Search Results (464)

The main purpose of this study was to analyze the dynamics of the conditional correlation between Bitcoin and BOVA11 (a Brazilian stock market ETF that has seen a significant increase in foreign investors) across the pre-, during, and post-COVID-19 pandemic periods. This analysis allowed us to investigate the Bitcoin characteristics as a diversifier, hedge, or safe haven relative to the ETF. The study employed a DCC-GARCH model using daily closing prices from 2 January 2015 to 26 September 2025. A robustness check was conducted using Large Language Models (LLMs). Results indicated that in the pre- and post-pandemic periods, Bitcoin showed no significant correlation with the ETF, potentially acting as a weak hedge. Conversely, during the pandemic, Bitcoin behaved as a diversifier for the ETF rather than a safe haven. This finding may surprise market participants, particularly given the widespread narrative of Bitcoin as “digital gold” and, therefore, a natural protection in scenarios of high uncertainty. The results suggest that, during the pandemic, Bitcoin’s behavior aligned more closely with risk assets than with safe havens, underscoring the need for cautious, context-specific empirical assessments of its protective properties. Full article

In modern aerospace cockpits, the display and control console (DCC) serves as a critical human–machine interface. Light weight is particularly important in this industry, especially for key equipment such as the DCC. To address the excessive weight of aluminum alloy DCCs while achieving desirable mechanical properties and vibration-damping performance, this study developed a Carbon Fiber Reinforced Polymer (CFRP) DCC; its superior performance was verified through finite element analysis (FEA) and a vibration test. Compared with conventional aluminum alloy structures, the newly designed DCC achieves approximately a 40% weight reduction while meeting all rigidity, strength, and vibration requirements. This study successfully demonstrates the feasibility of using CFRP to replace aluminum alloy in aircraft DCC and provides a systematic design methodology for similar structures. Full article

Active substance-based Ballast Water Management Systems (BWMS) can generate disinfection by-products (DBPs) by reacting with dissolved organic matter (DOM). However, current IMO G9-based assessments often overlook qualitative DOM variations. This study investigated DBP formation following NaDCC treatment in natural seawater dominated by the diatom Skeletonema costatum and the dinoflagellate Akashiwo sanguinea. Laboratory-cultured DOM was also analyzed using ATR-FT-IR, PCA, and 2D-COS to evaluate structural differences. In field experiments, S. costatum treatment primarily produced brominated trihalomethanes (THMs) and specific haloacetic acids (HAAs) with a limited composition. Conversely, A. sanguinea treatment yielded a diverse range of DBPs, including nitrogenous DBPs (HANs). FT-IR results, supported by 2D-COS, revealed that A. sanguinea-derived DOM underwent non-monotonic structural changes and distinct sequential functional group reactions, suggesting multiple, time-delayed precursor interactions. These findings demonstrate that phytoplankton species-specific DOM composition significantly dictates DBP profiles and temporal dynamics. Therefore, environmental risk assessments for BWMS must incorporate the qualitative characteristics of biogenic DOM and dominant species traits, particularly during coastal bloom events, to ensure more accurate management strategies. Full article

Disseminated cutaneous coccidioidomycosis (DCC) is an uncommon manifestation of Coccidioides infection resulting from hematogenous spread to the skin. While recurrence after treatment discontinuation has been reported in 17 to 50 percent of cases, associated frequency, timing, and risk factors are not well defined. We conducted a retrospective review of biopsy-proven or probable DCC cases between January 2008 and March 2024, and investigated for evidence of recurrence. Demographic, clinical, and treatment data were abstracted, including antifungal regimen, adherence, immune status, and coccidioidal titers. A total of 45 subjects met the inclusion criteria, including 27 immunocompetent and 18 immunosuppressed patients. Eleven (24.4%) experienced one or more recurrences, totaling 22 recurrences; 19 of these (86.4%) occurred at previously affected sites. Ten immunocompetent patients (37.0%) had 21 total recurrences, while one immunosuppressed patient (5.6%) experienced a single recurrence. Median antifungal-free interval before recurrence was 14 months (range, 1–96), and 10 recurrences (90.9%) occurred while off antifungal therapy. Ten patients underwent initial surgical excision, with four (40.0%) experiencing a total of 11 recurrences afterwards. DCC recurrence was common, mostly among immunocompetent individuals not on suppressive antifungal therapy, and frequently presented with multiple recurrences. Recurrences were almost always at prior lesion sites, often years after treatment discontinuation. Full article

This study explores how the volatility spillover mechanism and dynamic dependence among the founding BRICS equity markets, namely IBOVESPA, MICEX, Nifty 50, SSE, and JSE, have evolved over time using a multivariate DCC-GARCH model. The analysis is conducted across three distinct regimes: the pre-COVID-19 period (1 January 2010 to 10 March 2020), the COVID-19 crisis (11 March 2020 to 23 February 2022), and the Russia–Ukraine war and sanction period (24 February 2022 to 31 March 2024). The findings indicate that, prior to the COVID-19 pandemic, the BRICS equity markets experienced significant short-term volatility spillovers and significant volatility persistence, indicative of slow financial integration, as opposed to rapid contagion. In comparison, the COVID-19 pandemic resulted in significant structural shifts in the form of increased shock transmission, greater co-movement, and evident financial contagion among the markets. During the post-COVID-19 conflict period, while there was considerable persistence in volatility, the primary drivers of volatility spillovers were geopolitical. Across the three sub-periods, the volatility spillover network shows pronounced structural changes. Before COVID-19, IBOVESPA, MICEX, and SSE act as net transmitters, while Nifty 50 and JSE are net receivers. During the COVID-19 crisis, SSE and JSE become the main shock transmitters, whereas IBOVESPA, MICEX, and Nifty 50 shift to receiver roles. In the post-COVID-19 Russia–Ukraine war period, the network becomes more asymmetric, with JSE and Nifty 50 again emerging as net transmitters, while MICEX and SSE function primarily as net receivers. Overall, this study demonstrates that BRICS equity market interdependence is regime-specific and greatly dependent on exogenous global events. Full article

In this study, we evaluated the returns and return volatility of a Brazilian stablecoin linked to fertilizers during periods preceding its discontinuation. In light of the safe haven literature, we also tested the correlation between this stablecoin and a traditional cryptocurrency, Bitcoin, and modeled its behavior during periods of Bitcoin’s extreme returns. In terms of methodology, we employ GARCH-family models (including DCC-GARCH) to analyze daily data from 1 December 2022 to 16 January 2025. We also employ an analysis using Large Language Models (LLMs), evaluating the stablecoin time series considering the period of its discontinuation. The results indicated that as the discontinuation date approached, the stablecoin exhibited statistically significant lower returns and higher volatility. While the DCC-GARCH indicated no correlation between the assets, we found that the stablecoin’s returns exhibited a negative relationship with Bitcoin’s extreme returns, challenging its potential efficacy as a safe haven. This article offers practical contributions for digital asset investors, indicating that even physically backed stablecoins, designed for stability, are subject to significant volatility, idiosyncratic risks, and potential discontinuation. Full article

Ultra-short-term photovoltaic (PV) power forecasts are vital for secure grid operation as solar penetration rises. We propose a two-stage hybrid framework, WDT–CRMABIL–Fusion. In Stage 1, we apply a three-level discrete wavelet transform to PV power and key meteorological series (shortwave radiation and panel irradiance). We then forecast the approximation and detail sub-series using specialized component predictors: a 1D-CNN with dual residual multi-head attention (feature-wise and time-wise) together with a BiLSTM. In Stage 2, a compact dense fusion network recombines the component forecasts into the final PV power trajectory. We use 5-min data from a PV plant in Milan and evaluate 5-, 10-, and 15-min horizons. The proposed approach outperforms strong baselines (DCC+LSTM, CNN+LSTM, CNN+BiLSTM, CRMABIL direct, and WDT+CRMABIL direct). For the 5-min horizon, it achieves MAE = 1.60 W and RMSE = 4.21 W with $R^2$ = 0.943 and CORR = 0.973, compared with the best benchmark (MAE = 3.87 W; RMSE = 7.89 W). The gains persist across K-means++ weather clusters (rainy/sunny/cloudy) and across seasons. By combining explicit multi-scale decomposition, attention-based sequence learning, and learned fusion, WDT–CRMABIL–Fusion provides accurate and robust ultra-short-term PV forecasts suitable for storage dispatch and reserve scheduling. Full article

Pan-Homophonic events denote fluctuations in stock prices that are triggered by phonetic similarities between event keywords and stock tickers. As a relatively novel and under-researched phenomenon, they mirror a subtle yet influential behavioral deviation within financial markets. Centering on the case of Chuandazhisheng, this study delves into how such events produce dynamic and time-varying impacts on stock prices. A linguistic amplitude segmentation method is devised to discriminate between high- and low-intensity events based on information entropy. To separate pan-homophonic-driven price movements from broader market trends, the Relational Stock Ranking (RSR) model is integrated with a Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) framework to establish an adjusted price benchmark. The empirical analysis reveals a sequential price response: initial moderate fluctuations in the low-amplitude phase often yield to more prominent volatility in the high-amplitude phase. While price surges typically occur within one or two days of the event, they generally revert within approximately three weeks. Moreover, repeated exposures to homo- phonic stimuli seem to attenuate the response, indicating a decaying spillover pattern. These findings contribute to a more profound understanding of the intersection between linguistic cues and market behavior and provide practical insights for investor education, information filtering, and regulatory supervision. Full article

Poly(ethylene oxide) (PEO)-based solid polymer electrolytes typically suffer from limited ionic conductivity at near-room temperature and often require inorganic reinforcement. Halide solid-state electrolytes such as Li₃InCl₆ (LIC) offer fast Li⁺ transport but are moisture-sensitive and typically require pressure-assisted densification. Here, we fabricate a flexible LIC–PEO composite electrolyte via slurry casting in acetonitrile with a small amount of LiPF₆ additive. The free-standing membrane delivers an ionic conductivity of 1.19 mS cm⁻¹ at 35 °C and an electrochemical stability window up to 5.15 V. Compared with pristine LIC, the composite shows improved moisture tolerance, and its conductivity can be recovered by mild heating after exposure. The electrolyte enables stable Li|LIC–PEO|Li cycling for >620 h and supports Li|LIC–PEO|NCM111 cells with capacity retentions of 84.2% after 300 cycles at 0.2 C and 80.6% after 150 cycles at 1.2 C (35 °C). Structural and surface analyses (XRD, SEM/EDX, XPS) elucidate the composite microstructure and interfacial chemistry. Full article

Accurately forecasting the dynamic linkages among carbon, energy, and stock markets is essential for effective risk management and the design of energy transition strategies. This study proposes a BOHB-optimized Multivariable Graph Neural Network (BOHB-MSGNN) framework to forecast dynamic correlations derived from a DCC-GARCH model. Using data from the EU ETS market and related energy and stock markets, we document strong and persistent interconnectedness across markets, with the carbon market exhibiting the closest linkage to natural gas, followed by coal, stocks, and oil. Moreover, the proposed BOHB-MSGNN model significantly outperforms benchmark models in predicting dynamic risk correlations across multiple error metrics, owing to its ability to capture both intra-series and inter-series dependencies. Minimum-variance portfolios based on predicted correlations achieve returns similar to those using realized correlations. Forecasts also suggest a moderate decline in future correlations, highlighting diversification opportunities. These results offer practical implications for portfolio allocation, risk management, and carbon market policy. Full article

Rosuvastatin calcium is a promising lipid-lowering agent and the drug of choice in hyperlipidemia. Conventional solid oral delivery of rosuvastatin is limited by its poor solubility and ultimately poor bioavailability. An attempt was made to fabricate the cocrystals of RSC for enhancing solubility and bioavailability. Cocrystals were prepared by a microwave synthesiser-assisted solvent evaporation technique with multiple cocrystal formers. Rosuvastatin-Ascorbic acid (RSC-AA) cocrystals showed the highest solubility (~5-fold increased) amongst all twenty drug-coformer combination (DCC). RSC-AA cocrystals (1:1 ratio) were further characterized by various analytical techniques like FTIR, DSC and XRD to confirm the formation of cocrystals. RSC-AA cocrystals also showed improved flow properties and compressibility in comparison with pure drug, and it was demonstrated using the SeDeM diagram. RSC-AA cocrystals were further formulated into an immediate-release tablet by implementing experimental optimization. Comparative dissolution study of the cocrystal and pure drug tablet revealed improved dissolution after cocrystallization. RSC-AA cocrystal tablet showed the % drug release of 95.61 ± 3.94 while RSC pure drug showed the drug release of 67.83 ± 3.29. In vivo pharmacokinetic analysis showed significant improvement in systemic availability and cumulative absorption of the drug. The peak plasma concentration (Cmax) for RSC pure drug was 13.924 ± 0.477 μg/mL, while RSC-AA cocrystals showed a peak plasma concentration of 22.464 ± 0.484 μg/mL. Area Under Curve (AUC) of RSC-AA cocrystal was also significantly greater compared to the pure drug. In the stability study analysis, the shelf life was calculated from a graphical method and was found to be around 34.58 months for RSC-AA cocrystal tablets and 19.87 months for RSC pure drug tablets, which indicates improved stability with cocrystallization. Overall, the cocrystallization resulted in significant improvement in dissolution and solubility of RSC. Full article

Edge detection is a fundamental component of vision tasks, yet the fusion stage that combines multi-cue evidence has received limited attention. We explore the use of a family of Choquet-based fusion operators generalised by restricted dissimilarity functions for robust, training-free, single-scale edge detection on the BSDS500 dataset. Local cues are extracted from eight connected neighbours after Gaussian or Gravitational smoothing; ordered samples are aggregated with a fuzzy power measure using three operator families: d-CF, d-XC, and d-CC integrals. Binary edge maps are obtained through non-maximum suppression and Rosin thresholding. Evaluation follows the Bezdek framework for edge detection, utilising the Estrada–Jepson correspondence, and extracts precision, recall, and the F-score. All inferential statistics are restricted to within-family comparisons among our variants. The main results are that gravitational smoothing consistently improves performance, and the best performance is achieved with the absolute-difference restricted dissimilarity under gravitational smoothing. Under Gaussian smoothing, the best performance is obtained with the modulus of the squared difference and with the squared difference of the roots. These findings indicate that restricted-dissimilarity-based Choquet operators, particularly d-CC integrals with gravitational smoothing, form a straightforward and interpretable fusion mechanism, motivating further analysis of component interactions and multi-scale extensions. Full article

This study investigates risk contagion and dependence structures between U.S. and Chinese technology-related stock markets, focusing on the electronics and semiconductor sectors. We employ DCC-GARCH models to capture time-varying correlations and copula models to analyze nonlinear and tail dependencies. To highlight extreme risk dynamics, we extend the analysis to Value-at-Risk (VaR) series derived from a GARCH(1,1)-Skewed-t model. Empirical results reveal three major findings. First, volatility clustering and negative skewness are evident across markets, with extreme downside risks concentrated during the 2015 Chinese stock market crash and the 2020 COVID-19 pandemic. Second, copula results show stronger upper-tail dependence in cross-border broad markets and more symmetric dependence within domestic Chinese markets, while U.S. sectoral linkages exhibit the highest vulnerability during downturns. Third, dynamic copula analysis indicates that downside contagion is episodic and crisis-driven, whereas rebound co-movements are structurally persistent. These findings contribute to understanding systemic vulnerability in global technology markets. They provide insights for investors, regulators, and policymakers on monitoring cross-market contagion and managing systemic risk under stress scenarios. Full article

This paper analyzes the effectiveness of some defensive assets inside global stock portfolios by applying a standard VaR approach to daily data from 2021 to 2024. The 5Y US note is by far the best hedging instrument for single-hedged portfolios, while in multiple-hedged portfolios further VaR reductions are obtained including commodities, utilities, and real estate stocks. Bitcoin’s hedging performance is strongly negative, displaying an average VaR difference of more than two basis points with respect to the best-performing multiple-hedged portfolio in moderately defensive scenarios. This gap implies much higher maximum potential daily losses for Bitcoin’s single-hedged portfolios. Dynamic risk profiles of multiple-hedged portfolios display a smoother pattern than single-hedged portfolios, particularly during turbulent periods corresponding to the start of the Russia–Ukraine war, emphasizing the crucial benefits of higher asset diversification. Full article

This study examined how visual attention to specialty coffee label elements relates to consumers’ stated purchase intention. A total of 105 regular specialty coffee consumers viewed the front and back panels, simultaneously, of six commercially available labels while their eye movements were recorded with an eye tracker. Areas of Interest (AOIs) were defined for the label’s content, and a Normalized Fixation Ratio (NFR; proportional fixation time scaled by AOI area) was calculated. Purchase intention was measured on a seven-point structured scale, and the association between NFR and purchase intention was modeled using Landscape Segmentation Analysis (LSA). Heatmaps showed that central regions of the front and back panels were attentional “hot zones”, particularly when they contained sensory claims, cupping score, origin and traceability, roast level, coffee variety, and the “specialty coffee” designation. In contrast, weight, best-before date, grain or ground, and contact information consistently received little attention. Higher NFR values for sensory and origin-related cues were positively associated with purchase intention; labels that gave these attributes visual prominence achieved the highest intention scores. These findings indicate that consumers prioritize sensory and traceability-related information over technical or administrative cues and that both the content and graphic salience of label elements are critical for driving perceived value and choice. Results provide evidence-based guidance for structuring specialty coffee labels to optimize communication. Full article