Search Results (5,334)

The application of contagion risk spread modeling within the banking sector is a relatively recent development, emerging as a response to the persistent threat of liquidity risk that has affected financial institutions globally. Liquidity risk is recognized as one of the most destructive financial threats to banks, capable of causing severe and irreparable damage if overlooked or underestimated. This study aims to identify the most effective control strategy for managing financial contagion using a Susceptible–Infected–Recovered (SIR) epidemic model, incorporating time delays in both state and control variables. The proposed strategy seeks to maximize the number of resilient (vulnerable) banks while minimizing the number of infected institutions at risk of bankruptcy. Our goal is to formulate intervention policies that can curtail the propagation of financial contagion and mitigate associated systemic risks. Our model remains a simplification of reality. It does not account for strategic interactions between banks (e.g., panic reactions, network coordination), nor for adaptive regulatory mechanisms. The integration of these aspects will be the subject of future work. We establish the existence of an optimal control strategy and apply Pontryagin’s Maximum Principle to characterize and analyze the control dynamics. To numerically solve the control system, we employ a discretization approach based on forward and backward finite difference approximations. Despite the model’s simplifications, it captures key dynamics relevant to major European banks. Simulations performed using Python 3.12 yield significant results across three distinct scenarios. Notably, in the most severe case (${\alpha }_3=1.0$), the optimal control strategy reduces bankruptcies from 25% to nearly 0% in Spain, and from 12.5% to 0% in France and Germany, demonstrating the effectiveness of timely intervention in containing financial contagion. Full article

This study investigates the use of a local fiber, specifically milkweed that grows in Quebec, Canada, for nonwoven building applications. Milkweed is a natural fiber with an ultra-lightweight hollow structure that provides excellent acoustic and thermal insulation properties. To provide three-dimensional stability to nonwovens, milkweed fibers were blended with a low-melt fiber composed of a polyethylene terephthalate core and a polyolefin sheath (LM 2.2), and polylactic acid (PLA) fibers. Several nonwovens with different fiber contents were manufactured using an air-laid Spike process. The nonwovens were compared with a commercially available thermal insulation material made of 100% hemp. The thermal conductivity and thermal resistance were measured at different temperatures. The sound absorption coefficient of the nonwovens was determined both using an impedance tube and the Johnson–Champoux–Allard (JCA) acoustic model. The results showed that all nonwovens exhibit thermal conductivity values below 70 mW/m·K at temperatures ranging from −4 °C to 24 °C, which are lower than many materials commonly used in building applications. A sample presented a thermal resistance that is 8%, 10%, and 45% higher than those of rock wool, polyisocyanurate (PIR), and fiberglass, respectively. Full article

Game theory problems have a wide array of applications and intricate structures. Because of this, there are different types of solution concepts available in the literature. In this work, strong Nash equilibria (a type of solution to game theoretic problems that extends Nash equilibria) are explored. Some new sufficient conditions for the existence of said solutions are put forth. An algorithm is also provided that, when convergent, will lead to a strong Nash equilibrium. Some tests to determine the practical efficiency of the algorithm are included. Full article

After delivering my Keynote address to the young scientists at the International Gap Junction meeting, “International Colloquium on Gap Junctions and Cancer: Discussing how cellular communication modifies carcinogenesis and cancer treatment outcomes” (San Paulo, Brazil, 10–14 July 2023), I was asked to condense the talk into a manuscript covering the 50+ years of my scientific journey of basic biomedical research. While this journey had to omit so many important experiences, people and external events, I have tried to illustrate how my initial motivation, personal perspective of my abilities, and naïve goal as a young scientist did not prepare me for the non-linear path to where I ended. That path had many twists, turns, barriers, disappointments, surprises and wrong directions, as well as associations with co-workers, students and collaborators who afforded me with great wisdom, support and technical advice. In the history of science, few individuals have left their footprints in a straight path; however, my early education in human evolutionary genetics provided me a strong background framework, on which multiple other acquired disciplines, forced by circumstances along my uneven journey, allowed me to grow intellectually, as well as making me aware of my limitations. As my late mentor, Dr. Van Rensselaer Potter said: “… humility with responsibility”. At the completion of my experimental journey, I continued to reflect on the implied meanings of my and others’ results to view the current state of collected knowledge on global health issues as one of all scientists’ obligations, namely, to weigh the value and bioethical implications of our work to global society. “ Full article

According to a recent experimental phenomenology–information processing theory, the sensory strength, or vividness, of visual mental images self-reported by human observers reflects the intensive variation in subjective time duration during the process of generation of said mental imagery. The primary objective of this study was to test the hypothesis that a biologically plausible essential multilayer perceptron (MLP) architecture can validly map the phenomenological categories of subjective time duration onto levels of subjectively self-reported vividness. A secondary objective was to explore whether this type of neural network cognitive modeling approach can give insight into plausible underlying large-scale brain dynamics. To achieve these objectives, vividness self-reports and reaction times from a previously collected database were reanalyzed using multilayered perceptron network models. The input layer consisted of six levels representing vividness self-reports and a reaction time cofactor. A single hidden layer consisted of three nodes representing the salience, task positive, and default mode networks. The output layer consisted of five levels representing Vittorio Benussi’s subjective time categories. Across different models of networks, Benussi’s subjective time categories (Level 1 = very brief, 2 = brief, 3 = present, 4 = long, 5 = very long) were predicted by visual imagery vividness level 1 (=no image) to 5 (=very vivid) with over 90% success in classification accuracy, precision, recall, and F1-score. This accuracy level was maintained after 5-fold cross validation. Linear regressions, Welch’s t-test for independent coefficients, and Pearson’s correlation analysis were applied to the resulting hidden node weight vectors, obtaining evidence for strong correlation and anticorrelation between nodes. This study successfully mapped Benussi’s five levels of subjective time categories onto the activation patterns of a simple MLP, providing a novel computational framework for experimental phenomenology. Our results revealed structured, complex dynamics between the task positive network (TPN), the default mode network (DMN), and the salience network (SN), suggesting that the neural mechanisms underlying temporal consciousness involve flexible network interactions beyond the traditional triple network model. Full article

The increasing environmental concerns of plastic waste have encouraged more interest in environmentally friendly packaging, but consumer willingness to pay (WTP) for green alternatives in emerging markets such as Saudi Arabia is not fully explored. This research explores the relationship between awareness of sustainability and price sensitivity in determining WTP for green packaging in the Saudi retail market. The study utilizing a mixed method included both a Contingent Valuation Method (CVM) and a Discrete Choice Modeling (DCM). In it, data was gathered and analyzed using a sample of 424 urban consumers in Saudi Arabia’s major cities. The findings of OLS regression indicated awareness of sustainability had a significant, positive effect on WTP, whereas price sensitivity had a negative effect. There was a marginal interaction effect indicating that awareness could overcome price aversion. Logistic regression supported awareness as a dominant factor in binary product choice, although price sensitivity was not significant in the said model. The multinomial logit model also showed that the type of package, environmental labels (more so the “100% recyclable” type), and price had significant effects on consumer preferences. These results indicate that there is acceptance of sustainable packaging by consumers in Saudi Arabia if the product is communicated effectively and priced competitively. Full article

Syringic acid (SYA) is a significant phenolic compound with the potential for various biomedical uses, including uses of its hepatoprotective properties. Doxorubicin (DOX) is a drug used in the treatment of several tumors, but its side effects, particularly hepatotoxicity, limit its effectiveness. This study investigated the therapeutic effects of SYA on DOX-induced hepatic injury in rats. Molecular docking studies were performed using AutoDock Vina. Five groups of Sprague–Dawley rats (eight in each group) were studied. Gp1 was a negative control group; Gps2–5 was administered intraperitoneally (i.p.) with DOX at a dosage of 4 mg/kg once a week for a month; and Gp2 was left as a positive control group. Gps3–5 received oral SYA at doses of 25, 50, or 75 mg/kg/day, respectively, for a month. Histopathological, molecular, and biochemical analyses were conducted one month after the last SYA dosages were given. The findings demonstrated that by reversing biochemical changes and reducing oxidative stress and inflammation, SYA therapy considerably reduced DOX-induced hepatotoxicity in rats. These results implied that SYA may lessen the hepatotoxicity that DOX causes in rats. Full article

M. O’C. Drury and Norman Malcolm both report that Wittgenstein gave them copies of Samuel Johnson’s Prayers and Meditations, a book that he said he valued highly. Given that Wittgenstein’s commentators have mined the ideas of other religious thinkers he admired (Kierkegaard, Tolstoy, and so on) in order to illuminate his ambiguous thinking about religion, it is perhaps strange that this voiced appreciation of Johnson’s prayers has not been further investigated. The purpose of this paper is to correct that neglect. This is done by way of an exploration of the nature and content of Johnson’s prayers, and an analysis of how these prayers reflect the tormented state of Johnson’s mind and his concerns about indolence, death and judgment. Wittgenstein had noted that Malcolm would only like Johnson’s prayers if he looked at them “from the angle from which I see them”, something which in the context of his letter to Malcolm suggests the very “human” quality of these prayers, and their origin in Johnson’s personal struggles. A description of Wittgenstein’s own struggles (which mirror to some extent those of Johnson in their worries about indolence, judgment, and a guilt that requires confession) can then form the background to an understanding, not just of Wittgenstein’s personal spiritual state of mind, but of his philosophical account of religious belief and the turbulent human passions from which religion arises. Significant points of contact are noted between the respective thinking of Wittgenstein and Johnson, suggestive of new avenues of research that might profitably be explored. Full article

Protein-rich foods, such as meats, eggs, nuts, legumes, and dairy foods, can be important sources of micronutrients, especially those micronutrients that tend to be widely under-consumed. The source of dietary protein, animal or plant origin, is therefore a relevant consideration in the transition to healthier and sustainable diets. In this study, 1589 Australian adult diets with higher diet quality and lower environmental impact were isolated from Australian Health Survey data. These diets were primarily differentiated by lower intake of energy-dense/nutrient-poor discretionary foods. These diets were grouped according to the proportion of total protein obtained from animal and plant sources. On average, 55% of protein was from animal sources and 45% was plant derived. As the proportion of animal protein increased, total dietary protein intake also increased, and total energy intake decreased. Diets with between 60 and 80% of protein from animal sources met the greatest number of Estimated Average Requirements (EARs). Furthermore, diets with this ratio of animal protein were closest to benchmarks when assessed as a proportion of EAR met. That said, across all identified “sustainable healthy diets”, calcium, vitamins B6 and A, zinc, and magnesium were at risk of inadequate intake. This evidence suggests that a diet with around 60–80% of total protein coming from animal sources can reduce the risks of inadequate intake of micronutrients in a sustainable diet. Full article

This article proposes a standard protocol to produce bacterial nanocellulose (Komagateibacter medellinensis). It will briefly review the main raw materials (common agro-industrial waste in tropical countries), process of obtaining bacterial nanocellulose membranes, and the cleaning process for said membranes. The processing of the membranes using a grinder and Ultra-Turrax is then shown, listing the characteristics provided by each of these methods to produce bacterial nanocellulose microparticles by spray drying. The average microparticle size obtained by spray drying was (4.76 ± 1.12 µm), and thermal stability (maximum degradation temperature) was 345 °C. This research clearly states that the grinder was selected as the most efficient mechanical method due to its improved dispersion performance and lower clogging during spray drying. Finally, physical (scanning electron microscopy-SEM, transmission electron microscopy-TEM, and thermogravimetric analyzer-TGA) and microbiological (mesophiles, yeasts, fungi, and fecal coliforms) characterization is demonstrated. These microparticles are intended to be used in the food industry to produce functional and enriched foods, protecting the bioactive components of interest. Full article

This study evaluates the structural properties and adsorption capacities of four bio-based adsorbents, sawdust (SD), straw (ST), chicken feathers (CFs), and shrimp shells (SSs), for chemical oxygen demand (COD) removal from olive mill wastewater (OMW). Response Surface Methodology (RSM) with a Box–Behnken Design (BBD) was applied to optimize the operational parameters, resulting in maximum COD uptake capacities of 450 mg/g (SD), 575 mg/g (ST), 700 mg/g (CFs), and 750 mg/g (SSs). Among these materials, SSs exhibited the highest COD removal efficiency of 85% under optimal conditions (pH 8, 20 g/L, 30 °C, 5 h, 111 rpm). A mixture design approach was then used to explore the synergistic effects of combining lignocellulosic (SD and ST), chitin-based (SSs), and keratin-based (CFs) adsorbents. The optimized blend (SD 10%, ST 28.9%, SS 38.3%, and CF 22.6%) achieved a COD removal efficiency of 82%, demonstrating the advantage of using mixed biopolymer systems over individual adsorbents. Adsorption mechanisms were investigated through isotherm models (Langmuir, Freundlich, Temkin, and Redlich–Peterson) and kinetic models (pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion). Lignocellulosic adsorbents predominantly followed physisorption mechanisms, while chitin- and keratin-rich materials exhibited a combination of physisorption and chemisorption. Thermodynamic analysis confirmed the spontaneous nature of the adsorption process, with SSs showing the most favorable Gibbs free energy (ΔG = −21.29 kJ/mol). A proposed mechanism for the adsorption of organic compounds onto the bio-adsorbents involves hydrogen bonding, electrostatic interactions, π–π interactions, n–π stacking interactions, hydrophobic interactions, and van der Waals forces. These findings highlight the potential of biopolymer-based adsorbents and their optimized combinations as cost-effective and sustainable solutions for OMW treatment. Full article

Semi-natural grasslands are key biodiversity reservoirs in Mediterranean mountain ecosystems. Grazing pressure may significantly influence plant communities and soil conditions, with potential effects on ecosystem functioning. This study evaluated the impact of grazing intensity on floristic diversity, community structure, and soil physico-chemical and microbiological properties across eight grasslands in the Jbel Bouhachem massif (northern Morocco). Species richness, Shannon diversity, and floristic composition were assessed using PERMANOVA and NMDS ordination. Soil parameters and microbial groups were analyzed through laboratory measurements, with statistical comparisons based on Wilcoxon and t-tests. No significant differences were found in species richness or alpha diversity between grazing intensities, although floristic dispersion was higher under intensive grazing. Soil texture, potassium, iron, zinc, and electrical conductivity differed significantly between treatments. Among microbial groups, only yeasts and molds showed higher abundance under intensive grazing, while sulfite-reducing clostridia were exclusively detected in these plots. These results suggest that grazing intensity has a selective impact on soil properties and microbial communities, while plant diversity remains relatively stable. Full article

Background: Accurate assessment of drug cytotoxicity in vitro is essential for preclinical evaluation of anticancer agents. Methodological parameters such as cell density and solvent concentrations can significantly influence the reproducibility and reliability of cell-based assay results. Objective: This study aims to optimize cell seeding density and evaluate the cytotoxic effects of common solvents (DMSO and ethanol) on different cancer cell lines, complemented by in silico analysis to elucidate underlying mechanisms. Materials and Methods: Six cancer cell lines (HepG2, Huh7, HT29, SW480, MCF-7, and MDA-MB-231) were seeded at different densities to determine the optimal cell seeding number ideal for cell viability assay at 24, 48, and 72 h. The cytotoxicity of DMSO and ethanol was assessed in these cell lines using an MTT assay at multiple time points. In silico docking studies were conducted to investigate the interactions between solvents and key proteins involved in apoptosis, membrane function, and metabolism. Results: A cell density of 2000 cells per well yielded consistent linear viability across cell lines and time points. DMSO at 0.3125% showed minimal cytotoxicity across all cell lines (except MCF-7) and time points; the cytotoxic effect at higher concentrations is variable depending on cell type and exposure duration. Ethanol exhibited rapid and concentration-dependent cytotoxicity, reducing viability by more than 30% at as low as 0.3125% concentration after 24 h. Docking analyses revealed that DMSO binds specifically to apoptotic and membrane proteins, suggesting a role in inducing apoptosis. In contrast, ethanol primarily interacts with metabolic proteins, consistent with its effect on membrane disruption and rapid cell death. Conclusion: DMSO at 0.3125% is a good choice as a solvent since it has low toxicity in most tested cell lines; however, the safe concentration limit is dependent on cell type and exposure duration. Ethanol exhibited higher cytotoxicity, necessitating careful concentration management. The in silico analysis supports these findings, indicating that DMSO interacts with apoptosis-related proteins, whereas ethanol primarily affects metabolic processes. These results highlight the importance of precise cell density optimization and solvents for reliable cytotoxicity assessment in cell-based assays. Full article

Assessing dogs’ quality of life (QoL) pre- and post-adoption is crucial for shelters and rehoming organisations making decisions with far reaching and dire consequences for both dogs and humans. Making these assessments objectively and in a standardized way is important. As a first step to accomplish these two imperative goals, an assessment tool was developed based on the Framework of Dogs’ Needs, a robust model of needs at a species, breed/breed type, and individual levels based on scientific literature and expert opinion. It qualifies dogs’ QoL as a function of how well their needs are met. Because this tool will be used in real world situations, ensuring it is feasible and comprehensible by a non-scientific audience is key. Therefore, the three-step assessment tool was piloted with a dog owner sample (n = 14): a participant-completed questionnaire, an investigator given questionnaire with video chat observations (of the dog and their home environment), and participant recorded videos (of the dog displaying specific behaviours and scenarios). Participants then completed a feedback gathering survey on the entire process. Issues and aspects to change were also noted throughout by the principal investigator. Most issues pertained to the participant recorded videos, particularly regarding recording feasibility. Most participants said the collective time and effort involved in the assessment procedure would not discourage them from participating. Necessary changes were made to the tool based on all feedback and issues noted. It is now ready for usage in a larger project to assess dogs’ QoL throughout the sheltering and rehoming process. Full article

In the field of industrial inspection, image segmentation is a common method for surface inspection, capable of locating and segmenting the appearance defect areas of products. Most existing methods are trained specifically for particular products. The recent SAM (Segment Anything Model) serves as an image segmentation foundation model, capable of achieving zero-shot segmentation through diverse prompts. Nevertheless, SAM’s performance in special downstream tasks is not satisfactory. Additionally, SAM requires prior manual interactions to complete segmentation and post-processing of the segmentation results. This paper proposes SAID (Segment All Industrial Defects) to deal with these issues. The SAID model encodes single-annotated prompt–image pairs into scene embedding via Scene Encoder, achieving automatic segmentation and eliminating the reliance on manual intervention. Meanwhile, SAID’s Feature Alignment and Fusion Module effectively addresses the alignment issue between scene embedding and image embedding. Experimental results demonstrate that SAID outperforms SAM in segmentation capabilities across various industrial scenes. Under the one-shot target scene segmentation task, SAID also improves the mIoU metrics by 5.79 and 0.87 compared to the MSNet and SegGPT, respectively. Full article