Search Results (251)

To enable accurate evaluation of satellite laser communication terminals under solar outage interference, this paper presents the design and implementation of a solar radiation simulation system targeting the 1540–1560 nm communication band. The system reconstructs co-propagating interference conditions through standardized and continuously tunable output, based on high irradiance and spectral uniformity. A compound beam homogenization structure—combining a multimode fiber and an apodizator—achieves 85.8% far-field uniformity over a 200 mm aperture. A power–spectrum co-optimization strategy is introduced for filter design, achieving a spectral matching degree of 78%. The system supports a tunable output from 2.5 to 130 mW with a 50× dynamic range and maintains power control accuracy within ±0.9%. To suppress internal background interference, a BRDF-based optical scattering model is established to trace primary and secondary stray light paths. Simulation results show that by maintaining the surface roughness of key mirrors below 2 nm and incorporating a U-shaped reflective light trap, stray light levels can be reduced to 5.13 × 10⁻¹² W, ensuring stable detection of a 10⁻¹⁰ W signal at a 10:1 signal-to-background ratio. Experimental validation confirms that the system can faithfully reproduce solar outage conditions within a ±3° field of view, achieving consistent performance in spectrum shaping, irradiance uniformity, and background suppression. The proposed platform provides a standardized and practical testbed for ground-based anti-interference assessment of optical communication terminals. Full article

Background/Objectives: Upper tract urothelial carcinoma (UTUC) is a rare and biologically distinct subset of urothelial malignancies, comprising approximately 5–10% of urothelial cancers. UTUC presents unique diagnostic and therapeutic challenges, with both a higher likelihood of invasive disease at presentation and a less favorable prognosis compared to urothelial carcinoma of the bladder. Current treatment strategies for UTUC are largely derived from bladder cancer studies, underscoring the need for UTUC-directed research. This review provides a comprehensive overview of UTUC, encompassing diagnostic approaches, systemic and intraluminal therapies, surgical management, and future directions. Methods: A narrative review was conducted synthesizing evidence from guideline-based recommendations, retrospective and prospective clinical studies, and ongoing trials focused on UTUC. Results: Neoadjuvant cisplatin-based chemotherapy is increasingly preferred in UTUC due to the risk of postoperative renal impairment that may preclude adjuvant cisplatin use. Surgical management includes kidney-sparing approaches and radical nephroureterectomy (RNU), with selection guided by tumor risk and patient comorbidities. While endoscopic management (EM) preserves renal function, it carries a higher recurrence and surveillance burden; RNU remains standard for high-risk cases. Systemic therapy for advanced and metastatic UTUC mirrors that of bladder urothelial carcinoma. Enfortumab vedotin (EV) plus pembrolizumab showed superior efficacy over chemotherapy in the EV-302 trial, with improved response rate, progression-free survival, and overall survival across subgroups, including UTUC. For patients ineligible for EV, the CheckMate-901 study supported first-line chemoimmunotherapy with gemcitabine, cisplatin, and nivolumab. Further systemic therapy strategies include maintenance avelumab post-chemotherapy (JAVELIN Bladder 100), targeted therapies such as erdafitinib (THOR trial), and trastuzumab deruxtecan (DESTINY-PanTumor02) in FGFR2/3-altered and HER2-positive disease, respectively. Conclusions: Historically, the therapeutic landscape of UTUC has been extrapolated from bladder cancer; however, ongoing research specific to UTUC is deriving more precise regimens involving the use of immune checkpoint inhibitors, antibody–drug conjugates, and biomarker-driven therapies. Full article

Objective: Uncovering the renoprotective and anti-inflammatory effects of atorvastatin treatment in diabetic-and-obese rats by employing traditional renal function indicators (urea and creatinine) and four prototypical cytokines (IL-1β, il-6, IL-17α, TNFα). Method: Twenty-eight male Wistar rats, aged 6 months, 350–400 g, were randomized into four groups. The first group, G-I, the denominated control, were fed standard chow over the whole course of the experiments. The rodents in G-II were exposed to a High-Fat Diet. The last two groups were exposed to Streptozotocin peritoneal injection (35 mg/kg of body weight). A short biochemical assessment was performed before diabetes model induction to ensure appropriate glucose metabolism before experiments. Following model induction, only rodents in group G-IV were gradually introduced to the same High-Fat Diet as received by G-II. Model confirmation 10 days after injections marked the start of statin treatment in group G-IV, by daily gavage of atorvastatin 20 mg/kg of body weight/day for 21 days. At the end of the experiments, the biochemical profile of interest comprised typical renal retention byproducts (urea and creatinine) and the inflammatory profile described using plasma levels of TNFα, IL-17α, IL-6, and IL-1β. Results: Treatment with Atorvastatin was associated with a statistically significant improvement in renal function in G-IV compared to untreated diabetic rodents in G-III. Changes in inflammatory activity showed partial association with statin therapy, TNFα and IL-17α mirroring the trend in urea and creatinine values. Conclusions: Our results indicate that atorvastatin treatment yields a myriad of pleiotropic activities, among which renal protection was clearly demonstrated in this model of diabetic-and-obese rodents. The statin impact on inflammation regulation may not be as clear-cut, but the potential synergy of renal function preservation and partial tapering of inflammatory activity requires further research in severely metabolically challenged models. Full article

Aquilaria sinensis (Lour.) Gilg, the exclusive botanical source of Chinese agarwood, holds significant medicinal value. This study investigated the agarwood-inducing potential of a Fusarium strain obtained through prior isolation work. Through integrated morphological characterization and molecular phylogenetic analysis, the strain was conclusively identified as Fusarium equiseti. GC-MS analysis revealed that fungal inoculation induced the synthesis of characteristic sesquiterpenes and aromatic compounds consistent with natural agarwood profiles. Quantitative determination demonstrated progressive accumulation of agarotetrol, a key quality marker, reaching 0.034%, 0.039%, and 0.038% at 2, 4, and 6 months post-inoculation, respectively—significantly exceeding levels from physical wounding (p < 0.05) and PDA control treatments. Histological examination showed characteristic yellow-brown oleoresin deposits concentrated in the inner phloem, mirroring the anatomical features of wild-type agarwood. Critical quality parameters measured in December-harvested samples included ethanol extractives (17.69%), chromone derivatives 2-[2-(4-methoxyphenyl) ethyl] chromone, and 2-(2-phenylethyl) chromone (2.13%), all meeting or surpassing the specifications outlined in the National Standard for Agarwood Classification (LY/T 3223-2020). These comprehensive findings establish F. equiseti as a promising microbial agent for sustainable agarwood production in A. sinensis plantations. Full article

Background: Native vertebral osteomyelitis (NVO) presents diagnostic and therapeutic challenges requiring adherence to complex clinical guidelines. The emergence of large language models (LLMs) offers new avenues for real-time clinical decision support, yet their utility in managing NVO has not been formally assessed. Methods: This study evaluated four LLMs—Consensus, Gemini, ChatGPT-4o Mini, and ChatGPT-4o—using 13 standardized questions derived from the 2015 IDSA guidelines. Each model generated 13 responses (n = 52), which were independently assessed by three orthopedic surgeons for accuracy (4-point scale) and comprehensiveness (five-point scale). Results: ChatGPT-4o produced the longest responses (428.0 ± 45.4 words), followed by ChatGPT-4o Mini (392.2 ± 97.4), Gemini (358.2 ± 60.5), and Consensus (213.2 ± 68.8). Accuracy ratings showed that ChatGPT-4o and Gemini achieved the highest proportion of “Excellent” responses (54% and 51%, respectively), while Consensus received only 20%. Comprehensiveness scores mirrored this trend, with ChatGPT-4o (3.95 ± 0.79) and Gemini (3.82 ± 0.68) significantly outperforming Consensus (2.87 ± 0.66). Domain-specific analysis revealed that ChatGPT-4o achieved a 100% “Excellent” accuracy rating in therapy-related questions. Statistical analysis confirmed significant inter-model differences (p < 0.001). Conclusions: Advanced LLMs—especially ChatGPT-4o and Gemini—demonstrated high accuracy and depth in interpreting clinical guidelines for NVO. These findings highlight their potential as effective tools in augmenting evidence-based decision-making and improving consistency in clinical care. Full article

Blasting-induced seismic waves are typically nonlinear and non-stationary signals. The EMD-Hilbert transform is commonly used for time–frequency analysis of such signals. However, during the empirical mode decomposition (EMD) processing of blasting-induced seismic waves, endpoint effects occur, resulting in varying degrees of divergence in the obtained intrinsic mode function (IMF) components at both ends. The further application of the Hilbert transform to these endpoint-divergent IMFs yield artificial time–frequency analysis results, adversely impacting the assessment of blasting-induced seismic wave hazards. This paper proposes an improved EMD endpoint effect suppression algorithm that considers local endpoint development trends, global time distribution, energy matching, and waveform matching. The method first analyzes global temporal characteristics and endpoint amplitude variations to obtain left and right endpoint extension signal fragment S(t)_L and S(t)_R. Using these as references, the original signal is divided into “b” equal segments S(t)₁, S(t)₂ … S(t)_b. Energy matching and waveform matching functions are then established to identify signal fragments S(t)_i and S(t)_j that match both the energy and waveform characteristics of S(t)_L and S(t)_R. Replacing S(t)_L and S(t)_R with S(t)_i and S(t)_j effectively suppresses the EMD endpoint effects. To verify the algorithm’s effectiveness in suppressing EMD endpoint effects, comparative studies were conducted using simulated signals to compare the proposed method with mirror extension, polynomial fitting, and extreme value extension methods. Three evaluation metrics were utilized: error standard deviation, correlation coefficient, and computation time. The results demonstrate that the proposed algorithm effectively reduces the divergence at the endpoints of the IMFs and yields physically meaningful IMF components. Finally, the method was applied to the analysis of actual blasting seismic signals. It successfully suppressed the endpoint effects of EMD and improved the extraction of time–frequency characteristics from blasting-induced seismic waves. This has significant practical implications for safety assessments of existing structures in areas affected by blasting. Full article

Despite significant technological advancements in aviation safety systems, human-operator condition monitoring remains a critical challenge, with more than 75% of aircraft incidents stemming from attention-related perceptual failures. This study addresses a fundamental question in sensor-based condition monitoring: how can temporal- and frequency-domain EEG sensor data be optimally integrated to detect precursors of system failure in human–machine interfaces? We propose a three-stage diagnostic framework that mirrors industrial condition monitoring approaches. First, raw EEG sensor signals undergo preprocessing into standardized one-second epochs. Second, a novel hybrid feature-extraction methodology combines time- and frequency-domain features to create comprehensive sensor signatures of neural states. Finally, our dual-architecture CNN–LSTM model processes spatial patterns via CNNs while capturing temporal degradation signals via LSTMs, enabling robust classification in noisy operational environments. Our contributions include (1) a multimodal data fusion approach for EEG sensors that provides a more comprehensive representation of operator conditions, and (2) an artificial intelligence architecture that balances spatial and temporal analysis for the predictive maintenance of attention states. When validated on aviation-related EEG datasets, our condition monitoring system achieved significantly higher diagnostic accuracy across various noise conditions compared to existing approaches. The practical applications extend beyond theoretical improvement, offering a pathway to implement more reliable human–machine interface monitoring in critical systems, potentially preventing catastrophic failures by detecting condition anomalies before they propagate through the system. Full article

Introduction: The monitoring of autonomic nervous balance during childhood remains underexplored. However, heart rate variability (HRV) is widely recognized as a biomarker of health risk across the lifespan. Juvenile idiopathic arthritis (JIA), a group of chronic inflammatory joint disorders, is associated with persistent inflammation and pain, both of which contribute to increased cardiovascular risk, commonly linked to reduced HRV. Among HRV parameters, very-low frequency (VLF) components have been associated with physiological recovery processes. This study aimed to assess HRV during sleep in patients with JIA. Methods: We studied 10 patients with JIA and 10 age-, gender-, and Tanner stage-matched healthy controls. All participants underwent polysomnographic monitoring following an adaptation night in the sleep laboratory. HRV was analyzed using standard time and frequency domain measures over 5 min epochs across all sleep stages. Frequency components were classified into low- and high-frequency bands, and time domain measures included the standard deviation of the beat-to-beat intervals. Group differences in HRV parameters were assessed using nonparametric tests for independent samples, with a significance level set at p < 0.05. Results: JIA exhibited greater sleep disruption than controls, including reduced NREM sleep, longer total sleep time, and increased wake time after sleep onset. HRV analyses in both time and frequency domains revealed significant differences between groups across all stages of sleep. In JIA patients, the standard deviation of the normal-to-normal interval during slow wave sleep (SWS) and total power across all sleep stages (p < 0.05) was reduced. In JIA patients, the standard deviation of the normal-to-normal interval during slow wave sleep and total power across all sleep stages were significantly reduced (p < 0.05). VLF power was also significantly lower in JIA patients across all sleep stages (p = 0.002), with pronounced reductions during N2 and SWS (p = 0.03 and p = 0.02, respectively). A group effect was observed for total power across all stages, mirroring the VLF findings. Additionally, group differences were detected in LF/HF ratio analyses, although values during N2, SWS, and REM sleep did not differ significantly between groups. Notably, the number of affected joints showed a moderate positive correlation with the parasympathetic HRV parameter. Conclusions: Patients with JIA exhibited sleep disruption and alterations in cardiovascular autonomic functioning during sleep. Reduced HRV across all sleep stages in these patients suggests underlying autonomic nervous dysfunction. Addressing sleep disturbances in patients with chronic pain may serve as an effective strategy for managing their cardiovascular risk. Full article

In this study, we define the $k$-Cullen, $k$-Cullen–Lucas, and Modified $k$-Cullen sequences, and certain terms in these sequences are given. Then, we obtain the Binet formulas, generating functions, summation formulas, etc. In addition, we examine the relations among the terms of the $k$-Cullen, $k$-Cullen–Lucas, Modified $k$-Cullen, Cullen, Cullen–Lucas, Modified Cullen, $k$-Woodall, $k$-Woodall–Lucas, Modified $k$-Woodall, Woodall, Woodall–Lucas, and Modified Woodall sequences. The generating functions were derived and analyzed, especially for cases where Fibonacci numbers were assigned to parameter $k.$ Graphical representations of the generating functions and their logarithmic transformations revealed interesting growth trends and convergence behavior. Further, by multiplying the generating functions with exponential expressions such as $e^k$, we explored the self-similar nature and mirrored dynamics among the sequences. Specifically, it was observed that the Modified Cullen sequence exhibited a symmetric and inverse-like resemblance to the Cullen and Cullen–Lucas sequences, suggesting the presence of deeper structural dualities. Additionally, indefinite integrals of the generating functions were computed and visualized over a range of Fibonacci-indexed k values. These integral-based graphs further reinforced the phenomenon of symmetry and self-similarity, particularly in the Modified Cullen sequence. A key insight of this study is the discovery of a structural duality between the Modified Cullen and standard Cullen-type sequences, supported both algebraically and graphically. This duality suggests new avenues for analyzing generalized recursive sequences through generating function transformations. This observation provides new insight into the structural behavior of generalized Cullen-type sequences. Full article

The current treatment for refractory BRAF-V600E mutant metastatic colorectal cancer (mCRC) involves combined inhibition of BRAF and the epidermal growth factor receptor (EGFR). However, tumour responses are often short-lived due to a rebound in mitogen-activated protein kinase (MAPK) activity. In this study, we combined short-term cell viability assays with long-term regrowth assays following drug removal over a period of three weeks. This allowed assessment of regrowth after therapy discontinuation. We tested the effect of combined BRAF inhibition (encorafenib) and EGFR inhibition (afatinib) on BRAF-V600E mutant CRC patient-derived organoids (PDOs). Combined EGFR/BRAF inhibition initially caused a major reduction in PDO growth capacity in BRAF-V600E mutant PDOs. This was followed by rapid regrowth after drug removal, mirroring clinical outcomes. EGFR inhibition in BRAF-V600E mutant PDOs led to activation of the insulin receptor (IR) and insulin-like growth factor-1 receptor (IGF1R). The IGF1R/IR inhibitor linsitinib prevented the rebound in MAPK activity following removal of afatinib and encorafenib, prevented regrowth of CRC PDOs, and improved the anti-tumour response in an in vivo model. PDO regrowth assays allow the identification of pathways driving tumour recurrence. IR/IGF1R-inhibition prevents regrowth following golden standard MAPK pathway-targeted therapy and provides a strategy to improve the treatment of BRAF-V600E mutant CRC Full article

Range expansions driven by global warming are increasingly documented, particularly in birds and insects. The House Bunting, a species native to North Africa, has recently established the first confirmed breeding population in mainland Europe in Algeciras, southern Spain. This study presents the results of the first systematic survey of this population, conducted in December 2024. Using a standardized survey method across a grid of hexagonal sampling units, we recorded a minimum of 18 individuals, including juveniles, indicating both successful reproduction and possible new arrivals. Observations were concentrated in low-rise urban areas, mirroring the species’ preferred habitats in Morocco. The presence of individuals with juvenile plumage in December suggests an extended breeding season, which may facilitate population growth. Given the geographical proximity to North Africa and predicted increases in aridity due to climate change, further expansion into Iberia appears likely. Although no immediate ecological impacts have been detected, the potential for interactions with resident species justifies continued monitoring. This study provides a baseline for assessing the establishment and growth of this population, contributing to a broader understanding of how climate change influences species distributions and the colonization dynamics of expanding bird populations. Full article

This work proposes two voltage-controlled oscillators using noise-filtering technique. The first one is a 24-GHz voltage-controlled oscillator, and the second one is based on a push–push architecture with a $\mathsf{\lambda }$/4 transmission line to further increase the frequency up to 48 GHz. The designs are implemented and verified in a standard 90-nm CMOS process. Typically, the current mirror transistor in the tail current has a nonlinear effect. When the transistor operates in the nonlinear region, noise will be introduced. Therefore, a set of LC filters with a resonant frequency at 2$f_0$ are added to the design of this section to filter the noise at 2$f_0$ through the capacitor to the ground. The measurement results show that the design of a single oscillator has an oscillation frequency of 24.37 GHz, a tuning range of 6.5%, and a phase noise of −97.19 dBc/Hz @1MHz. The measurement results of the push–push architecture show that the double oscillation frequency is 49.8 GHz, the tuning range is 7.2%, and the phase noise is −80.52 dBc/Hz @1MHz. The chip areas of 24-GHz LC VCO and 48-GHz push–push LC VCO are 0.68 mm × 0.69 mm and 0.7 mm × 0.7 mm, respectively. Full article

Exploring the spatiotemporal evolution of urban and rural settlements in African countries could provide critical insights into the patterns of urbanization, regional disparities, and sustainable development in the context of rapid socio-economic and demographic changes. Using global human settlement data alongside multi-source socio-economic and environmental datasets, this study investigates the spatiotemporal dynamics of human settlements in Tanzania from 1975 to 2020. A combination of methods, including hotspot analysis, standard deviation ellipse analysis, and geographic detectors, is employed to examine the characteristics of settlement evolution and the underlying factors contributing to regional differentiation. The findings reveal that over the past 45 years, the expansion of urban centers and urban clusters in Tanzania has significantly accelerated, while rural areas have experienced a corresponding decline, reflecting a shift from low-density to high-density settlements and a transformation from rural to urban landscapes. Dar es Salaam, Mwanza, and Arusha have consistently been hotspots for urban center growth, while Kagera has emerged as a primary hotspot for urban clusters. The distribution of rural hotspots and coldspots generally mirrors that of urban clusters. The spatial distribution of urban centers, urban clusters, and rural areas follows a northwest–southeast orientation, with the spatial distribution of urban centers gradually stabilizing. However, the development gap between urban clusters in the northwest and rural areas in the southeast is widening and narrowing, respectively. Socio-economic factors exert a stronger influence on the development of settlements than natural environmental factors. Population density, GDP density, and road network density are significant drivers of settlement patterns, with their influence intensifying over time. Full article

In pursuit of a higher-quality post-pandemic economic recovery, Chinese authorities have accelerated the development of the e-CNY. This study posits that the e-CNY distinguishes itself from other payment instruments through its controlled anonymity, programmability, and non-interest-bearing attributes. By analyzing patents filed by the Digital Currency Research Institute of the People’s Bank of China between 2016 and 2023, the paper elucidates potential implementation strategies for these distinctive features. The findings suggest that the e-CNY may facilitate a zero-interest accrual model within the prevailing legal framework. Restricted authority access and the anonymity ensured by encrypted data further allow users to maintain a high degree of confidentiality. Additionally, conditional automatic transfers—a prominent function in the e-CNY’s smart contracts—mirror traditional automatic transfers for directed fund utilization without impeding the circulation of fiat currency. The People’s Bank of China has sought to thoughtfully integrate these functionalities into its Central Bank Digital Currency framework, aiming to minimize potential conflicts with existing legal standards. Instead of relying solely on extensive legislative revisions, China’s experience illustrates how deliberate and incremental CBDC design choices can reconcile regulatory compliance with innovative technological advancements. Full article

Background and Objectives: Brain-computer interface (BCI) technology is revolutionizing stroke rehabilitation by offering innovative neuroengineering solutions to address neurological deficits. By bypassing peripheral nerves and muscles, BCIs enable individuals with severe motor impairments to communicate their intentions directly through control signals derived from brain activity, opening new pathways for recovery and improving the quality of life. The aim of this study was to explore the beneficial effects of BCI system-based interventions on upper limb motor function and performance of activities of daily living (ADL) in stroke patients. We hypothesized that integrating BCI into occupational therapy would result in measurable improvements in hand strength, dexterity, independence in daily activities, and cognitive function compared to baseline. Materials and Methods: An observational study was conducted on 56 patients with subacute stroke. All patients received standard medical care and rehabilitation for 54 days, as part of the comprehensive treatment protocol. Patients underwent BCI training 2–3 times a week instead of some occupational therapy sessions, with each patient completing 15 sessions of BCI-based recoveriX treatment during rehabilitation. The occupational therapy program included bilateral exercises, grip-strengthening activities, fine motor/coordination tasks, tactile discrimination exercises, proprioceptive training, and mirror therapy to enhance motor recovery through visual feedback. Participants received ADL-related training aimed at improving their functional independence in everyday activities. Routine occupational therapy was provided five times a week for 50 min per session. Upper extremity function was evaluated using the Box and Block Test (BBT), Nine-Hole Peg Test (9HPT), and dynamometry to assess gross manual dexterity, fine motor skills, and grip strength. Independence in daily living was assessed using the Functional Independence Measure (FIM). Results: Statistically significant improvements were observed across all the outcome measures (p < 0.001). The strength of the stroke-affected hand improved from 5.0 kg to 6.7 kg, and that of the unaffected hand improved from 29.7 kg to 40.0 kg. Functional independence increased notably, with the FIM scores rising from 43.0 to 83.5. Cognitive function also improved, with MMSE scores increasing from 22.0 to 26.0. The effect sizes ranged from moderate to large, indicating clinically meaningful benefits. Conclusions: This study suggests that BCI-based occupational therapy interventions effectively improve upper extremity motor function and daily functions and have a positive impact on the cognition of patients with subacute stroke. Full article