Security and efficiency remain a serious concern for Internet of Things (IoT) environments due to the resource-constrained nature and wireless communication. Traditional schemes are based on the main mathematical operations, including pairing, pairing-based scalar multiplication, bilinear pairing, exponential operations, elliptic curve scalar multiplication, and point multiplication operations. These traditional operands are cost-intensive and require high computing power and bandwidth overload, thus affecting efficiency. Due to the cost-intensive nature and high resource requirements, traditional approaches are not feasible and are unsuitable for resource-limited IoT devices. Furthermore, the lack of essential security attributes in traditional schemes, such as unforgeability, public verifiability, non-repudiation, forward secrecy, and resistance to denial-of-service attacks, puts data security at high risk. To overcome these challenges, we have introduced a novel signcryption algorithm based on hyperelliptic curve divisor multiplication, which is much faster than other traditional mathematical operations. Hence, the proposed methodology is based on a hyperelliptic curve, due to which it has enhanced security with smaller key sizes that reduce computational complexity by 38.16% and communication complexity by 62.5%, providing a well-balanced solution by utilizing few resources while meeting the security and efficiency requirements of resource-constrained devices. The proposed strategy also involves formal security validation, which provides confidence for the proposed methodology in practical implementations. Full article

Siniperca chuatsi rhabdovirus (SCRV) is a major strain of viral fish virus resulting in multiple transmissions and devastating damage in aquaculture. Currently, there are no available approved therapeutics. In this study, we screened and identified a novel curcumin analog (EF-24) for evaluating its in vitro anti-SCRV properties and potential molecular mechanisms. Present results demonstrated that EF-24 could strongly delay the occurrence of cytopathic effects (CPEs) in epithelioma papulosum cyprinid cells (EPCs) and inhibit SCRV replication and viral nucleoprotein expression in the early stages of infection by the time-of-addition assay. Furthermore, flow cytometry analysis after Annexin V-FITC/PI double staining and immunofluorescence microscopy observation after JC-1 incubation showed that EF-24 downregulated cell mitochondrial apoptosis induced by SCRV. The enzymatic activities of caspase-3 and caspase-9 were also reduced after EF-24 treatment, indicating that EF-24 may protect cells from SCRV infection by decreasing mitochondrial intrinsic apoptosis in infected cells. Collectively, we demonstrated for the first time that the curcumin analog EF-24 possesses antiviral ability against SCRV, suggesting its potential for effective control of fish rhabdovirus spreading. Full article

The influence of different solvents, including aqueous and nonaqueous types, on the physicochemical properties of V₂O₅ nanostructures was thoroughly investigated. Various characterization techniques, such as XRD, XPS, FTIR, Raman spectroscopy, UV-vis DRS, SEM, TEM, and BET, were employed to analyze the obtained materials. Additionally, the adsorption properties of the synthesized V₂O₅ nanostructures for methylene blue were examined, and kinetic parameters of adsorption were calculated. The results demonstrate that the morphology of the obtained crystals can be finely controlled by manipulating water concentration in the solution, showcasing its profound impact on both the structural characteristics and adsorption properties of the nanostructures. Furthermore, the structural changes of the resulting V₂O₅ material induced by solvents show strong impacts on its photocatalytic properties, making it a promising photocatalyst. Full article

Drones offer significant safety and security advantages by enhancing situational awareness across various fields. However, realizing these benefits hinges on well-designed drone systems. This study builds upon previous research on drone deployment challenges and proposes the Drone Safety and Security Surveillance System (D4S). D4S aims to standardize similar drone-based systems, enhancing situational awareness and supporting decision-making processes. While initially tailored for safety and security, D4S holds potential for broader applications. Two system architectures have been proposed and evaluated with positive feedback from safety and security professionals. D4S has the potential to revolutionize safety practices, improve situational awareness, and facilitate timely decision making in critical scenarios. Full article

Limited availability of hydrometeorological data and lack of data sharing practices have added to the challenge of hydrological modelling of large and transboundary catchments. This research evaluates the suitability of latest near real-time global precipitation measurement (GPM)-era satellite precipitation products (SPPs), IMERG-Early, IMERG-Late and GSMaP-NRT, for hydrological and hydrodynamic modelling of the Brahmaputra Basin. The HEC-HMS modelling system was used for the hydrological modelling of the Brahmaputra Basin, using IMERG-Early, IMERG-Late, and GSMaP-NRT. The findings showed good results using GPM SPPs for hydrological modelling of large basins like Brahmaputra, with Nash–Sutcliffe efficiency (NSE) and R² values in the range of 0.75–0.85, and root mean square error (RMSE) between 7000 and 9000 m³ s⁻¹, and the average discharge was 20611 m³ s⁻¹. Output of the GPM-based hydrological models was then used as input to a 1D hydrodynamic model to assess suitability for flood inundation mapping of the Brahmaputra River. Simulated flood extents were compared with Landsat satellite-captured images of flood extents. In critical areas along the river, the probability of detection (POD) and critical success index (CSI) values were above 0.70 with all the SPPs used in this study. The accuracy of the models was found to increase when simulated using SPPs corrected with ground-based precipitation datasets. It was also found that IMERG-Late performed better than the other two precipitation products as far as hydrological modelling was concerned. However, for flood inundation mapping, all of the three selected products showed equally good results. The conclusion is reached that for sparsely gauged large basins, particularly for trans-boundary ones, GPM-era SPPs can be used for discharge simulation and flood inundation mapping. Full article

Background/Objectives:  Chronic total occlusion (CTO) is a prevalent finding in patients with coronary artery disease and is associated with increased mortality. Prior reports on the efficacy of percutaneous coronary intervention (PCI) compared to optimal medical therapy (OMT) were controversial. Following the emergence of recently published new evidence, a meta-analysis is warranted. The current meta-analysis assessed the effects of PCI compared to OMT in the treatment of CTO. Methods: A structured literature search was performed. Randomized controlled trials (RCTs) and non-randomized controlled studies of interventions were eligible. The primary outcome was an accumulated composite of cardiac mortality, myocardial infarction and target vessel/lesion revascularization events. Results: Thirty-two studies reporting on 11260 patients were included. Of these, 5712 (50.7%) were assigned to the PCI and 5548 (49.3%) were allocated to the OMT group. The primary outcome occurred in 14.6% of the PCI and 20.1% of the OMT group (12 trials, OR 0.66, 95% CI 0.50 to 0.88, p = 0.005, I² = 67%). Subgrouping demonstrated a consistent reduction in the primary outcome for the PCI group in RCTs (six trials, OR 0.58, 95% CI 0.33 to 0.99, p = 0.05). The primary outcome reduction was irrespective of the study design, and it was replicable in sensitivity and subgroup analyses. Advantages in other outcomes were rather related to statistical pooling effects and dominated by observational data. Conclusions: CTO-PCI was associated with improved patient-oriented primary outcome compared to OMT in a study-level meta-analysis. This composite outcome effect was mainly driven by target vessel treatment, but a significant reduction in mortality and myocardial infarction was observed, irrespectively. These findings have hypothesis-generating implications. Future RCTs with adequate statistical power are eagerly awaited. Full article

To investigate the interconnected effects of manufacturing processes on microstructure evolution during hot-rolling, a through process model is required. A novel numerical implementation of the mean-field approach was introduced to efficiently describe the grain growth of larger systems and extended durations. In this approach, each grain is embedded within an average medium and interacts with the average medium, thus avoiding the complexities of individual grain interactions. The proposed upsampling approach dynamically adjusts the simulation grain ensemble, ensuring efficiency and accuracy regardless of the initial number of grains present. This adaptation prevents undersampling artifacts during grain growth. The accuracy of the model is verified against analytical solutions and experimental data, demonstrating high agreement. Moreover, the effects of different initial conditions are successfully investigated, demonstrating the model’s versatility. Due to its simplicity and efficiency, the model can be seamlessly integrated into other microstructure evolution models. Full article

Lefamulin is a first-in-class systemic pleuromutilin antimicrobial and potent inhibitor of bacterial translation, and the most recent novel antimicrobial approved for the treatment of community-acquired pneumonia (CAP). It exhibits potent antibacterial activity against the most prevalent bacterial pathogens that cause typical and atypical pneumonia and other infectious diseases. Early studies indicate additional anti-inflammatory activity. In this study, we further investigated the immune-modulatory activity of lefamulin in the influenza A/H1N1 acute respiratory distress syndrome (ARDS) model in BALB/c mice. Comparators included azithromycin, an anti-inflammatory antimicrobial, and the antiviral oseltamivir. Lefamulin significantly decreased the total immune cell infiltration, specifically the neutrophils, inflammatory monocytes, CD4⁺ and CD8⁺ T-cells, NK cells, and B-cells into the lung by Day 6 at both doses tested compared to the untreated vehicle control group (placebo), whereas azithromycin and oseltamivir did not significantly affect the total immune cell counts at the tested dosing regimens. Bronchioalveolar lavage fluid concentrations of pro-inflammatory cytokines and chemokines including TNF-α, IL-6, IL-12p70, IL-17A, IFN-γ, and GM-CSF were significantly reduced, and MCP-1 concentrations were lowered (not significantly) by lefamulin at the clinically relevant ‘low’ dose on Day 3 when the viral load peaked. Similar effects were also observed for oseltamivir and azithromycin. Lefamulin also decreased the viral load (TCID₅₀) by half a log10 by Day 6 and showed positive effects on the gross lung pathology and survival. Oseltamivir and lefamulin were efficacious in the suppression of the development of influenza-induced bronchi-interstitial pneumonia, whereas azithromycin did not show reduced pathology at the tested treatment regimen. The observed anti-inflammatory and immune-modulatory activity of lefamulin at the tested treatment regimens highlights a promising secondary pharmacological property of lefamulin. While these results require confirmation in a clinical trial, they indicate that lefamulin may provide an immune-modulatory activity beyond its proven potent antibacterial activity. This additional activity may benefit CAP patients and potentially prevent acute lung injury (ALI) and ARDS. Full article

The modern theory of stress, initially proposed by Hans Selye in 1956, signifies an important development in our understanding of this phenomenon. Selye’s The Stress of Life serves as a foundational book for subsequent scientific questions. In this article, we focus on a comprehensive look at stress and use a literature review to explain its theoretical foundations as well as its clinical equivalent. Our research focuses on the complex mechanisms of stress, with a particular emphasis on the consequences of cardiac remodeling and adaptation processes. Myocardial remodeling might be seen as a response to increased stress in acute or chronic situations. Stressed heart morphology (SHM) is a very interesting description representing basal septal hypertrophy (BSH), which is detectable in both acute emotional stress and chronic stress due to increased afterload in hypertension. Acute stress cardiomyopathy (ASC) and hypertension in the same individuals could be clinically linked. Also, in this report, we mention the geometric and functional similarity of the left ventricle (LV) septal base in both acute and chronic clinical situations. Therefore, cardiac imaging methods are crucial to assessing LV segmental aspects in ASC patients. We propose a new paradigm that ASC may develop in hypertensive patients with SHM. We document the segmental progression of microscopic LV remodeling using a third-generation microscopic ultrasound and note that BSH takes a longer time to occur morphologically than an acutely developed syndrome. However, the majority of ASC events have a predominant base, and the absence of segmental remodeling details, including BSH and cardiac decompensation with apical ballooning, on echocardiographic reports may mask the possible underlying hypertensive disease. In fact, beyond ASC cases, previously undiagnosed hypertension is very common, even in developed countries, and is associated with masked target organ damage. Full article

The objective of this study was to propose a teacher training program based on the flipped classroom model with MOOCs to strengthen access to information and information literacy among primary education teachers in the Lambayeque region of Peru. The non-experimental design was assumed with a quantitative approach and a propositional, descriptive type. A diagnosis was made using a questionnaire given to 917 primary school teachers. It was discovered that nearly all of the items in the questionnaire revealed a deficiency in the ability to navigate, search, and filter information, data, and digital content; the highest percentages were at the Basic level, with the exception of the item expressing information needs in an organized manner, which was at the Advanced C2 level. The lowest percentage was at the Advanced C1 level, and the majority of the lower percentages were at the Advanced level. In addition, there are competency deficiencies in the evaluation of information, data, and digital content of nearly all the items: the highest percentages were at the Basic level, with the exception of the item involving the processing of information, data, and digital content, where 26.4% were at the Intermediate B1 level and just 2.8% managed to be at the highest level, which is Advanced C2. Furthermore, when it came to storage and retrieval of information, data, and digital content competency, all the high percentages were at the Basic level, and all the low percentages were at the highest level, that is, Advanced. These findings helped us to understand that teachers have only a basic knowledge of information literacy and information competency. As a result, it is necessary to advocate for a teacher training program based on the flipped classroom model with MOOCs. This idea was supported by the opinions of five experts, who stated that its implementation would enable primary teachers of Regular Basic Education in the region of Lambayeque (Peru) to develop their access to information and information literacy competency area. Full article

Most of the deep-learning algorithms on stock price volatility prediction in the existing literature use data such as same-frequency market indicators or technical indicators, and less consider mixed-frequency data, such as macro-data. Compared with the traditional model that only inputs the same-frequency data such as technical indicators and market indicators, this study proposes an improved deep-learning model based on mixed-frequency big data. This paper first introduces the reserve restricted mixed-frequency data sampling (RR-MIDAS) model to deal with the mixed-frequency data and, secondly, extracts the temporal and spatial features of volatility series by using the parallel model of CNN-LSTM and LSTM, and finally utilizes the Optuna framework for hyper-parameter optimization to achieve volatility prediction. For the deep-learning model with mixed-frequency data, its RMSE, MAE, MSLE, MAPE, SMAPE, and QLIKE are reduced by 18.25%, 14.91%, 30.00%, 12.85%, 13.74%, and 23.42%, respectively. This paper provides a more accurate and robust method for forecasting the realized volatility of stock prices under mixed-frequency data. Full article

Potassium deficiency is one of the important factors restricting cucumber growth and development. This experiment mainly explored the effect of Bacillus subtilis (B. subtilis) on cucumber seedling growth and the photosynthetic system under different potassium levels, and the rhizosphere bacteria (PGPR) that promote plant growth were used to solubilize potassium in soil, providing theoretical support for a further investigation of the effect of biological bacteria fertilizer on cucumber growth and potassium absorption. “Xinjin No. 4” was used as the test material for the pot experiment, and a two-factor experiment was designed. The first factor was potassium application treatment, and the second factor was bacterial application treatment. The effects of different treatments on cucumber seedling growth, photosynthetic characteristics, root morphology, and chlorophyll fluorescence parameters were studied. The results showed that potassium and B. subtilis had obvious promotion effects on the cucumber seedling growth and the photosynthesis of leaves. Compared with the blank control, the B. subtilis treatment had obvious effects on the cucumber seedling height, stem diameter, leaf area, total root length, total root surface area, total root volume, branch number, crossing number, g_s, WUE, Ci, and A; the dry weight of the shoot and root increased significantly (p ≤ 0.05). Potassium application could significantly promote cucumber growth, and the effect of B. subtilis and potassium application was greater than that of potassium application alone, and the best effect was when 0.2 g/pot and B. subtilis were applied. In conclusion, potassium combined with B. subtilis could enhance the photosynthesis of cucumber leaves and promote the growth of cucumber. Full article

(1) Background: Non-invasive prenatal testing (NIPT) is a screening test for fetal aneuploidy using cell-free fetal DNA. The fetal fragments (FF) of cell-free DNA (cfDNA) are derived from apoptotic trophoblast of the placenta. The level of fetal cfDNA is known to be influenced by gestational age, multiple pregnancies, maternal weight, and height. (2) Methods: This study is a single-center retrospective observational study which examines the relationship between the fetal fraction (FF) of cell-free DNA in non-invasive prenatal testing (NIPT) and adverse pregnancy outcomes in singleton pregnancies. A total of 1393 samples were collected between 10 weeks and 6 days, and 25 weeks and 3 days of gestation. (3) Results: Hypertensive disease of pregnancy (HDP) occurred more frequently in the low FF group than the normal FF group (5.17% vs. 1.91%, p = 0.001). Although the rates of small for gestational age (SGA) and placental abruption did not significantly differ between groups, the composite outcome was significantly higher in the low FF group (7.76% vs. 3.64%, p = 0.002). Furthermore, women who later experienced complications such as HDP or gestational diabetes mellitus (GDM) had significantly lower plasma FF levels compared to those without complications (p < 0.001). After adjustments, the low FF group exhibited a significantly higher likelihood of placental compromise (adjusted odds ratio: 1.946). (4) Conclusions: Low FF in NIPT during the first and early second trimesters is associated with adverse pregnancy outcomes, particularly HDP, suggesting its potential as a predictive marker for such outcomes. Full article

Background and Objectives: Age-related macular degeneration (AMD) is one of the leading causes of central vision loss among elderly patients, and its dry form accounts for the majority of cases. Although several causes and mechanisms for the development and progression of AMD have previously been identified, the pathogenesis of this complex disease is still not entirely understood. As inflammation and immune system involvement are strongly suggested to play a central role in promoting the degenerative process and stimulating the onset of complications, we aimed to analyze the frequency of serum anti-retinal (ARAs) and anti-endothelial cell antibodies (AECAs) in patients with dry AMD and to determine their relationship with the clinical features of the disease, notably the area of geographic atrophy (GA). Materials and Methods: This study included 41 patients with advanced-stage dry AMD and 50 healthy controls without AMD, matched for gender and age. ARAs were detected by indirect immunofluorescence using monkey retina as an antigen substrate, and the presence of AECAs was determined using cultivated human umbilical vein endothelial cells and primate skeletal muscle. Results: ARAs were detected in 36 (87.8%) AMD patients (titers ranged from 1:20 to 1:320) and in 16 (39.0%) (titers ranged from 1:10 to 1:40) controls (p = 0.0000). Twenty of the forty-one patients (48.8%) were positive for AECAs, while in the control group, AECAs were present only in five sera (10.0%). The titers of AECAs in AMD patients ranged from 1:100 to 1:1000, and in the control group, the AECA titers were 1:100 (p = 0.0001). There were no significant correlations between the presence of AECAs and disease activity. Conclusions: This study demonstrates a higher prevalence of circulating AECAs in patients with dry AMD; however, no correlation was found between the serum levels of these autoantibodies and the area of GA. Full article

The Preboreal (11.75–10.70 ka BP) is still the least paleogeographically studied time interval in the central part of the East European Plain. High-resolution multi-proxy studies of lacustrine sediments at the Seltso site located in the Desna River floodplain (Dnieper River basin) were conducted. Radiocarbon dating, loss-on-ignition determination, sedimentological and palynological studies and identification of Non-Pollen Palynomorphs in lacustrine sediments allow us to reconstruct changes in vegetation caused by rapid warming at the Younger Dryas–Holocene boundary, short-term climatic fluctuations within the Preboreal and subsequent resumption of warming. Initial Preboreal warming reached its maximum at about 11.5 ka BP when a relatively dry continental climate existed. Between 11.4 and 11.2 ka BP, a short-term cooling corresponding to the Preboreal Oscillation in Greenland occurred, as indicated by a significant reduction of woody vegetation and expansion of open plant communities. In the Late Preboreal, approximately 11.2–10.7 ka BP, warming resumed, which was accompanied by a decrease in the climate continentality. Comparison with high-resolution lithological and palynological data from eight reliably dated sections of the central East European Plain indicates that in northwestern and central Europe, the impact of the Preboreal Oscillation cooling on the vegetation and the lake ecosystems’ development was probably somewhat stronger. Full article

This paper investigates the problem of exponential $H_{\infty }$ output control for switching fuzzy systems, considering both impulse and non-impulse scenarios. Unlike previous research, where the average dwell time (ADT: ${\tau }_a$) and the upper bound of inter-event intervals (IEIs: T) satisfy the condition ${\tau }_a\ge \frac{ln\mu +(\alpha +\beta )T}{\alpha }=\frac{ln\mu +\beta T}{\alpha }+T$, implying that frequent switching is difficult to achieve, this paper demonstrates that by adopting the mode-dependent event-triggered mechanism (ETM) and a switching law, frequent switching is indeed achieved. Moreover, the question of deriving the normal $L_2$ norm constraint is solved through the ADT method, although only a weighted $L_2$ norm constraint was obtained previously. Additionally, by constructing a controller-mode-dependent Lyapunov function and adopting logarithmic quantizers, the sufficient criteria of exponential $H_{\infty }$ output control problem are presented. The validity of established results is demonstrated by a given numerical simulation. Full article

The use of autonomous and unmanned systems continues to increase, with uses spanning from package delivery to simple automation of tasks and from factory usage to defense industries and agricultural applications. With the proliferation of unmanned systems comes the question of how to secure the command-and-control communication links among such devices and their operators. In this work, we look at the use of the Messaging Layer Security (MLS) protocol, designed to support long-lived continuous sessions and group communication with a high degree of security. We build out MAUI—an MLS API for UxS Integration that provides an interface for the secure exchange of data between a ScanEagle unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV) in a multi-domain ad-hoc network configuration, and experiment on system limits such as the ciphersuite set-up time and message handling rates. The experiments in this work were conducted in virtual and physical environments between the UAV, USV, and a controller device (all of different platforms). Our results demonstrate the viability of capitalizing on MLS’s capabilities to securely and efficiently transmit data for distributed communication among various unmanned system platforms. Full article

To address the issue of limited application scenarios associated with connectivity assurance based on two-dimensional (2D) trajectory planning, this paper proposes an improved deep reinforcement learning (DRL) -based three-dimensional (3D) trajectory planning method for cellular unmanned aerial vehicles (UAVs) communication. By considering the 3D space environment and integrating factors such as UAV mission completion time and connectivity, we develop an objective function for path optimization and utilize the advanced dueling double deep Q network (D3QN) to optimize it. Additionally, we introduce the prioritized experience replay (PER) mechanism to enhance learning efficiency and expedite convergence. In order to further aid in trajectory planning, our method incorporates a simultaneous navigation and radio mapping (SNARM) framework that generates simulated 3D radio maps and simulates flight processes by utilizing measurement signals from the UAV during flight, thereby reducing actual flight costs. The simulation results demonstrate that the proposed approach effectively enable UAVs to avoid weak coverage regions in space, thereby reducing the weighted sum of flight time and expected interruption time. Full article

Hybrid composite materials have been widely used to advance the mechanical responses of fiber-reinforced composites by utilizing different types of fibers and fillers in a single polymeric matrix. This study incorporated three types of fibers: basalt woven fiber and steel (AISI304) wire meshes with densities of 100 and 200. These fibers were mixed with epoxy resin to generate plain composite laminates. Three fundamental mechanical tests (tensile, compression, and shear) were conducted according to the corresponding ASTM standards to characterize the steel wire mesh/basalt/epoxy FRP composites used as plain composite laminates. To investigate the flexural behavior of the hybrid laminates, various layer configurations and thickness ratios were examined using a design of experiments (DoE) matrix. Hybrid samples were chosen for flexural testing, and the same procedure was employed to develop a finite element (FE) model. Material properties from the initial mechanical testing procedure were integrated into plain and hybrid composite laminate simulations. The second FE model simulated the behavior of hybrid laminates under flexural loading; this was validated through experimental data. The results underwent statistical analysis, highlighting the optimal configuration of hybrid composite laminates in terms of flexural strength and modulus; we found an increase of up to 25% in comparison with the plain composites. This research provides insights into the potential improvements offered by hybrid composite laminates, generating numerical models for predicting various laminate configurations produced using hybrid steel wire mesh/basalt/epoxy FRP composites. Full article

Essential oils (EOs) are vital secondary metabolites in plants. They have garnered substantial attention owing to their distinct flavors and desirable attributes, including potent antioxidant, antibacterial, and antitumor properties. Nevertheless, the active constituents of EOs exhibit intricate chemical structures, and conventional separation techniques are inadequate for purifying the individual chemical components from EOs. High-speed countercurrent chromatography, based on the principles of a hydrodynamic equilibrium system, has emerged as a liquid–liquid chromatographic separation method renowned for its ability to handle substantial single injection volumes and the absence of irreversible adsorption. Consequently, in recent years, this technique has been widely employed in the isolation and refinement of natural products. In this review, a comprehensive analysis is conducted, contrasting the merits and demerits of high-speed countercurrent chromatography with conventional separation methods. The solvent systems, elution modes, commonly employed detectors, and practical applications are reviewed in the context of high-speed countercurrent chromatography for essential oil separation and purification. Furthermore, this review offers a glimpse into the potential prospects of applying this technique, with the intention of serving as a valuable reference for the use of high-speed countercurrent chromatography in the purification of EOs. Full article

Conventional distillation methods cannot effectively separate the components of an azeotropic mixture since both phases have the same composition, thereby preventing further separation. Additional techniques such as pressure swing distillation or distillation with entrainers are often employed to overcome this limitation and achieve separation. The aim of this investigation was to select the most effective method for separating n-hexane and ethanol. The feasibility of three methods was analyzed: reduced pressure distillation, extractive distillation, and liquid–liquid extraction. The mutual solubility of n-hexane and prepared deep eutectic solvents (DESs) (nine hydrophilic: choline chloride with glycerol, ethylene glycol, or carboxylic acid (malic, citric, glycolic); tetramethylammonium chloride with glycolic acid; lactic acid with glycerol; K₂CO₃ with glycerol or ethylene glycol; two hydrophobic: menthol with decanoic or dodecanoic acid) was experimentally determined. Extraction experiments were conducted to test the solubility of DESs in the feed mixture. The effect of changing DES-to-feed mass ratio was further investigated with choline chloride–glycerol (1:2). The same DES and both hydrophobic DESs were able to increase the relative volatility and enhance the separation of ethanol and n-hexane. Based on the obtained results, extraction was selected as the most effective method for the separation of n-hexane and ethanol. Full article

Background: Lyme disease (LD) is an emergent vector-borne disease caused by Borrelia spp. and transmitted through infected ticks, mainly Ixodes spp. Our objective was to determine meteorological and environmental factors associated with LD transmission in Europe and the effect of climate change on LD. Materials and methods: A systematic review following the PRISMA guidelines was performed. We selected studies on LD transmission in the European Union (EU) and the European Economic Area (EEA) published between 2000 and 2022. The protocol was registered in the PROSPERO database. Results: We included 81 studies. The impact of environmental, meteorological or climate change factors on tick vectors was studied in 65 papers (80%), and the impact on human LD cases was studied in 16 papers (19%), whereas animal hosts were only addressed in one study (1%). A significant positive relationship was observed between temperature and precipitation and the epidemiology of LD, although contrasting results were found among studies. Other positive factors were humidity and the expansion of anthropized habitats. Conclusions: The epidemiology of LD seems to be related to climatic factors that are changing globally due to ongoing climate change. Unfortunately, the complete zoonotic cycle was not systematically analyzed. It is important to adopt a One Health approach to understand LD epidemiology. Full article