Objective: The aim of this study was to optimize the fermentation process of Radix Ranunculi ternate via microbial fermentation and analyze the changes in the contents of the main components, the antioxidant and hypoglycemic capacities of the extract before and after fermentation. Methods: The solid-state fermentation process was optimized using single-factor tests and the response surface method, with the yield of the alcohol extract of R. ternate as an evaluation index. Results: The best fermentation process was optimized using solid-state endophytic fungus fermentation technology as follows: strain addition ratio of Chaetomium globosum/Fusarium equiseti =1:1, fermentation for 5 d, sieve size of 40 mesh, liquid/material ratio of 0.8:1 mL·g−1, fermentation temperature of 31 °C, and inoculation amount of 7.5%. Under the optimized conditions, the contents of the water-soluble extract and total polysaccharides decreased by 12.71% and 12.95%, respectively, in the fermentation, The contents of ethanol-soluble-extract, flavonoids, saponins, polyphenols, organic acids, and total amino acids of fermented R. ternate increased by 19.77%, 57.14%, 79.67%, 14.29%, 17.63% and 3.82%, respectively, and the scavenging rate for DPPH, ABTS+, ·OH free radicals and inhibitory rate for α-amylase also increased by 19.02%, 14.17%, 7.53% and 34.54%, respectively, compared with unfermented R. ternate. Conclusions: Solid-state fermentation opens new avenues for the development and application of R. ternate as natural antioxidant and hypoglycemic food.

For the last two decades, an increasing demand for low-cost adsorbents for drinking water treatment has been challenged in the rural areas of developing countries that have problems with arsenic (As) contamination. In this work, spent bleaching earth (SBE), a residual material that is formed during the process of refining vegetable oil, has been utilized to prepare the new magnetic adsorbent Fe-SBE/C by modifying its surface area through calcination and co-precipitation with iron. The experimental results demonstrate that Fe-SBE/C exhibits a substantial adsorption capacity towards both arsenite (As(III)) and arsenate (As(V)). Optimal pH conditions were found to be pH 10 for As(III) and pH 3 for As(V), resulting in adsorption percentages of 76.7% and 94.1%, respectively. Other experimental parameters such as calcination conditions, adsorbent dosage, iron-loading ratio, and the presence of co-existing ions were thoroughly investigated. The kinetic study revealed that the adsorption processes follow the Elovich and intraparticle diffusion models, suggesting a combined adsorption mechanism of boundary layer control and chemisorption. Furthermore, the isotherm followed the Langmuir model with a maximum adsorption capacity of 202.61 μg g-1 for As(III) and 187.61 μg g-1 for As(V). Through thermodynamic analysis and reinforcement by activation energy data, this research validates that the observed adsorption process is indicative through chemisorption. The regeneration study revealed the potential for multiple cycles of arsenic removal, highlighting the practical applicability of Fe-SBE/C in environmental contexts. In conclusion, the findings of this study underscore the efficacy of Fe-SBE/C in arsenic removal and present it as a promising and environmentally friendly solution for mitigating arsenic pollution.

Hepatitis E virus (HEV) is a common cause of acute hepatitis worldwide, accounting for approximately 25% of deaths among pregnant women. We previously reported that pregnancy serum facilitates HEV replication in vitro. However, the differences in host cells with HEV infection induced by pregnancy serum and fetal bovine serum (FBS) are unclear. In this study, differentially expressed proteins were identified in HEV-infected hepatoma cells (HepG2) supplemented with different sera by using isobaric tags for relative and absolute quantitation. Proteomic analysis indicated that HEV infection significantly induced 1014 differentially expressed proteins in HEV-infected HepG2 cells when supplemented with FBS compared with pregnancy serum. Further validation by Western blot confirmed that filamin A, heat-shock proteins 70 and 90, Cytochrome c, and Thioredoxin were associated with HEV infection. This comparative analysis provides an important basis to further investigate HEV pathogenesis in pregnant women and HEV replication.

Peripheral artery disease (P.A.D.) is a significant health issue in developed countries. Stenosis of an artery produces substantial changes in blood flow and, consecutively, in its hemodynamics. By simulating the stenosis (obstruction) - arterial environment, valuable insights are obtained. Various methodologies are used to simulate an arterial flow distribution. In this study, a 0D model using a printed circuit board (P.C.B.) is proposed. The model mimics a medium-sized single artery stenosis. Various degrees of stenosis are simulated. Results show that the P.C.B. model accurately predicts the hemodynamic changes produced by stenosis of a medium-sized artery. Also, the model is sensitive to the arterial wall stats. In conclusion, the P.C.B. design is a viable method for hemodynamic simula-tions. Moreover, to enhance the precision and intricacy of the simulation, the complexity and design of the P.C.B. must be augmented. Additionally, alongside subsequent computational fluid dynamics (C.F.D.) studies, the model will extract significant insights into the vascular dynamics of arterial stenosis

Understanding plant species and community status is the most fundamental step in assessing biodiversity and considering environmental conservation, and these depend on the identification of plant species. Plant identification is usually done manually using botanical illustrations, but due to the diversity of plant species, identifying a single species from among many candidates listed in illustrated books is a labor-intensive and time-consuming task, even for experts. Against this background, systems for automatic plant species recognition are in demand by experts and amateurs alike. In this study, we proposed a method for automatic plant identification by applying multifractal analysis to images of leaf veins, including veinlets. In the experiment, we conducted two experiments: one to see if there is a change in the number of dimensions depending on the degree of leaf growth, and the other to see how the number of dimensions changes depending on the taxonomic group. As a result, there was almost no change depending on the degree of growth, and the number of dimensions varied depending on the taxonomic group, suggesting that different taxonomic groups can be classified into different taxonomic groups, suggesting that multifractal analysis can be applied to leaf vein images, including veinlets, to enable automatic plant identification.

Light pollution of the night sky is a phenomenon increasingly observed around the world and reported in the form of thematic maps. The major contributor to light pollution is ill-adjusted or inappropriately designed artificial lighting by outdoor light sources. The phenomenon occurs mainly over urban areas, but affects both the urban environment and the areas adjacent to it. The problem of excessive artificial light emission at night and the negative effects it causes has already become so serious and global in its impact that effective and comprehensible methods of cartographic presentation of this phenomenon have been explored. The literature on the subject provides examples of how to present the results of measurements of light pollution of the night sky, but these have been developed using different colour scales, often in discretionary ranges and units of measurement. This paper presents an overview of the measurement scales and units found in the literature to describe the phenomenon of light pollution that obscures the night sky. A proposal of the author’s color scale for the presentation of the phenomenon was proposed and shown by example. The differences between measurement scales and how they affect interpretation of results are discussed. Furthermore, a recommendation is made for a standardised method of cartographic visualisation of the spatial distribution and presentation of light smog measurement results.

The use of educational robotics has become increasingly popular in STEM education, offering motivating and hands-on learning experiences. This paper explores the potential of educational robotics for teaching plane curves at the university level. Specifically, it investigates the development and implementation of a LEGO SPIKE Prime robot designed to draw various central trochoids, including epicycloids and hypocycloids. The robot’s construction and programming are described, emphasizing the relationship between the robot’s physical movements and the mathematical equations of the curves it produces. The study also examines the integration of dynamic geometry software, which allows for visualization of the curves and verification of the robot’s accuracy. The paper concludes that educational robotics can serve as a valuable tool for enhancing both theoretical and practical understanding of mathematical and engineering concepts, offering a more engaging and interactive approach to learning.

The importance of bio robotics has been increasing day by day. Researchers are trying to mimic nature in a more creative way so that, the system can easily adopt the complex nature and its environment. Hence, bio robotic gripper plays a role in physical connection between the environment and bio robotics system. While handling the physical world in biorobots gripper, the complexity occurs in feedback system where sensor plays a vital role. Therefore, human centered gripper sensor has a good impact on bio robotics field. But categorical classification and their selection process is not very systematic. This review paper follows PRISMA methodology to summarize the previous works on bio robotics gripper sensor and its selection process.. This paper discusses challenges in soft robotics systems, and the importance of sensing systems to facilitate critical control mechanisms along with their selection considerations. Furthermore, a classification of soft actuation based on gripper has been introduced. Moreover, some unique characteristics for soft robotics sensor are explored namely compliance, flexibility, multifunctionality, sensor nature, surface properties, and material requirements. In addition, a categorization of sensors for soft robotic gripper in terms of modalities has been established ranging from the tactile and force sensor to slippage sensor. Various tactile sensors ranging from piezoelectric sensing to optical sensing are explored as it has utmost importance in soft gripper to effectively address the increasing requirements for intelligence and automation. Finally, taking everything into consideration, a flow diagram has been suggested for selecting sensors specific to soft robotics applications.

Background: Telemonitoring systems in cardiology have shown potential in improving chronic cardiovascular disease (CVD) management. This study aims to evaluate the impact of telemonitoring, mainly through mobile applications, on patient outcomes such as self-care, blood pressure control, quality of life, and hospitalization. Methods: We systematically reviewed studies assessing telemonitoring methods for patients with chronic CVD. The analysis included studies from various geographic regions and healthcare settings, focusing on qualitative outcomes without performing a meta-analysis. Results: Telemonitoring was found to aid in maintaining blood pressure and significantly enhance self-care abilities. Improvements in quality of life were observed in some studies, though results varied. Most studies indicated telemonitoring could effectively manage blood pressure and reduce hypertension-related complications. However, the heterogeneity of interventions and outcomes measured across trials posed challenges for a comprehensive meta-analysis. Conclusions: Integrating telemonitoring systems into routine care can significantly improve disease management and patient outcomes for chronic CVD patients. Future research should standardize telemonitoring interventions and outcome measures, conduct long-term studies, and evaluate the cost-effectiveness of these systems. Greater blindness in future randomized controlled trials and more studies on atrial fibrillation are also necessary. Significant potential exists for telemonitoring to improve patient outcomes and assist in managing chronic illnesses.

Under the new pattern of “double carbon” development, good ESG performance is the best way to promote the sustainable development of enterprises, and the ESG investment strategies are directly affected by the strategic vision of managers. Based on the upper echelons theory and stakeholder theory, this paper takes Chinese A-share listed companies from 2011 to 2022 as samples to empirically analyze the impact of managerial myopia on corporate ESG performance. The results show that managerial myopia significantly inhibits corporate ESG performance, mainly by inhibiting corporate green investment and green innovation sustainability. Furthermore, for state-owned enterprises (SOE), heavy polluting enterprises (HPE) and non-high-tech enterprises, the inhibitory effect of manager myopia on ESG performance is stronger. When the enterprise is in the growth stage, the above inhibition effect is more severe. For external governance, the greater the analyst attention and public environmental attention are, the more conducive they are to alleviating the restraining effect of managerial myopia on enterprise ESG performance. Therefore, effectively improving the time cognition level of managers and strengthening external supervision have become important measures for comprehensively optimizing the ESG performance.

Abstract: Due to sever land degradation throughout Ethiopia, the government has been implementing massive soil and water conservation works at the watershed scale since 2010 to conserve soil and water resources. However, most of the rivers in Ethiopia carry huge amount of sediment in rainy season and streams dried up in the dry period. Planned research was conducted on two paired micro-catchments Mt.Yewel with the main objective of evaluating the impact of soil and water conservation measures on base flow modification. Stream flow and rainfall data were collected from 22/11/2020 to 8/11/2022 on both micro-catchments at their outlets and center respectively. Base flow separation was done using Sp. Hydro base flow separation tool and SPSS Ver.21 statistical software was employed for data analysis. Flow duration curve (FDC) for both watersheds were developed. The FDC indicated that the base flow from treated micro-catchment ishigher and sustained in the dry season while it is low and un-sustained in untreated micro-catchment. From statistical analysis, there is a significant difference in base flow enhancement between the treated and untreated micro-catchment (P<0.001). Hence, catchment treatment contributed to improve groundwater recharge and sustain base flow in the dry season by reduce surface runoff during rainy season.

This paper proposed an optimal tracking control scheme through adaptive dynamic programming(ADP) for a class of partially unknown discrete-time nonlinear systems based on radial basis function neural network(RBF-NN). In order to acquire the unknown system dynamics, we use two RBF-NNs, the one is used to construct the identifier, and the another is used to directly approximate the steady-state control input, where a novel adaptive law is proposed to update neural network weights. While the optimal feedback control and the cost function are derived via feedforward neural networks approximating, it is proposed to regulate the tracking error, the critic network and the actor network are then trained online to obtain the solution of the associated Hamilton–Jacobi–Bellman (HJB) equation being built under the ADP framework. Simulations verify the effectiveness of the optimal tracking control technique using the neural networks.

Air pollution, climate change and global warming show direct linkage. Introduction - Background: Research in the field has proposed and demonstrated their link to increased allergenicity in plants, leading to increased allergic diseases. Allergen patterns are changing in response to climate change. Across Europe, up to 12% of the population suffers from allergic diseases (bronchial asthma and allergic rhinitis) caused by the pollen grains. The medical costs of these types of allergies are enormous and are increasing with the spread of common ragweed - Ambrosia artemisiifolia* in Europe. In practice, more and more patients are turning to allergists. Methods: Based on these data, the research aims to identify safety measures and specific legislation to control and eradicate common ragweed in the countries most affected by the spread of this plant in Europe, increase in population exposure in countries affected by the presence of common ragweed and the socio-economic impact of allergic rhinitis and bronchial asthma at European level.[1][2] Our database search did not reveal any other research that has addressed this topic to date. Results: This research identifies specific legislation to the countries most affected by the spread of this plant pollen grains at European level, changes in allergen patterns and monitoring/safety eradication measures decided by local authorities, and data on the spread of common ragweed over the last two decades, costs per treatment, increased allergic rhinitis and bronchial asthma morbidity in the most affected areas. Conclusions: At European level, there are no universally valid models for eradicating this weed. Various methods can be used to limit the spread of common ragweed and its pollen production (e.g. mowing once or twice a year of overgrown land, ploughing, chemical control, public information, etc.). Local and regional cooperation should be considered essential to promote phytosanitary &amp; safety measures and exchange of information on methods to identify and manage the spread of common ragweed. Unified legislation at European level would help all affected countries; reduce morbidity from respiratory allergic diseases and the costs of treating these diseases.

The complex network relationship between leaf traits and their multiple traits is closely related to the environment, and is the result of interactions between various environmental factors such as climate and soil. Based on previous work, we selected 20 P. euphratica trees along the desert riparian forest of the main stream of the Tarim River for leaf sample collection and habitat survey. We used 27 leaf traits of P. euphratica to visualize the leaf trait network (LTN). Through network structure parameters, such as edge density, diameter, average path length, and average clustering coefficient, the spatial pattern of the LTN and its relationships with 11 soil factors and 19 climatic factors were discussed using principal component analysis and correlation analysis. The results showed that: (1) there were significant differences in the parameters of the leaf trait network of P. euphratica along the main stream of the Tarim River. The variation coefficients of the diameter and average path length were the largest, respectively, whereas that of the average clustering coefficient was the smallest. (2) There were both positive and negative correlations between each parameter and soil factors, such as soil water content, total potassium, and organic matter, and climatic factors, such as isothermality, minimum temperature of the coldest month, and precipitation of the wettest month. (3) The explanatory power of climate alone on the leaf traits of P. euphratica was generally higher than that of soil factors, indicating that climatic conditions play a more decisive role in shaping the network structure of leaf traits of P. euphratica. However, regarding the influence of network modularity, the contribution of soil factors was significant, indicating that the influence of soil conditions on some LTN parameters cannot be ignored.

Segment Anything Model 2 (SAM 2) is a state-of-the-art development by Meta AI Research, designed to address the limitations of its predecessor, SAM, particularly in the realm of video segmentation. SAM 2 employs a transformer-based architecture enhanced with streaming memory, enabling real-time processing for both images and videos. This advancement is important given the exponential growth of multimedia content and the subsequent demand for efficient video analysis. Utilizing the SA-V dataset, SAM 2 excels in handling the intricate spatio-temporal dynamics inherent in video data, ensuring accurate and efficient segmentation. Key features of SAM 2 include its ability to provide real-time segmentation with minimal user interaction, maintaining robust performance even in dynamic and cluttered visual environments. This study provides a comprehensive overview of SAM 2, detailing its architecture, functionality, and diverse applications. It further explores the model's potential in improving practical implementations across various domains, emphasizing its significance in advancing real-time video analysis.

Background/Objectives: The global burden of metabolic dysfunction-associated steatotic liver disease (MASLD) is increasing at an alarming rate. Cardiovascular disease (CVD) is the leading cause of mortality in MASLD patients, therefore, the therapeutic interventions for MASLD should improve coronary risk factors such as obesity, diabetes and dyslipidemia, in addition to improving liver function. The evidence on effect of sodium-glucose cotransporter 2 inhibitors (SGLT2is) which have beneficial pharmacological properties for MASLD, especially the long-term effects, on the progression of MASLD in Asian population is very limited. Methods: The retrospective longitudinal study was performed by using the medical records at the National Center for Global Health and Medicine, Kohnodai Hospital, Japan. We picked up patients with type 2 diabetes who had taken SGLT2is for at least 3 years or longer between April 1, 2014 and March 31, 2018. We collected the data on metabolic parameters, including blood tests and anthropometric parameters, and compared the data before and after the initiation of SGLT2is treatment. Results: During the observation period, 324 patients had taken SGLT2is for 3 years. The 3-year-SGLT2is treatment significantly reduced body weight, hemoglobin A1c, low-density lipoprotein-cholesterol, triglyceride and non-high-density lipoprotein-cholesterol (HDL-C) and significantly increased HDL-C. Furthermore, this treatment significantly improved liver function and the markers for hepatic steatosis and hepatic fibrosis. Conclusions: Considering that the development of CVD determines the prognosis of MASLD patients, the long-term SGLT2is treatment may be an ideal therapy for MASLD patients.

Currently, there is a high interest in smart sensors and integrated composite materials in various industries such as construction, aviation, automobile, medical, information technology, communication, and manufacturing. Here, a new conceptual design for a force and temperature sensor system is developed by integrating fiber optic Bragg grating sensors embedded within composite materials, and a mathematical model is proposed that allows one to estimate strain and temperature based on signals obtained from optical Bragg gratings. This is important for understanding the behaviors of sensors under different conditions and for creating effective monitoring systems. Describing the strain gradient distribution, especially considering different materials with different values of Young's modulus, provides insight into how different materials respond to applied forces and temperature changes. The shape of the strain gradient distribution was obtained, which is a quadratic function with a maximum value of 1500 µ, with a maximum value at the center of the lattice and a symmetrically decreasing strain value with distance from the central part of the fiber Bragg grating. With axial strain at the installation site of the Bragg grating sensor under applied force values ranging from 10 to 11 N, the change in strain was linear. As a result of theoretical research, it was found that the developed system with fiber-optic sensors based on Bragg gratings embedded in composite materials is resistant to external influences and temperature changes.

The seed habit is the most complex and successful method of sexual reproduction in vascular plants. It represents a remarkable moment in the evolution of plants that afterwards spread on land. In particular, seed size had a pivotal role as for evolutionary success and agronomic trait, especially in the field of crop domestication. Given that crop seeds constitute one of the primary products for consumption, it follows that seed size represents a fundamental determinant of crop yield. This adaptative feature is strictly controlled by genetic traits from both maternal and zygotic tissues, although seed development and growth are also affected by environmental cues. Despite being a highly exploited topic for both basic and applied research, there are still many issues to be elucidated as for developmental biology as well as for agronomic science. This review addresses a number of open questions related to cues that influence seed growth and size, and how developmental processes are influenced by them. Besides, new insights on the genetic-molecular control of this adaptive trait are presented.

Objective: To determine the effect of sandblasting before and after sintering on the surface roughness of zirconia and the micro-tensile bond strength of a pressable veneering ceramic to zirconia. Methods: Pre-sintered zirconia blocks (IPS e.max ZirCAD, Ivoclar Vivadent) were divided into a control group (CTR, no surface treatment) and four test groups of three specimens each: Pre-S-30, Pre-S-50, Pre-S-110 were sandblasted with 30µm SiO2, 50µm Al2O3 and 110µm Al2O3 particles respectively, before sintering, Post-S-30 was sandblasted with 30µm SiO2 after sintering. For each treatment, the surface roughness was measured (Ra, Perthometer M4P, Mahr Perthen). After sintering the zirconia blocks, a liner and a pressable ceramic (IPS e.max ZirPress, Ivoclar Vivadent) were fired. Sixteen micro-bars were obtained from each block and submitted to the micro-tensile bond strength (µTBS) test. Data were analyzed with one-way ANOVA. Any correlation between Ra and µTBS was evaluated (Sperman test). Results: Sandblasting before sintering with 110µm Al2O3 (Ra=3.44±0.44µm), 50µm Al2O3 (Ra=2.32±0.46µm), and 30µm SiO2 (Ra=1.22±0.22µm) resulted in significantly higher roughness than sandblasting after sintering with 30µm SiO2 (Ra=0.46±0.11µm). The highest µTBS was measured when the sintered zirconia was sandblasted with 30μm SiO2 (26.79±14.80 MPa), which was significantly different from that of specimens that were sandblasted before sintering (Pre-S-30=20.90±11.70; Pre-S-50=21.27±15.19; Pre-S-110=23.99±16.83) or were not treated (CTR=17.44±14.03). Conclusions: Sandblasting zirconia before sintering enhances the surface roughness proportionally to the particle size of the sand used. Sandblasting with 30µm SiO2 after sintering appeared to improve bonding between the veneering ceramic and zirconia. Clinical Significance: Sandblasting with 30µm SiO2 after sintering may improve bonding between veneering ceramics and zirconia, thus reducing ceramic fractures/chippings.

Design process can be divided into stages of analysis and synthesis. This paper presents the application of the object-oriented technique to the synthesis as well as theoretical considerations concerning to design of gear size ranges. The synthesis consists in composition (aggregation) of single details into units – according to the rule: “from details up to general view”. The basics of the object-oriented synthesis were formulated. Furthermore, the consecutive stages of synthesis were formulated. The interactions between these stages were discussed. Some aspects were described in details e.g.: creation of interfaces for performance of the embodiment phase the designed artefact via CAD system drawing with specification (dimensions are still parametrically set). The final step of the procedure is creation of so called substantial (concrete) form of artifacts i.e. final assignment of dimensions which stored in the special data base. The final stage of the design process is issuing of technical documentation (technical drawings) created automatically via CAD system. The considerations are terminated by the list of advantages connected with the object-oriented approach to design (in comparison to the traditional way).

Aiming at the limitations of single-functionality, limited applicability, and complex designs prevalent in current metasurfaces, we propose a terahertz multifunctional and multiband tunable metasurface utilizing a VO2-metal hybrid structure. This metasurface structure comprises a top VO2-metal resonance layer, a middle polyimide dielectric layer, and a gold film reflective layer at the bottom. This metasurface exhibits multifunctionality, operating independently of polarization and incident angle. The varying conductivity states of the VO2 layers, enable the metasurface to achieve various terahertz functionalities, including single-band absorption, broadband THz absorption, and multiband perfect polarization conversion for linear (LP) and circularly polarized (CP) incident waves. Finally, we believe that the functional adaptability of the proposed metasurface expands the repertoire of options available for future terahertz device designs.

The development of accurate dynamic battery pack models for electric vehicles (EVs) is critical for the ongoing electrification of the global automotive vehicle fleet, since these serve as a key element in the energy performance of an EV powertrain system. The Equivalent Circuit Model (ECM) technique at the cell level is commonly employed for this purpose, combining accuracy and efficiency in the representation of battery operation within the broader powertrain system. In this study, a second-order ECM model of a battery cell is being developed using Modelica, an equation-based modeling language. Parameter lookup tables at multiple levels of state of charge (SoC), extracted from Li-ion battery cells with 4 different commonly used cathode materials, have been utilized. This approach allows for a representation of the battery systems that are used in a wide range of commercial EV applications. To verify the model, an integrated EV model is developed and simulation results of the FTP75 driving cycle have been compared against an equivalent application in MATLAB Simulink. The findings demonstrate a close match between the results obtained from both software across different system points. Specifically, the maximum deviation of SoC is limited to 0.08% and the maximum value of relative voltage deviation is 1.4%. The verified model enables the exploration of multiple possible architecture configurations of EV powertrains with Modelica.

In recent decades, the requirements for implantable medical devices increased, but the risks of implant rejection still exist. These issues are primarily associated with poor osseointegration, leading to biofilm formation on the implant surface. This study focuses on addressing these issues by developing a biomaterial for implant coatings. 45S5 Bioglass has been widely used in tissue engineering due to its ability to form a hydroxyapatite layer, ensuring a strong bond between the hard tissue and the bioglass. In this context, 45S5 bioglasses, modified by the incorporation of different amounts of copper oxide, from 0 to 8 mol%, were synthesized by the melt-quenching technique. The incorporation of Cu ions does not show a significant change in the glass structure. Since the bioglass exhibited the capacity of being polarized, and therefore promoting the osseointegration effectiveness, the electrical properties of the prepared samples were studied using the impedance spectroscopy method, in the frequency range of 102-106 Hz and temperature range of 200-400 K. The effects of CuO on charge transport mobility were investigated. Additionally, the bioactivity of the modified bioglasses was evaluated through immersion tests in simulated body fluid. The results revealed the initiation of a Ca-P-rich layer formation on the surface within 24 h, indicating the potential of the bioglasses to enhance the bone regeneration process.

Dirofilariosis is an infectious disease caused by species of the Dirofilaria genus. It is manifested by the appearance of a subcutaneous swelling, especially in the eye region. We present the case of a 29-year-old patient that accused facial asymmetry in the right genian region. Following clinical and paraclinical evaluations, the diagnosis of parasitic cyst was established in the context of dirofilariosis with Dirofilaria repens (D. repens). Treatment consisted of surgical excision of the formation associated with prophylactic antibiotic medication. Macroscopic analysis of the excision piece revealed a structure that contains a cystic cavity and a filamentous form with a length of approximately 10 mM and a diameter of 1 mM. This is the first case of dirofilariosis located in the genian region reported in Romania. The overview of this pathology is important to raise awareness among physicians about its presence and its clinical variations.

Microwave technology has a potential application in the extraction of zinc from sulphide ores, knowledge of the dielectric properties of these ores plays a major role in the microwave design and simulation for any process. The dielectric properties of zinc sulfide concentrate for two different apparent densities—1.54 and 1.63 g/cm³—have been measured by using the resonance cavity perturbation technique at 915 and 2450 MHz during the roasting process for the temperature ranging from room temperature to 850 °C. The variations of dielectric constant, the dielectric loss factor, the dielectric loss tangent and the penetration depth with the temperature, frequency and apparent density have been investigated numerically. The results indicate that the dielectric constant increases as the temperature increases and temperature has a pivotal effect on the dielectric constant, while the dielectric loss factor has a complicated change and all of the temperature, frequency and apparent density have a significant impact to dielectric loss factor. Zinc sulfide concentrate is high loss material from 450 to 800 °C on the basis of theoretical analyses of dielectric loss tangent and penetration depth, its ability of absorbing microwave energy would be enhanced by increasing the apparent density as well. The experimental results also have proved that zinc sulfide concentrate is easy to be heated by microwave energy from 450 to 800 °C. In addition, the experimental date of dielectric constant and loss factor can be fitted perfectly by Boltzmann model and Gauss model, respectively.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with cognitive dysfunction, memory decline, and behavioral disturbance, and pathologically characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. Although various hypotheses have been proposed to explain the pathogenesis of AD, including the amyloid beta hypothesis, oxidative stress hypothesis, and abnormal phosphorylation of tau proteins, the exact pathogenic mechanisms underlying AD remain largely undefined. Furthermore, effective curative treatments are very limited. Epidemiologic studies provide convincing evidence for a significant association between type 2 diabetes and AD. Here, we showed energy metabolism using glucose, lactate and ketone bodies and lipids as energy substrates in normal brain, and changes in such energy metabolism due to type 2 diabetes. We also showed the influences of such altered energy metabolism due to type 2 diabetes on the pathology of AD. Furthermore, we comprehensively searched the risk factors related with type 2 diabetes for AD, and showed possible therapeutic interventions based on considering risk factors and altered brain energy metabolism due to type 2 diabetes for the development of AD.

This study evaluates the efficiency of biodegradable polyurethane foams as thermal insulation materials compared to conventional materials like expanded polystyrene (EPS). Key parameters analyzed include thermal conductivity, energy savings, CO2 emission reductions, and investment payback periods. Biodegradable polyurethane foams demonstrated a thermal conductivity of 0.022 W/(m·K), significantly lower than EPS's 0.035 W/(m·K), leading to higher energy savings. Calcu-lations reveal an annual energy saving of 443,820 kWh for polyurethane foams, compared to 441,330 kWh for EPS. Financially, polyurethane foams save approximately €53,258.4 annually, while EPS saves €52,959.6. In terms of environmental impact, polyurethane foams reduce CO2 emissions by 88,764 kg annually, versus 88,266 kg for EPS. Despite the higher initial cost of pol-yurethane foams (€50/m² compared to €30/m² for EPS), the payback period is remarkably short at 0.094 years (1.13 months) compared to EPS's 0.057 years (0.68 months). These findings highlight biodegradable polyurethane foams as a superior option for thermal insulation, offering significant energy, financial, and environmental benefits.

Mesenchymal stem cells (MSCs) hold immense therapeutic potential due to their regenerative and immunomodulatory properties. However, to utilize this potential, it is crucial to optimize their in vitro cultivation conditions. Three-dimensional (3D) culture methods using cell-laden hydrogels aim to mimic the physiological microenvironment in vitro, thus preserving MSC biological functionalities. Cellulosic hydrogels are particularly promising due to their biocompatibility, sustainability, and tunability in terms of chemical, morphological, and mechanical properties. This study investigated the impact of (1) two physical crosslinking scenarios for hydrogels derived from anionic cellulose nanofibers (CNF) used to encapsulate adipose-derived MSCs (adMSCs) and (2) physiological culture conditions on the in vitro proliferation, differentiation, and extracellular vesicle (EV) production of these adMSCs. Our results revealed that additional Ca2+-mediated crosslinking, intended to complement self-assembly and gelation of aqueous to-CNF in the adMSC cultivation medium, adversely affected both the mechanical properties of the hydrogel spheres and the growth of the encapsulated cells. However, cultivation under dynamic and hypoxic conditions significantly improved the proliferation and differentiation of the encapsulated adMSCs. Furthermore, we demonstrated that adMSCs in CNF hydrogel spheres exhibited potential for scalable EV production with potent immunosuppressive capacities in a bioreactor system. These findings underscore the importance of physiological culture conditions and the suitability of cellulosic materials for enhancing the therapeutic potential of MSCs. Overall, our study provides valuable insights for optimizing the in vitro cultivation of MSCs for various applications, including tissue engineering, drug testing, and EV-based therapies.

Questionnaires for self-report of food-elicited emotions are an established practice in consumer studies. However, most tools are originally developed in English and translated into other languages, which limits their use. The aim of this study was to develop the first Greek emotion lexicon and measurement tool for consumers, using standard methodology and extending it. The lexicon was compiled using linguistic sources and extended using the World Wide Web and a popular social media platform for the collection of authentic language and usage data. Terms were also collected from consumers using questionnaires and a variety of stimuli. Terms collected from consumers only comprise: healthy, distrustful, curious, childish, impressed, tolerant, impatient It was validated by application in various case studies, providing discrimination across and within food categories, and by comparison to the Greek translation of a standard tool in English, the EsSense Profile. The comparison was conducted by measuring emotions elicited by six food categories and demonstrated that it is preferable to use emotion measurement tools developed in the linguistic and cultural context of intended use, as they convey consumers’ emotions naturally and more accurately. This tool can be used as a Check- or Rate- All-That-Apply questionnaire to measure consumer responses to food categories and products. The methodology and validation presented can be applied for the compilation of emotion lexicons in languages less studied than English.

China’s greenhouse industry has thousands of years of development history, although the development of modern greenhouses has come late. After decades of development of China, its greenhouse industry is in the forefront of the world. China’s greenhouse industry is experiencing rapid development, transformation and upgrading. China ranks first in the world in terms of greenhouse area, used mainly for vegetable cultivation and plays an important role in the utilization of agricultural resources and food production. In 2023, the cumulative area of new greenhouses nationwide was 1835.87 million ha. In this paper we present the latest developments in the greenhouse sector. More specifically, we present a greenhouse market development overview, the greenhouse production, the greenhouse industry, and technology development. Current problems are underpinned, development opportunities and prospects are analyzed, and measures and specific proposals are detailed for the technological development of the greenhouse sector both for increasing product quantity and quality.

The sweetpotato whitefly, Bemisia tabaci MEAM1, is a pest known to significantly impact tomato development and yields through direct damage and virus transmission. To manage this pest, the current study compared the effectiveness of various insecticide rotations. Field trials included rotations involving synthetic insecticides, biochemicals, and microbial agents, applied according to their labeled highest concentrations. Results indicated that while standard synthetic insecticides consistently reduced whitefly egg and nymph counts significantly, microbial biopesticide rotations also achieved reductions, although less consistently. This study demonstrated that while traditional chemical treatments remain highly effective, integrating microbial biopesticides containing Beauveria bassiana and Cordyceps javanica present a viable alternative that could mitigate resistance development and reduce environmental impact. The findings suggest the potential for optimizing integrated pest management (IPM) and Insecticide Resistance Management (IRM) strategies by incorporating a variety of modes of action to sustainably manage B. tabaci MEAM1 populations in agricultural settings.

Mangrove forests provide a wide range of goods and services that sustain communities around the world. This paper explores utilization patterns of extractable mangrove resources by communities within the proposed Kenya – Tanzania Transboundary Conservation Area (TBCA). Some 152 household surveys and 12 Nominal Group Technique discussions were carried out. At least 16 direct use products were reported to be extracted from the mangroves, with 90% of households found to use mangrove products. Changing patterns of mangrove use in the areas and accessibility point towards unsustainable utilization and promote illegal activities. Overharvesting of mangrove wood products was reported to be the major threat facing the forests. Patterns of mangrove use in the study site reveal a high level of mangrove-dependence by communities for their livelihood. There is a need to address the problems of open access through capacity building and awareness creation, development and implementation of harvest plans as well as introduction of alternative livelihood options to the communities in the area.

Railway has been used as one of the most crucial means of transportation in public mobility and economic development. For efficiently operating railways, the electrification system in railway infrastructure, which supplies electric power to trains, is essential facilities for stable train operation. Due to its important role, the electrification system needs to be rigorously and regularly inspected and managed. This paper presents a supervised learning method to classify Mobile Laser Scanning (MLS) data into ten target classes representing overhead wires, movable brackets and poles, which are recognized key objects in the electrification system. In general, the layout of railway electrification system shows a strong regularity of spatial relations among object classes. The proposed classifier is developed based on Conditional Random Field (CRF), which characterizes not only labeling homogeneity at short range, but also the layout compatibility between different object classes at long range in the probabilistic graphical model. This multi-range CRF model consists of a unary term and three pairwise contextual terms. In order to gain computational efficiency, MLS point clouds is converted into a set of line segments where the labeling process is applied. Support Vector Machine (SVM) is used as a local classifier considering only node features for producing the unary potentials of CRF model. As the short-range pairwise contextual term, Potts model is applied to enforce a local smoothness in short-range graph. While, long-range pairwise potentials are designed to enhance spatial regularities of both horizontal and vertical layouts among railway objects. We formulate two long-range pairwise potentials as the log posterior probability obtained by Naïve Bayes classifier. The directional layout compatibilities are characterized in probability look-up tables which represent co-occurrence rate of spatial relations in horizontal and vertical directions. The likelihood function is formulated by multivariate Gaussian distributions. In the proposed multi-range CRF model, the weight parameters to balance four sub-terms are estimated by applying the Stochastic Gradient Descent (SGD). The results show that the proposed multi-range CRF can effectively classify detailed railway elements, representing the average recall of 97.66% and the average precision of 97.07% for all classes.

Fever control is essential in patients with severe traumatic brain injury (TBI). The efficacy of therapeutic hypothermia (TH) in severe TBI has been investigated over the last few decades; however, in contrast to experimental studies showing benefits, no evidence of efficacy has been demonstrated in clinical practice. In this review, the mechanisms and history of hypothermia were briefly outlined, while the results of major randomized controlled trials (RCTs) and meta-analyses investigating TH for adult TBI are introduced and discussed. The retrieved meta-analyses showed conflicting results, with a limited number of studies indicating benefits of TH. Some studies have shown benefits of long-term TH compared with short-term TH. Although TH is effective at lowering elevated intracranial pressure (ICP), reduced ICP does not lead to favorable outcomes. Low-quality RCTs overestimated the benefits of TH, while high-quality RCTs showed no difference or worse outcomes with TH. RCTs assessing standardized TH quality demonstrated the benefits of TH. As TBI has heterogeneous and complicated pathologies, applying a uniform treatment may not be ideal. A meta-analysis of young patients who underwent early cooling and hematoma removal showed better TH results. TH should not be abandoned, and its optimal should be advocated on an individual basis.

Immune checkpoint inhibitors (ICI) are a promising form of immunotherapy that has significantly changed the therapeutic landscape for many advanced cancers. They have shown unique clinical benefit against a broad range of tumour types and a strong overall impact on survival in studied patient populations. However, there are still many limitations holding back this immunotherapy from reaching its full potential as a possible curative option for advanced cancer patients. A great deal of research is being undertaken in the hope of driving advancements in this area, building a better understanding of the mechanisms behind immune checkpoint inhibition and ultimately developing more effective, safer, and wider-reaching agents. Taking into account the current literature on this topic, this review aims to explore in depth the basis of the use of ICIs in the treatment of advanced cancers, evaluate its efficacy and safety, consider its current limitations, and finally reflect on what the future holds for this very promising form of cancer immunotherapy.

This paper focuses on studying the mapping properties of singular integral operators on product spaces. The boundedness of such operators is established on Triebel-Lizorkin spaces whenever their kernel functions belong to Grafakos and Stefanov class. Our results generalize and improve some previously known results.

Internet of thing (IoT) has been used in different aspect of life as industry, and daily life. Aligned with IoT, Quantum computers have been generated with high features that can accomplish complicated tasks with high speed. IoT and Quantum computers don’t match in resources and due to this collaboration between the two terms, it was found there are many challenges with quantum computers brought some security concerns. This paper will examine all challenges and future direction that face the use of IoT through using different quantum cryptograph methods. The first part on the paper discussed the vulnerabilities of existing cryptographic methods like RSA and ECC. these two methods were used as basic level for IoT security protocols. These cryptographic algorithms could be easily attacked by quantum computers so to ensure that IoT devices are secure must develop quantum resistant cryptographic algorithms. Next this paper will examine the challenges in implementing quantum resistant cryptographic algorithm in any IoT device through quantum resistant cryptographic algorithms such as lattice-based cryptography, code-based cryptography, multivariate cryptography, and hash-based signatures. Then, the paper discussed the future direction of securing IoT in quantum computing. In conclusion, securing IoT devices in quantum presents many challenges that require to be addressed where quantum resistant algorithms can be a solution that mitigate threats.

In aerospace, robotics, network engineering and mechanical engineering, there exist complex and urgent challenges that can be abstracted into mathematical optimization problems. Therefore, exploring solutions to these optimization problems is a crucial task. Metaheuristic algorithms have been applied across various fields.The Snake Optimization Algorithm (SO) is an innovative metaheuristic method recognized for its efficient solving capabilities.However, this algorithm encounters challenges such as diminished search efficiency in the later stages and a propensity to become ensnared in local optima. To mitigate these issues, this paper introduces an enhanced Snake Optimization Algorithm (ISO). ISO integrates the RIME Algorithm(RIME)and introduces two effective enhancement strategies to improve its capability to evade local optima.To assess the effectiveness of ISO,the population distribution state was first measured using three algorithms, including Star Discrepancy, and the exploration and exploitation performance was analyzed using the CEC2017 test functions. Subsequently, utilized 23 benchmark functions for testing.The evaluation outcomes indicate that ISO exhibits outstanding performance in terms of convergence velocity and robustness.Additionally, it was applied to engineering fields including UAV path planning,Robot path planning, Wireless sensor network node deployment and Pressure vessel design.In comparison to the SO algorithm, the ISO algorithm demonstrates superior stability, converges earlier, and improves its ability to solve for optimal .These findings highlight the significant potential of the ISO algorithm in diverse test functions and a wide range of interdisciplinary problems.

Localized protein translation occurs through trafficking of mRNAs and protein translation machineries to different compartments of the cell, leading to rapid on-site synthesis of proteins in response to signaling cues. The spatiotemporally precise nature of the local translation process necessitates continual developments of technologies reviewed herein to visualize and map biomolecular components and the translation process with better spatial and temporal resolution, and with fewer artifacts. We also discuss approaches to control local translation, which can serve as a design paradigm for subcellular genetic devices for eukaryotic synthetic biology.

With more companies entering the realm of electric vertical take-off and landing (eVTOL), and governments enacting policies to support the development of low-altitude economies, the commercial potential of eVTOL is being recognized by the public. However, true commercialization is still a long way off. This article analyzes the technologies, product features, potential markets, and government policies related to eVTOL, and constructs a four-stage, four-layer Policy-Technology Roadmap (P-TRM) model to guide the R&D process of eVTOL. Then transform it into a system structural model, and the Decision-making Trial and Evaluation Laboratory (DEMATEL) method is used to identify several key nodes in the R&D process. Utilizing the Technology Adoption Life Cycle (TALC) theory for interpretation and analysis, the article concludes by proposing strategies in product, technology, and policy support for how eVTOL can successfully cross the chasm. This preliminary analysis of the development path, key nodes, and necessary measures for crossing the chasm provides insights for the R&D and commercialization of eVTOL.

The work aims to develop an electromagnetic shielding measurement methodology and design an electromagnetic shielding effectiveness test setup for thin sheet material testing. In brief, multiple shielding effectiveness standards are described and analyzed in the thin sheet material testing framework. Two types of the developed shielding effectiveness test probe in high and low-frequency ranges are validated comprehensively. Extensive descriptions and data of developed testing methodology are also reported.

Photovoltaic (PV) systems, which are renewable energy sources, are increasingly being utilized in distributed generation. To maintain a stable energy balance, energy storage systems such as batteries (BAT) play a vital role. Electric vehicles (EVs) offer a promising solution with rechargeable battery systems for operation. The BATs must maintain their state of charge within design boundaries, despite intermittent PV and load power fluctuations, and advanced power control and management techniques are essential for their effective operation. The article evaluates an intelligent controller that uses a Sliding Mode Control adaptive deep learning algorithm Convolutional Neural Networks (SMC-CNN) and a unique Strategy for managing supervisory power. (SPMS) for photovoltaic systems with battery energy storage for better regulation of DC bus voltage. SMC-CNN offers exceptional resilience and seamless functionality, minimizing fluctuations in DC bus voltage in the control strategy design requirements. The primary goals are maintaining a consistent power supply and ensuring continuous service by preventing system components from exceeding capacity. This study aims to enhance the control of DC bus voltage in the PV and battery system, with the primary significance focusing on the following aspects. The advanced SPMS has been created, incorporating control system constraints to enhance SOC balancing speed and reduce fluctuations in DC bus voltage. Power flow management involves optimizing energy flow between the PV system, battery system, and load while minimizing battery capacity requirements. The proposed SMC-CNN and SPMS are demonstrated through real-time simulation using Matlab/Simulink, as demonstrated in comprehensive case studies.

The publication presents an innovative tower cultivation device designed to significantly increase vertical farming efficiency. The device divides the cultivation system into separate chambers. One division corresponds to the different growth phases of the plants, while another reflects the daily variation in conditions. Each chamber presents slightly different conditions and cultivation patterns from the others. For the early stages, crops are grown horizontally in trays once they mature, transplanted into mobile cultivation towers. The closed circulation of ventilation and irrigation reduces water consumption by up to 95%. A unique separate day-night division optimises light, temperature and humidity conditions, mimicking natural growth patterns. This approach not only saves water and energy but also optimises cultivation in a three-dimensional space. The presented solution focuses on the often overlooked aspects of cultivating in vertical farms and makes this method of growing much more cost-effective and feasible to implement on a large scale.

It has been demonstrated that cancer cells that have survived cancer treatment may be more malignant than the original cancer cells. These cells are considered to be the main cause of metastasis in prognosis. A Nanog-overexpressing colon-26 (Nanog+colon26) was generated and its metastatic potential was confirmed to be enhanced, indicating higher malignancy. Extracellular vesicles (EVs) secreted from the cell line (Nanog+colon26EVs) were administered to mice at 5 μg nine times (three times per week for three weeks) via the tail vein (PBS was used as a control). Subsequently, Nanog+colon26 cells were administered to mice via the spleen, and the quantity of metastatic colonies in the liver was analyzed two weeks later. The results demonstrated that the administration of EVs suppressed metastasis. The enhanced phagocytic activity of macrophages observed in the group treated with Nanog+colon26EVs indicated the involvement of the immune system in the observed metastasis-suppressing effect. Small RNA sequencing was conducted to identify Nanog-dependent miRNAs that exhibited significant changes (Fc>=1.5 or Fc

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

Rapidly digestible starch can be obtained by gelatinization (cooking), cooking extrusion, use of small granule starch, breaking down starch granules, or by hydrolysis to maltodextrins. Resistant starch includes five groups: the first group is physically encapsulated starch within a food/polymer matrix, the second one is some native starch, the third one is recrystallized starch, the fourth one is chemically modified starch, and the fifth one is starch-lipid complexes. Starch digestion in the human body is also influenced by the degree of chewing, activity of α-amylase in the intestine, and transit time through the stomach and small intestine. Resistant starch or dietary fiber (DF) enriches specific bacterial groups located in the large intes-tine. They produce short chain fatty acids (SCFAs) and gases, causes the lowering of the pH, and inhibits pathogens. SCFAs are considered endogenous signaling molecules, acting through their free fatty-acid receptors 2 and 3 which can trigger the secretion of glucagon-like peptide-1 and peptide PYY, being released together following a meal to mediate postprandial satiety. A sufficient intake of DF reduces the risk of cardiovascular disease, coronary heart disease, stroke, hyperten-sion, colorectal cancer, and type 2 diabetes. Gluten matrix or phenolic compounds can lead to a low digestion rate of starch.

Glioblastoma (GBM) is the most common malignant brain tumor in adults. Despite advancements in treatment, the prognosis for patients with GBM remains poor due to its aggressive nature and resistance to therapy. CRISPR-based genetic screening has emerged as a powerful tool for identifying genes crucial for tumor progression and treatment resistance, offering promising targets for tumor therapy. In this review, we provide an overview of the recent advancements in CRISPR-based genetic screening approaches and their applications in GBM. We highlight how these approaches have been used to uncover genetic determinants of GBM progression and susceptibility to various therapies. Furthermore, we discuss ongoing challenges and future directions of CRISPR-based screening methods in advancing GBM research.

Concrete is more stable than filler as a false roof in a downward approach type infill quarry, but the mechanical model of a concrete false roof is not clear. As a result, there has been limited application. Therefore, it is necessary to establish the mechanical model of a concrete artificial false roof to enhance the stability of the downward approach infill quarry. This paper combines theoretical analysis, model derivation, finite element analysis and field application methods. Firstly, the basic assumptions of thin plate theory and elasticity mechanics are used as the premise to establish the differential equations of the deflection curve of the concrete thin plate false roof. Then, the three types of bending moment generation of the concrete thin plate false roof are explored. Secondly, the relationship between the location of dangerous surface and dangerous point in hard-supported weak-slab structure and soft-supported weak-slab structure is analyzed, and the type of uniform load and calculation model of concrete thin-slab false roof are improved. Finally, according to the established mechanical model of thin slab false roof, finite element analysis and field application were carried out. The results show that there are three types of deflection curve differential equations in the concrete thin slab false roof perpendicular to the strike, and three extreme points exist in the middle section of the thin slab and on both sides of the surrounding rock. The hazardous surface of the hard-supported weak-slab structure is present at the intersection of the encircling rock and the thin-slab fake ceiling, with the perilous point situated on the top of this surface. The hazardous surface of the soft-supported weak-slab structure can be found in the centre section of the thin-slab fake ceiling, with the perilous point being located at the bottom of this surface. Moreover, the damage mode for both structures is that of maximum tensile stress damage. Upon conducting a finite element analysis, the results indicate that the concrete's maximum tensile stress is significantly high.

The evaluation of wrinkles in deep-drawn fiber-based materials is crucial for the assessment of product quality and the optimization of manufacturing processes. Wrinkles, a common phenomenon in deep-drawing paper materials with high drawing depths, significantly impair the appearance and mechanical properties of the final product. The objective of this study is to identify the key process parameters affecting wrinkling and to deepen the understanding of their roles and interactions using wrinkle data for deep-drawn paper products. Image analysis techniques are employed, supported by a specially constructed darkroom platform to ensure uniform light intensity for capturing photographs. An automated program is developed for the detection and evaluation of wrinkle characteristics and distribution, which allows the free choice of the region to be detected and the representation of the wrinkle geometry not limited by the number. To enhance the precision of this program, the ellipticity is initially rectified for products without flanges, specifically cup-shaped deep-drawn products. The ellipticity is caused by the pronounced springback effect of the paperboard. The approach is employed to investigate the impact of material properties, blank holder force, drawing depth, drawing clearance, and punch speed on wrinkling formation after the deep drawing process. The findings reveal that the blank holder force and drawing clearance are critical factors in wrinkle formation, with higher forces generally leading to increased wrinkle numbers.

Hypertrophic cardiomyopathy (HCM) is a common form of cardiomyopathy in cats, and heart failure occurs as diastolic dysfunction progresses. HCM in cats is broadly classified as non-obstructive and obstructive hypertrophic cardiomyopathy, depending on the presence or absence of outflow tract obstruction. Measurement of the intraventricular pressure differences (IVPD) using Color M-mode (CMM) has attracted attention as a reliable diastolic index as it correlates with catheterization, the gold standard for assessment of diastolic performance. Since, IVPD is affected by the size of the heart, the intraventricular pressure gradient (IVPG) index, which is unaffected by heart size, is used by dividing IVPD be LV length. In the present study, CMM IVPG was used to non-invasively assess diastolic impairment in cats with obstructive hypertrophic cardiomyopathy. This study was conducted on ten control cats and 18 cats in the HCM group. Although no severe left atrial enlargement was observed in the HCM group, the Basal IVPG was significantly increased in the HOCM group compared to the control group. While IVPD typically suggests impaired diastolic function and reduced ventricular compliance, the significant increase observed in the HOCM group compared to controls may suggest an indirect elevation in left atrial pressure, likely secondary to left ventricular outflow tract obstruction. The increase in IVPG in HOCM, as shown in this study, is a pathological effect of left ventricular outflow tract obstruction that cannot be detected by conventional echocardiographic indices, and evaluating IVPG is useful for evaluating cardiac function from a different perspective than conventional methods.

Plant‒fungal associations often drive plant invasion success by increasing host growth, disease resistance, and tolerance to environmental stress. In this study, to determine whether the numerically dominant foliar endophyte Colletotrichum can directly enhance the resistance of the invasive plant Ageratina adenophora to disease and environmental stressors, we planted sterile A. adenophora seedlings, inoculated them with three endophytic fungal strains of Colletotrichum with distinct genetic backgrounds and compared their role in the resistance of A. adenophora to the pathogenicity of three foliar pathogens from the Didymellaceae family, as well as to abiotic stress, including drought and nutrient stress. We observed that the foliar endophyte Colletotrichum reduced photosynthesis-related physiological indicators, increased resistance-related indicators, and decreased the biomass of A. adenophora in the absence of pathogen attack, drought and nutrient stress. However, some endophytic Colletotrichum strains exhibit positive effects on resistance to certain foliar pathogen attacks, and some endophytes increase the biomass of A. adenophora under drought or nutrient stress. Our results revealed that there are certain positive effects of foliar Colletotrichum endophytes on A. adenophora in response to biotic and abiotic stresses, which may be beneficial for its invasion.

The medicinal herb Centaurium erythraea is well-known for its natural ability to treat digestive issues like dyspepsia and liver insufficiency by promoting the secretions of the liver and esophagus. This study aimed to analyze the effectiveness of Centaurium erythraea extracts in treating diabetes. Decoction and Soxhlet procedures were used to examine the extracts, with water serving as the solvent. The extracts were tested for antioxidant capacity, antimicrobial effects, and inhibitory effects on alpha-amylase activity. In comparison to the aqueous extract, the decocted extract had higher levels of polyphenols, total tannins, and anthocyanins, as well as more effective antioxidant capacities. Due to its reduction of alpha-amylase activity and enteric absorption of glucose, Centaurium erythraea has also shown considerable anti-hyperglycemic action.

Mixed plastic packaging waste sorting residues (MPO323) were treated by thermal pyrolysis to utilize pyrolysis oil and char. The pyrolysis oil was found to contain aromatic and aliphatic hydrocarbons. Chlorine and bromine contents were up to 40,000 mg/kg and 200 mg/kg, respectively. Additionally, other elements like sulfur, phosphorous, iron, aluminum, and lead were detected, which can be interpreted as impurities regarding the utilization of the oils by means of chemical recycling. The pyrolysis char showed high contents of potentially active species like silicon, calcium, aluminum, iron, and others. To enhance the content of aromatic hydrocarbons and to reduce the level of contaminants, the pyrolysis oil was reformed with the corresponding pyrolysis char to act as an active material in a fixed bed. The temperature of the reactor and the flow rate of the pyrolysis oil feed were varied to gain insights on cracking and reforming reactions as well as on the performance with regard to decontamination.

Evapotranspiration is a critical component of the hydrological cycle, and it has a decisive impact on the ecosystem balance in arid and semi-arid regions. The Yinchuan Plain, located in the Gobi of Northwest China, has a strong surface ET. In order to assess the ET pattern in this region, we obtained the ETa of Yinchuan Plain between 1987 and 2020 using the GEE platform. We employed the Surface Energy Balance Model (SEBAL), specifically geeSEBAL, to analyze the change pattern of ET over different seasons, years, and land types. The results show that: ① In spring, the daily ETa of the Yinchuan Plain is highest in the central lake wetland area, with a maximum value of 4.32 mm day-1. In summer, it is concentrated around the croplands and water bodies, with a maximum value of 6.90 mm day-1; In Autumn and winter, it is mainly concentrated around the water bodies and impervious areas, with maximum values of 3.93 and 1.56 mm day-1, respectively. ② From 1987 to 2020, the ET of the Yinchuan Plain showed an obvious upward and downward trend in some areas with significant land use changes, but the overall ET of the region remained relatively stable without dramatic fluctuations. ③ The evapotranspiration of different underlying land use types in the Yinchuan Plain region is as follows: water body&gt;cultivated land&gt;impervious&gt;grassland&gt;bare land. Our results showed that geeSEBAL is highly applicable in the Yinchuan Plain area. It allows for the accurate and detailed inversion of ET in the study area, which facilitates the study of regional hydrological cycle and water governance.

The use of omega-3 fatty acids (omega-3 FA) in the treatment of atopic dermatitis (AD) is an area of ongoing research. Some studies suggest that dietary supplementation with omega-3 FA can help manage symptoms of AD by reducing lesion severity, skin inflammation, dryness and itching, while other show no significant beneficial effect. The aim of this study was to evaluate the effect of omega-3 FA form fish oil in combination with GLA form blackcurrant seed oil in children with AD. This is a longitudinal, prospective, randomized, triple blind, placebo-controlled parallel clinical trial. The study was conducted during the 2-year period from autumn, winter, and spring avoiding the summer when AD usually improves. Children were randomized to receive the active study product (Mega Kid®) containing specific blend of omega-3 and omega-6 fatty acids or placebo. Primary outcomes were change in severity of AD measured using SCORing Atopic Dermatitis (SCORAD) patient oriented SCORAD (PO-SCORAD) and the difference in TCS use. Secondary outcomes were change in itch intensity, sleep quality and Family Dermatology Life Quality Index (FDLQI). Data were analyzed for 52 children (26 in the intervention group and 26 in the placebo group). In children receiving active product intention-to-treat analysis showed that after 4 months of treatment, there was a significant decrease in the SCORAD index (from median 42 to 25, p < 0.001) and use of topical corticosteroids (from median 30 to 10 mg/day, p < 0.001) but also significant improvement in itch, sleep quality and overall quality of life. Omega-3 fatty acids in combination with GLA and vitamin D has a great beneficial effect in treatment of atopic dermatitis in children. Therefore, we can conclude that supplementation with this specific combination could be considered a safe and effective intervention that can significantly reduce the severity of AD in pediatric patients.

This study evaluates the efficiency of biodegradable polyurethane foams as thermal insulation materials compared to conventional materials like expanded polystyrene (EPS). Key parameters analyzed include thermal conductivity, energy savings, CO2 emission reductions, and investment payback periods. Biodegradable polyurethane foams demonstrated a thermal conductivity of 0.022 W/(m·K), significantly lower than EPS's 0.035 W/(m·K), leading to higher energy savings. Calculations reveal an annual energy saving of 443,820 kWh for polyurethane foams, compared to 441,330 kWh for EPS. Financially, polyurethane foams save approximately €53,258.4 annually, while EPS saves €52,959.6. In terms of environmental impact, polyurethane foams reduce CO2 emissions by 88,764 kg annually, versus 88,266 kg for EPS. Despite the higher initial cost of polyurethane foams (€50/m² compared to €30/m² for EPS), the payback period is remarkably short at 0.094 years (1.13 months) compared to EPS's 0.057 years (0.68 months). These findings highlight biodegradable polyurethane foams as a superior option for thermal insulation, offering significant energy, financial, and environmental benefits.

The imperative to achieve carbon neutrality has driven significant advancements in the construction sector, particularly in the production and utilization of building materials. This paper explores innovative strategies and practices designed to reduce the carbon footprint of construction materials, with a focus on both the production processes and the application of sustainable materials. Key innovations include the development of low-carbon and carbon-negative materials, the integration of renewable energy sources in production, and the implementation of advanced recycling technologies. Case studies of successful projects demonstrate how these strategies can be applied in real-world scenarios, highlighting both the benefits and challenges encountered. The analysis also delves into the technical and economic aspects of these innovations, addressing the barriers to their widespread adoption and proposing solutions to overcome these challenges. Through a comprehensive examination of current practices and future trends, this paper aims to provide a roadmap for the construction industry to achieve carbon neutrality, contributing to broader climate change mitigation efforts and fostering a more sustainable built environment.

Mulberry leaves, when infected by pathogens, can suffer significant yield loss or even death if early disease detection and timely spraying are not performed. To enhance the detection performance of mulberry leaf diseases in natural environments and to precisely locate early small lesions, we propose a high-precision, high-efficiency disease detection algorithm named YOLOv8-RFMD. Based on improvements to You Only Look Once version 8 (YOLOv8), we first proposed the Multi Dimension Feature Attention (MDFA) module, which integrates important features at the pixel-level, spatial and channel dimensions. Building on this, we designed the RFMD Module, which consists of the Conv-BatchNomalization-SiLU (CBS) module, Receptive-Field Coordinated Attention (RFCA) Conv, and MDFA, replacing the Bottleneck in the model’s Residual block. We then employed Adown down sampling structure to reduce the model size and computational complexity. Finally, to improve the detection precision of small lesion features, we replaced the complete intersection over union (CIOU) loss function with the Normalized Wasserstein Distance (NWD) loss function. Results show that the YOLOv8-RFMD model achieves an mAP50 of 94.3% and an mAP50:95 of 67.8% on experimental data, representing increases of 2.9% and 4.3% respectively compared to the original model. The model size is reduced by 0.53 MB to just 5.45 MB, and the number of floating-point operations is reduced by 0.3 G to only 7.8 G. The improved model meets the deployment requirements of mobile embedded devices and can provide a theoretical reference for the automated spraying operations of mulberry leaves.

Starting from the fact that one of the global control strategies of the Permanent Magnet Synchronous Motor (PMSM), namely the Direct Torque Control (DTC) type control strategy, is characterised by the fact that the inner flux and torque control loop usually uses hysteresis ON-OFF type controllers and the oscillations introduced by them have to be cancelled out by the outer speed loop controller (which is usually a PI speed controller and whose performance is good around the global operating points and for relatively small variations of the external parameters and disturbances caused in particular by the load torque variation), while retaining the advantages of the DTC strategy, this paper presents the improvement of the performance of the PMSM sensorless control system using Proportional Integrator (PI), PI Equilibrium Optimizer Algorithm (EOA), Fractional Order (FO) PI, Tilt Integral Derivative (TID) and FO Lead-Lag for constant flux, and Sliding Mode Control (SMC) and FOSMC for variable flux. The performance indicators of the control system are the usual ones: response time, settling time, overshoot, steady-state error and speed ripple, plus another one given by the fractal dimension (FD) of the PMSM rotor speed signal, and the hypothesis that the FD of the controlled signal is higher when the control system provides better performance is verified. The paper also presents the basic equations of the PMSM, based on which the synthesis of integer and fractional controllers, the synthesis of an observer for estimating the PMSM rotor speed, electromagnetic torque and stator flux are presented. The comparison of the performance of the proposed control systems and the demonstration of the parametric robustness are performed by numerical simulations in Matlab/Simulink using Simscape Electrical and Fractional Order Modelling and Control (FOMCON). Real-time control based on an embedded system using a TMS320F28379D controller demonstrates the good performance of the PMSM sensorless control system based on the DTC strategy in a complete hardware-in-the-loop (HIL) implementation.

The double burden of malnutrition (DBM) is escalating in low- and middle-income countries (LMICs), including in Rwanda, most notably in urbanizing areas. The 2019-2020 Rwanda Demographic Health Survey (DHS) revealed 33% of children under 5 are stunted while 42% of women in urban areas are overweight or obese. This coexistence has contributed to a surge in non-communicable diseases (NCDs), particularly in secondary cities. Using the World Health Organization’s (WHOs) “double-duty action” (DDA) concept, this study aims to identify and evaluate interventions with double-duty potential in Rwanda, focusing on the districts of Rusizi and Rubavu. Guided by Hawkes et al.’s conceptual framework for identifying DDA entry points, a desk review of national policies pinpointed 4 programs with DDA potential: early childhood development (ECD) centers, the school feeding program, farmer field schools (FFS), and the provision of nutrition-sensitive direct support. In-person interviews with key stakeholders assessed their implementation and a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis informed context-specific recommendations for their improvement. Recommendations include targeting beliefs surrounding nutrition, improving trainings for community educators, enhancing parent – particularly father – involvement, and close follow-up. These findings offer actionable strategies for governments and nutrition stakeholders and may benefit similar interventions in other rapidly urbanizing LMICs.

Accurate traffic simulation models play a crucial role in developing intelligent transport systems that offer timely traffic information to users and efficient traffic management. However, calibrating these models to represent real-world traffic conditions accurately poses a significant challenge due to the dynamic nature of traffic flow and the limitations of traditional calibration methods. This article introduces a machine learning-based approach to calibrate macroscopic traffic simulation models using real-time traffic video stream data. By leveraging computer vision technologies to extract key traffic parameters from video streams, the approach demonstrated a notable improvement in aligning the generated data from the calibrated simulation model with car sensor data, achieving an average improvement of over 50% compared to the uncalibrated macroscopic model. Moreover, there was a substantial reduction in data drift for the machine learning model integrated into the virtual transport space using vehicle-to-everything technology, resulting in a more than fourfold decrease in the average absolute error of the model.

The Covid-19 pandemic was a challenge for the whole world and it had major secondary effects on humans and environmental health. The viral infection induced, in many situations, secondary bacterial infections, especially enteric infections by destabilizing the balance of the gastrointestinal microbiota. The large-scale use of antibiotics and biocides both for curative and preventive purposes has determined an increase in bacterial resistance and at the same time the possibility of pathogenic microorganisms’ multiplication and their dissemination to natural environments. Wastewater is the main vector of faecal microorganisms that favour their dissemination into natural aquatic ecosystems. The present paper aimed to analyze the effect of Covid-19 pandemic on the microbiological quality of wastewater from sewage treatment plants in Romania and its impact on receiving rivers. In order to highlight different and important areas of Romania, 3 cities from the east, center and west were selected for a microbiological evaluation of their WWTPs influent and effluent between ante-Covid-19 and Covid-19 pandemic peak period, when the Covid-19 pandemic had a direct impact on WWTPs microbial composition. Our study showed a higher contamination with fecal bacteria linked to a higher Covid-19 incidence. The increased usage of pharmaceutical compounds, at their turn, increased the number of resistant bacteria reaching the environment via WWTP effluents.

The hospital indoor environment plays a significant role in shaping the microbial exposures that humans encounter. Resistance to antibiotics is one of the mechanisms employed by bacteria to develop resilience against stress in indoor environments. The extensive usage of antibiotics has been a key factor in driving changes in the ecological function of antibiotic resistance genes (ARGs) and their acquisition by pathogenic bacteria. By integrating the 16S rRNA Illumina sequencing and high throughput-qPCR approaches with water and air dust samples across seven departments at Peking University Shenzhen Hospital, China, this study yielded intriguing findings regarding the department-specific variation, transmission, and correlation of bacteria, ARGs and MGEs within the hospital indoor environment. One notable observation was that the seasonal variation played a vital role in shaping the bacterial composition in the overall hospital indoor environment across seven studied departments. Nevertheless, a similar significant seasonal impact was only observed in the blood test room and emergency departments, rather than in the other five departments. Another intriguing finding was the correlation between ARGs and MGEs abundance. This correlation was evident in the overall hospital indoor environment, which was conversely not found in the emergency, pneumology and gynecology departments. Additionally, while there was no significant relationship that occurred between bacterial communities and ARGs/MGEs within the hospital, the gynecology department demonstrated a close link between bacterial communities and the presence of ARGs/MGEs. Notably, the gynecology department also stood out as an important source of bacteria and ARGs/MGEs for other departments. This study underscores the need for careful surveillance and monitoring of antibiotic resistance, particularly in Legionella spp. in man-made water systems. The findings also show the importance of monitoring and understanding the genetic elements such as Tp614 involved in gene transfer and recombination, as well as their impact on antimicrobial treatment efficacy.

: Tunnel instability and lining integrity are intimately tied to the creep properties of the surrounding rock. The acquisition of rock mass creep parameters is critical in ascertaining the appropriate timing for lining construction. Nevertheless, creep tests on rock specimens conducted in a controlled setting cannot be straightforwardly extrapolated to rock mass creep analysis. This study performs laboratory-based creep tests on mudstone samples and establishes the corresponding creep constitutive model. Integration of a Mohr-Coulomb element with the Burgers model in series serves to characterise the yield creep behaviour of the rock mass. Additionally, the research outlines a series of 100 orthogonal experiments utilising randomised creep parameters, and formulates a GA-BP neural network inversion model. Employing long-term deformation measurements from the crown and sidewalls of the project site, this study deduces the creep parameters of the mudstone in the investigated tunnel section and examines the prolonged deformation traits of the surrounding rock. Drawing on the deformation traits of the surrounding rock and the forces impacting the primary support and lining structures, this paper evaluates the earliest and latest viable lining casting periods and pinpoints an optimal timing interval for lining implementation. The methodologies employed herein can serve as a benchmark for analogous endeavors internationally.

Ulcerative colitis (UC) is a chronic inflammatory disease, the incidence of which is increasing worldwide. However, the etiology and pathogenesis of UC remains unclear. The n-butanol extract of pulsatilla decoction (BEPD) of the traditional Chinese medicine herbal formula has been shown to be effective in treating UC. We aimed to explore the molecular mechanism underlying the effects of BEPD on UC, in particular its effects on neutrophil extracellular trap (NET) formation by neutrophils. High-performance liquid chromatography was used to determine the principal compounds of BEPD. UC was induced in mice using dextran sodium sulfate, and mice were treated with 20, 40, or 80 mg/kg BEPD daily for seven days. Colonic inflammation was determined by assessing the disease activity index, histopathology, colonic mucosal damage index, colonic mucosal permeability, and pro- and anti-inflammatory cytokine levels. The infiltration and activation status of neutrophils in the colon were determined by analyzing the levels of chemokine (C-X-C motif) ligand (CXCL)1 and CXCL2, reactive oxygen species, Ly6G, and numerous NET proteins. Our results showed that BEPD improved the disease activity index, histopathology, and colonic mucosal damage index scores of mice with UC, and restored colonic mucosal permeability compared with untreated mice. The expression levels of the pro-inflammatory cytokines interleukin-1β, interleukin-6, and tumor necrosis factor-α in colon tissues were significantly decreased, while the expression levels of anti-inflammatory cytokines in colon tissues were significantly increased, exceeding those of control mice. In addition, BEPD reduce the expression of the neutrophil chemokines CXCL1 and CXCL2 in the colon tissue of mice with UC, reduced neutrophil infiltration, reduced reactive oxygen species levels, and significantly reduced the expression of NET proteins. BEPD also significantly reduced NET formation. The results of this study suggest that BEPD exerts therapeutic effects in a murine model of UC by inhibiting neutrophil infiltration and activation in the colon, as well as by inhibiting the expression of key proteins involved in NET formation and reducing NET formation, thereby alleviating local tissue damage and disease manifestations.

Facial appearance significantly influences several life outcomes, and a convex profile often prompts patients to seek treatment to enhance their facial esthetics. This study aimed to assess the facial appearance outcomes of combined orthodontic and orthognathic intervention compared to orthodontic camouflage treatment in convex facial profile individuals. The study sample comprised 36 consecutively selected Class II Division 1, convex facial profile patients. Two groups of 18 non-growing patients with similar characteristics were compared. Group A was treated with orthodontics and orthognathic surgery, whereas Group B with orthodontics exclusively. Pre- and post-treatment profile and frontal facial photographs were presented simultaneously to orthodontists, oral and maxillofacial surgeons, convex profile patients, and laypeople, asking them to assess changes in facial appearance. Considerable positive changes in facial appearance were perceived for Group A, compared to no changes for Group B, with a 17/100 VAS units difference. The rater groups demonstrated a high degree of consistency (ICC > 0.88). Multivariate analysis revealed significant differences in perceived changes between the two treatment groups (F = 14.63, P < 0.001, Pillai's Trace = 0.36, partial η2 = 0.36), with no significant effects from the rater group (P > 0.05). Similar results were evident when only profile photos were rated (P > 0.05). The combined orthodontic and surgical intervention is an efficient approach for the enhancement of facial appearance in convex profile cases. On the contrary, orthodontic treatment alone has no such impact. These findings should be properly communicated during patient consultation and considered for treatment planning.

Urban indicators characterize a specific urban space through calculated values, such as building coverage, building height, floor area ratio, and many others. Urban indicators established in spatial development plans should ensure the preservation of spatial order when introducing new construction investments. They should also harmonize with the existing urban structure, and even modernize it towards sustainable development. When determining these indicators, surrounding space is analyzed. Conventionally, building indicators in the existing space are determined based on available documents, usually 2D spatial data such as large-scale maps or cadastral maps. The aim of this research is to investigate the method of calculating building indicators using 3D urban building models that will be created from airborne Light Detection and Ranging (LiDAR) measurements. In the discussion of the results, indicators calculated based on LiDAR data are compared with calculated from 2D cadastral data. The calculated 3D indicators correlate with the classically calculated indicators. The accuracy of computed building area, volume, and other indicators depends on the LiDAR point cloud density and accuracy. The indicators calculated from 3D data align with new trends in defining Building Morphology Indicators (BMI).

Maintaining patient trust, providing quality care, and safeguarding patients' rights and safety, all of which require strong adherence to ethical principles. This study assessed the key differential factors influencing healthcare ethics (HCE) practice in two Ghanaian hospitals. This study employed an analytical cross-sectional design, utilizing simple random sampling to recruit 382 healthcare professionals. Bivariate analysis was conducted using Chi-square tests and T-tests, while Random Forest analysis was applied to identify variables of relative importance to HCE practice. The study found no significant differences in HCE knowledge or practices between the facilities. However, in both facilities, knowledge of HCE significantly influenced HCE practice, indicating that individuals with better knowledge of HCE were more likely to practice HCE. Further, the analysis identified age, knowledge, education, and facility type as the most relevant factors in general. In the sub-analysis, the key factors varied between facilities: for Facility A, age, knowledge, gender, and the intention to change profession were most relevant, while for Facility B, knowledge, education, gender, and age were the dominant factors. HCE training programs should be tailored to meet the unique needs of each facility to ensure effectiveness since factors influencing HCE may vary by facility.

A method for the synthesis of C4-benzhydryl functionalized 3,4-dihydropyridin-2-ones using complementary addition of benzhydryllithium and/or benzhydrylmagnesiate reagents to 2-pyridones, with high regioselectivity triggered by substituents, is described. A partially stereoselective cyclization was successfully demonstrated using TfOH and/or TIPSOTf as Brønsted and Lewis acids, respectively, leading to C6-phenyl functionalized 7,8-benzomorphanones. It is also shown that the use of functionalized -enelactams obtained with an active methoxy-substituted benzyl group at C3, enabled the preparation of a new C3-C6 bridged system within -lactam framework.

In recent years, rapid urbanization has intensified the need for sustainable solutions to address growing demands on urban infrastructure, climate change, and resource constraints. As smart cities strive to enhance citizen experiences by improving infrastructure, increasing accessibility, and accelerating economic growth, artificial intelligence (AI) and the Metaverse offer transformative potential for developing sustainable urban environments. However, integrating AI with the Metaverse for sustainable smart city development remains underexplored amid data management and processing challenges, privacy, security, and technological integration. This study addresses this gap by reviewing advancements in AI and its role within the Metaverse's architecture in smart cities. It explores how AI enables data analysis, enhances user experiences through computer vision and natural language processing, optimizes connectivity with 6G and Edge AI, strengthens security through blockchain, and manages the creation of digital twins. Through a comprehensive analysis of peer-reviewed publications and research projects, the review investigates how AI is integrated into key technologies to realize the Metaverse for sustainable smart cities. Specific applications in smart environments, mobility, energy, health, governance, and the economy are highlighted through AI-enabled use cases, offering a practical roadmap for implementing solutions to enhance citizens' quality of life, promote economic growth, and achieve sustainability. Lastly, future directions are discussed, addressing potential challenges by emphasizing interoperability and scalability and underscoring the need for robust data governance frameworks and AI ethics guidelines to address privacy, security, and ethical concerns. This approach aims to unlock the full potential of AI in enhancing the sustainability of smart cities within the Metaverse.

Heart failure with preserved ejection fraction (HFpEF) is a multifariousness syndrome, account-ing for over half of heart failure (HF) patients receiving clinical treatment. The prevalence of HFpEF is rapidly increasing in the coming decades as the global population ages. It is becoming clearer that HFpEF has a lot of different causes, which makes it challenging to find effective treatments. Currently, there are no proven treatments for people with deteriorating HF, or HFpEF. Although the pathophysiologic foundations of HFpEF are complex, excessive reactive oxygen species (ROS) generation and increased oxidative stress caused by mitochondrial dys-function seem to play a critical role in the pathogenesis of HFpEF. Emerging evidence from an-imal models and human myocardial tissues from failed hearts shows that mitochondrial aberra-tions cause a marked increase in mitochondrial ROS (mtROS) production and oxidative stress. Furthermore, studies have reported that common HF medications like beta blockers, angioten-sin receptor blockers, angiotensin-converting enzyme inhibitors, and mineralocorticoid receptor antagonists indirectly reduce the production of mtROS. Despite the harmful effects of ROS on cardiac remodelling, maintaining mitochondrial homeostasis and cardiac functions requires small amounts of ROS. In this review, we will provide an overview and discussion of recent findings on mtROS production, its threshold for imbalance, and the subsequent dysfunction that leads to related cardiac and systemic phenotypes in the context of HFpEF. We will also focus on newly discovered cellular and molecular mechanisms underlying ROS dysregulation, current therapeutic options, and future perspectives for treating HFpEF by targeting mtROS and associ-ated signal molecules.

This study investigates the impact of circular economy (CE) strategies on organizational resilience (OR) within the metal industry, focusing on a case study of a forging department in a large man-ufacturing company. The idea of the paper is to link the macroeconomic topic of circular economy (CE) with microeconomic and practical activities in the organization, exploring how CE principles can improve resource efficiency, sustainability, and organizational resilience. A systematic literature review and case study methodology were used to assess the relationship between CE and OR. The findings reveal that companies with higher circularity demonstrate better resilience, both in normal operations and during crises. Specifically, in the case study, the closure of the forging department, following a detailed analysis using the Inputs-Mediators-Outputs (IMO) model, emerged as the most sustainable option, yielding financial, environmental, and operational benefits. This decision aligned with the company’s long-term goals of energy efficiency and carbon neutrality. The research highlights the significance of integrating CE strategies with business processes to not only achieve sustainability but also to build a more adaptable and resilient organization. Future research should explore broader applications of this framework across different industries to strengthen the links between circular economy practices and organizational resilience.

Numerous varieties of Capsicum annuum L. with multiple valuable traits, such as adaptation to biotic and abiotic stress factors, can be found in south-east Romania, well known for vegetable cultivation and an important area of biodiversity conservation. To obtain useful information toward a sustainable agriculture, management and conservation of local pepper varieties, we analyzed the genetic diversity and we did deep molecular characterization using Whole Genome Resequencing (WGS) for variant/mutation detection. The pepper varieties used in the present study were registered by VRDS in the ISTIS catalog between 1974 and 2019 and maintained in conservative selection, however, no studies have been published yet using WGS analysis in order to characterize this specific germplasm. The genome sequences, annotation and alignments provided in this study offer essential resources for genomic research as well as for future breeding efforts using the C. annuum local varieties.

More than 90% of patients affected by mastocytosis are characterized by a somatic point mutation of c-KIT, which induces ligand-independent activation of the receptor and downstream signal triggering, ultimately leading to mast cell proliferation and survival. The most frequent mutation is c-KIT p.D816V, but other rarer mutations can also be found. These mutations often have a very low variant allele frequency (VAF), well below the sensitivity of common next-generation sequencing (NGS) methods used in routine diagnostic panels. Highly sensitive methods are developing for detecting mutations. This review summarizes the current indications on the recommended methods and on how to manage and interpret molecular data for the diagnosis and follow-up of patients with mastocytosis.

The European Parliament had adopted legislative resolution of 10 April 2024 on the proposal for a directive of the European Parliament and of the Council concerning urban wastewater treatment. The reduction of pollution in discharged treated wastewater in the parameters of BOD5, total ni-trogen and total phosphorus was emphasized. Based on these results, it stated that the impacts on the quality of lakes, rivers and seas in the EU are visible and tangible. At the same time, it was emphasized that the sector of urban wastewater removal and treatment is responsible for 0.8% of the total electricity consumption and about 0.86% of all greenhouse gas emissions in the entire EU. Almost a third of these emissions could be prevented by improving the treatment process, better use of sewage sludge and increasing energy efficiency, as well as a higher rate of use of renewable resource technologies. It is also necessary to better integrate treatment processes into the circular economy. Sludge management and water reuse is sub-optimal as too many valuable resources are still being wasted. This review article is focused on sustainable municipal wastewater treatment, innovative and new wastewater treatment processes and technologies (combined and hybrid processes, Anammox, etc. and their use in practice with the aim of increasing environmental and energy efficiency and reducing the carbon footprint. The research is focused on the possibilities of increasing the efficiency of energy processing of sludge, reuse of nitrogen and phosphorus, sludge and reuse of treated wastewater.

With the development of the energy sector based on renewable primary sources, structural changes are emerging for the entire national energy system. Initially, it was estimated that energy generation based on fossil fuels would decrease until its disappearance. However, the evolution of CO2 capture capacity leads to a possible coexistence for a certain period with the renewable energy sector. The paper develops this concept of coexistence of the two systems, with the positioning of green hydrogen not only within the renewable energy sector but also as a transformation vector for carbon dioxide captured in the form of synthetic fuels such as CH4 and CH3OH. The paper also analyzes the economic aspects related to price differences for energy produced in the two sectors, as well as their interconnection. The technical aspect, as well as the economic one, for storage through various other solutions besides hydrogen, has been highlighted. The development of the renewable energy sector and its demarcation from the fossil fuel energy sector, even with the transcendent vector represented by green hydrogen, leads to the deepening of dispersion aspects between the electricity sector and the thermal energy sector, a less mentioned aspect in current works but of great importance.

Backscatter communication, which transmits information by passively reflecting radio frequency (RF) signals, has become a focal point of interest due to its potential to significantly enhance the energy efficiency of Wireless Power Mobile Edge Computing (WPMEC) networks and extend the operational lifespan of terminal devices. However, there is little research on the integration of user cooperation in WPMEC scenarios within volatile network environments. In this paper, we propose a dynamic task offloading scheme for a Backscatter-assisted WPMEC system, which involves two mobile devices (MDs) and a Hybrid Access Point (HAP) with user cooperation. We formulate the energy efficiency (EE) maximization problem as a stochastic programming problem, considering the randomness of task arrivals and time-varying wireless channels. By leveraging Dinkelbach’s method and stochastic network optimization technique, we transform the problem into a series of deterministic sub-problems for each time slot, and convert the non-convex sub-problem into convex ones. We propose a low-complex EE maximization algorithm to solve the convex problems efficiently. Extensive simulations are conducted to validate the performance of our algorithm under various system parameter settings. Experiment results demonstrate that our algorithm not only outperforms the benchmark algorithms by approximately 23%, but also stabilize all queues within the MEC system.

This paper introduces an innovative approach that enables automated and precise prediction of the steel's chemical composition based on the desired Jominy curve. The microstructure, and in fact the presence of martensite, is decisive for the hardness of the steel, so the study considered the occurrence of this phase at particular distances from the quenched-end of the Jominy sample. Steels for quenching and tempering and case hardening were investigated. With representative collected dataset of hardness values from quenched-end of Jominy specimen, microstructure and chemical composition of steels, the complex regression model was made using supervised artificial neural networks. The balance between cost and required hardenability can be achieved through optimizing the chemical composition of steel. This model of designing steel with required hardenability can be of great benefit in the mechanical engineering and manufacturing industry. The model is verified experimentally.

With prosperous development and successful application of deep learning technologies in the field of remote sensing, numerous deep-learning based methods have emerged for synthetic aperture radar (SAR) automatic target recognition (ATR) tasks over the past few years. Generally, most deep-learning based methods can achieve outstanding recognition performance in condition that an abundant of labeled samples are available to train the model. However, in real application scenarios, it is difficult and costly to acquire and to annotate abundant SAR images due to the imaging mechanism of SAR, which poses a big challenge to existing SAR ATR methods. Thereby, SAR target recognition under the situation of few-shot, where only a scarcely few of labeled samples are available, is a fundamental problem that needs to be solved. In this paper, we put forward a new method named enhanced prototypical network with customized region-aware convolution (CRCEPN) to specially tackle the few-shot SAR ATR tasks. To be specific, We first develop a feature extraction network based on a customized and region-aware convolution, which can adaptively adjust convolutional kernels and their receptive fields according to each SAR image’s own characteristics as well as the semantical similarity among spatial regions, thus augmenting its capability to extract more informative and discriminative features. To achieve accurate and robust target identity prediction under the few-shot condition, we then propose an enhanced prototypical network which can improve the representation ability of the class prototype by properly making use of training and test samples together, thus effectively raising the classification accuracy. Meanwhile, a new hybrid loss is designed to learn a feature space with both inter-class separability and intra-class tightness as much as possible, which can further upgrade the recognition performance of the proposed method. Experiments performed on the moving and stationary target acquisition and recognition (MSTAR) dataset and the OpenSARShip dataset demonstrate that the proposed method is competitive with some state-of-the-art methods for few-shot SAR ATR tasks.

One of the relevant goals in forging technologies is simplifying the existing process and developing new processes that can retain the original or very close to the original dimensions and billet shape after the end of the deformation cycle. This study attempts to develop a forging equipment design that provides alternating cyclic loading; the alternate cyclic forging (ACF) method is proposed. To preliminary evaluate the ACF and study the plastic deformation behavior, numerical simulation via finite element modeling (FEM) was conducted using DEFORM-3D. The main attention was paid to the metal flow characteristics, effective strain and stress distribution, and the forging load. The ACF results in non-uniform metal flow with the formation of diagonal and vortex flows were demonstrated. Maximum effective strains and stresses zones are localized at two points of the billet contact with the surface of the tooling container and at two points of the interface between the punches. It was also assumed that reducing the contact area between the punch and the billet using separate semi-cylindrical punches can reduce the forging load. Preliminary finite element analysis (FEA) results of the proposed process after four successive steps of the deformation cycle confirmed the feasibility of its general implementation.

The climate change constitutes nowadays an enormous global threat for human health and environmental sustainability. The expanding world population and the increased global needs for food production have an important negative impact upon environment. Diet can link human health with environmental sustainability. Food production systems are closely related to anthropogenic greenhouse gas emissions and the aggravation of climate change, and current western type, animal-based, dietary patterns may lead to adverse environmental footprints. In the present narrative review, we address the interconnection of the Mediterranean diet (MD) with climate change and sustainability. MD is a highly recommended dietary intervention for the prevention and management of various endocrine and cardiometabolic diseases. Beyond its evidence-based, health-promoting effects, it also has beneficial environmental impact, reducing greenhouse gas emissions and enhancing biodiversity, food security and sustainability. Based on the evidence reviewed herein, MD should be incorporated within the framework of a “One Health” model, which involves the improvement not only of human health but also of planetary health and food system sustainability. Our review aims to provide a stimulus for health pro-fessionals to strongly recommend the implementation of MD under the current pressure of climate change, despite all barriers, targeting both human health preservation and the planetary well-being.

This study explores fault-tolerant consensus in leader-following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler-Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.

Multimodal emotion classification (MEC) involves analyzing and identifying human emotions by integrating data from multiple sources, such as audio, video, and text. This approach leverages the complementary strengths of each modality to enhance the accuracy and robustness of emotion recognition systems. However, one significant challenge is effectively integrating these diverse data sources, each with unique characteristics and levels of noise. Additionally, the scarcity of large, annotated multimodal datasets in Bangla limits the training and evaluation of models. In this work, we unveiled a pioneering multimodal Bangla dataset, MAViT-Bangla (Multimodal Audio Video Text Bangla dataset). This dataset, comprising 1002 samples across audio, video, and text modalities, is a unique resource for emotion recognition studies in the Bangla language. It features emotional categories such as anger, fear, joy, and sadness, providing a comprehensive platform for research. Additionally, we developed a framework for emotion recognition that employs a cross-modal attention mechanism among unimodal features. This mechanism fosters the interaction and fusion of features from different modalities, enhancing the model’s ability to capture nuanced emotional cues. The effectiveness of this approach was demonstrated by achieving an F1-score of 0.64, a significant improvement over unimodal methods.

Transportation contributes significantly to greenhouse gas emissions, with electrification offering a promising solution. This study evaluates the degradation of State of Health (SOH) over 2.5 years for electrified buses under different charging protocols: DC Fast charging and Flash charging. The vehicles’ models, charging protocols, and financial implications are discussed. High-level simulations reveal that after 2.5 years, the Flash charging vehicle’s SOH reaches 88.93%, while the DC fast charging vehicle reaches 89.46%, showing a 0.47% difference. This slight variance is attributed to Flash charging vehicles avoiding full charge/discharge cycles, reducing battery aging impact. Considering this minimal SOH degradation difference, the choice between DC Fast charging and Flash charging primarily hinges on capital expenditure disparities. Flash charging, with its lower initial battery capacity and reduced capital costs, presents a compelling alternative for city busoperators seeking to electrify their fleets.

Lirianthe delavayi has valuable ornamental and medicinal value, is an important economic tree, and has a long history of cultivation. As important regulatory molecules, miRNAs are involved in important physiological processes, such as the plant stress response, organ morphogenesis, hormone secretion, and signaling. In this study, based on miRNA sequencing analysis of wild and cultivated Lirianthe delavayi, we explored the differences in posttranscriptional regulation during the cultivation of Lirianthe delavayi from the aspect of miRNA molecular regulation. The results revealed the following: 1. A total of 365 miRNAs were sequenced and identified, and their first bases had obvious uracil (U) base preferences. Among them, 242 miRNAs were classified into 32 miRNA families; 2. Analysis of miRNA expression differences revealed that 39 miRNAs had significant expression differences between wild and cultivated populations; 3. Bioinformatics target gene prediction and target gene enrichment analysis of significantly differentially expressed miRNAs revealed that the target genes were significantly enriched in plant‒pathogen interactions, sphingolipid metabolism, defense responses, and ADP binding. 4. The plant‒pathogen interaction pathway involves seven differentially expressed miRNAs and 30 miRNA‒target gene regulatory pairs, which are involved mainly in pathogen signature molecule recognition and binding, signal transduction, and the regulation of disease resistance molecules or gene expression; Ath-MIR169g-p3_2ss7AG19GA, ath-MIR169g-p5_2ss7AG19GA, and ath-miR408-3p_L-3 are expressed only in wild population, and it is hypothesized that the domestication process from wild to cultivation species may be accompanied by the loss of disease resistance-related miRNAs. This study provides a reference for exploring the posttranscriptional-level regulatory mechanisms of adaptive changes in Lirianthe delavayi from wild to cultivated.

A model for enabling the production of lower carbon cement paste is proposed in this research. The model is based on predicting the strength of cement pastes with partial replacement of wheat straw ash (WSA) and silica fume (SF), two major wastes of agricultural and industrial production. The model is set up based on response surface methodology and Box-Behnken design, and included a suite of mechanical tests with distinct replacements following a micro an meso characterization. The model shows capability for predicting strength of any cement paste, including partial substitution of WSA and/or SF at any combination level with excellent accuracy, which is verified with three validation mixtures demonstrating maximum errors of less than 6% at the three ages. The analysis of the response surface evidences that any cement replacement in the range of 0-20% WSA and above 5% SF allows the reduction of the carbon footprint by maximizing the incorporation of both wastes. The proposed model can be used by setting the required strength of cement paste and calculating the maximum possible replacement, which should contribute to making the construction industry more sustainable by utilizing local waste.

Device to Device (D2D) is a pivotal technology in the next generation of communication, allowing for direct task offloading between mobile devices (MDs) to improve the efficient utilization of idle resources. This paper proposes a novel algorithm for dynamic task offloading between active MDs and idle MDs in the D2D-MEC (Mobile Edge Computing) system by deploying multi-agent deep reinforcement learning (DRL) to minimize the long-term average delay of delay-sensitive tasks under deadline constraints. Our core innovation is a dynamic partitioning scheme for idle and active devices in the D2D-MEC system, accounting for stochastic task arrivals and multi-time-slot task execution, which has been insufficiently addressed in existing literature. We adopt a queue-based system to formulate a dynamic task offloading optimization problem. To address the challenges of large action space and coupling of actions across time slots, we model the problem as a Markov Decision Process (MDP) and perform the multi-agent DRL through Multi-Agent Proximal Policy Optimization (MAPPO). We employ a centralized training with decentralized execution (CTDE) framework to enable each MD to make offloading decisions solely based on its local system state. Extensive simulations demonstrate the efficiency and fast convergence of our algorithm. In comparison with the existing sub-optimal results deploying single-agent DRL, our algorithm reduces the average task completion delay by 11.0% and the ratio of dropped tasks by 17.0%.

Background: Our study investigates the prevalence and causes of injuries among undergraduate dental students during clinical sessions. Methods: The study was conducted at the Department of Dentistry, National and Kapodistrian University of Athens, focusing on injuries reported from 2021 to 2024. Data were collected through self-reported questionnaires and clinical records. The primary variables assessed included the type of injury, the instrument involved, the clinical procedure being performed, and the immediate actions taken post-injury. Serological testing was conducted on both students and patients to assess the risk of bloodborne pathogen transmission. Results: The findings revealed a high prevalence of injuries, with needles being the most common cause, followed by burs and dental probes. The most frequent injury type was piercing, primarily affecting the fingers. Periodontal treatments, restorative procedures, and endodontic treatments were the main activities leading to injuries. Despite normal medical records for most patients treated by injured students, serological testing showed significant positivity rates for HCV and HBV. It is noteworthy that most injured students demonstrated their commitment to safety by adhering to recommended post-exposure protocols, including wound cleaning, disinfecting, and serological testing. Our study highlights the critical need for enhanced biosafety awareness and training among dental students to reduce injury risks. Conclusions: These findings underline the necessity for integrated safety protocols and continuous education to improve clinical practices and ensure student safety.

The extensive metabolic diversity of microalgae, coupled with their rapid growth rates and cost-effective production, position these organisms as highly promising resources for a wide range of biotechnological applications. These characteristics allow microalgae to address crucial needs in both the agricultural, medical, and industrial sectors. Microalgae are proving to be val-uable in various fields, including the remediation of diverse wastewater types, the production of biofuels and biofertilizers, and the extraction of various products from their biomass. For decades, the microalga Chlamydomonas has been widely used as a fundamental research model organism in various areas such as photosynthesis, respiration, sulfur and phosphorus metabolism, nitrogen metabolism, and flagella synthesis, among others. However, in recent years, the potential of Chlamydomonas as a biotechnological tool for bioremediation, biofertilization, biomass, and bio-products production has been increasingly recognized. Bioremediation of wastewater using Chlamydomonas presents significant potential for sustainable reduction of contaminants and fa-cilitates resource recovery and valorization of microalgal biomass, offering important economic benefits. Chlamydomonas has also established itself as a platform for the production of a wide va-riety of biotechnologically interesting products, such as different types of biofuels, and high-value-added products. The aim of this review is to achieve a comprehensive understanding of the potential of Chlamydomonas in these aspects, and to explore their interrelationship, which would offer significant environmental and biotechnological advantages.

The construction sector of the Kingdom of Saudi Arabia (KSA), valued at USD 152 billion and employing 2.54 million people by 2023, is crucial to its economy. However, it faces challenges such as delays, disputes, and cost overruns. This study aims to address these issues by implementing Building Information Modeling (BIM) in the KSA, based on an extensive literature review highlighting the role and significance of BIM in mitigating construction claims. BIM improves collaboration, communication, and data integration among stakeholders. Hence, this study proposes a comprehensive BIM package framework comprising Revit Architecture, Microsoft Project, and Cost-X to reduce claims effectively. Validated through a KSA claims case study with a USD 1,870,000 claims value and 360-day delay, the BIM package significantly reduced the claims value to USD 188,000 and saved 275 days. Interview sessions were conducted to validate the effectiveness of the BIM package; 95% favored the use of BIM, 86% supported NEC4 contract adoption alongside BIM, 100% acknowledged BIM's potential in reducing design errors, 95% were confident in the case study's accuracy, and 82% were satisfied with data accuracy. This study confirms that BIM is an effective approach for minimizing construction claims in the KSA.

This study explores the complexities of sport manager selection, investigating the impact of affirmative action, recruitment strategies, organizational culture, diversity initiatives in board selection, and career advancement insights from coaches' perspectives. To conduct this investigation, a purposive sampling technique was employed, selecting 65 prominent sports managers and coaches from Romania. Participants, aged between 35 to 58 years old, boasted an average of 10 to 20 years of sports experience and were chosen based on specific criteria, including academic qualifications. Data collection occurred over an extended period, spanning from fall 2022 to spring 2024, through semi-structured interviews with sport managers and coaches. The findings unveiled persistent challenges in effectively implementing affirmative action measures, as sport managers grapple with balancing the promotion of deserving candidates while maintaining continuity in board culture. Achieving meaningful diversity necessitates nuanced approaches that consider both candidate quality and cultural compatibility. Moreover, the study sheds light on coaches' perspectives when considering executive council positions, highlighting various pathways to career advancement. Recruitment practices prioritized informal methods, emphasizing board cohesion. Despite the recognized importance of diversity, challenges persist in selecting candidates solely based on demographic representation. The study provides valuable insights into promoting diversity and inclusivity within sports organizations' executive councils. Future research directions may include exploring longitudinal trends and delving into the qualitative experiences of underrepresented groups, with the aim of advancing understanding and promoting equity within sports organizations.

The goal of this research is to determine the optimal microwave-assisted sol-gel synthesis pa-rameters of TiO2 nanoparticles with the achievement of the crystalline TiO2 nanoparticles with the highest specific surface area and the lowest energy band gap. Titanium isopropoxide was used as a precursor to prepare the sol (colloidal solution) of TiO2, isopropanol as a solvent, acetylacetone for complexation, and nitric acid as a catalyst. Four samples of titanium dioxide were synthesized from the prepared colloidal solution in a microwave reactor at a temperature of 150 °C for 30 minutes and at a temperature of 200 °C for 10, 20, and 30 minutes. The phase composition of the prepared samples was determined by X-ray diffraction analysis (XRD) and Fourier-transform infrared spectroscopy (FTIR). Nitrogen adsorption/desorption isotherms were used to determine the spe-cific surface area and pore size distributions by Brunauer-Emmett-Teller (BET) method. The band gap energy values of the TiO2 samples were determined by diffuse reflectance spectroscopy (DRS). CrystallineTiO2 nanoparticles with the highest specific surface area and the lowest energy band gap were obtained for the TiO2 sample synthesized at 200 °C for 10 minutes.

Mesenchymal stem cells due to their multipotent ability are considered one of the best candidates to be used in regenerative medicine. The most used source of those stem cells long the last decades was the bone marrow, despite its limited cell resources and the painful and very invasive surgical treatment. Therefore, the scientific community investigated many alternative sources for the harvesting of these stem cell subpopulations. Adipose tissue attracted the biggest interest thanks to special features, such as great tissue abundance, easy availability, and in the end the large amount of positive mesenchymal stem cells. Once it was verified that these stem cell subpopulations possess the same bone marrow differentiation potential, it became evident that they would be the ideal candidate to be used in regenerative and tissue engineering applications. Even the regenerative use of these cells long become a sensitive point because not all the acquired phenotypes resulted in the best source for plastic procedures. As documented in the literature, the ideal fillers for regenerative is represented by stem cell population. Therefore, it became crucial to investigate any kind of biological mechanism on the differentiative ability of those mesenchymal stem cells, especially their regulative factors. One of the most studied and important regulators are the miRNAs. Indeed, miRNA play a crucial role in the differentiation process of adipose stem cell cultures isolated from patients or obtained by commercial cell lines toward osteocytes, chondrocytes, and adipocytes differentiated populations.

This review paper presents a comprehensive synthesis of current knowledge on the contamination of water systems by polycyclic aromatic hydrocarbons (PAHs). PAHs, organic contaminants characterized by two or more fused aromatic rings, are notably problematic due to their persistence, bioaccumulation, and significant health risks. The review commences with an examination of various sources of PAHs in aquatic environments, encompassing both anthropogenic activities, such as industrial discharges, urban runoff, and oil spills, and natural phenomena including volcanic eruptions and wildfires. Subsequently, the discussion shifts to the distribution patterns of PAHs within different aquatic ecosystems, with an analysis of factors that influence their transport. Considerable focus is placed on the entry mechanisms of PAHs into water systems and their interactions with diverse environmental matrices. Additionally, the ecotoxicological effects of PAHs on aquatic life are scrutinized, with particular emphasis on molecular, individual, and ecosystemic impacts. This includes an exploration of PAH bioaccumulation in aquatic organisms and their potential mutagenic and carcinogenic consequences. The review further addresses the challenges associated with detecting and quantifying PAHs in aquatic settings, reflecting on the advancements in analytical methodologies and the complexities introduced by their varied physicochemical properties. The paper concludes with a summary of existing regulatory frameworks and guidelines governing PAH contamination in water systems, underscoring the imperative for global collaboration in the monitoring and management of PAH pollution.

Injury to the peritoneum during surgery is followed by a healing process that frequently results in the attachment of adjacent organs by a fibrous mass, referred to commonly as adhesions. Because injuries to the peritoneum during surgery are inevitable, one must understand the mechanisms of adhesion formation to prevent its occurrence. This requires a thorough understanding of the molecular sequence that results in the attachment of injured peritoneum and the development of fibrous tissue. Recent data show that fibroblasts from the injured peritoneum may play a critical role in forming adhesion tissues. Therefore, identifying changes in gene expression patterns in the peritoneal fibroblasts during the process may provide clues to the mechanisms by which adhesion develops. This review presents many papers discussing genes implied in peritoneal adhesion.

The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The early part of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns have been quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology-air pollution relationships have been visualised/interpretated on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs elevated PM10 pollution in the valley. Two local meteorological patterns, the hot-dry-northwesterly wind conditions and the hot-dry-calm conditions, were found most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of eastward migrating continental high pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere.

Lake sediment records are of great importance for understanding the evolution of watershed environments. Various studies have been carried out to constrain the depositional ages of lake sediments and examine their physical, chemical, and biological characteristics, aiming to construct historical vegetation, environment and climate patterns in Chinese lake watersheds. In this study, we obtained relevant literature on lake sediment records by searching the key word 'age-depth' from the databases – Web of Science and China National Knowledge Infrastructure (CNKI, the largest Chinese academic database). We analyzed the literature based on its type (published in a Chinese/English journal or as a Master’s/PhD thesis), period of publication, journal (if published in a journal), key authors, study area, dating scale, and main aims. The results suggest that the lakes in the plateau regions are the most popular research topic typically covering 100–200 years (short-term) and 500–30,000 years (long-term). The literature focuses on a wide range of topics, from past environmental evolution in the watershed to lake ecology, and provides a solid foundation for better understanding regional climate change and the preservation of lake environments and ecosystems. In the future, resulting data from environmental reconstruction with lake sediments will be needed to integrate with emerging information processing technologies (e.g., artificial intelligence and meta-analysis), to disentangle the complex interplay between Earth surface processes and global climate change; furthermore, strengthening interdisciplinary collaboration will deepen our comprehension of man-land relationship and promote the sustainable management of lake ecosystems in the context of global climate change.

As one of the typical deposits in Sichuan-Yunnan-Guizhou Pb-Zn metallogenic province, the Daliangzi Pb-Zn deposit has a close genetic relation with the structural system of “black/fracture zone” formed under the action of NWW-approx. EW strike-slip structures in the metallogenic province, but the mechanism of rock and ore-controlling action of the structural system remains unclear. Based on detailed analysis of tectonite-mineralized alteration lithofacies of R1 “black/fracture zone”, the tectonite-mineralized alteration lithofacies zones can be divided into 4 types in succession outward from the Pb-Zn mineralization center, i.e., ① brecciated and stockwork-like Pb-Zn mineralization-complex breccia facies zone, ② stockwork-like Pb-Zn mineralization-simple breccia and cataclasite facies zone, ③ veined pyrite-sulfide-dolomitic cataclasite facies zone, and ④ fine-veined calcite-black carbonized dolomite facies zone; Cl- and SO42--rich high-temperature oxidizing ore-bearing fluid mixes with reducing fluid in Zone ① while migration and precipitation occur in Zone ④. With the evolution of ore-forming fluid, the homogenization temperature decreases from Zone ① to Zone ④, the salinity increases from Zone ① to Zone ② and then decreases to Zones ③ and ④, and the fluid density has little change on the whole; the contents of Zn, Pb, Cu, Ga, Ge, Cd, Ag, and other metallogenic elements, the Zn/Pb ratio, and the CaO/MgO mole ratio decrease gradually from Zone ① to Zone ④; and REE fractionation, calcilization, silicification, and pyritization enhance gradually from Zone ① to Zone ④. This series of changes are the product of diapirism (cryptoexplosion) of strike-slip structures and “black/fracture zone”, among which the second-order structures (F5, F100, and other faults) derived from NWW-approx. EW striking dextral shear-tension faults F1 and F15 control the brecciated and stockwork-like Pb-Zn mineralized complex breccia facies zones and the stockwork-like Pb-Zn mineralized simple breccia and cataclasite facies zones. Therefore, this paper establishes the zoning mode of tectonite-mineralized alteration lithofacies of “black/fracture zone” and proposes that Zones ① and ② are important prospecting criteria. conclusions.

The article presents several innovative systems developed through student laboratory projects, including two autonomous vehicles, a four-legged walking robot, an active ankle-foot orthosis, a ball on beam balancing mechanism, a ball on plate system, and a manipulator arm—all powered by pneumatic artificial muscles (PAMs). Fluidic muscles offer significant potential in various mechatronic systems, robots, and manipulators due to their flexible, lightweight nature and compliance. Their ability to produce smooth and adaptable motions is particularly beneficial in applications requiring natural and human-like movement, such as rehabilitation and assistive devices. Although PAMs powered control systems face challenges with nonlinear phenomena, their biologically inspired design holds promise for future applications across various industries. These may include innovative applicability in industrial, automotive, and aerospace sectors, as well as use in sports, medical aids, entertainment, and animatronics. Incorporating self-made laboratory systems actuated by PAMs into control systems education offers a comprehensive learning opportunity that combines theoretical concepts with hands-on experience. This approach develops the necessary skills of future engineers, expanding their understanding of technical principles and preparing them for future challenges in engineering practice.

Responding to changing value creation processes in the sheet metal working sec-tor, where the complexity and interchangeability of products challenge traditional dif-ferentiation strategies, this empirical analysis explores integrating service-oriented and data-driven business models as new paths to ensure competitiveness, especially for small and medium-sized enterprises (SMEs). This study aims to capture the current state and challenges associated with the implementation of these business models in this sector. The research was conducted through semi-structured interviews with SMEs in the industry. The findings indicate that service-oriented and data-driven business models are not yet widely adopted and that manufacturing companies re-quire support in their implementation. Fields of action were identified for the industry. These are "Creating awareness and understanding", "Recognizing added value", "In-creasing company maturity" and "Understanding the change process". Cooperation between science and industry is essential in tackling these fields of action to ensure the successful integration of such business models in manufacturing companies. This pa-per identifies challenges in the fields of action that companies must address through a structured approach promoting awareness, recognizing value, improving organiza-tional maturity, and understanding the change process to successfully implement ser-vice-oriented and data-driven business models.