With sustainability dominating the industry, recycling the generated waste from different processes is becoming increasingly important. This study focuses on recycling waste generated during aluminum anodizing waste (AAW) in friction material formulations for automotive braking applications. However, before utilization, the waste needs to be pre-treated, which mainly involves drying. Hence, four different industrial drying methods were studied to dry the AAW, and the corresponding characteristics were observed by evaluating its residual humidity and crushability index. The waste powders were further characterized using FT-IR and SEM/EDXS to understand their constituents. The initial analysis showed that the waste subjected to the drying process P2 and P1 with the lowest final humidity fetched the most desirable results, with P1 having the simpler drying procedure. The AAW powders were added in a commercial friction material formulation at 6 and 12 wt.% and subjected to friction, wear, and non-exhaust particulate matter analysis. The worn surfaces were analyzed using SEM/EDXS evaluation to understand the extension and composition of the deposited secondary contact plateaus. It was seen that the 12 wt.% addition of waste processed using the P1 technique provided the most satisfactory friction, wear, and emission characteristics, along with expansive secondary contact plateaus with a good contribution of the waste in its formation. This study showed a good relationship between the processing method and a formulation’s tribological and emission characteristics, thereby paving the way for using this drying method for other waste requiring pre-treatment. Full article

Static waste heat recovery, by means of thermoelectric generator (TEG) modules, constitutes a fast-growing energy harvesting technology on the way towards greener transportation. Many commercial solutions are already available for small internal combustion engine (ICE) vehicles, whereas further development and cost reductions of TEG devices expand their applicability at higher-power transportation means (i.e., ships and aircrafts). In this light, the integration of waste heat recovery based on TEG modules in a shipboard distribution network is studied in this work. Several voltage step-up techniques are considered, whereas the most suitable ones are assessed via the LTspice simulation platform. The design procedure of the selected LLC resonant converter is presented and analyzed in detail. Furthermore, a flexible control strategy is proposed, capable of either output voltage regulation (constant voltage) or maximum power point tracking (MPPT), according to the application demands. Finally, both simulations and experiments (on a suitable laboratory testbench) are performed. The obtained measurements indicate the high efficiency that can be achieved with the LLC converter for a wide operating area as well as the functionality and adequate performance of the control scheme in both operating conditions. Full article

In light of electrical energy’s increasing role in economic systems worldwide, prioritizing investments in sustainable power supplies has become paramount. This study proposes a model based on cloud theory and game theory to evaluate sustainable power supply investment projects. It establishes a foundation for assessing the merits of power supply investments, which are crucial for continuous electricity provision and economic advancement. By integrating an enhanced analytic hierarchy process and the entropy method, the study develops a dual-weighted evaluative index system. This hybrid approach addresses ambiguities and enhances the weight determination accuracy, which, when applied to the Liaojiawan Transformer Substation, verifies the project’s high benefit level, corroborated by empirical data. This innovative methodology offers a strategic framework for future power supply investments. Full article

This review aims to analyze the technological and scientific applications regarding cocoa fermentation through a prospective study of patent documents and research articles. The Espacenet database was used as a patent research tool by searching both the IPC code “A23G1” and the terms “cocoa” and “ferment*”. A total of 130 documents were found—49 were related to the subject. The Scopus database was also searched for scientific articles using the terms “cocoa” and “fermentation”. A total of 812 articles were found—517 were related to the subject. Cocoa fermentation has not yet reached technological maturity, despite the growth in patent documents and scientific research observed in the last two decades. The creation of the Cacao of Excellence Program (2009), among others, has incentivized sustainability and quality in cocoa-producing countries. Brazil, Colombia, and Indonesia are leading with scientific publications in the last 5 years, despite the lack of patents filed. The United Kingdom, France, China, Canada, and Germany, despite not being cocoa-producing countries, are the main holders of the technology. Patent documents analyzed relate to food science, biotechnology, engineering, and chemistry. Microbial biotechnology has gained attention as a key factor to produce a higher-quality cocoa bean. Saccharomyces is the most frequent genus of yeast used as a starter culture in patent documents. Some patent documents propose the addition of fruits during cocoa fermentation, but a few scientific studies have been found on the matter. Overall, technological applications and scientific studies have focused on improving cocoa quality. The cocoa market is expected to increase significantly in the next few years, representing an opportunity to develop high-quality cocoa using novel fermentation techniques. Full article

This research paper presents a comprehensive study on the implementation of photovoltaic (PV) energy systems at Al-Abrar Mosque in Saudi Arabia. The primary objective was to explore optimal regional solar power strategies. By synergistically integrating technical evaluations of the PV system with economic analyses, including the payback period and levelized cost of energy (LCOE), alongside an investigation of net metering and net billing scenarios, we delineated a pathway toward achieving net zero billing for the mosque’s energy requirements. This study examined two scenarios: Scenario I involved net metering, while Scenario II explored net billing. Our theoretical and simulation results, derived from detailed analyses conducted using PVsyst software, unequivocally demonstrated the superiority of net metering for this specific application. With net metering, the mosque’s energy needs can be efficiently met using minimal infrastructure—comprising only 34 photovoltaic modules and a single inverter. In contrast, net billing requires significantly higher resource demands, underscoring the economic and spatial advantages of net metering. Additionally, the payback period for Scenario I is 7.9 years, while for Scenario II, it extends to 87 years. Through rigorous simulations, this study reaffirmed the practicality and feasibility of the net metering approach within the context of Saudi Arabia. Furthermore, our research provides actionable insights for implementing sustainable solutions at specific sites, such as the Al-Abrar Mosque, and contributes to advancing renewable energy knowledge in the region. Full article

The employment of the maritime medium by Southern Levantine societies is examined here through its engagement with coastline facilitation and the building of artificial harbors where natural bays are insufficient or non-existent. The development and availability of technologies and methods are surveyed and analyzed vis-à-vis local choices made to adopt or to reject mediating tools such as jetties, quays, and seawalls. The article discusses technological and conceptual innovations against the background of long-term practices, essentially in favor of natural features. Despite the early adoption of emerging technologies by such exemplars as Iron Age Atlit, Hellenistic Akko-Ptolemaïs, or Roman Caesarea, the rest of the Southern Levant did not join in, and Caesarea, Akko-Ptolemaïs, and Atlit fell short of maintaining their facilities in the long term. The solution for ships was found instead in natural anchorages and, much more dominantly, in the beaching of smaller vessels and offshore anchoring of larger ones. Full article

Deep neural network (DNN) inference demands substantial computing power, resulting in significant energy consumption. A large number of negative output activations in convolution layers are rendered zero due to the invocation of the ReLU activation function. This results in a substantial number of unnecessary computations that consume significant amounts of energy. This paper presents ECHO, an accelerator for DNN inference designed for computation pruning, utilizing an unconventional arithmetic paradigm known as online/most significant digit first (MSDF) arithmetic, which performs computations in a digit-serial manner. The MSDF digit-serial computation of online arithmetic enables overlapped computation of successive operations, leading to substantial performance improvements. The online arithmetic, coupled with a negative output detection scheme, facilitates early and precise recognition of negative outputs. This, in turn, allows for the timely termination of unnecessary computations, resulting in a reduction in energy consumption. The implemented design has been realized on the Xilinx Virtex-7 VU3P FPGA and subjected to a comprehensive evaluation through a rigorous comparative analysis involving widely used performance metrics. The experimental results demonstrate promising power and performance improvements compared to contemporary methods. In particular, the proposed design achieved average improvements in power consumption of up to $81\%$, $82.9\%$, and $40.6\%$ for VGG-16, ResNet-18, and ResNet-50 workloads compared to the conventional bit-serial design, respectively. Furthermore, significant average speedups of $2.39\times$, $2.6\times$, and $2.42\times$ were observed when comparing the proposed design to conventional bit-serial designs for the VGG-16, ResNet-18, and ResNet-50 models, respectively. Full article

Globally, breast cancer is a significant cause of mortality. Recent research focused on identifying compounds regulating the transient receptor potential vanilloid 1 (TRPV1) ion channel activity for the possibility of developing cancer therapeutics. In this study, the antiproliferative properties and mechanisms of action through TRPV1 of Maclura pomifera, a dioecious tree native to the south-central USA, have been investigated. Male and female extracts of spring branch tissues and leaves (500 µg/mL) significantly reduced the viability of MCF-7 and T47D cells by 75–80%. M. pomifera extracts induced apoptosis by triggering intracellular calcium overload via TRPV1. Blocking TRPV1 with the capsazepine antagonist and pretreating cells with the BAPTA-AM chelator boosted cell viability, revealing that M. pomifera phytochemicals activate TRPV1. Both male and female M. pomifera extracts initiated apoptosis through multiple pathways, the mitochondrial, ERK-induced, and endoplasmic reticulum-stress-mediated apoptotic pathways, demonstrated by the expression of activated caspase 3, caspase 9, caspase 8, FADD, FAS, ATF4, and CHOP, the overexpression of phosphorylated PERK and ERK proteins, and the reduction of BCL-2 levels. In addition, AKT and pAKT protein expressions were reduced in female M. pomifera-treated cells, revealing that female plant extract also inhibits PI3K/Akt signaling pathways. These results suggest that phytochemicals in M. pomifera extracts could be promising for developing breast cancer therapeutics. Full article

Common Spatial Pattern (CSP) has been recognized as a standard and powerful method for the identification of Electroencephalography (EEG)-based Motor Imagery (MI) tasks when implementing brain–computer interface (BCI) systems towards the motor rehabilitation of lost movements. The combination of BCI systems with robotic systems, such as upper limb exoskeletons, has proven to be a reliable tool for neuromotor rehabilitation. Therefore, in this study, the effects of temporal and frequency segmentation combined with layer increase for spatial filtering were evaluated, using three variations of the CSP method for the identification of passive movement vs. MI+passive movement. The passive movements were generated using a left upper-limb exoskeleton to assist flexion/extension tasks at two speeds (high—85 rpm and low—30 rpm). Ten healthy subjects were evaluated in two recording sessions using Linear Discriminant Analysis (LDA) as a classifier, and accuracy (ACC) and False Positive Rate (FPR) as metrics. The results allow concluding that the use of temporal, frequency or spatial selective information does not significantly ($p<$ 0.05) improve task identification performance. Furthermore, dynamic temporal segmentation strategies may perform better than static segmentation tasks. The findings of this study are a starting point for the exploration of complex MI tasks and their application to neurorehabilitation, as well as the study of brain effects during exoskeleton-assisted MI tasks. Full article

The goal of this study is to address the challenges associated with identifying and planning a mobile land robot’s path to optimize its speed in a stationary environment. Our focus was on devising routes that navigate around obstacles in various spatial arrangements. To achieve this, we employed MATLAB R2023b for trajectory simulation and optimization. On-board data processing was conducted, while obstacle detection relied on the omnidirectional video processing system integrated into the robot. Odometry was facilitated by engine encoders and optical flow sensors. Additionally, an external video system was utilized to verify the experimental data pertaining to the robot’s movement. Last but not least, the algorithms and hardware equipment used enabled the robot to go along the path at greater speeds. Limiting the amount of time and energy required to travel allowed us to avoid obstacles. Full article

The functional adaptation and underlying molecular mechanisms of hemoglobins (Hbs) have primarily concentrated on mammals and birds, with few reports on reptiles. This study aimed to investigate the convergent and species-specific high-altitude adaptation mechanisms of Hbs in two Eremias lizards from the Qinghai-Tibet Plateau. The Hbs of high-altitude E. argus and E. multiocellata were characterized by significantly high overall and intrinsic Hb-O₂ affinity compared to their low-altitude populations. Despite the similarly low Cl⁻ sensitivities, the Hbs of high-altitude E. argus exhibited higher ATP sensitivity and ATP-dependent Bohr effects than that of E. multiocellata, which could facilitate O₂ unloading in respiring tissues. Eremias lizards Hbs exhibited similarly low temperature sensitivities and relatively high Bohr effects at lower temperatures, which could help to stably deliver and release O₂ to cold extremities at low temperatures. The oxygenation properties of Hbs in high-altitude populations might be attributed to varying ratios of β2/β1 globin and substitutions on the β2-type globin. Notably, the Asn12Ala in lowland E. argus could cause localized destabilization of the E-helix in the tetrameric Hb by elimination of hydrogen bonds, thereby resulting in its lowest O₂ affinity. This study provides a valuable reference for the high-altitude adaptation mechanisms of hemoglobins in reptiles. Full article

This study considers residential segregation as a critical driver of racial/ethnic health disparities and introduces a proxy measure of segregation that estimates the degree of segregation at the census tract level with a metric capturing the overrepresentation of a racialized/ethnic group in a census tract in relation to that group’s representation at the city level. Using Dallas, Texas as a pilot city, the measure is used to investigate mean life expectancy at birth for relatively overrepresented Hispanic, non-Hispanic white, non-Hispanic Black, and Asian census tracts and examine for significant differences between mean life expectancy in relatively overrepresented census tracts and that group’s mean life expectancy at the state level. Multivariable linear regression analysis was utilized to assess how segregation measured at the census tract level associates with life expectancy across different racialized/ethnic groups, controlling for socioeconomic disparities. This study aimed to expose the need to consider the possibility of neighborhood mechanisms beyond socioeconomic characteristics as an important determinant of health and draw attention to the importance of critically engaging the experience of place in examinations of racial and ethnic health disparities. Multivariable linear regression modeling resulted in significant findings for non-Hispanic Black, non-Hispanic white, and Asian groups, indicating increased census tract-level life expectancy for Black and white residents in highly segregated census tracts and decreased life expectancy for residents of tracts in which the Asian community is overrepresented when compared to state means. Unadjusted models demonstrated socioeconomic inequities between first and fourth quartile census tracts and pointed to the importance of mixed methods in health disparities research and the importance of including the voice of community members to account for places of daily lived experience and people’s relationships with them. Full article

This study investigated the impact of storage temperatures (−20 °C, room temperature, and 40 °C) on the sensory evaluation, metabolites, and volatile compounds of green tea stored for 12 months. The sensory evaluation revealed that tea samples stored at −20 °C retained their emerald green colour, tender aroma, and refreshing taste. Green tea biochemical constituents, including water extracts and total free amino acids, were measured by Chinese National Standard Methods (GB/T 8305-2013 and GB/T 8314-2013). Tea polyphenols and flavonoids were determined using spectrophotometric methods, while phytochemicals were detected using validated HPLC, and volatile compounds were detected using validated gas chromatography coupled with triple quadrupole mass spectrometry. The analysis showed that tea polyphenols were highest at −20 °C, and flavonoids were significantly reduced at higher temperatures. A similar trend was observed for amino acids, soluble sugar content, and water extracts. Tea catechins, including (-)-epigallocatechin-3-gallate (EGCG) and (-)-gallocatechin gallate (GCG), were highest at −20 °C, showing their susceptibility to temperature. A volatile compound analysis revealed distinct profiles with variations in the abundance of compounds, such as di-methyl sulfide, phenyl ethyl alcohol, indole, and benzaldehyde. This study identifies temperature-sensitive compounds, providing insights into the mechanisms underlying tea quality deterioration during storage. Full article

This paper reports for the first time on a new layered magnetic heterometallic erbium telluride EuErCuTe₃. Single crystals of the compound were obtained from the elements at 1120 K using CsI as a flux. The crystal structure of EuErCuTe₃ was solved in the space group Cmcm (a = 4.3086(3) Å, b = 14.3093(9) Å, and c = 11.1957(7) Å) with the KZrCuS₃ structure type. In the orthorhombic structure of erbium telluride, distorted octahedra ([ErTe₆]⁹⁻) form two-dimensional layers ($\left\{{\left[\mathrm{E}\mathrm{r}{\left(\mathrm{T}\mathrm{e}1\right)}_{2/2}^e{\left(\mathrm{T}\mathrm{e}2\right)}_{4/2}^k\right]}^{-}\right\})_{\infty }^2$, while distorted tetrahedra ([CuTe₄]⁷⁻) form one-dimensionally connected substructures ($\left\{{\left[\mathrm{C}\mathrm{u}{\left(\mathrm{T}\mathrm{e}1\right)}_{2/2}^e{\left(\mathrm{T}\mathrm{e}2\right)}_{2/1}^t\right]}^{5-}\right\}_{\infty }^1$) along the [100] direction. The distorted octahedra and tetrahedra form parallel two-dimensional layers ($\left\{{\left[\mathrm{C}\mathrm{u}\mathrm{E}\mathrm{r}{\mathrm{T}\mathrm{e}}_3\right]}^{2-}\right\}_{\infty }^2)$ between which Eu²⁺ ions are located in a trigonal-prismatic coordination environment (${\left[{\mathrm{E}\mathrm{u}\mathrm{T}\mathrm{e}}_6\right]}^{10-})$. The trigonal prisms are connected by faces, forming chains ($\left\{{\left[{\mathrm{E}\mathrm{u}\left(\mathrm{T}\mathrm{e}1\right)}_{2/2}{\left(\mathrm{T}\mathrm{e}2\right)}_{4/2}\right]}^{2-}\right\}_{\infty }^1$) along the [100] direction. Regularities in the variations in structural parameters were established in the series of erbium chalcogenides (EuErCuCh₃ (Ch = S, Se, and Te)) and tellurides (EuLnCuTe₃ (Ln = Gd, Er, and Lu)). Ab-initio calculations of the crystal structure, phonon spectrum, and elastic properties of the compound EuErCuTe₃ were performed. The types and wavenumbers of fundamental modes were determined, and the involvement of ions in the IR and Raman modes was assessed. The experimental Raman spectra were interpreted. The telluride EuErCuTe₃ at temperatures below 4.2 K was ferrimagnetic, as were the sulfide and selenide derivatives (EuErCuCh₃ (Ch = S and Se)). Its experimental magnetic characteristics were close to the calculated ones. The decrease in the magnetic phase transition temperature in the series of the erbium chalcogenides was discovered. Full article

In this study, different extraction methods and conditions were used for the extraction of antioxidants from brown macroalgae Fucus spiralis. The extraction methodologies used were ultrasound-assisted extraction (ultrasonic bath and ultrasonic probe), extraction with a vortex, extraction with an Ultra-Turrax^® homogenizer, and high-pressure-assisted extraction. The extracts were analyzed for their total phenolic content (TPC) and their antioxidant activity, and evaluated through the 2,2-difenil-1-picrilhidrazil (DPPH) free radical scavenging method and ferric reducing antioxidant power (FRAP) assay. Ultrasonic probe-assisted extraction yielded the highest values of TPC (94.78–474.16 mg gallic acid equivalents/g extract). Regarding the antioxidant activity, vortex-assisted extraction gave the best DPPH results (IC₅₀ 1.89–16 µg/mL), while the highest FRAP results were obtained using the Ultra-Turrax^® homogenizer (502.16–1188.81 μmol ascorbic acid equivalents/g extract). For each extraction method, response surface methodology was used to analyze the influence of the experimental conditions “extraction time” (t), “biomass/solvent ratio” (R), “solvent” (S, water % in water/ethanol mixture), and “pressure” (P) on TPC, DPPH, and FRAP of the F. spiralis extracts. In general, higher TPC content and higher antioxidant capacity (lower IC₅₀ and higher FRAP) were obtained with higher R, t, and P, and lower S (higher ethanol %). The model regarding the combined effects of independent variables t, R, and S on the FRAP response values for vortex-assisted extractions best fitted the experimental data (R² 0.957), with optimal extraction conditions of t = 300 s, R = 50 g, and S = 25%. Full article

There is a fundamental subsets–partitions duality that runs through the exact sciences. In more concrete terms, it is the duality between elements of a subset and the distinctions of a partition. In more abstract terms, it is the reverse-the-arrows of category theory that provides a major architectonic of mathematics. The paper first develops the duality between the Boolean logic of subsets and the logic of partitions. Then, probability theory and information theory (as based on logical entropy) are shown to start with the quantitative versions of subsets and partitions. Some basic universal mapping properties in the category of $Sets$ are developed that precede the abstract duality of category theory. But by far the main application is to the clarification and interpretation of quantum mechanics. Since classical mechanics illustrates the Boolean worldview of full distinctness, it is natural that quantum mechanics would be based on the indefiniteness of its characteristic superposition states, which is modeled at the set level by partitions (or equivalence relations). This approach to interpreting quantum mechanics is not a jury-rigged or ad hoc attempt at the interpretation of quantum mechanics but is a natural application of the fundamental duality running throughout the exact sciences. Full article

Background: Risk assessment is the process of collecting information towards the goal of protecting the physical and psychological integrity of the victim, taking into account factors associated with violence to assess the severity of violence, protect victims, and prevent recidivism. This type of risk assessment is commonly used in situations of domestic violence and needs to be adjusted for the contexts of child and adolescent victimization. Objective: Resources and standardized criteria to guide a child-centered domestic violence victimization risk assessment are lacking. This systematic review aimed to evaluate the instruments, risk factors and outcomes identified in the literature for situations of domestic violence involving children. Methods: Following the PRISMA protocol, 313 articles from the EBSCO, Web of Science and PubMed databases were screened and 13 were identified for analysis. Results: An analysis of the characteristics of some instruments created to assess the impact of domestic violence involving children shows that caregivers’ risk factors are strong predictors of child abuse, highlighting the interrelationship with other factors, as well as warning about the cumulative risk, including child homicide. Conclusions: The literature confirms the importance of family system factors regarding the risk of the mistreatment of children in situations of domestic violence. Risk assessment must cater to the needs and specificities of individual children. Full article

Most mainstream statistical models will achieve poor performance in Out-Of-Distribution (OOD) generalization. This is because these models tend to learn the spurious correlation between data and will collapse when the domain shift exists. If we want artificial intelligence (AI) to make great strides in real life, the current focus needs to be shifted to the OOD problem of deep learning models to explore the generalization ability under unknown environments. Domain generalization (DG) focusing on OOD generalization is proposed, which is able to transfer the knowledge extracted from multiple source domains to the unseen target domain. We are inspired by intuitive thinking about human intelligence relying on causality. Unlike relying on plain probability correlations, we apply a novel causal perspective to DG, which can improve the OOD generalization ability of the trained model by mining the invariant causal mechanism. Firstly, we construct the inclusive causal graph for most DG tasks through stepwise causal analysis based on the data generation process in the natural environment and introduce the reasonable Structural Causal Model (SCM). Secondly, based on counterfactual inference, causal semantic representation learning with domain intervention (CSRDN) is proposed to train a robust model. In this regard, we generate counterfactual representations for different domain interventions, which can help the model learn causal semantics and develop generalization capacity. At the same time, we seek the Pareto optimal solution in the optimization process based on the loss function to obtain a more advanced training model. Extensive experimental results of Rotated MNIST and PACS as well as VLCS datasets verify the effectiveness of the proposed CSRDN. The proposed method can integrate causal inference into domain generalization by enhancing interpretability and applicability and brings a boost to challenging OOD generalization problems. Full article

Supervised discretisation is widely considered as far more advantageous than unsupervised transformation of attributes, because it helps to preserve the informative content of a variable, which is useful in classification. After discretisation, based on employed criteria, some attributes can be found irrelevant, and all their values can be represented in a discrete domain by a single interval. In consequence, such attributes are removed from considerations, and no knowledge is mined from them. The paper presents research focused on extended transformations of attribute values, thus combining supervised with unsupervised discretisation strategies. For all variables with single intervals returned from supervised algorithms, the ranges of values were transformed by unsupervised methods with varying numbers of bins. Resulting variants of the data were subjected to selected data mining techniques, and the performance of a group of classifiers was evaluated and compared. The experiments were performed on a stylometric task of authorship attribution. Full article

In this study, a new method of obtaining photoactive cements is presented. The goal was to obtain photoactive cements using a method that could reduce the production costs. In the study, an intermediate product from the production of titanium dioxide using the sulfate method, taken from the installation before the calcination process, was used to obtain photoactive cements. Laboratory conditions corresponding to introducing this amorphous TiO₂ into cement clinker during its cooling were simulated. The study shows that the temperature from 300 to 800 °C and the time of amorphous TiO₂ contact with the cement clinker within 30 min is sufficient to obtain a photoactive cement. The highest photocatalytic activity was obtained for the material with 5 wt.% TiO₂ content, and the method used did not cause a significant decrease in the bending and compressive strength of the new photoactive cements. The obtained materials were characterized by determining the crystal size of the TiO₂, the sulfur content and the photocatalytic activity during NO decomposition under UV radiation. The bending and compressive strength were measured. The influence of the addition of photocatalysts on the beginning and end of the setting time was also investigated. Full article

Due to the openness of the vehicle-to-grid (V2G) network, the upload of charging and discharging data faces severe security challenges such as eavesdropping, tampering, and forgery. These challenges can lead to privacy breaches, transmission delays, and service quality degradation. To address these issues, a V2G network architecture based on cloud–fog-end is designed, and a charging and discharging data privacy protection scheme is proposed. We employ a pseudonym mechanism to achieve the conditional privacy protection of electric vehicle (EV) users. We design a certificateless aggregate signcryption (CLASC) algorithm to guarantee the security of uploading the charging and discharging privacy data. The algorithm solves certificate management and key escrow issues, utilizes aggregate signature operations to save network bandwidth, and avoids complex computations like bilinear pairings and exponents. Additionally, the scheme delegates the aggregate verification process to the fog layer, thereby alleviating the computational burden on the cloud layer, decreasing transmission delays, and enhancing the efficiency and reliability of the V2G network. The analysis results indicate that the scheme not only meets the required security objectives, but also has lower computational and communication overheads, making it suitable for scenarios involving the charging and discharging of large-scale EVs in V2G networks. Full article

The present work describes test results for glass crystal materials based on the SiO₂-Al₂O₃-MgO-K₂O system after 5, 10, 15, and 20 wt.% zinc oxide was added. The glazing analysis involved determining the effect of the additive on the characteristic temperatures and properties of the surface obtained, such as color, gloss, and roughness, as expressed by a Ra parameter. The obtained glazes were also analyzed for changes in phase composition (quantitative and qualitative XRD tests), changes in microstructure (based on images obtained with a scanning electron microscope), and structure (based on analyses and decomposition of spectra obtained using mid-infrared spectroscopy). As a result, the maximum addition of zinc oxide provided the best results. Full article