As antibiotic resistance increasingly undermines traditional infection management strategies, there is a critical demand for innovative wound care solutions that address these emerging challenges. This study introduces a novel antibacterial wound dressing based on Cross-Linked Pullulan (Pul) and Polyhexamethylene Biguanide (PHMB) for enhanced wound management and infection control. The dressing’s adsorption rate reached 200% of its original weight within 30 min, exceeded 300% after 5 h, and exhibited significant non-Newtonian fluid properties. The dressings were able to release the loaded medication completely within 20 min; additionally, the dressing demonstrated significant antibacterial activity against a broad spectrum of bacteria. Significantly, the therapeutic effects of the Pul-PHMB/GP dressing were evaluated in a mouse model. Compared to untreated wounds, wounds treated with Pul-PHMB/GP exhibited a significant gelation process within 5 min post-treatment and showed a significant increase in wound healing rate within 12 days. This powder preparation overcomes the limitations associated with liquid and gel dressings, notably in storage and precise application, preventing the premature expansion or dissolution often caused by PHMB in high-humidity environments. The powder form can transform into a gel upon contact with wound exudate, ensuring accurate coverage of irregular wounds, such as those from burns or pressure sores, and offers excellent chemical and physical stability in a dry state, which facilitates storage and transport. This makes the dressing particularly suitable for emergency medical care and precision therapy, significantly improving the efficiency and adaptability of wound treatment and providing robust support for clinical treatments and emergency responses. Full article

Existing direct and inverse kinematic models of planar parallel robots assume that the robot’s active joints are all at the bases. However, this approach becomes excessively complex when modeling a planar parallel robot in which the active joints are within one single kinematic chain. To address this problem, our article unveils an alternative for a 3RRR symmetric planar robot modeling technique for the derivation of the robot workspace and the analysis of its direct and inverse kinematics. The workspace was defined using a system of inequalities, and the direct and inverse kinematics models were generated using vectorial analysis and an optimized geometrical approach, respectively. The resulting models are systematically presented and validated. Two final model renditions are delivered supplying a thorough equation analysis and an applicability discussion based on the importance of the robot’s mobile platform orientation. The advantages of this model are discussed in comparison to the traditional modeling approach: whereas conventional techniques require the solution of complex eighth-degree polynomials for the analysis of the active joint configuration of these robots, these models provide an efficient back-of-the-envelope analysis approach that requires the solution of a simple second-degree polynomial. Full article

This article presents the results of an experimental verification of three-phase Dy transformer dynamics under no-load conditions. This study is motivated by previous ferroresonance analyses where the occurrence of inrush currents has been observed. The measurements covered all available electrical quantities in a transient state (12 measured and 3 additionally computed waveforms) during the device’s start-up under no-load conditions, as well as in a long-term steady state. A detailed analytical analysis is carried out for the obtained comprehensive set of measurement results. As a result of the conducted research, the mathematical model of the pre-magnetized three-phase Dy transformer is modified. Particular attention is paid to the issue of residual magnetism of the transformer core and its consideration in further research. The original strategy for energizing a three-column three-phase Dy transformer with a suitable pre-magnetization of its columns and original control switching system with a given/set value of the initial phase in the supply voltage is put to the test. The evolution of the induced inrush phenomenon up to the quasi-steady state under given (forced) conditions is documented (currents, voltages and the dynamics of changes taking place in the core (hysteresis loops)). This article represents a continuation of ongoing work on the study of transient states (dynamics of transformer inrush currents). At present, the Dy three-phase transformer is analyzed because of the requirements of industrial operators. Full article

European hazelnut (Corylus avellana L.) cultivation has grown worldwide in recent years, even though the world’s production is still fulfilled by a few dozen cultivars well adapted to the local environments of their selection. After Turkey, Italy is the second largest producer of hazelnuts, and the province of Viterbo, in central Italy, is recognized as one of the most suitable districts for hazelnut cultivation. The production in this area relies almost entirely on local cultivar ‘Tonda Gentile Romana’, whereas cultivar ‘Nocchione’ is used as the main pollinizer. More recently, cultivar ‘Tonda di Giffoni’ has been introduced in new local plantations. Cultivation of many cultivars in different areas is of fundamental importance to test their adaptability to different environmental conditions, a need currently accentuated by ongoing climate change. With this aim, a European hazelnut collection field was established in 2000 in Caprarola municipality (Viterbo province), where plants of twelve hazelnut cultivars were observed over four growing seasons for their phenological, agronomic and nut traits. The cultivars studied, namely ‘Barcelona’, ‘Camponica’, ‘Ennis’, ‘Merveille de Bollwiller’, ‘Negret’, ‘Nocchione’, ‘Riccia di Talanico’, ‘San Giovanni’, ‘Tombul’, ‘Tonda di Giffoni’, ‘Tonda Gentile’ and ‘Tonda Gentile Romana’, showed a high diversity in their phenological behaviour, yield efficiency and nut and kernel traits. Cultivars ‘Negret’, ‘Tombul’ and ‘Tonda Gentile’, with poor yields over the years of research, do not seem suitable to be cultivated as main cultivars in the studied environment, contrary to ‘Camponica’ and ‘San Giovanni’, which produced abundantly, reaching a total of almost 30 and 25 kg plant^—1 of in–shell hazelnuts, respectively. Cultivars ‘Tonda Gentile Romana’ and ‘Nocchione’ confirmed their yield consistency, whereas ‘Ennis’, ‘Barcelona’ and ‘Tombul’ seem suitable to be introduced as pollinizers thanks to their male blooming overlapping with the female blooming of the main cultivar ‘Tonda Gentile Romana’. Cultivar ‘Tonda di Giffoni’ did not perform well in the studied environment, despite being recognized as one of the highest-yield cultivars. Full article

Chitosan, a versatile biopolymer derived from chitin, has garnered significant attention in various biomedical applications due to its unique properties, such as biocompatibility, biodegradability, and mucoadhesiveness. This review provides an overview of the diverse applications of chitosan and its derivatives in the antibacterial, anticancer, wound healing, and tissue engineering fields. In antibacterial applications, chitosan exhibits potent antimicrobial properties by disrupting microbial membranes and DNA, making it a promising natural preservative and agent against bacterial infections. Its role in cancer therapy involves the development of chitosan-based nanocarriers for targeted drug delivery, enhancing therapeutic efficacy while minimising side effects. Chitosan also plays a crucial role in wound healing by promoting cell proliferation, angiogenesis, and regulating inflammatory responses. Additionally, chitosan serves as a multifunctional scaffold in tissue engineering, facilitating the regeneration of diverse tissues such as cartilage, bone, and neural tissue by promoting cell adhesion and proliferation. The extensive range of applications for chitosan in pharmaceutical and biomedical sciences is not only highlighted by the comprehensive scope of this review, but it also establishes it as a fundamental component for forthcoming research in biomedicine. Full article

Soil–Vegetation–Atmosphere Transfer (SVAT) models are a promising avenue towards gaining a better insight into land surface interactions and Earth’s system dynamics. One such model developed for the academic and research community is the SimSphere SVAT model, a popular software toolkit employed for simulating interactions among the layers of vegetation, soil, and atmosphere on the land surface. The aim of the present review is two-fold: (1) to deliver a critical assessment of the model’s usage by the scientific and wider community over the last 15 years, and (2) to provide information on current software developments implemented in the model. From the review conducted herein, it is clearly evident that from the models’ inception to current day, SimSphere has received notable interest worldwide, and the dissemination of the model has continuously grown over the years. SimSphere has been used so far in several applications to study land surface interactions. The validation of the model performed worldwide has shown that it is able to produce realistic estimates of land surface parameters that have been validated, whereas detailed sensitivity analysis experiments conducted with the model have further confirmed its structure and architectural coherence. Furthermore, the recent inclusion of novel functionalities in the model, as outlined in the present review, has clearly resulted in improving its capabilities and in opening up new opportunities for its use by the wider community. SimSphere developments are also ongoing in different aspects, and its use as a toolkit towards advancing our understanding of land surface interactions from both educational and research points of view is anticipated to grow in the coming years. Full article

Overcoming the blood–brain barrier (BBB) remains a significant hurdle in effective drug delivery to the brain. While the BBB serves as a crucial protective barrier, it poses challenges in delivering therapeutic agents to their intended targets within the brain parenchyma. To enhance drug delivery for the treatment of neurological diseases, several delivery technologies to circumvent the BBB have been developed in the last few years. Among them, nanoparticles (NPs) are one of the most versatile and promising tools. Here, we summarize the characteristics of NPs that facilitate BBB penetration, including their size, shape, chemical composition, surface charge, and importantly, their conjugation with various biological or synthetic molecules such as glucose, transferrin, insulin, polyethylene glycol, peptides, and aptamers. Additionally, we discuss the coating of NPs with surfactants. A comprehensive overview of the common in vitro and in vivo models of the BBB for NP penetration studies is also provided. The discussion extends to discussing BBB impairment under pathological conditions and leveraging BBB alterations under pathological conditions to enhance drug delivery. Emphasizing the need for future studies to uncover the inherent therapeutic properties of NPs, the review advocates for their role beyond delivery systems and calls for efforts translating NPs to the clinic as therapeutics. Overall, NPs stand out as a highly promising therapeutic strategy for precise BBB targeting and drug delivery in neurological disorders. Full article

This study investigates codon usage bias within the chloroplast genomes of 18 Taraxacum species, focusing on the base composition and various metrics including GC content, Relative Synonymous Codon Usage (RSCU), Effective Number of Codons (ENc), and GC3s. Our analysis revealed a pronounced preference for A/T-ending codons across Taraxacum species, with GC content across the first, second, and third positions of the codons (GC1, GC2, GC3) and the average GC content consistently below 50%. A detailed examination using the RSCU metric identified 29 commonly preferred A/T-ending codons, indicating a strong codon usage bias towards these endings. Specifically, the codon for leucine (UUA) emerged as highly preferred, while the codon for serine (AGC) was least favored. Through the ENc–GC3s plot analysis, we explored the forces shaping this bias, finding evidence that both mutation pressure and natural selection significantly influence codon preference, with most coding sequences showing weak bias. The PR2 plot analysis further confirmed the role of these factors by demonstrating a higher frequency of T over A and C over G at the third codon position, pointing towards a mutation bias complemented by natural selection. Collectively, our findings highlight a consistent pattern of codon usage bias in the chloroplast genomes of Taraxacum species, influenced by a combination of mutation pressure, natural selection, and possibly other unidentified factors. Full article

This research investigates the potential of utilizing recycled concrete aggregate (RCA) and recycled sand (RS), derived from crushed concrete cubes, as sustainable alternatives in construction materials. The study comprehensively evaluates the properties of RCA and RS, focusing on workability, impact resistance, abrasion resistance, and compressive strength to determine their viability as substitute construction materials. A notable finding is RS’s enhanced fire and heat resistance when used as a fine aggregate in mortar blends, mixed with cement and Sinicon PP in a 3:1 ratio. The experimental analysis included thorough assessments of uniformity, durability, and curing time, alongside Scanning Electron Microscopy (SEM) for structural examination. Results show that RCA has an Aggregate Impact Value (AIV) of 5.76% and a Los Angeles Abrasion Value (LAA) of 21.78%, demonstrating excellent strength of the recycled aggregates. The mortar mix was also prepared using recycled sand, cement, and Sinicon PP, and its stability was confirmed through soundness tests, which resulted in a 0.53 mm expansion and a satisfactory consistency level of 44%. Ultrasonic pulse velocity (UPV) tests also indicated high-quality concrete formation using RCA and RS. SEM imaging corroborated this by revealing a bond between the cement paste and the aggregates. Incorporating RS and RCA in concrete mixtures impressively yielded a compressive strength of 26.22 N/mm² in M20-grade concrete. The study concludes that using RCA and RS waste materials in the construction sector underlines that sustainable practices can be integrated without compromising material quality. This approach aligns with sustainable development goals and fosters a more environmentally friendly construction industry. Full article

Traditional neuroimaging methods have identified alterations in brain activity patterns following mild traumatic brain injury (mTBI), particularly during rest, complex tasks, and normal vision. However, studies using graph theory to examine brain network changes in mTBI have produced varied results, influenced by the specific networks and task demands analyzed. In our study, we employed functional MRI to observe 17 mTBI patients and 54 healthy individuals as they viewed a simple, non-narrative underwater film, simulating everyday visual tasks. This approach revealed significant mTBI-related changes in network connectivity, efficiency, and organization. Specifically, the mTBI group exhibited higher overall connectivity and local network specialization, suggesting enhanced information integration without overwhelming the brain’s processing capabilities. Conversely, these patients showed reduced network segregation, indicating a less compartmentalized brain function compared to healthy controls. These patterns were consistent across various visual cortex subnetworks, except in primary visual areas. Our findings highlight the potential of using naturalistic stimuli in graph-based neuroimaging to understand brain network alterations in mTBI and possibly other conditions affecting brain integration. Full article

Giga-casting, a revolutionary approach for manufacturing large, single-piece car body components from aluminium, has emerged as a potential game-changer in the automotive industry. However, these large, thin-walled castings are prone to distortions during solidification and heat treatment processes. Straightening these distortions is crucial to ensure structural integrity, facilitate downstream assembly, and maintain aesthetic qualities. This paper proposes a novel method for straightening giga-cast components using a multi-pin straightening machine. The machine’s versatility stems from its ability to adapt to various geometries through multiple strategically controlled straightening pins. This paper introduces the concept of a “straightening stroke decision algorithm” to achieve precise straightening and overcome the challenges of complex shapes. This algorithm determines the stroke length for each pin, combining a polynomial model representing the global stiffness of the component with a machine learning model that captures the stiffness changes arising from the current geometry. The effectiveness of the proposed approach is evaluated through comprehensive numerical experiments using finite element analyses. The straightening performance is assessed for the straightening algorithm with different machine learning models (deep neural network and XGBoost) and compared to a traditional optimisation method. The proposed surrogate models decided the straightening strokes so that the maximum remaining distortion became 0.02% of the largest dimension of each target geometry. The results of the numerical experiment showed that the proposed straightening method is suitable for straightening distortion in large thin-walled components. Full article

Intestinal homeostasis results from the proper interplay among epithelial cells, the enteric nervous system (ENS), interstitial cells of Cajal (ICCs), smooth muscle cells, the immune system, and the microbiota. The disruption of this balance underpins the onset of gastrointestinal-related diseases. The scarcity of models replicating the intricate interplay between the ENS and the intestinal epithelium highlights the imperative for developing novel methods. We have pioneered a sophisticated tridimensional in vitro technique, coculturing small intestinal organoids with myenteric and submucosal neurons. Notably, we have made significant advances in (1) refining the isolation technique for culturing the myenteric plexus, (2) enhancing the isolation of the submucosal plexus—both yielding mixed cultures of enteric neurons and glial cells from both plexuses, and (3) subsequently co-culturing myenteric and submucosal neurons with small intestinal organoids. This co-culture system establishes neural innervations with intestinal organoids, allowing for the investigation of regulatory interactions in the context of gastrointestinal diseases. Furthermore, we have developed a method for microinjecting the luminal space of small intestinal organoids with fluorescently labeled compounds. This technique possesses broad applicability such as the assessment of intestinal permeability, transcytosis, and immunocytochemical and immunofluorescence applications. This microinjection method could be extended to alternative experimental setups, incorporating bacterial species, or applying treatments to study ENS-small intestinal epithelium interactions. Therefore, this technique serves as a valuable tool for evaluating the intricate interplay between neuronal and intestinal epithelial cells (IECs) and shows great potential for drug screening, gene editing, the development of novel therapies, the modeling of infectious diseases, and significant advances in regenerative medicine. The co-culture establishment process spans twelve days, making it a powerful asset for comprehensive research in this critical field. Full article

Leaf chlorophyll content (LCC) is an important physiological index to evaluate the photosynthetic capacity and growth health of crops. In this investigation, the focus was placed on the chlorophyll content per unit of leaf area (LCC_A) and the chlorophyll content per unit of fresh weight (LCC_W) during the tuber formation phase of potatoes in Northern Shaanxi. Ground-based hyperspectral data were acquired for this purpose to formulate the vegetation index. The correlation coefficient method was used to obtain the “trilateral” parameters with the best correlation between potato LCC_A and LCC_W, empirical vegetation index, any two-band vegetation index constructed after 0–2 fractional differential transformation (step size 0.5), and the parameters with the highest correlation among the three spectral parameters, which were divided into four combinations as model inputs. The prediction models of potato LCC_A and LCC_W were constructed using the support vector machine (SVM), random forest (RF) and back propagation neural network (BPNN) algorithms. The results showed that, compared with the “trilateral” parameter and the empirical vegetation index, the spectral index constructed by the hyperspectral reflectance after differential transformation had a stronger correlation with potato LCC_A and LCC_W. Compared with no treatment, the correlation between spectral index and potato LCC and the prediction accuracy of the model showed a trend of decreasing after initial growth with the increase in differential order. The highest correlation index after 0–2 order differential treatment is DI, and the maximum correlation coefficients are 0.787, 0.798, 0.792, 0.788 and 0.756, respectively. The maximum value of the spectral index correlation coefficient after each order differential treatment corresponds to the red edge or near-infrared band. A comprehensive comparison shows that in the LCC_A and LCC_W estimation models, the RF model has the highest accuracy when combination 3 is used as the input variable. Therefore, it is more recommended to use the LCC_A to estimate the chlorophyll content of crop leaves in the agricultural practices of the potato industry. The results of this study can enhance the scientific understanding and accurate simulation of potato canopy spectral information, provide a theoretical basis for the remote sensing inversion of crop growth, and promote the development of modern precision agriculture. Full article

Exoskeletons are being explored for assisting motion therapy for neurological impairment-related rehabilitation. Soft robotic exoskeletons are gaining more attention for upper-extremity applications due to their simplistic actuation mechanisms and compliant nature. To regain fine motor hand functions, it is desired to have both hand and wrist motions in a coordinated fashion, as most daily living tasks require a combination of both hand and wrist joint motions. However, a soft robotic exoskeleton with hand and wrist motion together is an underdeveloped area. This paper presents a pneumatically actuated soft robotic exoskeleton designed to provide coordinated assistive motion to the hand and wrist joints using PD-based feedback control. The results showed the potential of the exoskeleton to provide flexion/extension rehabilitation exercises and task-oriented rehabilitation practices. Additionally, the results have confirmed that the implemented PD control ensures that the exoskeleton reaches the targeted angular trajectories and velocities. Two modes, full and partial assistance, were successfully tested to verify the ability of the exoskeleton to accommodate varying levels of impairment. Full article

The recognition of the Aerococcus urinae complex (AUC) as an emerging uropathogen has led to growing concerns due to a limited understanding of its disease spectrum and antibiotic resistance profiles. Here, we investigated the prevalence of macrolide resistance within urinary AUC isolates, shedding light on potential genetic mechanisms. Phenotypic testing revealed a high rate of macrolide resistance: 45%, among a total of 189 urinary AUC isolates. Genomic analysis identified integrative and conjugative elements (ICEs) as carriers of the macrolide resistance gene ermA, suggesting horizontal gene transfer as a mechanism of resistance. Furthermore, comparison with publicly available genomes of related pathogens revealed high ICE sequence homogeneity, highlighting the potential for cross-species dissemination of resistance determinants. Understanding mechanisms of resistance is crucial for developing effective surveillance strategies and improving antibiotic use. Furthermore, the findings underscore the importance of considering the broader ecological context of resistance dissemination, emphasizing the need for community-level surveillance to combat the spread of antibiotic resistance within the urinary microbiome. Full article

The main objective of this work is to present a comprehensive and integrated methodology to enhance the resilience of transportation critical infrastructure (TCI), focusing on the interplay between geotechnical assets and the transport network. Societies are greatly dependent on transport infrastructure systems, and as the mobility of passengers and the transport of freight is continuously growing, a disruption due to natural or man-made hazards creates significant impacts and dysfunctionalities on their operation and necessitates response measures to minimize vulnerability and ensure continuous functionality and robustness through resilience. Therefore, resilience quantification allows the design of ad hoc operation action plans before, during, and after a disruption, considering the dynamics of societal, ecological, and technological (SET) environments. The current work focuses on resilience quantification methodologies for TCIs and on the influence of single geotechnical asset (i.e., slope failure) resilience capacity on the overall system (i.e., national road network) resilience. Two case studies of unexpected transport network disruptions that took place in Greece are presented, and resilience metrics and performance indicators are applied to quantify the influence of the recovery stage. Full article

Monolayer (CrN, AlTiN) and bilayer (CrN/AlTiN) coatings are formed on the surface of conventional heat-treated and gas-nitrided X45CrMoV5-3-1 tool steel via Cathodic Arc Physical Vapor Deposition (CAPVD), and the adhesion characteristics and room- and high-temperature wear behavior of the coatings are compared with those of the un-nitrided ones. Scratch tests on the coatings show that the bilayer coating exhibits better adhesion behavior compared to monolayer ones, and the adhesion is further increased in all coatings due to the high load carrying capacity of the diffusion layer formed by the nitriding process. Dry friction tests performed at room temperature reveal that, among ceramic-based coatings, the coating system with a high adhesion has the lowest specific wear rate (0.06 × 10⁻⁶ mm³/N·m), and not only the surface hardness but also the nitriding process is important for reducing this rate. Studies on wear surfaces indicate that the bilayer coating structure has a tendency to remove the surface over a longer period of time. Hot wear tests performed at a temperature (450 °C) corresponding to aluminum extrusion conditions show that high friction coefficient values (>1) are reached due to aluminum transfer from the counterpart material to the surface and failure develops through droplet delamination. Adhesion and tribological tests indicate that the best performance among the systems studied belongs to the steel–CrN/AlTiN system and this performance can be further increased via the nitriding process. Full article

Many countries use low-cost sensors for high-resolution monitoring of particulate matter (PM_2.5 and PM₁₀) to manage public health. To enhance the accuracy of low-cost sensors, studies have been conducted to calibrate them considering environmental variables. Previous studies have considered various variables to calibrate seasonal variations in the PM concentration but have limitations in properly accounting for seasonal variability. This study considered the meridian altitude to account for seasonal variations in the PM concentration. In the PM₁₀ calibration, we considered the calibrated PM_2.5 as a subset of PM₁₀. To validate the proposed methodology, we used the feedforward neural network, support vector machine, generalized additive model, and stepwise linear regression algorithms to analyze the results for different combinations of input variables. The inclusion of the meridian altitude enhanced the accuracy and explanatory power of the calibration model. For PM_2.5, the combination of relative humidity, temperature, and meridian altitude yielded the best performance, with an average R² of 0.93 and root mean square error of 5.6 µg/m³. For PM₁₀, the average mean absolute percentage error decreased from 27.41% to 18.55% when considering the meridian altitude and further decreased to 15.35% when calibrated PM_2.5 was added. Full article

The accuracy of cosmic ray observations by the Large High Altitude Air Shower Observatory Wide Field-of-View Cherenkov/Fluorescence Telescope Array (LHAASO-WFCTA) is influenced by variations in aerosols in the atmosphere. The solar photometer (CE318-T) is extensively utilized within the Aerosol Robotic Network as a highly precise and reliable instrument for aerosol measurements. With this CE318-T 23, 254 sets of valid data samples over 394 days from October 2020 to October 2022 at the LHAASO site were obtained. Data analysis revealed that the baseline Aerosol Optical Depth (AOD) and Ångström Exponent (AE) at 440–870 nm (AE_440–870nm) of the aerosols were calculated to be 0.03 and 1.07, respectively, suggesting that the LHAASO site is among the most pristine regions on Earth. The seasonality of the mean AOD is in the order of spring > summer > autumn = winter. The monthly average maximum of AOD_440nm occurred in April (0.11 ± 0.05) and the minimum was in December (0.03 ± 0.01). The monthly average of AE_440–870nm exhibited slight variations. The seasonal characterization of aerosol types indicated that background aerosol predominated in autumn and winter, which is the optimal period for the absolute calibration of the WFCTA. Additionally, the diurnal daytime variations of AOD and AE across the four seasons are presented. Our analysis also indicates that the potential origins of aerosol over the LHAASO in four seasons were different and the atmospheric aerosols with higher AOD probably originate mainly from Northern Myanmar and Northeast India regions. These results are presented for the first time, providing a detailed analysis of aerosol seasonality and origins, which have not been thoroughly documented before in this region, also enriching the valuable materials on aerosol observation in the Hengduan Mountains and Tibetan Plateau. Full article

Rare earth elements comprise a group of 17 chemically similar elements, which increases the difficulty of separating them by traditional methods. For this reason, hydrometallurgy has been the most used method. However, it is important to evaluate the efficiency of the leaching processes used because, in addition to depending on the operating parameters of the leaching, they also depend on the mineralogical composition of the sample. In the present work, the extraction of Ce and La contained in the ferrocarbonatite mineral from the north of Mexico was studied. For the leaching tests, several leaching agents were used (HCl, H₂SO₄, HNO₃, and H₃PO₄ in different concentrations (0.5 [M], 1 [M], 1.5 [M]) and the temperature was modified to 20, 40, and 60 °C. A maximum recovery of 70% for Ce and La was obtained using HCl 1M in 4 h. The results of the kinetic study of the experiments showed that the best fitting model according to these kinetic models was the SCM controlled by a chemical reaction. Full article

Blockchain technology, initially developed as a decentralized and transparent mechanism for recording transactions, faces significant privacy challenges due to its inherent transparency, exposing sensitive transaction data to all network participants. This study proposes a blockchain privacy protection algorithm that employs a digital mutual trust mechanism integrated with advanced cryptographic techniques to enhance privacy and security in blockchain transactions. The contribution includes the development of a new dynamic Byzantine consensus algorithm within the Practical Byzantine Fault Tolerance framework, incorporating an authorization mechanism from the reputation model and a proof consensus algorithm for robust digital mutual trust. Additionally, the refinement of homomorphic cryptography using the approximate greatest common divisor technique optimizes the encryption process to support complex operations securely. The integration of a smart contract system facilitates automatic and private transaction execution across the blockchain network. Experimental evidence demonstrates the superior performance of the algorithm in handling privacy requests and transaction receipts with reduced delays and increased accuracy, marking a significant improvement over existing methods. Full article

For the first time, an attempt has been made to present, chronologically and in a systematized form, the development of ornithological studies at the National Museum of Natural History in Sofia (Bulgaria) from its foundation in the last decades of the 19th century to the present day. This 135-year period (1889–2024) includes the work of 12 curators of the ornithological collections. Their major contributions and most-significant ornithological publications are also presented. Full article