Search Results (2,520)

This paper develops a rigorous inferential framework for a class of Gaussian stochastic processes driven by white noise with constant drift, whose temporal evolution is governed by a Caputo fractional derivative of order ${\displaystyle \alpha \in (1/2,1)}$. The model belongs to the family of fractional Volterra processes, where memory is generated by the dynamics themselves rather than by correlated noise. We derive explicit analytical expressions for the mean, variance, and covariance structure of the solution, thereby characterizing in a precise manner how the fractional order ${\displaystyle \alpha }$ governs both variance growth and the strength of temporal dependence. In particular, the process exhibits correlated increments and a power-law variance scaling of order ${\displaystyle t^{2\alpha -1}}$, highlighting the dual role of ${\displaystyle \alpha }$ as a regularity and memory parameter. Building on this structural analysis, we address the statistical problem of estimating the parameter vector ${\displaystyle (\mu ,\sigma ,\alpha )}$ from discrete-time observations. Two complementary procedures are proposed for the estimation of the fractional order: a variance-growth method based on log–log regression of empirical variances, and a wavelet-based estimator exploiting multi-scale scaling properties of the process. For the drift and diffusion parameters ${\displaystyle (\mu ,\sigma )}$, we construct explicit Gaussian pseudo-maximum likelihood estimators derived from the Volterra covariance structure of the increment process. We establish unbiasedness, ${\displaystyle L^2}$-convergence, strong consistency, and asymptotic normality for all estimators. Furthermore, we derive Berry–Esseen type bounds that quantify the rate of convergence toward the Gaussian law, providing sharp distributional approximations in a genuinely fractional and non-Markovian setting. A Monte Carlo study is carried out, using high-resolution Volterra discretizations, large-scale simulation budgets, covariance-structured linear algebra, and multi-scale diagnostic tools. The numerical experiments confirm the theoretical convergence rates, demonstrate the finite-sample reliability of the estimators, and illustrate the sensitivity of the process dynamics to the fractional order ${\displaystyle \alpha }$: smaller values of ${\displaystyle \alpha }$ produce stronger memory effects and higher variability, while values closer to one lead to smoother and more stable trajectories. The proposed methodology unifies statistical inference for long-memory Gaussian processes with fractional differential stochastic dynamics, offering a coherent analytical and computational framework applicable in areas such as quantitative finance, anomalous diffusion in physics, hydrology, and engineering systems with hereditary effects. Full article

Environmental contamination by persistent industrial dyes such as Amido Black demands highly efficient photocatalysts for advanced water treatment. Structural, chemical, and optical strategies based on TiO₂ nanotube engineering are widely explored for this purpose. In this work, highly ordered TiO₂ nanotube arrays were fabricated by electrochemical anodization and subsequently decorated with Pd nanoparticles via potentiostatic electrodeposition (10–300 s), enabling precise control of Pd nanoparticle size and loading. The resulting materials were systematically characterized by SEM, TEM, XRD, XPS, UV–vis DRS, and PL spectroscopy, and their properties were correlated with the photocatalytic degradation of Amido Black under both UV and visible light irradiation. The study reveals a clear size-dependent duality in the role of Pd. For intermediate Pd nanoparticles (≈9 nm, 20 s), Pd behaves predominantly as an electron sink, forming an efficient Schottky junction with anatase TiO₂ that markedly suppresses charge carrier recombination. This configuration yields ≈ 97% Amido Black removal after 120 min of UV irradiation, with an apparent rate constant about three times higher than that of bare TiO₂ nanotubes. In contrast, for ultra-small Pd nanoparticles (≈6 nm, 10 s), interfacial defect states sensitize TiO₂ to visible light, enabling ≈ 65% degradation after 270 min and a rate constant roughly four times higher than that of undecorated nanotubes under visible illumination. At long deposition times (≥150 s), Pd agglomeration leads to enhanced photoluminescence and markedly reduced photocatalytic activity, indicating increased recombination and less effective utilization of photogenerated charges. This provides a practical design rule to rationally tailor Pd–TiO₂ nanotube photocatalysts for targeted UV or visible light applications in dye removal and broader environmental remediation scenarios Full article

In order to investigate the application potential of lightweight agricultural robots utilizing carbon fiber-reinforced polymer (CFRP) as the primary structural material, this study developed a dedicated rubber-tracked chassis tailored for peanut pest and disease monitoring robots. The chassis design is anchored to the widely applied “single ridge with double rows” cultivation pattern in peanut production and incorporates a real-time track tension monitoring mechanism integrated with pressure sensors. The overall structural configuration of the chassis fully conforms to the standard ridge parameters of mechanized peanut planting while fully considering the intrinsic material properties of CFRP. Additionally, a sprocketless drive wheel structure is specifically adopted to realize higher-precision motion control performance. A mathematical model was constructed to quantitatively characterize the tension correlation between the tight side and slack side of the rubber track, as well as the variation law of initial tension influenced by multiple factors including the total mass of the robot platform. With the curb weight of the robot platform set at 45 kg, the theoretical initial tension is calculated to be 24.5 N (equivalent to approximately 2.5 kg, taking the gravitational acceleration g = 9.8 m/s²). The prototype shows potential for maintaining consistent tension, though a mechanical weakness was identified and will be addressed in future work. Performance validation tests show that the chassis maintains stable operation with no sprocket slippage during field visual inspection. Full article

In many situations, the complete microscopic structure of a network is empirically inaccessible and has to be inferred from aggregate information using some probabilistic model. While several network reconstruction methods have been developed in the case of single-layer networks where nodes can be connected only by one type of link, the problem is still largely unexplored in the case of multiplex networks where several interdependent layers, each representing a distinct mode of connection, coexist. Even the most advanced network reconstruction techniques, when applied to each layer separately, may fail in replicating the inter-layer dependencies embodying the essence of multiplex networks. Here we develop a methodology to reconstruct a class of correlated multiplexes which includes, as a specific example that we study in detail, the multiplex network of international trade in different products. Our method starts from virtually any reconstruction model that successfully reproduces a set of desired marginal properties of each layer separately, i.e., node strengths and/or node degrees. It then introduces the minimal dependency structure required to replicate an additional set of higher-order properties, namely the portion of each node’s degree and each node’s strength that is shared and/or reciprocated across pairs of layers. These properties are found to provide empirically robust measures of inter-layer coupling, allowing for an accurate reconstruction of the world trade multiplex network. Our method allows for joint multi-layer connection probabilities to be reliably reconstructed from marginal ones, effectively bridging the gap between single-layer information and global multiplex properties. Full article

Objectives: The reduction in intrinsic capacity significantly impacts the functional abilities of older individuals, and is strongly linked to adverse health consequences. Safeguarding and enhancing an elderly person’s intrinsic capacity can lead to better life quality and improved social well-being. This research seeks to explore the relationships between social engagement, physical activity, and the likelihood of decline in intrinsic capacity among the elderly in China. Methods: Utilizing the CHARLS data from 2015, individuals with incomplete information were removed from our study. Our analysis included a total of 3502 samples. Social participation and physical activity were assessed through self-reported surveys. The evaluation of intrinsic capacity, based on WHO criteria, thoroughly examined participants in five areas: mobility, sensory functions, vitality, mental health and cognitive abilities. The links between social participation, physical activity and intrinsic capacity decline were revealed through logistic regression. Restricted cubic splines (RCS) were employed as a statistical model, exploring the relationships between dose and response. Interaction analysis was used to examine the interaction between social participation and physical activity. Analyses of subgroups facilitated the evaluation of variations based on factors including age, gender, duration of sleep, and chronic disease numbers. Results: In contrast to the low-level group, individuals with moderate to high degrees of social participation (OR = 0.80, p = 0.012; OR = 0.56, p < 0.001) and those with moderate to high levels physical activity (OR = 0.72, p = 0.019; OR = 0.74, p = 0.016) demonstrated a notably lower risk of decline in intrinsic capacities. A negative correlation was identified in a dose-response manner between social participation and the risk of IC decline. A U-shaped relationship was established between physical activity levels and the risk of intrinsic capacity decline. The fully adjusted interaction model showed that no significant interaction was observed between social participation and physical activity (p = 0.778). Furthermore, subgroup analyses showed that these associations remained generally consistent across older adults of different age groups, genders, sleep duration, and numbers of chronic diseases. Conclusions: In order to slow down the deterioration of intrinsic capacity in older adults in China, it may be beneficial to focus on sustaining elevated levels of social participation and engaging in moderate physical activity. Higher levels of social participation are associated with a lower risk of experiencing a decline in intrinsic capacity, whereas both insufficient and excessive physical activity are associated with an increased risk of intrinsic capacity decline. Full article

Gas bubble accumulation and transport play a critical role in the electrochemical performance and reaction uniformity of proton exchange membrane water electrolysis (PEMWE), particularly at high current density. However, the quantitative coupling between bubble coverage and local electrochemical activity remains insufficiently clarified. In this work, a visualization PEMWE combined with a printed circuit board (PCB)-based segmented measurement technique was developed to simultaneously characterize the spatial distributions of bubble coverage and local current density (LCD) under different current densities and operating temperatures. The results showed that both bubble coverage and LCD exhibited pronounced in-plane non-uniformity. The LCD generally displayed lower values in the central region and higher values near the edges, whereas high bubble coverage regions were mainly concentrated in the central and outlet-side areas. As the average current density increased from 0.5 A/cm² to 2.0 A/cm², the LCD range expanded from 0.43 to 0.53 A/cm² to 1.75–2.20 A/cm², while the local bubble coverage increased from 0.24 to 0.34 to 0.86–0.91. A clear negative spatial correlation between bubble coverage and LCD was identified, and this correlation became stronger with increasing current density. Moreover, the correlation exhibited marked spatial dependence, following the E5 > C3 > E1 > A5 > A1 order. Increasing the operating temperature from 50 to 70 °C alleviated the local heterogeneity, but it did not alter the fundamental coupling trend. These results demonstrate that bubble accumulation is a key factor governing current redistribution and local reaction non-uniformity in PEMWE, and they provide guidance for flow field optimization and high current density operation. Full article

Background: Heart failure (HF) is a highly prevalent condition among older adults, with a remarkable rate of re-hospitalization due to exacerbations. Frailty is strongly correlated with negative outcomes and might reveal patients in need of tailored follow-up. The aim of the study is to evaluate the predictive role of frailty in long-term re-hospitalization risk. Methods: In this prospective study, older adults hospitalized in an acute geriatric ward due to HF were included. Frailty was assessed at admission time by hospital frailty risk score (HFRS). Any hospital readmission was investigated up to one year after discharge. Patients were divided into tertiles upon receiving their HFRS, and readmission risk was evaluated by Cox regression models. Results: Among 213 patients (mean age 86 ± 7 years, 98, 46% male), 155 were frail according to HFRS. A total of 117 subjects were readmitted to hospital within one year after discharge. A Cox regression model showed that, even after adjustment for multiple selected variables, there was a significant increasing trend in the readmission risk across HFRS tertiles: compared with the lowest tertile, patients in the middle tertile had an risk of readmission of 1.29 (95% C.I.: 1.03–1.61), while those in the highest tertile showed a further 1.29 increase. Conclusions: Among patients with HF, long-term re-hospitalizations might be largely influenced by a previous state of frailty. HFRS is a feasible and broadly applicable tool that could be included in routine clinical practice to promptly identify heart failure patients at higher risk of readmission, in order to plan tailored assistance measures. Full article

Triazine herbicides are widely used for weed control in agricultural systems, and their occurrence in water bodies has been frequently reported worldwide. This study assessed the efficiency of a hydrochar derived from the epicarp and mesocarp of passion fruit residues for the removal of three triazine herbicides (atrazine, ametryn, and metribuzin), with the aim of developing a material suitable for application in water remediation programs. The adsorption capacity of biomass and hydrochar derived from passion fruit residues was evaluated with and without activation using 0.5 mol L⁻¹ phosphoric acid. The adsorption of herbicides was not significantly affected by pH within the range of 4 to 8. The acid hydrochar, which exhibited the highest removal capacity among the evaluated adsorbents, presented adsorption capacities of 18.05, 10.83, and 5.05 µg g⁻¹ for atrazine, ametryn, and metribuzin, respectively. These values correspond to removal efficiencies of approximately 62%, 72%, and 52% at initial concentrations of 0.33, 0.25, and 0.15 mg L⁻¹. The adsorption equilibrium time varied among the herbicides, reaching 4 h for atrazine and ametryn and 5 h for metribuzin. The adsorption dynamics between the adsorbents and adsorbates were best described by the pseudo-second-order kinetic model for ametryn and metribuzin, while atrazine had a higher correlation with the Elovich equation. The Weber–Morris model did not adequately describe the adsorption process. Among the isotherms tested, the Freundlich model provided the best fit for all three herbicides. The desorption rates of the acid hydrochar were 51%, 13%, and 83% for atrazine, ametryn, and metribuzin, respectively. Therefore, hydrochar derived from passion fruit residues represents a promising alternative for the remediation of triazine herbicides. Full article

Steroid hormones (SHs) have a high estrogenic potential, and urban wastewater is one of their main ways into the aquatic environment. Constructed wetlands (CWs) are considered one of the most sustainable alternatives for the treatment of wastewater from small communities. However, the use of gravel and sand implies a significant environmental impact associated with their extraction and transport. A more sustainable alternative is the use of plant residues, as they are abundant, inexpensive, and readily available, and they can improve the efficiency of hormone removal through sorption. Thus, the sorption of 15 SHs was studied on conventional, mineral substrates (gravel, sand, and volcanic ash) and alternative vegetal wastes, i.e., mulches from giant reed, palm tree, balsa wood, and pine needles. These materials were characterized by determining their Point of Zero Charge (pH_PZC), ash content, content of leachable polycyclic aromatic hydrocarbons (PAH) and heavy metals, total surface area (BET), and pore characteristics. Results indicated that SH sorption on the mineral substrates was quite low, in most cases less than 10–15%. However, in the mulches it reached between 50 and 95%, except for corticosteroids (11–43%). The pseudo-second-order kinetics provided the best fit in all cases, with R² values between 0.97 and 0.9999. Experiments with a contact time of 7 days showed that the palm tree was the only substrate that completely removed the three corticosteroids studied (cortisone, prednisone, and prednisolone). Additionally, a significant correlation was observed between removal due to sorption (%) and log octanol–water partition coefficient (log Kow). Freundlich isotherm provided a higher number of best fits than Langmuir. Lastly, to compare sand with palm mulch under more realistic experimental conditions, four lab-scale CWs (two with palm mulch and two with sand, with/without plants) were studied. The sand-based CWs achieved faster SH percentage removals, while after 24 h, SH mass removals were significantly higher in the palm mulch-based CWs. Full article

This study presents a quantitative investigation of substituent effects on the stability of 1:2 complexes formed between para-substituted 2-phenylbenzimidazole ligands and Cu(II) or Co(II) ions. The ligands, featuring hydroxyl (–OH), chloro (–Cl), and nitro (–NO₂) substituents, were synthesized via copper acetate-mediated oxidative cyclization. Stability constants (log K) were determined spectrophotometrically using both the Benesi–Hildebrand and Job methods, which yielded perfectly consistent results and confirmed ML₂ stoichiometry. For both metal series, the stability decreases in the order –OH > –Cl > –NO₂. Excellent linear correlations were obtained between log K and Hammett σ constants, yielding reaction constants of ρ = −0.79 for Cu(II) and ρ = −1.00 for Co(II). These negative ρ values confirm that electron-donating substituents enhance complex stability by increasing electron density on the donor nitrogen. Furthermore, the stability constants for Cu(II) complexes are approximately two orders of magnitude higher than those for Co(II), in agreement with the Irving–Williams series. This work establishes a clear, predictive structure–stability relationship and validates the combined methodological approach for quantifying metal–ligand interactions in tunable benzimidazole systems. Full article

Background: Recent data show that approximately 3.8% of the global population has a diagnosis of depression. Understanding psychological risk and protective factors is crucial for improving prevention strategies and mental health interventions. Among these, worry and emotional intelligence (EI) have emerged as relevant, yet they are rarely studied together. To date, no studies that analyzed the relationship between emotional intelligence, worry, and depression have been found. Therefore, this study aims to investigate the association among EI, worry, and depression. Methods: This study included 924 participants (N = 806 non-clinical and N = 118 subclinical sample with elevated depressive symptoms), with a mean age of M = 25.55 years (SD = 11.38). A total of 118 participants (12.8%) met the criteria for clinical depression based on the BDI-II cut-off. All participants completed the Penn State Worry Questionnaire, the Beck Depression Inventory-II, and the Emotional Intelligence Scale. To examine the relationships among all variables examined, zero-order correlation coefficients were calculated. To investigate the predictive power of EI and worry on depression, Bayesian linear regression was conducted. Results: The results showed significant and positive correlations between worry and depression in both samples. EI showed significant and negative correlations with both depression and worry in both the subclinical sample with elevated depressive symptoms and the non-clinical sample. Finally, worry emerged as the strongest contributor to the somatic dimension of depression in both groups. In the subclinical sample with elevated depressive symptoms, age and Evaluation and Expression of Emotion to Self, along with worry, were the best predictors of somatic symptoms. Conclusions: Our data suggest that higher worry levels are associated with higher levels of depressive symptoms, whereas higher EI was negatively associated with depressive symptoms and may play a potential buffering role. Training programs designed to enhance EI could help mitigate the impact of negative events, improve problem-solving skills, and enhance the expression of one’s own emotions. Full article

Background and Objectives: Sclerostin or dickkopf-1 (DKK1) inhibits the canonical Wnt/β-catenin signaling pathway, which regulates vascular calcification and may contribute to the development of arterial stiffness. The brachial–ankle pulse wave velocity (baPWV) measures peripheral arterial stiffness (PAS). This study aimed to investigate the correlation between sclerostin and DKK1 levels and PAS in patients with type 2 diabetes mellitus (T2DM). Materials and Methods: Biochemical data and sclerostin and DKK1 levels were analyzed in the fasting blood samples of 125 patients with T2DM. baPWV measurements using the VaSera VS-1000 automatic pulse wave analyzer classified patients with values > 18.0 m/s on either side into the PAS group. Results: Among patients with T2DM, 47 (37.6%) were classified as having PAS. These patients exhibited higher hypertension prevalence (p = 0.002); greater age (p < 0.001); elevated systolic (p < 0.001) and diastolic blood (p = 0.012) pressures; and increased fasting glucose (p = 0.001), glycated hemoglobin (p = 0.008), triglyceride (p = 0.001), blood urea nitrogen (p < 0.001), and creatinine (p = 0.001) levels, urine albumin-to-creatinine ratio (p = 0.039), and C-reactive protein (p = 0.024) and serum sclerostin (p < 0.001) levels, but decreased estimated glomerular filtration rate (p < 0.001). Multivariate logistic regression analysis identified serum sclerostin level (odds ratio, 1.127; 95% confidence interval, 1.058–1.200; p < 0.001) as an independent PAS predictor in patients with T2DM. Serum log-transformed sclerostin levels were positively correlated with left (p = 0.005) and right (p = 0.001) baPWV via Spearman’s rank-order correlation coefficient analysis. Conclusions: Serum sclerostin levels, but not DKK1 levels, are positively correlated with PAS in patients with T2DM. Full article

A comparative study on the effects of mechanical treatment by high-energy ball milling on talc (2:1 layered silicate) and kaolinite (1:1 layer silicate) was performed. Industrial samples of talc and kaolin were characterized by XRF, thermal analysis (DTA and TG), and XRD methods. The XRD analysis evidenced the destruction of the crystalline structures of both talc and kaolinite and accessory minerals in the samples, showing an increase in the amorphous phases and a progressive change to a more disordered structure. It was found that high-energy ball milling resulted in a reduction of 48% of talc at 4 h of grinding, and the reduction increased up to ~80% at 32 h. The mechanical treatment produced a decrease in initial kaolinite content by 25% after 4 h of grinding and a reduction of ~70% after 32 h. It was deduced by this analysis that the structure of kaolinite is more difficult to destroy by high-energy ball milling than the structure of talc under the same experimental milling conditions. The structural alterations in talc and kaolinite were anisotropic, with crystal degradation along [00l], and there was a progressive loss of long-range order; moreover, the crystal dimensions following the c-axis direction became too small to produce coherent diffraction. A decrease in crystal size (coherent diffraction microdomain) was observed by the mechanical treatment, with an increase in microstrains produced by high-energy ball milling. Thus, the crystal size decreased from 280 to 200 Å in talc (direction perpendicular to 002) and from 250 to 210 Å in kaolinite (direction perpendicular to 001) after 16 h of grinding, with an important reduction in crystal size up to a value of 138 Å but only in the case of kaolinite at 80 h of grinding, with talc completely amorphous to X-rays at the same grinding time. Microstrains followed an inverse evolution compared to the crystal size, with an increase in the values obtained by progressive grinding in both talc and kaolinite. The values of microstrains were found to be of the same order for talc and kaolinite, although they were relatively higher for talc since it is associated with a greater degree of structural alteration than kaolinite. The XRD results showed an inverse correlation between both parameters, with their relative values being higher for talc compared with kaolinite. The present study is of basic interest for further investigations into the effects of high-energy ball milling using talc and kaolin as raw materials with reduced particle size, for instance, in the ceramic and paper industries. Full article

Prosocial behavior supports social cohesion and legal order. Drawing on attachment theory and emotional socialization theory, this study examined whether peer attachment promotes prosocial behavior through positive legal emotion, defined as affective identification with and respect for law, and whether social exclusion moderates this pathway. A cross-sectional survey was conducted with 401 Chinese university students. Measures assessed peer attachment, positive legal emotion, social exclusion, and prosocial behavior. Gender and parental education were included as control variables. Correlational and regression analyses were conducted, followed by conditional process modeling using Hayes’ PROCESS Model 60 with 5000 bootstrap resamples to test mediation, moderation, and moderated mediation effects. Peer attachment significantly and positively predicted prosocial behavior. Positive legal emotion partially mediated the relationship between peer attachment and prosocial behavior. Social exclusion significantly moderated the association between peer attachment and positive legal emotion. The indirect effect of peer attachment on prosocial behavior through positive legal emotion became stronger as social exclusion increased. Moderated mediation analyses further confirmed that the indirect effect intensified at higher levels of social exclusion. Positive legal emotion represents an important psychological mechanism linking peer relationships to prosocial outcomes, while social exclusion functions as a key contextual boundary condition. Interventions that strengthen peer support, enhance legal emotional engagement, and reduce social exclusion may promote prosocial and legal socialization among university students and contribute to broader social integration and stability. Full article

Background: Artificial intelligence (AI) is increasingly incorporated into higher education. However, most empirical studies focus on technological adoption or learner satisfaction rather than on how pedagogical design, perceived learning impact, and student experience interact within AI-mediated learning environments. Understanding these relationships is essential to determine whether AI supports higher-order reasoning processes rather than merely increasing technological engagement. Objective: This preliminary study aimed to develop and evaluate a theory-driven AI-mediated pedagogical framework and examine relationships between pedagogical design, perceived learning impact, and student satisfaction in a university learning context. Methods: An observational educational evaluation was conducted during implementation of an AI-mediated instructional framework in an undergraduate physiotherapy course. The full academic cohort (n = 22) completed a 24-item questionnaire assessing seven pedagogical domains on a 5-point Likert scale. Descriptive statistics, Pearson correlations, exploratory regression modeling, and factor analysis were used to examine relationships among domains. Academic performance indicators were summarized descriptively. Results: Students reported high evaluations across all domains (means > 4.5/5). The strongest association with satisfaction was perceived learning impact (r = 0.79, p < 0.001). Moderate correlations were found for usability (r = 0.66), AI content quality (r = 0.61), pedagogical coherence (r = 0.58), critical thinking (r = 0.52), and ethical integration (r = 0.47). Academic pass rates exceeded 90%. Conclusions: Perceived learning impact emerged as the central mechanism linking AI-mediated instructional design to student satisfaction, suggesting that the educational value of AI depends on alignment with cognitively demanding learning processes. Full article