Search Results (360)

Remanufacturing in reverse logistics can not only support sustainable development but also provide a tractable way to achieve carbon neutrality. This study evaluates whether an original equipment manufacturer (OEM) should remanufacture outsource or authorize this reverse channel activity in the presence of government subsidies. Additionally, the model considers the equilibrium acquisition quantities, collection rates, prices, and effects of government subsidy under three reverse channel options: centralizing remanufacturing, outsourcing remanufacturing, and authorization remanufacturing. The analysis indicates that (i) a centralized approach with manufacturing and remanufacturing operations under a fixed government subsidy is always in the interest of the supply chain; (ii) that for the profit-maximizing third-party remanufacturer (3PR), the differentials in variable collection costs drive the strategy choice, and that a higher fixed scaling parameter of the collection cost favors outsourcing; and (iii) when the government aspires to reduce environmental effects and subsidy payments, the OEM and government have different reverse channel choice preferences. Surprisingly, profitability and environmental goals align under a high consumer acceptance of the remanufactured product. This paper extends the understanding of the remanufacturing strategy of an OEM and provides new insights on which reverse channel is optimal. Full article

Cartilage damage, particularly in the knee joint, presents a significant challenge in regenerative medicine due to its limited capacity for self-repair. Conventional treatments like microfracture surgery, autologous chondrocyte implantation (ACI), and osteochondral allografts often fall short, particularly in cases of larger defects or degenerative conditions. This has led to a growing interest in tissue engineering approaches that utilize biomaterial scaffolds to support cartilage regeneration. Among the many materials explored, chitosan—a naturally derived polysaccharide—has gained attention for its biocompatibility, biodegradability, and structural resemblance to the extracellular matrix (ECM) of cartilage. Recent advances in scaffold design have focused on modifying chitosan to improve its mechanical properties and enhance its biological performance. These modifications include chemical crosslinking, the incorporation of bioactive molecules, and the development of composite formulations. Such enhancements have allowed chitosan-based scaffolds to better support mesenchymal stem cell (MSC) differentiation into chondrocytes, paving the way for improved regenerative strategies. This review explores the latest progress in chitosan scaffold fabrication, preclinical findings, and the transition toward clinical applications. It also discusses the challenges that need to be addressed, such as mechanical stability, degradation rates, and the successful translation of research into viable therapeutic solutions. Full article

Exchange rate volatility poses significant challenges for emerging markets, influencing trade balances, inflation, and capital flows. South Africa’s Rand is particularly vulnerable to global risk sentiment, gold price fluctuations, and interest rate differentials, yet prior studies often analyse these factors in isolation. This study integrates them within an autoregressive distributed lag framework, using monthly data from 2005 to 2023 to capture both short-term fluctuations and long-term equilibrium effects. The findings confirm that higher global risk sentiment triggers immediate Rand depreciation, driven by capital outflows to safe-haven assets. Conversely, rising gold prices and favourable interest rate differentials stabilise the Rand, strengthening trade balances and attracting capital inflows. These results underscore the interconnected nature of global financial conditions and exchange rate movements. This study highlights the importance of economic diversification, foreign reserve accumulation, and proactive monetary policies in mitigating currency instability in emerging markets. Full article

Background: Differentiating pituitary adenoma (PA) from Rathke’s cleft cyst (RCC) on magnetic resonance imaging (MRI) remains challenging due to overlapping imaging features such as the cystic appearance, and location within the sellar region. A magnetic resonance image compilation (MAGiC) sequence can simultaneously acquire R1 and R2 relaxation rates. This study evaluated the diagnostic performance of MAGiC-driven imaging parameters for distinguishing PA from RCC. Methods: In total, 108 patients (54 each with PA or RCC) who underwent MRI using the MAGiC sequence were included in this study. The R1 and R2 relaxation rates were measured from the regions of interest identified in the MAGiC images. The relaxation rates between the PA and RCC groups were compared and diagnostic performance was assessed. Results: The relaxation rates of PA and RCC differed significantly. PA exhibited lower R1 (0.71 vs. 1.31, p < 0.001) and R2 (13.62 vs. 11.38, p = 0.029) relaxation rates than RCC. The R1 relaxation rate demonstrated superior diagnostic performance, with an area under the curve (AUC) of 0.74 (95% confidence interval [CI]: 0.65–0.82), surpassing the R2 rate (AUC 0.62; 95% CI: 0.52–0.71). The optimal threshold for R1 was determined to be 0.82, which provided a sensitivity of 79.6% and specificity of 74.1% (p < 0.001), whereas the optimal threshold for R2 was 14.89 (p = 0.030). Conclusions: MAGiC-driven parameters, particularly the R1 relaxation rate, show promise for improving the differentiation between PA and RCC. These findings suggest the potential for the broader application of MAGiC imaging in clinical practice to improve diagnostic accuracy. Full article

Adaptive radiations are characterized by increases in rates of lineage and trait evolution, typically due to the opening of new ecological opportunities such as may follow from dispersal to a new region or the evolution of a trait that allows exploitation of new niches. This results in clades that have accumulated unusually high biological diversity within a relatively short evolutionary timespan and hence the phenomenon has attracted longstanding interest amongst evolutionary biologists. Natricidae is a family of snakes with a primarily Old World distribution but which have colonized the New World on a single occasion. This dispersal event coincides with an increased speciation rate that has led to a species-rich New World clade. Herein, we take a phylogenetic comparative approach to investigate a likely adaptive radiation of New World natricids. We first confirmed previously reported findings of a single origin (providing new ecological opportunity) coinciding with a burst of lineage diversification. We then estimate the rates of evolution for three ecologically important traits (body size and broad categories of diet and habitat) separately for New World and Old World natricids. Of these three traits, our results provide evidence that only transition rates between terrestrial and (semi-)aquatic habitats are higher in the New World clade. Taken together, this supports a scenario of an adaptive radiation in natricids primarily associated with differentiation by habitat as the clade spread across the New World following its arrival there. Considering other adaptive radiations alongside our evidence for Natricidae, we propose the hypothesis that there is a common distinction between spatially constrained ‘island’ adaptive radiations (which often diverge along trophic axes) and continental adaptive radiations, which diverge as the clade spreads across a larger spatial scale and adapts to different habitats. Full article

Botanical insecticides derived from neem (Azadirachta indica A. Juss.) seeds have gained significant interest due to their sustainable characteristics and low environmental impact. However, their use in sericulture remains contentious due to the heightened sensitivity of domesticated silkworms to environmental stressors. This study systematically investigates the toxicodynamic effects of aqueous neem seed extract (ANSE) on fifth instar larvae of Thai multivoltine Bombyx mori L., focusing on larval mortality and carboxylesterase (CarE) enzyme activity in essential detoxification organs. Larvae were exposed to ANSE concentrations ranging from 5 to 50 mg L⁻¹ for up to 72 h. Key findings highlight a pronounced dose- and time-dependent increase in mortality, with an accurately determined LC₅₀ value of 17 mg L⁻¹ at the longest time exposure, accompanied by mortality rates reaching approximately 83% at the highest concentration tested, indicating considerable susceptibility. Additionally, notable and distinct organ-specific responses were observed, with significant inhibition of CarE activity in the midgut contrasting with elevated activities in the fat body and Malpighian tubules. These differential enzymatic responses reveal previously undocumented adaptive detoxification mechanisms. Consequently, the study advocates cautious and regulated application of neem-based insecticides in sericulture, recommending precise management of concentrations and exposure durations according to silkworm strain sensitivities to ensure optimal silk production. Full article

Many researchers focus on improving reproductive health in sows and ensuring successful breeding by accurately identifying the optimal time of ovulation through estrus detection. One promising non-contact technique involves using computer vision to analyze temperature variations in thermal images of the sow’s vulva. However, variations in camera distance during dataset collection can significantly affect the accuracy of this method, as different distances alter the resolution of the region of interest, causing pixel intensity values to represent varying areas and temperatures. This inconsistency hinders the detection of the subtle temperature differences required to distinguish between estrus and non-estrus states. Moreover, failure to maintain a consistent camera distance, along with external factors such as atmospheric conditions and improper calibration, can distort temperature readings, further compromising data accuracy and reliability. Furthermore, without addressing distance variations, the model’s generalizability diminishes, increasing the likelihood of false positives and negatives and ultimately reducing the effectiveness of estrus detection. In our previously proposed methodology for estrus detection in sows, we utilized YOLOv8 for segmentation and keypoint detection, while monocular depth estimation was used for camera calibration. This calibration helps establish a functional relationship between the measurements in the image (such as distances between labia, the clitoris-to-perineum distance, and vulva perimeter) and the depth distance to the camera, enabling accurate adjustments and calibration for our analysis. Estrus classification is performed by comparing new data points with reference datasets using a three-nearest-neighbor voting system. In this paper, we aim to enhance our previous method by incorporating the mean pixel intensity of the region of interest as an additional factor. We propose a detailed four-step methodology coupled with two stages of evaluation. First, we carefully annotate masks around the vulva to calculate its perimeter precisely. Leveraging the advantages of deep learning, we train a model on these annotated images, enabling segmentation using the cutting-edge YOLOv9 algorithm. This segmentation enables the detection of the sow’s vulva, allowing for analysis of its shape and facilitating the calculation of the mean pixel intensity in the region. Crucially, we use monocular depth estimation from the previous method, establishing a functional link between pixel intensity and the distance to the camera, ensuring accuracy in our analysis. We then introduce a classification approach that differentiates between estrus and non-estrus regions based on the mean pixel intensity of the vulva. This classification method involves calculating Euclidean distances between new data points and reference points from two datasets: one for “estrus” and the other for “non-estrus”. The classification process identifies the five closest neighbors from the datasets and applies a majority voting system to determine the label. A new point is classified as “estrus” if the majority of its nearest neighbors are labeled as estrus; otherwise, it is classified as “non-estrus”. This automated approach offers a robust solution for accurate estrus detection. To validate our method, we propose two evaluation stages: first, a quantitative analysis comparing the performance of our new YOLOv9 segmentation model with the older U-Net and YOLOv8 models. Secondly, we assess the classification process by defining a confusion matrix and comparing the results of our previous method, which used the three nearest points, with those of our new model that utilizes five nearest points. This comparison allows us to evaluate the improvements in accuracy and performance achieved with the updated model. The automation of this vital process holds the potential to revolutionize reproductive health management in agriculture, boosting breeding success rates. Through thorough evaluation and experimentation, our research highlights the transformative power of computer vision, pushing forward more advanced practices in the field. Full article

This paper presents a new model of the term structure of interest rates that is based on the continuous Ho–Lee one. In this model, we suggest that the drift and volatility coefficients depend additionally on a generalized inverse Gaussian (GIG) distribution. Analytical expressions for the bond price and its moments are found in the new GIG continuous Ho–Lee model. Also, we compute in this model the prices of European call and put options written on bond. The obtained formulas are determined by the values of the Humbert confluent hypergeometric function of two variables. A numerical experiment shows that the third and fourth moments of the bond prices differentiate substantially in the continuous Ho–Lee and GIG continuous Ho–Lee models. Full article

The synthesis and symbiotic mechanisms of truffle ectomycorrhizae have attracted considerable scientific interest in recent decades. Although previous research has successfully identified the symbiotic partners of truffles (Tuber spp.) and characterized their mature morphological features, the dynamic processes involved in truffle ectomycorrhizal formation remain insufficiently understood. In this study, we established an ectomycorrhizal synthesis system using Castanea mollissima seedlings inoculated with Tuber sinense spore suspensions under controlled greenhouse conditions, followed by an eight-month observation period. To systematically characterize and model the morphological changes during ectomycorrhizal development, we employed an innovative approach integrating resin sectioning with confocal microscopy. Ectomycorrhizal formation was initially observed two months post inoculation, with a colonization rate reaching 24.4 ± 5.3% by the third month. The ectomycorrhizae displayed a distinct color progression from light brown through ochre and finally dark brown, typically manifesting either monopodial or branched structures. Early developmental stages (2–3 months) were characterized by a thin mycelial membrane enveloping the root surface, accompanied by limited hyphal penetration into the root system. By the eighth month, the colonization rate stabilized at 45.2 ± 8.6%, with enhanced organization and density of the fungal mantle and extended Hartig nets reaching the periphery of outer cortical cells. The continuous growth and differentiation of mycorrhizal root tips generated repetitive root architectures, significantly enhancing symbiotic efficiency. These findings provide critical insights into the morphological development and symbiotic effectiveness of truffle ectomycorrhizae while establishing a methodological framework for investigating ectomycorrhizal associations in other economically significant plant–fungal systems. Full article

Background: We analyzed the performance of a multiplex PCR application (Unyvero IAI) in comparison to culture in a cohort of peritonitis patients undergoing peritoneal dialysis or with liver cirrhosis. Methods: We performed a single-center study of 47 patients with clinically suspected peritonitis and compared pathogen detection rates of culture and PCR. The main outcome of interest was a comparison of accuracy and time to final positive result. Results: In the total cohort, the pathogen detection rate in culture was 58.14% versus 34.88% in PCR (p = 0.03). Detection rates of bacteria in peritoneal dialysis patients were even higher by culture (70.83%) but comparably low by PCR (37.50%; p = 0.04). The majority of discordant results were in the Gram-positive spectrum (81.82%). Differential time to final positive result was 37.39 ± 16.75 h. Conclusion: Time gains by using PCR diagnostic have to be weighed against lower detection rates, mainly in Gram-positive infections. Full article

The assessment of cardiac autonomic regulation (CAR) with non-invasive techniques, such as heart rate variability (HRV), might be of practical interest in elite sports, considering its importance in determining training. We studied 117 soccer players (74 male and 43 female) from three First Division European soccer teams. We used a ranked Autonomic Nervous System Index (ANSI, resulting from the combination of multivariate statistical methodologies applied to HRV-derived indices) to assess CAR. We hypothesized that ANSI might differentiate playing positions, considering goalkeepers, defenders, midfielders, and forwards. We also assessed the perception of somatic symptoms and stress. We observed in male athletes that ANSI was significantly greater in males as compared to females (p < 0.001), being higher in midfielders and defenders (p = 0.035), who usually sustain the greatest external load. Interestingly, this result was not observed in female athletes, who, instead, reported a significantly higher perception of somatic symptoms (p = 0.018) and stress (p = 0.049), the latter being particularly high in midfielders and forwards (p = 0.045). This approach might represent a convenient model to study the effects of long-term physical exercise on CAR in soccer, even to unveil possible differences due to sex, different playing positions characterized by distinct exercise routines, or stress perception. Full article

Forecast risk management is central to the financial management process. This study aims to apply Monte Carlo simulation to solve three classic probabilistic paradoxes and discuss their implementation in corporate financial management. The article presents Monte Carlo simulation as an advanced tool for risk management in financial management processes. This method allows for a comprehensive risk analysis of financial forecasts, making it possible to assess potential errors in cash flow forecasts and predict the value of corporate treasury growth under various future scenarios. In the investment decision-making process, Monte Carlo simulation supports the evaluation of the effectiveness of financial projects by calculating the expected net value and identifying the risks associated with investments, allowing more informed decisions to be made in project implementation. The method is used in reducing cash flow volatility, which contributes to lowering the cost of capital and increasing the value of a company. Simulation also enables more accurate liquidity planning, including forecasting cash availability and determining appropriate financial reserves based on probability distributions. Monte Carlo also supports the management of credit and interest rate risk, enabling the simulation of the impact of various economic scenarios on a company’s financial obligations. In the context of strategic planning, the method is an extension of decision tree analysis, where subsequent decisions are made based on the results of earlier ones. Creating probabilistic models based on Monte Carlo simulations makes it possible to take into account random variables and their impact on key financial management indicators, such as free cash flow (FCF). Compared to traditional methods, Monte Carlo simulation offers a more detailed and precise approach to risk analysis and decision-making, providing companies with vital information for financial management under uncertainty. This article emphasizes that the use of Monte Carlo simulation in financial management not only enhances the effectiveness of risk management, but also supports the long-term growth of corporate value. The entire process of financial management is able to move into the future based on predicting future free cash flows discounted at the cost of capital. We used both numerical and analytical methods to solve veridical paradoxes. Veridical paradoxes are a type of paradox in which the result of the analysis is counterintuitive, but turns out to be true after careful examination. This means that although the initial reasoning may lead to a wrong conclusion, a correct mathematical or logical analysis confirms the correctness of the results. An example is Monty Hall’s problem, where the intuitive answer suggests an equal probability of success, while probabilistic analysis shows that changing the decision increases the chances of winning. We used Monte Carlo simulation as the numerical method. The following analytical methods were used: conditional probability, Bayes’ rule and Bayes’ rule with multiple conditions. We solved truth-type paradoxes and discovered why the Monty Hall problem was so widely discussed in the 1990s. We differentiated Monty Hall problems using different numbers of doors and prizes. Full article

We build on the literature of consumer debt–income inequality nexus, by developing a post-Keynesian model of growth and income distribution that incorporates both consumer and corporate borrowing. Specifically, we examine a non-linear dynamic system of three differential equations of workers’ debt-to-capital ratio, corporate debt-to-capital ratio, and the accumulation rate. We conduct simulations to solve the system for the long-run equilibrium points and examine local stability using the Routh–Hurwitz conditions. Additionally, we conduct a comparative statics analysis and investigate the stability of the model using a measure of the maximum distance among the three equilibrium points. Our key findings suggest that although our model shares several quantitative and qualitative aspects with the 2 × 2 models, the inclusion of corporate debt alters the impact of parameter changes on macroeconomic stability. This incorporation increases the number of parameters that have differing effects on stability across various scenarios. The ratio of external-to-internal borrowing, along with the interest rate, is among the few parameters that consistently undermines macroeconomic stability across all scenarios. Full article

In the present work, the application of lignin (LIG) as a bioactive additive for the preparation of drug-loaded tablets by direct compression has been studied, and its influence on the release of chlorzoxazone (CLZ) from the hydrophilic matrices has been followed. In hydrophilic matrices, the excipients Kollidon^® SR (KOL) and chitosan (CHT) have been used in various amounts and tested in the preparation of 500 mg tablets. They were used as matrix-forming agents, and their influence on the flow and the compressibility properties as well as their effect on the pharmaco-chemical characteristics of the matrix tablets have been studied. Based on the initial evaluation of the pharmaco-technical analysis, pharmaco-chemical characteristics, and in vitro release profile, three matrix tablet formulations (FLa, FLb, and FLc) were selected and further tested. They were evaluated through Fourier-transform infrared spectrometry (FTIR), X-ray diffraction (XRD), thermogravimetry (TG), differential scanning calorimetry (DSC), and in vitro dissolution tests. The three formulations were comparatively studied regarding the release kinetics of active substances using in vitro release testing. The in vitro kinetic study reveals a complex release mechanism occurring in two steps of drug release. The first one is a burst effect that occurs within the first 0–2 h, involving a rapid release of the majority of the drug in a short time, followed by the second step as a prolonged release of the drug, which is relatively constant with a fixed rate over the next 2–36 h. Two factors have been calculated to assess the release profile of chlorzoxazone: f1—the similarity factor and f2—the difference factor together with the correlation coefficient R². Comparing their values, the three optimal formulations have been selected, containing 55 mg LIG (FLa), 60 mg LIG (FLb), or 65 mg LIG (FLc), confirming that LIG next to KOL and CHT influenced the release characteristics of the matrix tablets. Due to the presence of lignin in the matrix of the three formulations, FLa, FLb, and FLc tablets with CLZ, the antioxidant activity has improved. The antioxidant activity of FLc was found to be 21.36% ± 1.06 greater than that of FLa and FLb. The tablets FLa, FLb, and FLc also presented higher antimicrobial activity against Staphylococcus aureus, Escherichia coli, Candida albicans, and colistin-resistant Klebsiella spp. The higher the concentration of LIG in the matrix (FLc), the higher the antimicrobial activity. By using LIG, the drug dose could be decreased. It can be concluded that lignin can be used as a multifunctional pharmaceutical bioactive additive/excipient for tablets. Its interesting properties have been proven, and its use as a pharmaceutical active additive should be exploited for different applications. Full article

The Heston-Hull-White (HHW) model is a generalization of the classical Heston approach that incorporates stochastic interest rates, making it a more accurate representation of financial markets. In this work, we investigate a computational procedure via a three-dimensional partial differential equation (PDE) to solve option pricing problems under the HHW framework. We propose a local radial basis function–finite difference (RBF–FD) framework under the integration of a new variant of the multiquadric function for efficiently resolving the model. Our study highlights the error analysis of the proposed weights for the first and second derivatives of a suitable function and demonstrates the effectiveness of the RBF–FD approach for this high-dimensional financial model. Full article