2–4 present the historical context and analysis of religious encounters in regions such as Siberia, Mongolia, China (including Taiwan, Southwest China, and Northeast China), Korea, etc. Sections 5 and 6 seek to demonstrate that shamanism operates according to two models: the first characterized by “segregation” and the second by “diffusion”, noting that these models exist on a dynamic continuum. In most historical situations, this study argues that shamanism initially encountered Christianity in a segregation mode, often leading to significant conflicts between the two. Over time, as shamanism’s religious attributes weakened, it paradoxically adapted to a diffusion model, integrating its ethos into other religions, including Christianity. The diffusion model has thus become an appropriate way to understand the current existent form of shamanism in East Asia. Full article

The rapid advancement in smart agriculture has introduced significant challenges, including data scarcity, complex and diverse disease features, and substantial background interference in agricultural scenarios. To address these challenges, a disease detection method based on few-shot learning and diffusion generative models is proposed. By integrating the high-quality feature generation capabilities of diffusion models with the feature extraction advantages of few-shot learning, an end-to-end framework for disease detection has been constructed. The experimental results demonstrate that the proposed method achieves outstanding performance in disease detection tasks. Across comprehensive experiments, the model achieved scores of 0.94, 0.92, 0.93, and 0.92 in precision, recall, accuracy, and mean average precision (mAP@75), respectively, significantly outperforming other comparative models. Furthermore, the incorporation of attention mechanisms effectively enhanced the quality of disease feature representations and improved the model’s ability to capture fine-grained features. Full article

Background and Objectives: Obstructive sleep apnea is an extremely diffuse pathology that, if left untreated, can lead to very serious cardiovascular consequences. The primary goal of treatment is to maintain airflow in the upper airway tract, which can be obtained thanks to orthognathic surgery such as maxillo-mandibular advancement (MMA). This procedure increases the volume of the posterior airway space (PAS)—a parameter considered fundamental in OSA physiology. However, the correlation between the degree of advancement, the volume increase, and the clinical improvement in OSA is not yet clear, even in patients who undergo virtual surgical planning. Aiming to test the correlation of these parameters and the role of PAS volume changes, we present our pre- and post-operative volumetric analysis of the PAS using cone beam computed tomography (CBCT) following CAD/CAM-assisted maxillomandibular advancement. Materials and Methods: We collected information from patients who underwent MMA for moderate or severe OSA, planned virtually with custom-made devices, between 2020 and 2022 at the Maxillofacial Surgery and Odontostomatology Unit of the Policlinico Hospital in Milan. The degree of mandibular advancement (pogonion antero-posterior advancement) was noted. All patients underwent pre- and post-operative CBCT and pre- and post-operative polysomnography to measure the Apnea–Hypopnea Index (AHI) parameters. Both exams were performed within six months before and after surgery. The surgeries were planned virtually along with the production of custom-made devices (cutting guides and mandibular osteosynthesis plates). Volumetric analysis of the PAS was performed pre- and post-CBCT images using medical segmentation software (Mimics, Materialise, Mimcs 26.0). Results: Ten patients (nine men and one woman) with a mean age of 51 years were included in this study. The mean pogonion advancement was 14.5 mm, ranging from 13.8 to 15.6. The mean pre-surgical AHI was 52.31 events/h, while the mean post-surgical AHI was 5.94 events/h (SD 5.34). The improvement in AHI was statistically significant (Wilcoxon matched-pairs signed-rank test, p value 0.004). The mean pre-surgical PAS volume was 8933 mm³, while the mean post-surgical volume was 10,609 mm³. In 8 out of 10 patients, the volume increased, with a mean increase of 2640 mm³ (max. 5183, min. 951), corresponding to a percentage increase variation ranging from 78% to 6%. In two patients, the volume decreased by 1591 (−16%) and 2767 mm³ (−31%), respectively. The difference between pre- and post-operative results was not statistically significant (paired t-test, p value 0.033). Conclusions: The results obtained confirm the efficacy of virtually planned MMA performed with custom-made devices in OSA therapy. However, they also show that PAS volume should not be used as a comprehensive parameter for OSA treatment evaluation because it does not always have a positive correlation with advancement and AHI. Full article

Pathological alterations in Alzheimer’s disease (AD) begin several years prior to symptom onset. Cortical mean diffusivity (cMD) may be used as a measure of early grey matter damage in AD as it reflects the breakdown of microstructural barriers preceding volumetric changes and affecting cognitive function. We investigated cMD changes early in the disease trajectory and evaluated the influence of amyloid-β (Aβ) and tau deposition. In this cross-sectional study, we analysed multimodal PET, DTI, and MRI data of 87 participants, and stratified them into Aβ-negative and -positive, cognitively normal, mildly cognitively impaired, and AD patients. cMD was significantly increased in Aβ-positive MCI and AD compared with CN in the frontal, parietal, temporal cortex, hippocampus, and medial temporal lobe. cMD was significantly correlated with cortical thickness only in patients without Aβ deposition but not in Aβ-positive patients. Our results suggest that cMD is an early marker of neuronal damage since it is observed simultaneously with Aβ deposition and is correlated with cortical thickness only in subjects without Aβ deposition. cMD changes may be driven by Aβ but not tau, suggesting that direct Aβ toxicity or associated inflammation causes damage to neurons. cMD may provide information about early microstructural changes before macrostructural changes. Full article

This study aims to characterize the conjunctival flora of patients scheduled for cataract surgery and determine the susceptibility profile of isolated bacteria to several commonly used topical antibiotics. Conjunctival swabs were taken from 44 consecutive patients (25 males, 19 females; mean age of 75.0 ± 12.6 years) who were scheduled for senile cataract surgery at two Italian centers before starting any prophylactic preoperative treatment. Swabs were processed for the detection of the microbial growth and for species identification. Selective culture media were used, and bacteria were identified using the MicroScan Specialty ID Panels (Beckman Coulter^®, Brea, CA, USA). Antimicrobial susceptibility for the following antibiotics (netilmicin, tobramycin, ofloxacin, oxacillin, levofloxacin, moxifloxacin, chloramphenicol, cefuroxime, and azithromycin) were assessed using the Kirby–Bauer disk diffusion method. Susceptibility for oxacillin was useful to identify methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-resistant Staphylococcus epidermidis (MRSE). Among the swabs analyzed, 61.4% showed only saprophytic flora, 30.7% showed only potential pathogenic flora, and 8.0% showed mixed flora. S. epidermidis (20.5%), S. intermedius (18.2%), and S. aureus (14.8%) were the most frequent isolates; MRSA and MRSE accounted for 8.0% and 6.8% of isolates. Less frequently (9%), Gram-negative bacteria such as Pseudomonas fluorescent, Serratia marcescens, Moraxella lacunata, Morganella morgani, and Stenotrophomonas maltophila were detected. All isolated organisms showed an excellent sensitivity to moxifloxacin and chloramphenicol (range 83–100%, range 67–100%, Gram-positive sensitivity for moxifloxacin and chloramphenicol, respectively; 100% Gram-negative sensitivity for both). A significant percentage of the eyes of candidates for surgery presented potential pathogenic flora alone or in association with saprophytic organisms. Staphylococci were the most frequently isolated bacteria. Tobramycin and Ofloxacin, widely used in the ophthalmic field, are confirmed to have a reduced sensitivity in vitro. Full article

Accurate crude oil price forecasting is essential, considering oil’s critical role in the global economy. However, the crude oil market is significantly influenced by external, transient events, posing challenges in capturing price fluctuations’ complex dynamics and uncertainties. Traditional time series forecasting models, such as ARIMA and LSTM, often rely on assumptions regarding data structure, limiting their flexibility to estimate volatility or account for external shocks effectively. Recent research highlights Generative Adversarial Networks (GANs) as a promising alternative approach for capturing intricate patterns in time series data, leveraging the adversarial learning framework. This paper introduces a Crude Oil-Driven Conditional GAN (CO-CGAN), a hybrid model for enhancing crude oil price forecasting by combining advanced AI frameworks (GANs), oil market sentiment analysis, and stochastic jump-diffusion models. By employing conditional supervised training, the inherent structure of the data distribution is preserved, thereby enabling more accurate and reliable probabilistic price forecasts. Additionally, the CO-CGAN integrates a Lévy process and sentiment features to better account for uncertainties and price shocks in the crude oil market. Experimental evaluations on two real-world oil price datasets demonstrate the superior performance of the proposed model, achieving a Mean Squared Error (MSE) of 0.000054 and outperforming benchmark models. Full article