Kombucha is a traditional beverage obtained by the microbial fermentation of tea using a symbiotic culture of bacteria and yeasts. In addition to several documented functional properties, such as anti-inflammatory activity and antioxidant activity, kombucha is often credited with high levels of vitamins, including riboflavin. To our knowledge, the vitamin B2 content in traditionally prepared kombucha has been determined in only two studies, in which the concentration measured by the HPLC technique ranged from 2.2 × 10⁻⁷ to 2.1 × 10⁻⁴ mol dm⁻³. These unexplained differences of three orders of magnitude in the vitamin B2 content prompted us to determine its concentration during the cultivation of kombucha under very similar conditions by spectrofluorimetry. The B2 concentrations during the 10-day fermentation of black tea ranged from 7.6 × 10⁻⁸ to 3.3 × 10⁻⁷ mol dm⁻³. Full article

Urban traffic congestion has become an increasingly serious problem, and the transportation industry is gradually becoming a high-energy-consuming industry. Intelligent Transportation System (ITSs) that integrate technologies such as electronic sensing, data transmission, and intelligent control have emerged as a new approach to fundamentally solving transportation problems. As one of the cores of intelligent transportation systems, multi-vehicle formation technology has the advantage of promoting vehicle information interaction, improving vehicle mobility, and enhancing traffic conditions. Due to the high cost and risk of conducting multi-vehicle formation experiments using real vehicles, experimenting with intelligent vehicles has become a viable option. Based on the leader–follower formation strategy, this study designed an intelligent vehicle formation system using the Arduino platform. It utilizes infrared sensors, ultrasonic sensors, and photoelectric encoders to perceive information about the vehicle fleet and the road. Information is aggregated to the master vehicle through ZigBee communication modules. The controller of the master vehicle applies a PID algorithm, combined with a differential steering model, to solve the speed instructions for each vehicle in the fleet. Motion control instructions are then transmitted to each slave vehicle through ZigBee communication modules, enabling the automatic adjustment of the fleet’s traveling speed and spacing. Additionally, a Bluetooth app has been designed for users to monitor and control the movement status of the fleet dynamically in real time. Experimental verification has shown that this research effectively improves intelligent fleets’ capabilities in environmental perception, intelligent decision-making, collaborative control, and motion execution. It also enhances road traffic efficiency and safety, providing new ideas and methods for the development of autonomous driving technology. Full article

The proliferation of wireless technologies, particularly the advent of 5G networks, has ushered in transformative possibilities for enhancing vehicular communication systems, particularly in the context of autonomous driving. Leveraging sensory data and mapping information downloaded from base stations using I2V links, autonomous vehicles in these networks present the promise of enabling distant perceptual abilities essential to completing various tasks in a dynamic environment. However, the efficient down-link transmission of vehicular network data via base stations, often relying on spectrum sharing, presents a multifaceted challenge. This paper addresses the intricacies of spectrum allocation in vehicular networks, aiming to resolve the thorny issues of cross-station interference and coupling while adapting to the dynamic and evolving characteristics of the vehicular environment. A novel approach is suggested involving the utilization of a multi-agent option-critic reinforcement learning algorithm. This algorithm serves a dual purpose: firstly, it learns the most efficient way to allocate spectrum resources optimally. Secondly, it adapts to the ever-changing dynamics of the environment by learning various policy options tailored to different situations. Moreover, it identifies the conditions under which a switch between these policy options is warranted as the situation evolves. The proposed algorithm is structured in two layers, with the upper layer consisting of policy options that are shared across all agents, and the lower layer comprising intra-option policies executed in a distributed manner. Through experimentation, we showcase the superior spectrum efficiency and communication quality achieved by our approach. Specifically, our approach outperforms the baseline methods in terms of training average reward convergence stability and the transmission success rate. Control-variable experiments also reflect the better adaptability of the proposed method as the environmental conditions change, underscoring the significant potential of the proposed method in aiding successful down-link transmissions in vehicular networks. Full article

Intelligent truck platoons can benefit road transportation due to the short gap and better fuel economy, but they are also subject to dynamic uncertainties and external disturbances. Therefore, this paper develops a novel robust control algorithm for connected truck platoons. By introducing a linearized expression method of platoon error dynamics based on state measurement, the state feedback mechanism combined with a nonsmooth controller for a truck platoon is proposed in the development of the distributed control method. The state-feedback controller can drive the nominal platoon system to the state of second-order consensus, and the nonsmooth controller counterparts the uncertainties and disturbances. The convergence and string stability of the proposed control algorithm are demonstrated both theoretically and experimentally, and the effectiveness and robustness are also verified by simulation tests. Full article

Micro-milling, widely employed across various fields, faces significant challenges due to the small diameter and limited stiffness of its tools, making the process highly susceptible to cutting chatter and premature tool breakage. Ensuring stable and safe cutting processes necessitates the prediction of chatter by considering the tool breakage. Crucially, the modal parameters of the spindle–holder–tool system are important prerequisites for such stability prediction. In this paper, the FRFs of the micro-milling tool are calculated by direct frequency response functions (FRFs) of the micro-milling cutter and cross-FRFs between a point on the shank and one on the tool tip. Additionally, by utilizing a cutting force model specific to micro-milling, the bending stress experienced by the tool is computed, and the tool breakage curve is subsequently determined based on the material’s permissible maximum allowable stress. The FRFs of the micro-milling tool, alongside the tool breakage curve, are then integrated to generate the final stability lobe diagrams (SLDs). The effectiveness and reliability of the proposed methodology are confirmed through a comprehensive series of numerical and experimental validations. Full article

This study investigates the efficacy of a novel low-cost phosphate adsorbent, denoted as SH-CGCS, derived from coal gasification coarse slag (CGCS) via an alkali activation method. SH-CGCS is a mesoporous material with a specific surface area (64 m²/g) approximately six times larger than CGCS (11 m²/g), which enhances its adsorption capacity compared with CGCS. Furthermore, SH-CGCS achieves a phosphate adsorption capacity of 38.5 mg/g in strongly acidic water (pH 3) and demonstrates robust acid resistance, which makes it particularly effective for phosphate removal from acidic wastewater. Results from coexisting anion experiments affirm the good adsorption selectivity of SH-CGCS for phosphate. Moreover, SH-CGCS exhibits proficiency in treating water containing low phosphate concentrations under flowing conditions. The maximum phosphate adsorption capacity of SH-CGCS calculated using the Langmuir model is 23.92 mg/g, surpassing that of other reported adsorbents. Importantly, saturated SH-CGCS can be regenerated and reused, which contributes to its practical applicability. The adsorption mechanisms of SH-CGCS for phosphate involve ligand exchange, inner-sphere complexation, surface precipitation, and electrostatic adsorption. Thus, this study not only enhances the overall utility of CGCS but also presents a simple and efficient method for removing phosphate. Our findings indicate that SH-CGCS holds considerable potential as a phosphate adsorbent, offering a promising solution for wastewater treatment. Full article

Background: The study aimed to characterize patients with leprosy admitted to Fontilles throughout the 20th and 21st centuries, focusing on differences across three periods (I, II, and III). It also explored variables linked to patient survival. Methods: This was a retrospective descriptive study analyzing the medical records of Fontilles patients from 1909 to 2020. It assessed 26 clinical, sociodemographic, and temporal variables (n = 2652). Results: Most patients were male, single, multibacillary (MB), and farmers, from Andalusia and the Valencian Community. The origin of patients shifted over time towards being mostly foreign-born in period III. More than a half were previously admitted and had family members with leprosy. While leprosy reactions decreased over time, neurological symptoms were increasingly diagnosed. The age at onset, admission, and death increased progressively over time. The survival of patients with leprosy at Fontilles depended on the age at admission and the period. Conclusions: Improved knowledge, services, and awareness regarding leprosy led to increased age at onset and more favorable outcomes. The prolonged time between symptom onset and diagnosis indicates that leprosy is still a neglected disease. Although MB forms are more severe, leprosy classification did not significantly impact the survival rates of patients at Fontilles. Full article

In this work, we have studied the microstructure and unusual ferromagnetic behavior in epitaxial tin dioxide (SnO₂) films implanted with 40 keV Co⁺ ions to a high fluence of 1.0 × 10¹⁷ ions/cm² at room or elevated substrate temperatures. The aim was to comprehensively understand the interplay between cobalt implant distribution, crystal defects (such as oxygen vacancies), and magnetic properties of Co-implanted SnO₂ films, which have potential applications in spintronics. We have utilized scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), vibrating sample magnetometry (VSM), differential thermomagnetic analysis (DTMA), and ferromagnetic resonance (FMR) to investigate Co-implanted epitaxial SnO₂ films. The comprehensive experimental investigation shows that the Co ion implantation with high cobalt concentration induces significant changes in the microstructure of SnO₂ films, leading to the appearance of ferromagnetism with the Curie temperature significantly above the room temperature. We also established a strong influence of implantation temperature and subsequent high-temperature annealing in air or under vacuum on the magnetic properties of Co-implanted SnO₂ films. In addition, we report a strong chemical effect of ethanol on the FMR spectra. The obtained results are discussed within the model of two magnetic layers, with different concentrations and valence states of the implanted cobalt, and with a high content of oxygen vacancies. Full article

Partial state of charge (PSOC) is an important use case for lead–acid batteries. Charging times in lead–acid cells and batteries can be variable, and when used in PSOC operation, the manufacturer’s recommended charge times for single-cycle use are not necessarily applicable. Knowing how long charging will take and what the variability in time required is allows for better planning of operations and algorithm creation for battery energy storage system (BESS) manufacturers. This paper details and demonstrates a procedure for identifying the charging time of cells when different charge throughputs occur prior to reaching full charge. The results showed that the charging time in PSOC operations was highly variable when a charge-factor-controlled full-charge procedure was used. Also noted were that higher voltages for the same state of charge were reached as the number of cycles following reaching full charge increased. None of the regimes tested in this paper caused any significant capacity degradation, which demonstrates that PSOC operations can be performed even on cells not specifically designed for them, provided the correct regime is chosen. Full article

This article presents a computer vision-based approach to switching electric locomotive power supplies as the vehicle approaches a railway neutral section. Neutral sections are defined as a phase break in which the objective is to separate two single-phase traction supplies on an overhead railway supply line. This separation prevents flashovers due to high voltages caused by the locomotives shorting both electrical phases. The typical system of switching traction supplies automatically employs the use of electro-mechanical relays and induction magnets. In this paper, an image classification approach is proposed to replace the conventional electro-mechanical system with two unique visual markers that represent the ‘Open’ and ‘Close’ signals to initiate the transition. When the computer vision model detects either marker, the vacuum circuit breakers inside the electrical locomotive will be triggered to their respective positions depending on the identified image. A Histogram of Oriented Gradient technique was implemented for feature extraction during the training phase and a Linear Support Vector Machine algorithm was trained for the target image classification. For the task of image segmentation, the Circular Hough Transform shape detection algorithm was employed to locate the markers in the captured images and provided cartesian plane coordinates for segmenting the Object of Interest. A signal marker classification accuracy of 94% with 75 objects per second was achieved using a Linear Support Vector Machine during the experimental testing phase. Full article

This study focuses on deriving and presenting an infinite series as the analytical solution for transient electroosmotic and pressure-driven flows in microtubes. Such a mathematical presentation of fluid dynamics under simultaneous electric field and pressure gradients leverages governing equations derived from the generalized continuity and momentum equations simplified for laminar and axisymmetric flow. Velocity profile developments, apparent slip-induced flow rates, and shear stress distributions were analyzed by varying values of the ratio of microtube radius to Debye length and the electroosmotic slip velocity. Additionally, the “retarded time” in terms of hydraulic diameter, kinematic viscosity, and slip-induced flow rate was derived. A simpler polynomial series approximation for steady electroosmotic flow is also proposed for engineering convenience. The analytical solutions obtained in this study not only enhance the fundamental understanding of the electroosmotic flow characteristics within microtubes, emphasizing the interplay between electroosmotic and pressure-driven mechanisms, but also serve as a benchmark for validating computational fluid dynamics models for electroosmotic flow simulations in more complex flow domains. Moreover, the analytical approach aids in the parametric analysis, providing deeper insights into the impact of physical parameters on electroosmotic and pressure-driven flow behavior, which is critical for optimizing device performance in practical applications. These findings also offer insightful implications for diagnostic and therapeutic strategies in healthcare, particularly enhancing the capabilities of lab-on-a-chip technologies and paving the way for future research in the development and optimization of microfluidic systems. Full article

This research investigates the influence of national culture, particularly power distance, on firms’ carbon dioxide (CO₂) emissions. Drawing on a large international dataset spanning over a decade, we examine how power distance, agency conflict, and socioeconomic stability interact to shape firms’ emission decisions. Our analysis reveals a significant positive relationship between power distance and firms’ CO₂ emissions, indicating that firms located in countries characterized by higher power distance tend to emit more greenhouse gases (GHGs). Furthermore, we find that agency conflict moderates this relationship, with firms experiencing high levels of debt or paying substantial dividends exhibiting lower emissions in high power distance environments. Additionally, socioeconomic stability attenuates the positive association between power distance and emissions, suggesting that the effectiveness of cultural influences on emission decisions is contingent upon the stability of the societal context. These findings underscore the importance of considering cultural dimensions, agency dynamics, and socioeconomic conditions in understanding corporate environmental behavior. Our research contributes to the literature by providing empirical evidence of the nuanced interplay between national culture, agency conflict, and socioeconomic stability in shaping firms’ emission decisions. Policymakers and practitioners can use these insights to develop more targeted environmental policies and strategies aimed at promoting sustainable development globally. Full article

This research aims to explore the fiscal and public finance viability on climate physical risk externalities cost for building social-economic-environmental sustainability. It analyzes climate physical risk impact on the real business cycle to change the macroeconomic output functions, its regressive cyclic impact alters tax revenue income and public expenditure function; This research also analyzes that the climate physical risk escalates social-economic inequality and change fiscal-financial policy functions, illustrates how the climate damage cost and adaptation cost distorts fiscal-finance cyclical and structural equilibrium function. This research uses binary and multinomial logistic regression analysis, dynamic stochastic general equilibrium method (DSGE) and Bayesian estimation model. Based on the climate disaster compensation scenarios, damage cost and adaptation cost, analyzing the increased public expenditure and reduced revenue income, demonstrates how climate physical risk externalities generate binary regression to financial fiscal equilibrium, trigger structural and cyclical public budgetary deficit and fiscal cliff. This research explores counterfactual balancing measures to compensate the fiscal deficit from climate physical risk: effectively allocating resources and conducting the financial fiscal intervention, building greening fiscal financial system for creating climate fiscal space. Full article

The objective of this research paper is to investigate the association between internal Corporate Governance (CG) mechanisms and stock price volatility in Egypt as an emerging market. The paper investigates the impact of ownership structure and board structure as internal CG mechanisms on stock price volatility. Data are analyzed using a two-way fixed effects model, a one-step dynamic panel data model, and a panel weighted least squares model. The study concluded that ownership concentration has a negative influence on volatility. Interestingly, an inverted U-shaped relationship between the percentage of ownership by the greatest shareholder and volatility is evidenced. Managerial ownership also showed a negative influence on volatility. As for board structure mechanisms, the findings show that both board size and frequency of board meetings negatively influence volatility, whereas board independence has a positive impact. Full article

The stock market, characterised by its complexity and dynamic nature, presents significant challenges for predictive analytics. This research compares the effectiveness of neural network models in predicting the S&P500 index, recognising that a critical component of financial decision making is market volatility. The research examines neural network models such as Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), Artificial Neural Network (ANN), Recurrent Neural Network (RNN), and Gated Recurrent Unit (GRU), taking into account their individual characteristics of pattern recognition, sequential data processing, and handling of nonlinear relationships. These models are analysed using key performance indicators such as the Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and Directional Accuracy, a metric considered essential for prediction in both the training and testing phases of this research. The results show that although each model has its own advantages, the GRU and CNN models perform particularly well according to these metrics. GRU has the lowest error metrics, indicating its robustness in accurate prediction, while CNN has the highest directional accuracy in testing, indicating its efficiency in data processing. This study highlights the potential of combining metrics for neural network models for consideration when making decisions due to the changing dynamics of the stock market. Full article

This study examines the capability of ChatGPT to provide financial advice based on personal finance cases. We first write our own cases and feed them to ChatGPT to get its advice (recommendations) on them. Next, we assess the quality and the validity of ChatGPT’s recommendations on these cases. We find that ChatGPT serves as a suitable starting point, but its recommendations tend to be generic, and they often overlook alternative solutions and viewpoints and priority of recommendations. Overall, our analysis demonstrates the strengths and weaknesses of using ChatGPT in personal finance matters. Further, it serves as a helpful guide to financial advisors, households, and instructors of personal finance who are already using or considering using ChatGPT and want to develop a suitable understanding of the benefits and limitations of this new technology in addressing their professional and personal needs. Full article

Background: The pulmonary artery wedge pressure (PAWP) is regarded as a reliable indicator of left ventricular end-diastolic pressure (LVEDP), but this association is weaker in patients with left-sided heart disease (LHD). We compared morphological differences in cardiac magnetic resonance imaging (CMR) in patients with heart failure (HF) and a reduced left ventricular ejection fraction (LVEF), with or without elevation of PAWP or LVEDP. Methods: We retrospectively identified 121 patients with LVEF < 50% who had undergone right heart catheterization (RHC) and CMR. LVEDP data were available for 75 patients. Results: The mean age of the study sample was 63 ± 14 years, the mean LVEF was 32 ± 10%, and 72% were men. About 53% of the patients had an elevated PAWP (>15 mmHg). In multivariable logistic regression analysis, NT-proBNP, left atrial ejection fraction (LAEF), and LV end-systolic volume index independently predicted an elevated PAWP. Of the 75 patients with available LVEDP data, 79% had an elevated LVEDP, and 70% had concomitant PAWP elevation. By contrast, all but one patient with elevated PAWP and half of the patients with normal PAWP had concomitant LVEDP elevation. The Bland–Altman plot revealed a systematic bias of +5.0 mmHg between LVEDP and PAWP. Notably, LAEF was the only CMR variable that differed significantly between patients with elevated LVEDP and a PAWP ≤ or >15 mmHg. Conclusions: In patients with LVEF < 50%, a normal PAWP did not reliably exclude LHD, and an elevated LVEDP was more frequent than an elevated PAWP. LAEF was the most relevant determinant of an increased PAWP, suggesting that a preserved LAEF in LHD may protect against backward failure into the lungs and the subsequent increase in pulmonary pressure. Full article

The quality of animal feed is increasingly affected by weather conditions, high humidity, and damage to grains, which have led to various mycotoxin-producing moulds. The aim of this study was to determine the effects of the combination of deepoxy-deoxynivalenol and beta-zearalenol on the development of preimplantation bovine embryos, the extent to which the presence of both mycotoxin metabolites affects the development of in vitro cultured bovine embryos, or whether the effect of both toxins enhances embryotoxicity. Ovaries were transported from the abattoir to the laboratory and, after maturation and fertilisation, zygotes were placed in an embryo culture medium (IVC) with different mycotoxin metabolite concentrations diluted in acetonitrile. It was found that the blastocyst rate of cleaved embryos was affected by 1 μL acetonitrile in 400 μL medium (0.25%) compared to the group without acetonitrile. For this reason, it was decided to use acetonitrile as a control group, and the desired mycotoxin metabolite concentrations were diluted in the lowest possible amount of acetonitrile (0.5 μL) that could be accurately added to the study groups. There was no statistical difference when the higher mycotoxin metabolite concentrations were added. Full article

Curcumin is a naturally occurring hydrophobic polyphenolic compound with a rapid metabolism, poor absorption, and low stability, which severely limits its bioavailability. Here, we employed a starch–protein-based nanoparticle approach to improve the curcumin bioavailability. This study focused on synthesizing nanoparticles with a zein “core” and a carboxymethylated short-chain amylose (CSA) “shell” through anti-solvent precipitation for delivering curcumin. The zein@CSA core–shell nanoparticles were extensively characterized for physicochemical properties, structural integrity, ionic stability, in vitro digestibility, and antioxidant activity. Fourier-transform infrared (FTIR) spectroscopy indicates nanoparticle formation through hydrogen-bonding, hydrophobic, and electrostatic interactions between zein and CSA. Zein@CSA core–shell nanoparticles exhibited enhanced stability in NaCl solution. At a zein-to-CSA ratio of 1:1.25, only 15.7% curcumin was released after 90 min of gastric digestion, and 66% was released in the intestine after 240 min, demonstrating a notable sustained release effect. Furthermore, these nanoparticles increased the scavenging capacity of the 1,1-diphenyl-2-picrylhydrazyl (DPPH•) free radical compared to those composed solely of zein and were essentially nontoxic to Caco-2 cells. This research offers valuable insights into curcumin encapsulation and delivery using zein@CSA core–shell nanoparticles. Full article

An eco-friendly approach towards the recovery of value-added extracts from olive tree leaves with the aid of supercritical CO₂ at 30 MPa was carried out. The impact of extraction temperature (35-90 °C) and presence of co-solvents (ethanol, water, and aqueous ethanol) on the total phenolic, flavonoid, and pigment content, as well as oleuropein, hydroxytyrosol, tyrosol, and α-tocopherol content was determined. In addition, the antioxidant activity of extracts from tree leaves using DPPH, ABTS, and CUPRAC assays was investigated. The results of the study showed that the most effective supercritical CO₂ extraction was at 90 °C with an addition of ethanol, which enabled the separation of extract with the highest content of tested compounds. Some of the highest recorded values were for oleuropein 1.9 mg/g, for carotenoids 5.3 mg/g, and for α-tocopherol 2.0 mg/g. Our results are expected to contribute to the efforts towards the valorization of olive leaves as a sustainable source of valuable compounds, and boost local economies as well as the interest of pharmaceutical, food, and cosmetic industries for novel food by-product applications. Full article

Baijiu is a renowned Chinese distilled liquor, notable for its distinctive flavor profile and intricate production process, which prominently involves fermentation and distillation. Ethyl carbamate (EC), a probable human carcinogen, can be potentially formed during these procedures, thus prompting significant health concerns. Consequently, the contamination of EC during Baijiu production has become an increasingly pressing issue. In this study, we developed a rapid and easily operable immunoassay for determining EC in the fermented materials used in Baijiu production. The development of a high-quality antibody specific to EC facilitated a streamlined analytical procedure and heightened method sensitivity. Furthermore, we systematically evaluated other essential parameters. Following optimization, the method achieved an IC₅₀ value of 11.83 μg/kg, with negligible cross-reactivity against EC analogs. The recovery study demonstrated the method’s good accuracy and precision, with mean recovery rates ranging from 86.0% to 105.5% and coefficients of variation all below 10%. To validate the feasibility of the technique, we collected and analyzed 39 samples simultaneously using both the proposed immunoassay and confirmatory gas chromatography–mass spectrometry (GC-MS). A robust correlation was observed between the results obtained from the two methods (R² > 0.99). The detected EC levels ranged from 2.36 μg/kg to 7.08 μg/kg, indicating an increase during the fermentation process. Full article

Chicken egg white (EW) proteins possess various useful techno-functionalities, including foaming, gelling or coagulating, and emulsifying. The gelling property is one of the most important functionalities of EW proteins, affecting their versatile applications in the food and pharmaceutical industries. However, it is challenging to develop high-quality gelled foods and innovative nutraceutical supplements using native EW and its proteins. This review describes the gelling properties of EW proteins. It discusses the development and action mechanism of the physical, chemical, and biological methods and exogenous substances used in the modification of EW gels. Two main applications of EW gels, i.e., gelling agents in foods and gel-type carriers for nutraceutical delivery, are systematically summarized and discussed. In addition, the research and technological gaps between modified EW gels and their applications are highlighted. By reviewing the new modification strategies and application trends of EW gels, this paper provides insights into the development of EW gel-derived products with new and functional features. Full article