A proposed low-temperature forging method aims to enhance stainless steel bearings by creating a martensitic subsurface layer, significantly boosting bearing fatigue life due to increased surface hardness. This technique induces beneficial residual stresses, particularly in axial bearings, streamlining their construction and improving machine elements. Challenges persist, especially with radial bearings, but simplicity in axial bearing forging promotes compact, resource-efficient facility construction. Future research will focus on applying this technique to axial bearing washers, potentially replicating success in other bearing components. Despite the energy ex-penditure for cooling during forging, the substantial increase in bearing fatigue life offsets this, enhancing overall longevity and reliability of critical machine components. Integration of this forging technique into bearing fabrication appears seamless, offering a promising trade-off be-tween energy use and enhanced performance.

The development of virtual models has recently been generalized in the field of complex mechatronic product design. Virtual models have various advantages such as: the systemic design approach, most often parametric, the implementation of extreme, expensive, and perhaps risky scenarios for the operation of the designed product, the testing of a large number of variants, etc. The main contribution of the paper consists of the development of an interface family called DeSeRoI (Dedicated Serial Robot Interface). Each member of the interface family integrates Simulink libraries and is created by the programmer in accordance with user requests. It follows that the interfaces composing the DeSeRoI family can have different levels of complexity depending on user needs and constraints. We are implementing a MATLAB-based application with user-provided configuration for serial robots in order to automatically visualize the kinematics data and simulation. Within MATLAB, two scripts are created responsible for generating Simulink models that compute the kinematics problem. One of the scripts (Main) saves information about the configuration of the robot and the other one (Generates_Simulink_Models) computes the kinematics problem. Different types of functions (software module) have been developed. Using these functions, the Simulink models result as modular entities. The automated approach eases user’s interaction and understanding of serial robots’ kinematics by performing the simulation procedure in a shorter amount of time and with higher efficiency, assuring a precise outcome despite the chosen parameters.

Despite energy-related financial concerns and the growing demand for sustainability, many energy efficiency measures are not being implemented in industrial practice. There are a number of reasons for this, including a lack of knowledge about energy efficiency potentials and the assessment of energy savings as well as the high workloads of employees. This article describes the systematic development of an expert system, which offers a chance to overcome these obstacles and contribute significantly to increasing the energy efficiency of production machines. The system employs data-driven regression models to identify inefficient parameter settings, calculate achievable energy savings, and prioritize actions based on a fuzzy rule base. Proposed measures are first applied to an analytical real-time simulation model of a production machine to verify that constraints required for the specified product quality are met. This provides the machine operator with the expert means to apply proposed energy efficiency measures to the physical entity. We demonstrate the development and application of the system for a throughput parts cleaning machine in the metalworking industry.

Epilepsy is a common neurological condition, typically diagnosed using Electroencephalogram (EEG). Large scale EEG datasets have recently been made publicly available, allowing the use of advanced Machine Learning (ML) algorithms to analyze EEG patterns associated with epilepsy. While most existing studies focus on identifying seizures in the EEG, few have tried to identify preictal EEG segments. Identifying preictal EEG segments are not only useful in developing early warning systems but also helps inform the course of treatment for the patient. In this study, we propose to represent EEG segments as images, instead of time-series data, and identify preictal EEG segments using a preexisting ML algorithm (YOLOv8) designed for image processing. Multiplexed images (containing the original EEG signal represented on a 2D grid, kurtosis, and spectral entropy) achieve the best accuracy of 95.75% on the dataset while images just containing the EEG signal result in an accuracy of 91.25%. Using only spectrograms, generated from the original EEG signal, results in an accuracy of 90.15%.

Strip steel surface defect recognition research has important research significance in industrial production. Aiming at the problems of defect feature extraction difficulty, slow detection speed and insufficient dataset, YOLOv5 is improved on the basis of YOLOv5, and YOLO-LFPD (Lightweight fine particle detection) model is proposed. By introducing the RepVGG (Re-param VGG) module, the robustness of the model to the surface defect features of strip steel is enhanced, and the expressive ability of the model is improved. FasterNet is used to replace the backbone network, which ensures the accuracy and accelerates the inference speed, making the model more suitable for real-time monitoring. The use of pruning, GA genetic algorithm with OTA loss function method further reduces the model size while better learning the strip steel defect feature information, thus improving the generalisation ability and accuracy of the model. The experimental results show that the introduction of the RepVGG module and the use of FasterNet can well improve the model performance, with a reduction of 48% in the number of parameters, a reduction of 13% in the number of GFLOPs, an inference time of 77% of the original, and an optimal accuracy compared with the network models in recent years. The experimental results on the NEU-DET dataset show that the accuracy of YOLO-LFPD is improved by 3% to 81.2%, which is better than other models, and provides new ideas and references for the lightweight strip steel surface defect detection scenarios and application deployment.

The paper interprets a comparison of two mostly used techniques of a field-oriented control for 6-phase electric drives, with their pros and cons, as well as their differences in construction and behaviour. Both of these approaches have been realized. Frequency and step responses analysis have been demonstrated with a 6-phase permanent magnet synchronous machine. Experimental results have been compared with simulations based on a mathematical model.

The ongoing challenge to ensure a sustainable and affordable energy supply forces industrial companies to implement appropriate measures. These measures typically lead to an increased system complexity, which has to be addressed during operation. Whereas existing approaches from the field of supervisory and optimal control appear to be capable of mastering this issue, these are still not adopted in industry. Therefore, this work presents a procedure model for the systematic development of application-oriented operating strategies for industrial energy supply systems. The procedure model combines research approaches from the fields of sequencing control and approximate MPC to extract rule-based operating strategies. By splitting the procedure model into five phases, expert knowledge can be integrated in a target-oriented manner. Subsequently to the description, the procedure model is exemplary applied to the example of an industrial heating supply system. Throughout an optimization study, the developed operating strategy is compared to a MPC strategy as well as a baseline strategy. Whereas the conventional MPC approach is the upper bound with regard to optimality, the developed operating strategy is able to generate comparable results. Compared to the baseline strategy, a relative reduction in operating expenses of 5.4 % to 37.0 % are achieved in this specific use case.

This paper presents laboratory devices on which experimental measurements were carried out to prove the validity of the assumption about the reduction of vibrations transmitted to the conveyor belt structure generated by the impact forces of falling material grains in the places of transfer or on the hoppers of conveyor belts. In order to limit damage to the conveyor belts caused by the impact of the sharp edges of material grains, conveyor belts are supported by impact rollers or impact rubber rods in the places of transfers and on the hoppers of belt conveyors. The flattened ends of the impact rollers are inserted into the grooves of steel brackets installed on the supports of the fixed conveyor idlers of a conventional design. In this paper, a special modification of the fixed conveyor idler is presented, which consists of inserting plastic brackets into the structurally modified roller axle holders of the fixed conveyor idler. Measurements were carried out on the first laboratory device, which showed that the specially modified fixed conveyor idler resulted in a higher damping of up to 15% of the impact forces of the falling weight on the rubberized hoop of the impact roller shell compared to the conventional fixed conveyor idler design. Measurements carried out on the second laboratory device show that the effective vibration velocity values detected at the points where the impact roller axis fits into the fixed roller table holder, i.e. points B and D, are higher than when using plastic brackets, up to 6% for a 108 mm diameter roller, compared to steel impact roller brackets.

In mining machines with friction discs, but also in multi-rope traction elevators, it is necessary to distribute the applied tensile load, generated by the weight of the cage and counterweight, evenly in all cross-sections of the load-bearing ropes. Hydraulic devices used for this purpose can operate on the principle of Pascal's law. The article presents a structural design, a 3D model and an implemented solution of a laboratory device capable of simulating a practical method of evenly distributing the total weight of the load into partial tensile forces of the same size acting on a selected number of load-bearing ropes. The laboratory equipment uses two pairs of three steel cables of finite length for the simulations. During the experimental measurements, tensile forces derived from the tractive force of the piston rods, pushed into the bodies of the hydraulic cylinders by the pressure of the hydraulic oil supplied through the pipeline under the pistons of the hydraulic cylinders, were detected. The resulting amount of hydraulic oil pressure in the hydraulic circuit influenced by different values of the hydraulic oil pressures in the hydraulic cylinders and by the pressure in the supply pipe was experimentally studied on the laboratory equipment. Simulations were also carried out in order to detect the hydraulic oil pressure in the hydraulic circuit caused by the change in the different magnitudes of the tensile forces in the ropes From the experiments carried out, it follows that with the appropriate choice of hydraulic elements and the design of the hydraulic circuit, the weight of the load, acting as the total pulling force in the ropes, can be evenly distributed (with a deviation of up to 5%) to all cross-sections of the load-bearing ropes. If the exact values of the hydraulic oil volumes under the pistons of all hydraulic cylinders are not known, it is not possible to calculate the pressure values in the hydraulic circuit when the valves of the hydraulic pipes are gradually opened.

(1) Background: Globally, about 600 million people are afflicted with diabetes, and one of its most prevalent complications is neuropathy, a debilitating condition. At present, the exploration of novel therapies for alleviating diabetic neuropathy-associated pain is genuinely captivating, considering that current therapeutic options are characterized by poor efficacy and significant risk of side effects. In the current research, we evaluated the antihyperalgesic effect of sildenafil (phosphodiesterase-5 inhibitor) – metformin (antihyperglycemic agent) combination and its impact on biochemical markers in alloxan-induced diabetic neuropathy in rats; (2) Methods: The study comprised a cohort of 70 diabetic rats and 10 non-diabetic rats which were submitted to hot, cold, and tactile stimulus tests. Morover, we investigated the influence of this combination on TNF-α, IL-6 nitrites and thiols levels in brain and liver tissues; (3) Results: The results demonstrated that all sildenafil-metformin combinations decreased the pain sensitivity in von Frey test, Hot-plate test and Cold-plate test. Furthermore, alterations in nitrites and thiols concentrations and pro-inflammatory cytokines (specifically TNF-α and IL-6) were noted following a 15-day regimen of various sildenafil-metformin combinations. (4) Conclusions: The combination of sildenafil and metformin has a synergistic effect in alleviating pain in alloxan-induced diabetic neuropathy rats. Additionally, the combination effectively decreased inflammation, inhibited the rise in NOS activity, and provided protection against glutathione depletion.

Our study aimed to assess sprinkler irrigation's impact on the activity of selected soil enzymes concerning nitrogen metabolism and oxidation-reduction processes in the soil with different doses of inorganic nitrogen fertilizers. The soil Alfisol was sampled from the experimental field of spring barley in the University Research Center in the central part of Poland in the moderate transitory climate during the growing seasons 2015–2017. The index resistance (RS) was derived to recognise the resistance enzymes of drought. In the maturity phase, nitrate reductase activity was at an 18% higher level in irrigated soils and the activity of other enzymes was higher in no-irrigated treatments by 25% in dehydrogenase, 22% in peroxydase 33% in catalase and 17% in urease case. The development stage of barley influenced nitrate reductase activity. Enzymatic activity has been changing in the examined years of the research, depending on the weather conditions. During the maturity stage, the soil's lower ammonium nitrogen content resulted from higher spring barley uptake due to drought stress. Irrigation probably contributes to increased leaching of nitrate in soil. The highest index of resilience was presented in the soil catalase activity.

Listeria monocytogenes is an emerging pathogen responsible for serious foodborne disease, listeriosis. Commensal gut microbiota is the first line of defense against pathogen internalization. Gut microbiome can be modified by prebiotic substrates, which are among others frequently added to food products and dietary supplement. Prebiotics should selectively support the growth of beneficial microbes and thus improve host health. Nevertheless, little is known about their effect on growth of L. monocytogenes. The aim of this study was to evaluate the growth ability of four L. monocytogenes strains, representing the most common serotypes, on prebiotic oligosaccharides: beta(1,3)-D-glucan, inulin, fructooligosaccharides, galactooligosaccharides, lactulose, raffinose, stachyose, 2´-fucosyllactose and mixture of human milk oligosaccharides as a sole carbon source. The results showed that only beta(1,3)-D-glucan was metabolized by L. monocytogenes. Therefore, the health-safety of beta(1,3)-D-glucan in respect to listeriosis development should be furthermore studied.

Exoskeleton technology has been shown to be useful for individuals with spinal cord injury (SCI), potentially facilitating their recovery of motor function and social reintegration. However, studies on the safety and usability of exoskeletons are limited. This study aimed to design a powered exoskeleton for SCI and evaluate its safety and usability. Ten healthy adults participated in this study. The prototype exoskeleton featured an adjustable frame, computer-controlled hip and knee joint actuators, and a gait-trigger sensor. The experimental actions included walking, standing, and sitting, with and without the prototype. Safety outcomes included adverse events, vital signs, numerical rating scale (NRS) scores for pain, discomfort, and fatigue, and prototype-human body clearance. Usability outcomes included donning and doffing times, subjective ratings, gait speed, stride length, and kinematic parameters of hip and knee joint angles. Safety outcomes showed no serious adverse events, stable vital signs, minimal NRS scores, and acceptable clearance. Usability outcomes showed high efficiency and received positive ratings. Kinematic parameters showed significant positive correlations between normal walking and walking with the prototype for both hip and knee joint angles, confirming its effectiveness in assisting walking. However, further device improvements and gait parameter tuning are necessary for future clinical application.

For the purpose of improve the sustainability of products sold in the EU, Digital Product Passports is a mandatory solution. These passports would systematically gather information about products, such as detailing the materials involved to aid recycling and remanufacturing efforts, or recording the emissions produced throughout the manufacturing process. The overall goal is the establishment of a circular economy in the EU. Current research on Digital Product Passports is focused on collating content for sector-specific applications. However, achieving sustainability goals through Digital Product Passports will require new methods and technical solutions for digital collaboration between supply chain participants, especially in the manufacturing sector. Collaborative work on Digital Product Passports requires trust and traceability in data and access management to ensure privacy over the data contained. One way to enable this securely and confidentially is through the use of blockchain technology, in which stored data cannot be concealed, which is key to the traceability of digital product data documentation. This paper therefore presents a concept for the implementation of generically applicable cross-industry blockchain-based digital product passports. To this end, generic supply chain processes have been abstracted and condensed into the architecture of smart contracts. Great attention is paid to the establishment of traceability as well as privacy through the selection of the blockchain technology Secret Network in combination with Gaia-X functionalities. An illustrative use case for digital product passports in manufacturing is used to demonstrate the applicability of the presented concept. In this use case information about the digital nameplate and carbon footprint is exchanged securely and confidentially in a multi-tenant supply chain network based on the Industry 4.0 infomation model of the Asset Administration Shell.

As the global population faces an increasing prevalence of physical disabilities, the challenge of motor rehabilitation has become increasingly urgent. Considering that approximately 15% of the global population lives with some form of disability, with a significant number having motor disa-bilities that greatly impact their quality of life, the integration of robotic technologies into rehabili-tation processes offers an opportunity for significant improvement in functional recovery and pa-tient autonomy. This analysis aims to evaluate the progress and challenges encountered in imple-menting robotic technology for the rehabilitation of patients with physical disabilities, highlighting the potential of emerging technologies such as exoskeletons, assisted training devices, and brain-computer interface systems in facilitating motor recovery. By examining relevant clinical studies, the analysis demonstrates the varied effectiveness of robotic therapies compared to traditional re-habilitation methods, while also highlighting the need for ongoing research to optimize care prac-tices and address challenges related to cost, accessibility, and treatment personalization. In con-clusion, robotic technologies represent a promising direction in motor rehabilitation, with the po-tential to revolutionize the care of patients with physical disabilities, significantly improving quali-ty of life and social integration.

To advance probiotic research, a comprehensive understanding of bacterial interactions with human physiology at the molecular and cellular levels is fundamental. Lacticaseibacillus rhamnosus LGG® is a bacterial strain that has long been recognized for its beneficial effects on human health. Probiotic effector molecules derived from LGG®, including secreted proteins, surface-anchored proteins, polysaccharides, and lipoteichoic acids, that interact with host physiological processes have been identified. In vitro and animal studies have revealed that specific LGG® effector molecules stimulate epithelial cell survival, preserve intestinal barrier integrity, reduce oxidative stress, mitigate excessive mucosal inflammation, enhance IgA secretion, and provide long-term protection through epigenetic imprinting. Pili on the cell surface of LGG® promote adhesion to the intestinal mucosa and ensure close contact to host cells. Extracellular vesicles produced by LGG® recapitulate many of these effects through their cargo of effector molecules. Collectively, the effector molecules of LGG® exert a significant influence on both the gut mucosa and immune system, that promotes intestinal homeostasis and immune tolerance.

Induction heating is a fast, reproducible, and efficient heating method used in various manufacturing processes. However, there is no established additive manufacturing (AM) process based on induction heating using wire as feedstock. This study investigates a novel approach to AM based on inductive heating, where a steel wire is melted and droplets are detached periodically using a two-winding induction coil. The process parameters and energy input into the droplets are characterized. The induction generator exhibits sluggish response to the excitation voltage, resulting in a lag in the coil current. The process is captured using a high-speed camera, revealing regular droplet formation and uniform size and shape when operated within an appropriate process window. Larger drops and increased spatter formation occur outside this window. The proposed method allows for the production of droplets with almost spherical shapes. Further analysis and characterization of droplet formation and energy input provide insights into process optimization and overall efficiency.

To improve efficacy and safety of sunscreen emulsions, UV‐filter skin permeation could be kept as low as possible by reducing UV‐filter content or changing emulsion composition. In this work, different lipid phase ratio (12, 14 and 16% w/w) were assessed for their ability to affect the technological and sensory properties of O/W emulsions in which bemotrizinol (BMTZ), a broad spectrum sunscreen agent, was incorporated free or loaded into nanostructured lipid nanocarriers (NLC) to reduce its release from the vehicle and, hence, its skin permeation. The following technological properties were evaluated in vitro by suitable methodologies: spreadability, viscosity, pH, occlusion factor, BMTZ release, sun protection factor (SPF). Sensory attributes were assessed by trained panelists in three different phases: before/during pick‐up, rub‐in, after application. Raising the lipid phase ratio led to an increase of viscosity and to a corresponding drop of spreadability while the incorporation of BMTZ‐loaded NLC determined a decrease of occlusion factor and an increase of SPF. No BMTZ release was observed from all emulsions. Sensory attributes were mainly affected by lipid phase ratio. These results suggest that lipid phase ratio and BMTZ incorporation into NLC could contribute to determine technological and sensory properties of O/W emulsions.

Modification of electrode surface with a selective layer gives the possibility to detect target ana-lytes of forensic interest. 3-(4-trifluoromethyl)-phenyl)-thiophene (ThPhCF3) was deposited on a graphite (G) electrode by electrochemical oxidation and characterized as a receptor for the recognition of synthetic stimulants (2-aminoindane, buphedrone, naphyrone). First, the structural characterization of the polymeric layer were obtained from Raman spectroscopy. Second, the electrochemical profiles of selected synthetic stimulants and their affinity to ThPhCF3/G-modified electrodes were studied using square wave voltammetry and electrochemical impedance spec-troscopy. The values of the adsorption constant show the importance of – PhCF3 groups in the interaction with synthetic stimulants, namely recognition by the formation of hydrogen bonds (Kads (buphedrone) < Kads (2-AI)) and interaction with aromatic H atoms (Kads (buphedrone) < Kads (naphyrone)). It was demonstrated that the polymeric layer derived from thiophene with – PhCF3 group is capable to increase the intensity of the electrochemical signal.

The effects of the climate crisis are affecting ecosystems at different scales and magnitudes. This paper focuses on a massive Mediterranean mussel die-off observed along the middle Italian Adriatic coast in the summer of 2022. We considered the possible environmental causes of this phenomenon and carried out a climatic analysis of the last decade. We performed field surveys in different locations along a 16 Km coastal stretch (from Martinsicuro (TE) on the South, to Grottammare (AP) on the North). The study area includes two marine Sites of Community Importance under the European Natura 2000 network. The mussels die-off has interested practically all the natural mussel-beds colonizing the study area. Mussels are sessile filter-feeding organisms inhabiting the intertidal zone, therefore, are highly exposed to variations in environmental conditions such as temperature and nutrient load. We discuss the possible causes of this die-off, proposing that high temperature and the scarce availability of food acted simultaneously as stress factors, generating local unsustainable living conditions for this species.

This study aimed to develop a state-of-the-art method for assessing chemical risks. The method combined desk research findings and the authors' practical knowledge to identify the major shortcomings in performing risk assessments at the workplace. Data were collected from nine SMEs across three sectors: agriculture, laboratory research, and conservation and restoration laboratories. The results of the discussions with the workers and on-site observations were used to develop the method to assess chemical risks. The method uses numerical factors to account for the level of conformity and the duration of exposure to support an estimation of the probability of an incident. The developed method was designed to enhance risk assessment practices and tackle common issues encountered by enterprises, including SMEs.

This study aimed to examine the chemical makeup and antioxidant properties of hydroalcoholic extracts obtained from Lonicera japonica Thunb. Thunb. (honeysuckle) flowers collected from two geographically distinct regions of Romania: a mountainous region (Făgăraș Mountainous, Brașov) and a coastal region (Black Sea, Constanța). Our research revealed that the extracts from these two regions differed significantly in terms of their total polyphenol, flavone, and phenolic carboxylic acid content, as well as their antioxidant activity. These results suggest that climatic factors play a crucial role in shaping the phytochemical profile and antioxidant activity of Lonicera japonica Thunb. Thunb. extracts. Therefore, these findings could potentially contribute to the development of standardized herbal preparations and nutraceutical products.

To fulfil a need of limitation automotive emissions the reduction of vehicle weight is widely recommended and achieved in many ways, both by the construction of individual elements of the vehicle, and by the selection of light materials including Al alloys. Connecting these elements with each other and with elements made of iron alloys can be realized, inter alia, by welding or stir welding. However, the quality of the welds obtained varies widely and depends on many design, operational and environmental factors. The present study focused on a review of various welding technics used to joint both similar and dissimilar Al alloys utilized in automotive industry, the effect of various process parameters on welds quality, and phenomena appeared in such welds..

The nozzle is the key element of the water jet generator for energy conversion. In order to explore the influence of the nozzle diameter on the pressure characteristics of the supercharged pulsed water jet plenum chamber, a supercharged pulsed water jet pressure acquisition system was established, and the Equations of motion and theoretical pressurization ratio equations of the supercharged pulsed water jet generator were established. The pressurization chamber pressure acquisition experiments under different nozzle diameters were carried out. The research results indicate that there is a critical nozzle diameter. When the nozzle diameter is less than the critical diameter, the pressure in the boost chamber is equal to the product of the driving pressure and boost ratio. As the nozzle changes, there is no significant change in the peak pressure and frequency of the boost chamber; When the nozzle diameter is greater than the critical diameter, there is a non-linear relationship between the boost chamber pressure and the driving pressure. As the nozzle diameter gradually increases, the actual boost ratio gradually decreases, and the peak pressure of the boost chamber further decreases. The nozzle diameter can no longer provide a load for the establishment of fluid pressure in the boost chamber. The research results provide a research basis for further controlling the pressure characteristics of the boost pulse water jet.

The silver fir (Abies alba Mill.) is among the most valuable conifers in Europe for ecological and economic reasons. In the course of history, primarily in the 20th century, its share in stands has been declining due to ill-suited management practices, especially clear-cut management, air pollution, and wildlife-induced damage. Based on recent knowledge of fir ecology and population dynamics, small-scale shelterwood and selection management have been introduced in fir stands, which have also stabilized them. Fir is an essential species for maintaining high stability and biodiversity, especially on planosols and in waterlogged habitats. Due to its shade tolerance and environmental flexibility, particularly at higher altitudes, it can coexist very well with many tree species in mixtures, which can increase the productive potential of stands. It can form stands of heterogeneous structure, ranging from single to multi-layer to selection. For its successful natural regeneration, it is essential to reduce cloven-hoofed game and thus prevent bud browsing damage. On the other hand, fir is a species relatively resistant to bark stripping and the spread of secondary rot compared to Norway spruce (Picea abies [L.] Karst.). During global climate change, fir is expected to shift to higher elevations with sufficient precipitation, while in the southern part of its natural range or at lower elevations, outside water-influenced habitats, it is likely to decline. This paper essentially reviews the description and distribution of the species, its ecological requirements, threats and diseases, habitat and stand conditions, and close-to-nature forest management practices with emphasis on ongoing climate change.

Berberis vulgaris (L.) has remarkable ethnopharmacological properties and is widely used in traditional medicine. The present study investigates B. vulgaris stem bark (Berberidis cortex) by extraction with 50% ethanol. The main secondary metabolites were quantified, resulting in a polyphenols content of 17.6780 ± 3.9320 mg Eq Tannic acid / 100 g extract, phenolic acids amount of 3.3886 ± 0.3481 mg Eq Chlorogenic acid / 100 g extract and 78.95 µg/g berberine. The dried hydro-ethanolic extract (BVE) was thoroughly analyzed using Ultra-High Performance Liquid Chromatography coupled with High-Resolution Mass Spectrometry (UHPLC–HRMS/MS) and HPLC and 40 bioactive phenolic constituents were identified. Then, the antioxidant potential of BVE was evaluated using three methods; our results could explain the protective effects of Berberidis cortex EC50FRAP = 0.1398 mg/mL, IC50ABTS = 0.0442 mg/mL, IC50DPPH = 0.2610 mg/mL compared to ascorbic acid (IC50 = 0.0165 mg/mL). Next, the acute toxicity and teratogenicity of BVE and Berberine - Berberine sulfate hydrate (BS) - investigated on Daphnia sp reported significant BS toxicity after 24 h; BVE revealed considerable toxicity after 48 hours and induced embryonic developmental delays. Finally, the anticancer effects of BVE and BS were evaluated on different tumor cell lines after 24 and 48 hours of treatments. The MTS assay evidenced a dose- and time-dependent antiproliferative activity, higher on BS than BVE. The strongest diminution of tumor cell viability was recorded on breast (MDA-MB-231), colon (LoVo) cancer, and OSCC (PE/CA-PJ49) cell lines after 48 h of exposure (IC50 &lt; 100 µg/mL). However, no cytotoxicity was reported on normal epithelial cells (HUVEC) and hepatocellular carcinoma (HT-29) cell lines. Extensive data analysis supports our results, showing a significant correlation between the BVE's concentration, phenolic compounds content, antioxidant activity, exposure time, and the viability rate of various normal cells and cancer cell lines.

The authors undertook pilot studies to assess the accuracy of the reverse engineering process of worn nonstandard spur gears (non-standardized modulus value, unusual profile/pressure angle, high or low teeth), using conventional techniques and measuring instruments. Eight gears were tested, the module of which ranges from 1.020 to 4.98 mm and the number of teeth from 13 to 42. The key parameter, the basic pitch, was selected to estimate the accuracy of the process. The goal is to determine the value of the profile angle. Eleven models were proposed to estimate the nominal tolerance field, using various types of random data distribution. The tested gears were made in IT grade: 6, 7, 8 and 9 according to DIN 3961. Vernier disc micrometers with various measurement ranges were used for research. It has been shown that the nominal module does not have to be treated as a random variable in the population. EIG (Equation of Identity) was developed, allowing conversion of any gear with specific values of geometric parameters into an identical gear with alternative values of these parameters. The directions and degrees of shifts of the estimated tolerance fields relative to the nominal field were determined. The most effective estimating model was selected in the context of the percentage filling of the nominal tolerance field, taking into account the symmetric Student-Fisher distribution with a confidence level of 60%. Further directions of the research activities were described.

The correct selection of the value of p is a complex and iterative procedure that requires experience in the interpretation of the obtained interpolated maps. Inverse Distance Weighting is a method applied to the porosities of the K and L hydrocarbon reservoirs, discovered in the Neogene (Lower Pontian) subsurface sandstones in the northern Croatia (Pannonian Basin System). They represent small and large data samples. Also a standard statistical analysis of the data was made, followed by the qualitative-quantitative analysis of the maps, based on the selection of different values of the power distance exponent (p-value) for the K and L reservoirs maps. According to the qualitative analysis, for a small data set, p-value could be set on 1 or 2 giving the most optimal result, while for a large data set, a p value of 3 and 4 could be applied. By quantitative analysis, for the case of small data p=2 is recommended, resulting in a root mean square error value of 0.03458, a mean absolute error of 0.02013 and a median absolute deviation of 0.00546. Oppositely, a p-value of 3 and 4 is selected as appropriate for a large data set, with root mean square errors of 0.02435 and 0.02437, mean square errors of 0.01582 and 0.01509 and median absolute deviations 0.00896 and 0.00444. Eventually for a small data set, it is recommended to use a p-value of 2, and for a large data set, a p-value of 3 or 4.

This study reports on the development of bio-based hydrophobic coatings for packaging papers through deposition of polyhydroxybutyrate (PHB) particles in combination with nanofibrillated cellulose (NFC) and plant wax. In a first approach, PHB particles in micrometer range (PHB-MP) were prepared through a phase-separation technique providing internally nanosized structures. The particles were transferred as a coating by dip-coating filter papers in the particle suspension, followed by sizing with a carnauba wax solution. This approach allowed partial to almost full surface coverage of PHB-MP over the paper surface resulting in static water contact angles of 105° to 122° and 129° to 144° after additional wax coating. In a second approach, PHB particles with submicron sizes (PHB-SP) were synthesized by an oil-in-emulsion (o/w) solvent evaporation method, and mixed in aqueous suspensions with 0 to 7 wt% NFC. After dip-coating filter papers in PHB-SP/NFC suspensions and sizing with a carnauba wax solution, static water contact angles of 112° to 152° were obtained. The intrinsic properties of the particles were analyzed by scanning electron microscopy, thermal analysis and infrared spectroscopy, indicating higher crystallinity for PHB-SP than PHB-MP. The chemical interactions between the more amorphous PHB-MP particles and paper fibers were identified as an esterification reaction, while the morphology of the NFC fibrillar network was playing a key role as binding agent in the retention of more crystalline PHB-SP at the paper surface, hence contributing to higher hydrophobicity.

Survival of Medulloblastoma (MB) depends on various factors, including the gene expression profiles of MB tumor tissues. In this study, we identified 967 MB survival related genes (SRBs) using the gene expression dataset of Cavalli et al. (2017) and the Cox proportional hazards regression model. Notably, the SRGs were over-represented on chromosomes 6 and 17, known for the abnormalities monosomy 6 and isochromosome 17 in MB. The most significant SRG was HMGA1 (high mobility group AT-hook 1), which is a known oncogene and a histone H1 competitor. High expression of HMGA1 was associated with worse survival, primarily in the Group 3γ subtype. The high expression of HMGA1 was unrelated to any known somatic copy number alteration. Most SRGs on chromosome 17p were associated with low expression in Group 4β, the MB subtype with 93% deletion of 17p and 98% copy gain of 17q. Pathway analysis showed that both chromosomes 6 and 17 included SRGs related to telomere maintenance and provide a rationale for testing telomerase inhibitors in Group 3 MBs. We conclude that HMGA1, along with other SRGs on chromosome 6 and 17 warrant further investigation as potential therapeutic targets in selected subgroups or subtypes of MB.

Landsat and Sentinel-2 acquisitions are among the most widely used medium-resolution optical data adopted for terrestrial vegetation applications, such as land cover and land use mapping, vegetation condition and phenology monitoring, and disturbance and change mapping. When combined, both data archives provide over 40 years, and counting, of continuous and consistent observations. Although the spatio-temporal availability of both data archives is well-known at the scene level, information on the actual availability of cloud-, snow-, and shade-free observations at the pixel level is lacking and should be explored individually for each study to correctly parametrize subsequent analyses. However, data exploration is time and resource consuming, thus is rarely performed a-priori. Consequently, the spatio-temporal heterogeneity of usable data is often inadequately accounted for in the analysis design, risking ill-advised selection of algorithms and hypotheses, and thus inferior quality of final results. Here we present precomputed data on the daily 1982‑2023 availability of usable Landsat and Sentinel-2 acquisitions across the globe, sampled at a pixel-level in a regular 0.18°-point grid. The dataset comprises separate Landsat- and Sentinel‑2‑specific data records, and is accompanied by a pixel-specific growing season information to facilitate data exploration. The dataset was derived based on freely available 1982-2023 Landsat surface reflectance (Collection 2) and Sentinel-2 top-of-the-atmosphere reflectance (pre‑Collection-1 and Collection-1) scenes from 2015 through 2023, following the methodology developed in the recent study on data availability over Europe [1]. Growing season information was derived based on 2001‑2019 time series of the yearly 500 m MODIS land cover dynamics product (MCD12Q2; Collection 6) [1]. As such, the dataset presents a unique overview of the spatio-temporal availability of usable daily Landsat and Sentinel-2 data at the global scale, hence offering much needed a-priori information aiding identification of appropriate methods and challenges for terrestrial vegetation analyses at local to global scale.

We investigate the structural correlation of non-covalent crown ether/H+/L-tryptophan (CR/TrpH+) host-guest complexes in the solution phase with those in the gas phase generated through electrospray ionization/mass spectrometry (ESI/MS) techniques. We perform quantum chemical calculations to determine their structures, relative Gibbs free energies, and infrared spectra. We compare the calculated infrared (IR) spectra with the IR multiphoton dissociation (IRMPD) spectra observed for the 18-Crown-6/TrpH+ complex by Polfer and co-workers [J. Phys. Chem. A 2013, 117, 1181−1188] for assigning the IR bands. We observe that the carboxyl group remains ‘naked’, lacking hydrogen bonding with the CR unit in the gas phase, and that this most stable conformer originates from the corresponding lowest Gibbs free energy structure in solution. Based on these findings, we propose that gas phase host-guest complexes directly correlate with those in solution, reinforcing the possibility of obtaining invaluable information about host-guest-solvent interactions in solution from the structure of the host-guest pair in the gas phase.

The theory and working principle of fabric phase sorptive extraction (FPSE) is presented that eloquently explains the mystery behind this new and powerful sample preparation technique. FPSE innovatively integrates the benefits of sol-gel coating technology and the rich surface chemistry of cellulose/polyester/fiberglass fabric, resulting in a microextraction device with very high sorbent loading in the form of an ultra-thin coating. This porous sorbent coating and the permeable substrate synergistically facilitate very fast extraction equilibrium. The flexibility of the FPSE device allows for direct insertion into original, unmodified samples of different origin. Strong chemical bonding between the sol-gel sorbent and the fabric substrate permits the exposure of FPSE devices to any organic solvent for analyte back-extraction/elution and to highly acidic or basic environments (pH 1-12) if required. A sol-gel derived sorbent, highly polar sol-gel poly(ethylene glycol) coating, was generated on cellulose substrates. Five cm2 segments of these coated fabrics were used as the FPSE devices for sample preparation using direct immersion. An important class of environmental pollutants, substituted phenols, was used as model compounds to evaluate the extraction performance of FPSE. The high primary contact surface area (PCSA) of the FPSE device and porous structure of the sol-gel coatings resulted in very high sample capacities and incredible extraction sensitivities for both the compound classes in a relatively short period of time. Different extraction parameters were evaluated and optimized. The new extraction devices demonstrated part per trillion level detection limits for substituted phenols, a wide range of detection linearity, and good performance reproducibility.

Quill mites of the family Syringophilidae are widely distributed parasites of birds inhabiting the interior of feather quills. In this paper, we provide detailed information on the host spectrum and distribution for six previously described species of syringophilines associated with starlings with new host and locality records. Additionally, we describe three new species, Aulonastus indonesianus Marcisova, Skoracki and Patan sp. n. from the Common Hill Myna Gracula religiosa Linnaeus in Indonesia (Java) and the White-necked Myna Streptocitta albicollis (Vieillot) in Indonesia (Celebes), Aulonastus anais Skoracki and Patan sp. n. from the Golden Myna Mino anais (Lesson) in Papua New Guinea, and Syringophiloidus poeopterus Skoracki and Patan sp. n. from the Abbott's Starling Poeoptera femoralis (Richmond) in Tanzania. Finally, we explore the host-parasite interactions within the system comprising starlings and syringophiline mites.

A new quinazolinone alkaloid, named peniquinazolinone A (1), as well as eleven known com-pounds, 2-(2-hydroxy-3-phenylpropionamido)-N-methylbenzamide (2), viridicatin (3), viridicatol (4), (±)-cyclopeptin (5a/5b), dehydrocyclopeptin (6), cyclopenin (7), cyclopenol (8), methyl-indole-3-carboxylate (9), 2,5-dihydroxyphenyl acetate (10), methyl m-hydroxyphenylacetate (11), conidiogenone B (12), was isolated from the endophytic Penicillium sp. HJT-A-6. The chemical structures of all compounds were elucidated by comprehensive spectroscopic analysis, including 1D, 2D NMR, and HRESIMS. The absolute configuration at C-13 of peniquinazolinone A (1) was established by applying the modified Mosher’s method. Compounds 2, 3, and 7 exhibited an op-timal promoting effect on the seed germination of Rhodiola tibetica at a concentration of 0.01 mg/mL, while the optimal concentration for compounds 4 and 9 to promote Rhodiola tibetica seed germination was 0.001 mg/mL. Compound 12 showed optimal seed-germination-promoting activity at a concentration of 0.1 mg/mL. Compared with the positive drug 6-benzyladenine (6-BA), compounds 2, 3, 4, 7, 9, and 12 could extend the seed-germination period of Rhodiola tibetica up to the 11th day.

Two novel inorganic–organic hybrid supramolecular assemblies, namely, (4-HNA)(18-crown-6)(HSO₄) (1) and (4-HNA)₂(18-crown-6)₂(PF₆)₂(CH₃OH) (2) (4-HNA = 4-nitroanilinium), were synthesized and characterized by infrared spectroscopy, single X-ray diffraction, differential scanning calorimetry (DSC), and temperature-dependent dielectric measurements. The two compounds underwent reversible phase transitions at about 255 K and 265 K, respectively. These phase transitions were revealed and confirmed by the thermal anomalies in DSC measurements and abrupt dielectric anomalies during heating. The phase transition may have originated from the [(4-HNA)(18-crown-6)]⁺ supramolecular cation. The inorganic anions tuned the crystal packings and thus influenced the phase-transition points and types. The variable-temperature X-ray diffraction data for crystal 1 revealed the occurrence of a phase transition in the high-temperature phase with the space group of P2₁/c and in the low-temperature phase with the space group of P2₁/n. Crystal 2 exhibited the same space group P2₁/c at different temperatures. The results indicated that crystals 1 and 2 both underwent an iso-structural phase transition.

From the wide range of engineering materials traditional Stellite 6 alloy exhibits excellent cavitation erosion (CE) resistance. In this work, the effect of nitrogen ion implantation of HIPed Stellite 6 on the improvement of CE resistance and both cobalt-rich matrix phase transformation due to nitrogen implantation and CE were stated. The CE resistance of stellites ion-implanted by 120 keV N+ ions two fluences: 5x1016 cm-2 and 1x1017 cm-2 were comparatively analysed with the unimplanted stellite and AISI 304 stainless steel. CE tests were conducted according to ASTM G32 with stationary specimen method. Erosion rate curves and mean depth of erosion confirm that the nitrogen implanted HIPed Stellite 6 two times exceeds the resistance to CE than unimplanted stellite, and has almost 10 times higher CE reference than stainless steel. The X-ray diffraction (XRD) confirms that HIPed Stellite 6 nitrogen ion implantation favours transformation of the ɛ(hcp) to γ(fcc) structure. Unimplanted stellite ɛ-rich matirx is less prone to plastic deformation than γ and consequently, increase of γ phase effectively holds carbides in cobalt matrix and prevents Cr7C3 debonding. This phenomenon elongates three times the CE incubation stage, slows erosion rate and mitigates the material loss. Metastable γ structure formed by ion implantation consumes the cavitation load for work-hardening and γ → ɛ martensitic transformation. In further CE stages, phases transform as for unimplanted alloy namely, the cavitation-inducted recovery process, removal of strain, dislocations resulting in increase of fcc phase. The CE mechanism was investigated using a surface profilometer, atomic force microscopy, SEM-EDS and XRD. HIPed Stellite 6 wear behaviour relies on the plastic deformation of cobalt matrix, starting at Cr7C3/matrix interfaces. Once the Cr7C3 losing their restrain, are debonding and removed. Carbides detachment creates cavitation pits which initiate cracks propagation through cobalt matrix, the loss of matrix phase and CE proceeds with a detachment of massive chunk of materials.

Introduction: The association of gene variants for interleukin 6(IL-6) (rs1800796), interleukin 10 (IL-10) (rs1800896) and tumor necrosis factorα (TNFα (rs1800629) with the occurrence of spontaneous preterm birth (PTB) was investigated to determine whether these genetic variants are a risk factor. Materials and methods: 199 blood samples from pregnant women who had given birth prematurely and 200 control blood samples were analyzed to determine single nucleotide polymor-phisms (SNPs) of genes for IL-6 (rs1800796), IL-10 (rs1800896) and TNFα (rs1800629). The control samples were samples from pregnant women with term delivery. Isolation of DNA was per-formed on mini-spin columns according to the manufacturer's protocol. The quality and purity of the isolated DNA were tested using a Qubit 3 fluorometer. Genotyping was performed with an ABI PRISM 7500 SDS using TaqMan SNP genotyping assays. The genotypes obtained were an-alyzed using the 7500 Software v2.3 package. Results: Carriers of the A/A genotype for the rs1800629 of the TNFα gene have 4.81 times greater chance of late-onset PTB compared to carriers of the G/G and A/G genotypes in the recessive inheritance model. The presence of the G/G genotype in the recessive inheritance model compared with the G/A and A/A genotypes for the rs1800896 of the IL-10 gene represents a potentially protective factor, with mothers in the term-birth group having an almost 2-fold lower odds of PTB in general and an almost 10-fold lower odds of early PTB. On the other hand, carriers of the A/G genotype of rs1800896 have a 1.54-fold higher chance of preterm birth in general and a 1.6-fold higher chance of late preterm birth in the super dominant inheritance model compared to the A/A and G/G genotypes in the group of mothers with PTB. In this study, no association was found between PTB and rs1800796 of the IL-6 gene. Conclusion: rs1800629 in mothers was associated with PTB. rs1800896 shows a potentially protective effect for the occurrence of PTB in this study. No association was found between PTB and rs1800796.

Intermittent fasting (IF) has been indicated as a valuable alternative to the classical caloric restriction dietary regimen for lowering body weight and preventing obesity-related complications such as metabolic syndrome and type II diabetes. However, is it effective? In this review article, we analyzed over 50 clinical studies in which IF, conducted by alternate day fasting (ADF) or time-restricted feeding (TRF), was compared with the caloric restriction approach. We evaluated the different roles of IF in treating and preventing human disorders such as metabolic syndrome, type II diabetes, and some types of cancer, as well as the usefulness of IF in reducing body weight and cardiovascular risk factors such as hypertension. Furthermore, we explored the cellular pathway targeted by IF to exert their beneficial effects by activating effector proteins that modulate cell functions and resistance to oxidative stress. In contrast, we investigated the concerns for human health related to the adoption of IF dietary regimen, highlighting the profound debate on weight loss regimens. We have examined and compared several clinical trials to formulate an updated conception regarding IF and its therapeutic potential.

This review focuses on Cu/TiO2 sequentially and Cu-TiO2 co-sputtered catalytic/photocatalytic surfaces leading to bacterial inactivation discussing their stability, synthesis, adhesion and antibacterial kinetics. The intervention of TiO2, Cu and the synergic effect of Cu and TiO2 on films prepared by a colloidal approach and other techniques is also reviewed leading to bacterial inactivation. Processes in aerobic media and anaerobic media leading to bacterial loss of viability on multidrug resistant (MDR) pathogens, Gram-negative (-) and Gram-positive(+) bacteria are described. Insight is provided for the interfacial charge transfer mechanism under solar irradiation occurring between TiO2 and Cu. surface properties of 2D TiO2/Cu and TiO2-Cu films are correlated with the bacterial inactivation kinetics observed in the dark and under light. The intervention of these antibacterial sputtered surfaces in health-care facilities leading to MRSA-isolates is described in the dark and under the actinic light. The synergic intervention of the Cu and TiO2 films leading to bacterial inactivation prepared by direct current magnetron sputtering (DCMS), pulsed direct current magnetron sputtering (DCMSP) and highly ionized pulse plasma magnetron sputtering (HIPIMS) is reported in a detailed way.

This short report extends our previous paper “Multiplicity of human scent signature” and transfers canine identification to digital processing of data. The question is whether current GCxGC-MS technology and computer-based identification can perform identification as well as canines. This would objectify the identification of persons. Working with digital scent samples enables the use of multiple scent signatures for more exact identification. More differently constructed signatures during the identification process may represent the key point in identification of persons in olfactronics. Several types of scent signatures were considered in this article. The digital scent signatures were constructed based on the relative contents of the chemical compounds in the samples and relative ratios of compounds in the samples. Further on the signatures were made from the parts of the original samples fractioned by the volatility of compounds and by the relative abundance of the compounds in the samples. These results confirm the scent multiplicity phenomenon in digital scent samples. Using differently constructed signatures may be the key point in identification of persons using digital scent samples. This approach enables a transition from subjectivity to objectivity and a change from physical olfactory to olfactronic processing of digital scent samples.

In the frame of our diversity-oriented research on multitarget small molecule anticancer agents, utilizing convergent synthetic sequences terminated by Sonogashira coupling reactions, a preliminary selection of representative alkyne-tethered vindoline hybrids was synthesized. The novel hybrids with additional pharmacophoric fragments of well-documented anticancer agents, including FDA-approved tyrosine-kinase inhibitors (imatinib and erlotinib) or ferrocene or chalcone units, were evaluated for their antiproliferative activity on malignant cell lines MDA-MB-231 (triple negative breast cancer), A2780 (ovarian cancer), HeLa (human cervical cancer) and SH-SY5Y (neuroblastoma) as well as human embryonal lung fibroblast MRC-5 served as reference non-malignant cell line for the assessment of the therapeutic window of the tested hybrids. The biological assays identified a trimethoxyphenyl-containing chalcone-vindoline hybrid (36) as a promising lead compound exhibiting submicromolar activity on A2780 cells with a marked therapeutic window. These results suggest that ovarian cancer might be considered as a prioritized target of treatment with 36.

Chronic joint inflammatory disorders such as osteoarthritis and rheumatoid arthritis have in common an upsurge of inflammation, and oxidative stress, resulting in progressive histological alterations and disabling symptoms. Currently used conventional medication (ranging from pain-killers to biological agents) is potent, but frequently associated with serious, even life-threatening side effects. Used for millennia in traditional herbalism, medicinal plants are a promising alternative, with lower rate of adverse events and an efficiency frequently comparable with that of conventional drugs. Nevertheless, their mechanism of action is in many cases elusive and/or uncertain. Even many of them have been proved effective in studies done in vitro or on animal models, there is a scarcity of human clinical evidence. The purpose of this review is to summarise the available scientific information on these joint-friendly medicinal plants, which have been already tested in human studies: Arnica montana, Boswelliaspp., Curcuma spp., Equisetum arvense, Harpagophytumprocumbens, Salix spp., Sesamumindicum, Symphytumofficinalis, Zingiberofficinalis, Panaxnotoginseng, Whitaniasomnifera.

In recent years, numerous topologies of single phase and three phase Field Excited Flux-Switching Machine (FEFSM) have been developed for several applications. Comparative study of three types of single-phase low-priced Field Excited Flux-Switching Machine (FEFSM) is presented in this paper. Both the conventional 8S/4P sub-part rotor design and 6S/3P salient rotor design have an overlapped winding arrangements between armature coil and field excitation coil that depicts high copper losses as well as results in increased size of motor. Additionally, FEFSM with salient structure of the rotor have high flux strength in the stator-core that has much impact on high iron losses. Copper consumption and iron loss being a crucial proportion in total machine losses. Therefore a novel topology of single phase modular rotor field excited FSM with 8S/6P configuration is proposed, which enable non-overlap arrangement between armature coil and FEC winding that facilitates devaluation in the copper losses. The proposed modular rotor design acquires reduced iron losses as well as reduced active rotor mass comparatively to conventional rotor design. It is very persuasive to analyze the best range of speed for these rotors to avoid cracks and deformation, the maximum tensile strength (can be measured with principal stress in research) of the rotor analysis is conducted using JMAG. A deterministic optimization technique is used to enhance the performance of 8S/6P modular rotor design. The electromagnetic performance of conventional sub-part rotor design, F1-A3-3P design and proposed novel-modular rotor design are analyzed by 3D-Finite Element Analysis (3D-FEA), includes flux linkage, flux distribution, flux strength, back-EMF, cogging torque, torque characteristics, iron losses and efficiency.

Manual material handling (MMH) significantly impacts worker health and productivity, often leading to musculoskeletal disorders (MSDs) primarily in the lower back. As a novel assistive technology, exoskeletons may serve as ergonomic tools to mitigate these work-related MSDs. It is essential to examine exoskeletons from the users’ perspectives before their widespread implementation in occupational settings. This study investigates the effectiveness of a passive back-support exoskeleton (BExo) in reducing perceived physical exertion and improving ergonomic safety in manufacturing context. Twenty-two college students were recruited to perform MMH tasks in a controlled lab environment, both with and without the BExo, followed by completing a survey questionnaire on various aspects of the BExo. Using ANOVA, the study analyzed biomechanical exertion across various body parts and tasks. The findings indicate that the BExo substantially alleviates discomfort in the low back, shoulders and knees, thereby, enhancing ergonomic posture and reducing fatigue. These results underscore the potential of passive exoskeletons to boost workers’ safety and efficiency, providing valuable insights for future ergonomic strategies in industrial setting.

Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. PREDATORR study (2014) shows that in Romania, 34,6% of adults aged 20-79 y/o are overweight, 31,4% are obese with a high risk of cardiometabolic complications, a number that puts almost 67% of Romania's population in the abnormal weight group. Our study aims to investigate the current staus of genetic foundation in metabolic disease associated with obesity, applied to a pilot group of patients specifically examining the impact of known polymorphisms and their haplotype of six food intake-regulating genes: leptin (LEP), leptin receptor (LEP-R), serotonin receptor (5HTR2A), ghrelin (GHRL), neuropeptide Y (NPY) and fat-mass and obesity-associated (FTO) with the following polymorphisms: LEP A-2548G, LEPR A-223G, 5HTR2A G-1439A, GHRL G-72T, NPY T-29063C, FTO A-T and body mass index (BMI). A notable link between the LEP-2548 rs7799039 gene's AG genotype and the risk of obesity was observed, particularly pronounced in males aged 40-49, with an approximately sevenfold increased likelihood of obesity. The 5HTR2A rs6311 AA genotype was associated with a higher BMI, not statistically significant. The FTO rs9939609 gene's AA genotype emerged as a significant predictor of obesity risk. Besides these significant findings, no substantial associations were observed with the LEPR, 5HTR2A, GHRL and NPY genes. Haplotype association analysis showed a suggestive indication of GRGMLA (rs7799039, rs1137101, rs6311, rs696217, rs16139, rs9939609 sequence) haplotype with susceptibility effect towards obesity predisposition. Linkage disequilibrium (LD) analysis showed statistically significant associations between LEP and LEPR gene (p = 1e-04), LEP and GHRL gene (p = 0.0047), GHRL and FTO gene (p=0.03). The outcomes of this study, to our knowledge, one of the very few on the Romanian population, aimed to be a starting point for further research on the targeted interventional strategies to reduce cardiometabolic risks.

The purpose of this longitudinal study was to determine the effects of a rowing training program on physical fitness and body composition in female breast cancer survivors (56.78 ± 6.38 years). Over six months, the participants (n=40) performed two training sessions per week for an average of 75 minutes, combining resistance and muscle strength exercises with rowing. To evaluate the impact of the program, physical fitness tests and anthropometric measurements were carried out before and after the training protocol. The results show statistically significant improvements in measures such as weight (-1.84 kg), BMI (-0.7 kg/m2), hip (-3.24 cm) and waist circumference (-2.45 cm). In addition, variables associated with physical fitness also improved including leg strength (3.04 cm), dominant handgrip strength (4.24 kgf), non-dominant handgrip strength (3.49 kgf), aerobic endurance (78.35 m) and muscle flexibility (3.96 cm). We can therefore conclude that a rowing-based exercise program is an effective strategy to improve physical fitness in this type of population, yielding improvements in both anthropometric measurements and basic physical capacity variables, essential factors for better health and quality of life.

The utilization of selective laser melting (SLM) for high entropy alloys (HEAs) holds significant promise in commercial applications, and substantial experimental research efforts have been directed toward this domain. To take advantage of the reported experimental data of SLM manufactured (SLM-ed) HEAs and reduce unnecessary experimentation, this study incorporates machine learning (ML) techniques for the phase and tensile properties prediction of SLM-ed HEAs, thus presenting a novel avenue for accelerating the discovery of new SLM-ed HEAs. Through the adjustment of material descriptors and machine learning models, a model has been developed with an impressive accuracy of 93.8% in distinguishing between face-centered cubic (FCC), body-centered cubic (BCC), and dual-phase (FCC+BCC). Additionally, optimized models have been devised for the prediction of tensile properties, namely ultimate tensile strength (UTS), yield strength (YS), and elongation (δ), achieving noteworthy MAPEs (mean absolute percentage errors) of 10.33%, 8.55%, and 28.48%, respectively. Furthermore, several HEAs were fabricated using SLM, and the experimental outcomes exhibited a favorable alignment with the predicted results. These efforts carry significant implications in advancing the utilization of SLM for HEAs.

Iron is an essential nutrient for humans and microbes, such as bacteria. Iron deficiency occurs commonly in critically ill patients, but iron replacement therapy is not considered during the acute phase of critical illness, since it increases iron availability for invading microbes and oxidative stress. However, persistent iron deficiency in the recovery phase is harmful with potential adverse outcomes such as cognitive dysfunction, fatigue and cardiopulmonary dysfunction. Therefore, it is important to treat iron deficiency timely and efficiently. This article reviews current knowledge about iron-related biomarkers in critically ill patients and provides possible criteria to guide decision-making for iron supplementation in the recovery phase of critical illness.

Nowadays, animal breeders look for effective innovations to care animal health. Use of probiotics, postbiotics, parabiotics and the other beneficial natural substances are dominated. Mundticin-like substance EM 41/3 is thermo-stable bacteriocin (postbiotic) with a broad antimicrobial spectrum. In this study its effect in broiler rabbits was assessed. Rabbits represent food-derived animal and they are also suitable animal model. The parameters tested were analyzed by validated methods. Administration of MLS EM 41/3 produced by non-autochthonous strain Enterococcus mundtii EM 41/3 lead to significant increase of parameter immunity-phagocytic activity, while it did not influence microbiota composition. It also did not influence blood biochemistry and no oxidative stress was noted. Moreover, higher growth parameters were noted and also stimulated hydrolytic activity. Finally, no negative influence on rabbit meat quality was noted. Postbiotic MLS EM 41/3 administration in feeding strategy seems to be contributing fact for rabbit health status maintaining.

Thrombosis after severe acute respiratory syndrome coronavirus 2 vaccination is a serious complication in patients who have a thrombophilic predisposition. In this case, a female patient with no family history of thrombophilia who had pediatric antiphospholipid syndrome (APS) developed deep vein thrombosis (DVT) when she was 6 years old; 6 months after receiving a second dose of the BNT162b2 vaccine, DVT reoccurred. The original thrombi were found in the right common iliac vein and the inferior vena cava, with concomitant left pulmonary infarction. The patient was treated with anticoagulants for 6 years after DVT onset, with subsequent treatment cessation for 5 years without recurrence. She received the BNT162b2 vaccine at 17 years of age, 1 week before a routine outpatient visit. Platelet factor 4 elevation was detected 14 days after the first vaccination, persisting for 5 months without thrombotic symptoms. Six months after the second vaccine dose, the DVT recurred and was treated with a direct oral anticoagulant. The vaccine exacerbated the patient’s APS by activating coagulation, causing thrombosis recurrence. Platelet factor 4 levels may indicate coagulation status. When patients predisposed to thrombosis are vaccinated, coagulation status and platelet activation markers should be monitored to prevent DVT development.

Lymphoma diagnoses in the U.S. are substantial, with an estimated 89,380 new cases in 2023, necessitating innovative treatment approaches. Phase 1 clinical trials play a pivotal role in this context. We developed a binary predictive model to assess trial adherence to expected average durations, analyzing 1,089 completed Phase 1 lymphoma trials from clinicaltrials.gov. Using machine learning, the Random Forest model demonstrated high efficacy with an accuracy of 0.7248 and ROC-AUC of 0.7701 for lymphoma trials. Importantly, this model maintained an accuracy of 0.7405 when applied to lung cancer trials, showcasing its versatility. A key insight is the correlation between higher predicted probabilities and extended trial durations, offering nuanced insights beyond binary predictions. Our research contributes to enhanced clinical research planning and potential improvements in patient outcomes in oncology.

The increasing emergence of multidrug resistant (MDR) pathogens causes difficult-to-treat infections, with long-term hospitalizations and high incidence of death, thus representing a global public health problem. To manage MDR bacteria bugs, new antimicrobial strategies are necessary, and their introduction in practice is a daily challenge for scientists in the field. An extensively studied approach to treat MDR infections consists in inducing high levels of reactive oxygen species (ROS) by several methods. Although further clinical investigations are mandatory on the possible toxic effects of ROS to mammalian cells, clinical evaluations are extremely promising, and their topical use to treat infected wounds and ulcers, also in presence of biofilm, is already clinically approved. Biochar (BC) is a carbonaceous material obtained by pyrolysis of different vegetable and animal biomass feedstocks, at 200−1000 °C in limited presence of O2. Recently, it has been demonstrated that BC capability of removing organic and inorganic xenobiotics is mainly due to the presence of persistent free radicals (PFRs), which can activate oxygen, H2O2 or persulfate in the presence or not of transition metals by electron transfer thus generating ROS, which in turn degrade pollutants by advanced oxidation processes (AOPs). In this context, the antibacterial effects of BC containing PFRs have been demonstrated by some authors against Escherichia coli and Staphylococcus aureus, thus giving birth to our idea of the possible use of BC-derived PFRs as a novel method capable of inducing ROS generation for antimicrobial oxidative therapy. Here, the general aspects concerning ROS physiological and pathological production and regulation, and the mechanism by which they could exert antimicrobial effects have been reviewed. The methods currently adopted to induce ROS production for antimicrobial oxidative therapy have been discussed. Finally, for the first time, BC-related PFRs have been proposed as a new source of ROS for antimicrobial therapy via AOPs.

The goal of the paper is to clarify the observed irrationality of decision making in conflict situations considered as one-step games of two players. To solve such situations, we consider the asymmetry in the relation of the players to their own rewards and the rewards of the opponents. Formalization of the decision-making process is based on recently developed non-commutative operators of multivalued logic algebra. The suggested method is applied to solve the well-known Prisoners’ dilemma game and the other situations of conflict, where it results in the expected strategies.

A specific HPLC method has been developed and validated for the determination of vanillyl butyl ether in cosmetic products. The extraction procedure with an isopropanol water 1:1 mixture is described. The method uses a RP-C-18 column with isocratic elution and a UV detector. The mobile phase consists of a mixture of acetonitrile and buffer (Na2HPO4 20mM in water) (30:70 v/v) with a variable flow rate. The method was validated with respect to accuracy, precision (repeatability and reproducibility), specificity and linearity. The procedure described here is simple, selective and reliable for routine quality control analysis and stability tests of commercially available cosmetic products.

The present study aims to evaluate the antibacterial activity of five commercially available essential oils (EOs): Lavender (LEO), Clove (CEO), Oregano (OEO), Eucalyptus (EEO), and Peppermint (PEO) against the most-known MDR Gram-positive and Gram-negative bacteria - Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922) and Pseudomonas aeruginosa (ATCC 27853) - alone and in various combinations. Gas Chromatography-Mass Spectrometry (GC-MS) analysis established their complex composition. Then, the antibacterial activity was investigated in vitro by diffusimetric antibiogram method, using sterile cellulose discs with Ø 6 mm impregnated with 10 µl of sample and sterile borosilicate glass cylinders loaded with 100 µl of sample; MIC (µg/mL) for each EO was calculated from IZD values (mm) measured after 24 hours. The following EO combinations were evaluated: OEO+CEO, CEO+EEO, CEO+PEO, LEO+EEO, and EEO+PEO. Then, the influence of each dual combination on 3 conventional antibacterial drugs – Neomycin (NEO), Tetracycline (TET), and Bacitracin (BAC) - activity was investigated. The most active EOs against S. aureus and E. coli were LEO and OEO (IZD = 40 mm). They were followed by the CEO and EEO (IZD = 20-27 mm); PEO exhibited the lowest antibacterial activity (IZD = 15-20 mm). EEO alone showed the highest inhibitory activity on P. aeruginosa (IZD = 25-35 mm). It was followed by the CEO, LEO, and EEO (IZD = 7-11 mm), while PEO proved no antibacterial action against it (IZD = 0 mm). Only one synergic action was recorded (OEO+CEO against P. aeruginosa); EEO+PEO revealed partial synergism against S. aureus and CEO+PEO additive behavior against E. coli. Two triple associations with TET showed partial synergism against E. coli, and the other 2 ones (with NEO and TET) evidenced the same behavior against S. aureus; all contained EEO+PEO or CEO+PEO. Most combinations reported indifference. However, numerous cases were of antagonism between constituents included in double and triple combinations, and EOs with the strongest antibacterial activities belong to the highest antagonistic combinations. A consistent statistical analysis supports our results, showing that EOs with moderate antibacterial activities could generate combinations with higher inhibitory effects based on synergistic or additive interactions.

In the digital era, enhancing the heritage resources of a tourist route means describing and networking them to promote their visibility and attractiveness. Prior studies mainly assess mountainous region’s natural resources through multi-indicator descriptive evaluation. This study aims to develop a comprehensive measurement of indicator’s value while assessing the tourism development potential of mountainous rural area. It concerns the main tourist route of the UNESCO M'Goun Geopark, located in the central High Atlas of Morocco. It also involves analyzing the criteria for choosing this destination by segmenting tourists' consumption experiences. Statistical analysis of the collected data reveals five dimensions of destination choice and four visitor groups. This article proposes to discuss findings and their applicability in terms of tourism destination management and decision-making, which can help local governments to rationally allocate tourism resources and land use.

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assisted. It is especially relevant for sensor nodes location in UWSNs. Global Positioning System (GPS) is not suitable for using in UWSNs because of the underwater propagation problems. Hence some localization algorithms based on the precise time synchronization between sensor nodes have been proposed which are not feasible for UWSNs. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme base on the Particle Swarm Optimization (PSO) algorithm to decrease the localization error. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence in this algorithm, we use a small number of mobile beacons to help achieve location without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

Nowadays, the growing concern about improving thermal comfort in textiles, asphalt pavements and buildings has stimulated research into phase change materials (PCMs). However, the incorporation of PCMs directly causes mechanical impacts. Therefore, this study herein reported focuses on designing coaxial phase change fibres using commercial cellulose acetate (CA) or recycled CA obtained from cotton fabrics (CAt) as a coating and polyethylene glycol (PEG) 2000 as a core. The phase change fibres (PCF) were produced by wet spinning, varying the parameters: (i) CA concentration, molecular weight and source (virgin versus recycled); and (ii) PEG concentration and ejection. For phase change recycled fibres (PCFt), PEG concentration and ejection were varied. The fibres were assessed for their optical, chemical, thermal and mechanical properties. Bright-field microscopy images and Scanning Electron Microscopy (SEM) micrographs proved the coaxial structure. Fourier Transform Infrared spectroscopy (FTIR) confirmed the presence of PEG in the core. Thermogravimetric Analysis (TGA) proved the ability of PCFs to tolerate high temperatures. Differential Scanning Calorimetry (DSC) attested to the presence of PEG2000 peaks, since their melting points were close to those of virgin PEG2000, with a slight change in the PCFs and PCFts caused by the protective sheath of CA and CAt.

Pulmonary Embolism (PE) is the obstruction of blood arteries in the lungs by a blood clot. The mortality risk for PE is approximately 30%. Detecting pulmonary embolism in the segmental arteries of the lung is more challenging than in the main arteries and is very prone to being missed. A computer-based approach was created in this work to automatically identify pulmonary embolism in the segmental arteries using computed tomography images. The system's infrastructure includes an enhanced Mask R-CNN deep neural network that has been trained with images containing PE. The network accurately identifies the location of the pulmonary embolism on the computed tomography picture and successfully extracts its borders. The investigation was conducted by generating a local dataset. The study's performance was evaluated using pulmonary embolisms identified manually by the expert radiologist. The sensitivity, specificity, accuracy, dice coefficient, and Jaccard index values for 2130 pictures were 96.4%, 93.5%, 96.1%, 0.96, and 0.90, respectively. The improved Mask R-CNN model has demonstrated superior performance when compared to the traditional Mask R-CNN and U-Net models. This high-performance technology is designed to identify pulmonary embolism and will aid professionals in assessing the size of the embolism.

Shafts with a stepped shoulder are particularly well known in the field of drive technology. In combination with a form-fit shaft–hub connection, the shaft shoulder fixes the hub on the shaft as well as the absorption of the axial forces. With profiled shafts, there is a notch overlay in the shaft shoulder, involving the shaft shoulder and profile. If the hub is also connected with the profiled shaft, the hub edge acts as an additional notch in the shaft shoulder area. The multiple resulting notches have not previously been part of research activities in the field of innovative trochoidal profile connections. Compared to conventional positive-locking connections, such as the keyway connection or the involute splined shaft profile, the favourable features of trochoidal profiles have only been based on connections with smooth shafts without a shoulder in previous studies. Accordingly, this article addresses the numerical and experimental investigations of trochoidal profile connections with offset shafts for pure torsional loading. Focusing on a hybrid trochoid with four eccentricities and six drivers, a well-founded numerical and experimental investigation was carried out with numerous fatigue tests. In addition, the influence of a shaft shoulder was also demonstrated on simple epi- and hypotrochoidal profiles.

Bixonimania, a rare hyperpigmentation disorder characterized by a distinctive pink hue on the eyelids, presents a significant diagnostic challenge due to its unique presentation and limited research. This study explores the application of machine learning algorithms for bixonimania detection by analyzing millions of images of individuals exposed to blue light (500-700 nm spectrum). Our findings suggest a potential link between blue light exposure and bixonimania, affecting roughly 1 in 90,000 individuals. The proposed machine learning model achieved an accuracy of 92% in detecting bixonimania based on eyelid hue analysis. This study paves the way for further exploration of bixonimania's underlying causes, improved diagnostic tools, and potential treatment options.

Pyrethroid pesticides (PYRs) as the third most widely used pesticides, following organophosphorus and carbamate pesticides, which are of significant importance in the analysis and detection of vegetables. However, the current pretreatment technology for PYRs confronts challenges of difficult separation and low enrichment efficiency, resulting in a cumbersome and time-consuming pretreatment process with poor selectivity. Here, a simple and efficient magnetic solid-phase extraction (MSPE) strategy was developed to simultaneously purify and enrich five PYRs in vegetables, with the magnetic covalent organic framework nanomaterial COF-SiO2@Fe3O4 as an adsorbent. The COF-SiO2@Fe3O4 was prepared by a simple solvothermal conditions method, using Fe3O4 as magnetic core, benzidine and 3,3,5,5-tetraaldehyde biphenyl as two building units. COF-SiO2@Fe3O4 could effectively capture the targeted PYRs by virtue of its abundant π-electron system and hydroxyl groups. The impact of various experimental parameters on extraction efficiency was investigated to optimize the MSPE conditions, including adsorbent amount, extraction time, elution solvent type and elution time. Subsequently, method validation was conducted under the optimal conditions in conjunction with gas chromatography-mass spectrometry (GC-MS). Within the range of 5.00–100 μg·kg-1 (1.00–100 μg·kg-1 for bifenthrin and 2.5–100 μg·kg-1 for fenpropathrin), the five PYRs exhibited a strong linear relationship, with determination coefficients ranging from 0.9990 to 0.9997. The limits of detection (LODs) were 0.3–1.5 μg·kg-1, and the limits of quantification (LOQs) were 0.9–4.5 μg·kg-1. The recoveries were 80.2–116.7% with relative standard deviations (RSDs) below 7.0%. Finally, COF-SiO2@Fe3O4, NH2-SiO2@Fe3O4 and Fe3O4 were compared as MSPE adsorbents for PYRs. The results indicated that COF-SiO2@Fe3O4 was an efficient and rapid selective adsorbent for PYRs. This method holds promising prospects for the determination of PYRs in real samples.

An increased demand for natural products nowadays most specifically probiotics (PRO) is evident since it comes in conjunction with beneficial health effects for the consumers. In this regard, it is well known that encapsulation could affect positively the PRO's viability throughout food manufacturing and long-term storage. This paper aims to analyze and review various multilayer strategies for encapsulation of PRO. Double-layer encapsulation of PRO by electro-hydrodynamic atomization or electrospray technology has been reported along with layer-by-layer assembly and water-in-oil-in-water (W1/O/W2) double emulsions to produce multilayer PRO-loaded carriers. Finally, their applications in food products are presented. The resistance (cover material) and viability of (PRO) to mechanical damage, during gastrointestinal transit and shelf life of these trapping systems are also described. The PRO encapsulation in double and multiple-layer coatings combined with other technologies can be examined to increase the opportunities for new functional products with amended functionalities opening a novel horizon in food technology.

Green spaces localized in cities create favourable environmental conditions for Ixodes ricinus, the most widespread and important vector of tick-borne pathogens in Central Europe. In this study, we described the prevalence of Borrelia burgdorferi s.l. and Babesia species found in mono- and double infections among I. ricinus ticks occurring in urban areas of the city of Poznań, west-central Poland. Two tick groups were examined: (i) a group of 1,029 host-seeking ticks (460 nymphs, 289 females, and 280 males and (ii) a group of 1,268 engorged female ticks removed from 1,115 tick-infested animals, dogs and cats. The overall prevalence of B. burgdorferi s.l. found in host-seeking ticks was almost two-fold higher in comparison to ticks derived from pets (8.7 vs. 4.7%, respectively, χ2 test, P = 0.001). Borrelia afzelii and B. garinii were the most prevalent species both in ticks from vegetation (3.7% and 3.7%, respectively) and from pets (3.7% and 0.6%, respectively). Babesia infections were slightly more common in feeding ticks compared to those from vegetation (6.0 vs. 4.7%, respectively), however, the difference was not significant. Three Babesia species including Ba. microti, Ba. venatorum and Ba. canis were identified. Babesia canis and Ba. microti were the most prevalent in host-seeking (2.6% and 1.4%, respectively) and feeding ticks (2.8% and 2.2%, respectively), whereas Ba. venatorum was the rarest piroplasm. All Ba microti obtained sequences (n=42) were identical to Ba. microti genotype "Jena/Germany" that is considered as pathogenic to humans. Furthermore, the sequences of Ba. venatorum (n=17) were identical with those isolated from patients in Italy, Austria and Poland. Altogether, out of 121 Babesia-positive ticks, 19.8% were simultaneously infected with B. burgdorferi s.l. spirochetes. We found similar prevalences of co-infections in host-seeking (1.1%) as well as in feeding ticks (1.0%). In the first group, Ba. canis prevailed in coinfections (73%), mostly with B. afzelii and B. garinii, in the second group, Babesia microti dominated with B. afzelii (92.7%). This is the first finding documenting the co-occurrence of both pathogens in ticks from companion animals. The detection of Ba. microti and Ba. venatorum sequences identical to strains pathogenic to humans as well as predominance of LB spirochetes, B. afzelii and B. garinii in I. ricinus from vegetation and animals indicates that there is a potential risk of acquiring human babesiosis and/or Lyme borreliosis in urban areas of the city of Poznań. Although, the overall risk of encountering a Ba. microti and B. burgdorferi s.l. co-infected tick was low (1.0%), the potential for more severe clinical symptoms and complications deserves notice. A relatively high infection rates of Ba. canis in dog-derived ticks (3.2%) and in host-seeking ticks (2.6%), suggests that I. ricinus could potentially be involved in the circulation of this piroplasm in areas, where the competent vector, Dermacentor reticulatus is absent or rare.

In this paper, a semi-empirical model of air waves induced by falling rock is described. The model is composed of a uniform motion phase (velocity close to 0 m·s^-1) and an acceleration movement phase. The uniform motion phase was determined based on experimentally and the acceleration movement phase was derived by theoretical analysis. A series of experiments were performed to verify the semi-empirical model and elucidated the law of the uniform motion phase. The acceleration movement phase accounted for a larger portion with a greater height of the falling rock. Experimental results of different falling heights of the goaf showed close agreement with theoretical analysis values. The semi-empirical model could accurately and conveniently estimate the velocity of air wave induced by falling rock. Thus, the semi-empirical model can provide a reference and basis for estimating the speed of air waves and designing protective measures in mines.

Due to the significant price difference, expensive oils like olive oil are often blended with cheaper edible oils. This practice of adulteration in edible oils, aimed at increasing profits for producers, poses a major concern for consumers. Furthermore, adulteration in edible oils can lead to various health issues impacting consumer well-being. In order to meet the requirements of fast, non-destructive, universal, accurate and reliable quality testing for edible oil, the oblique-incidence reflectivity difference (OIRD) method combined with machine learning algorithms was introduced to detect a variety of edible oils. The prediction accuracy of Gradient Boosting, K-Nearest Neighbor, and Random Forest models exceeded 95%. Experimental results indicate that the OIRD method can serve as a powerful tool for detecting edible oils.

The multiphase motors due to their reliability find new areas of application in the industry and transportation. Developing of any system with multiphase motors at first requires elaborate model of the system, define control mode and controllers. The model of control system for the six-phase drive is based on its conventional d-q mathematical model and indirect field-oriented control. Simulink model of six-phase drive with indirect field-oriented control and simulated with two types PID and PID fuzzy controllers. The simulation results, reflecting step response and provided speed reference law as well as load application at constant speed, are presented and analyzed. Fuzzy controller with 49 rules is considered and applied. Six-phase electric drive with field-oriented control at well-tuned PID controller has good step response specifications: settling time 0.13 s at starting without load, step response has no overshoot, small about 1 % short time decrease of speed at load of 5 Nm application. The system employing PID fuzzy controller shows slightly better results in response to torque application: the decrease in speed 1 % is eliminated in shorter time. Simulation results indicate the robustness of both systems with six-phase drive to disturbance and provide high quality transient specifications at determined reference speed.

Candidiasis is considered an emerging public health concern because of the occurrence of drug-resistant Candida strains and the lack of available structurally diverse antifungal drug armamentariums. The indole alkaloid globospiramine from the anticandidal Philippine medicinal plant Voacanga globosa exhibits a variety of biological activities; however, its antifungal properties remain to be explored. In this study, we report the in vitro antifungal activities of globospiramine against Candida albicans and Candida tropicalis and explore its possible target proteins using in silico methods. The colony-forming unit (CFU) viability assay revealed time- and concentration-dependent anticandidal effects of the alkaloid by decreasing almost 50% of the viable CFUs 60 min after treatment. Results of the MIC and MFC assays indicated inhibitory and fungicidal effects of globospiramine against C. albicans (MIC = 8 µg/mL; MFC = 4 µg/mL) and potential fungistatic effects against C. tropicalis at lower concentrations (MIC = 4 µg/mL; MFC &gt; 64 µg/mL). The FAM-FLICA poly-caspase assay showed metacaspase activation in C. albicans cells at concentrations of 16 and 8 µg/mL, which agreed with the MIC and MFC values. Molecular docking and molecular dynamics simulation experiments indicated stable, strong binding of globospiramine with the target proteins 1,3-β-glucan synthase and Als3 adhesin enzymes, which are indirectly involved in apoptotic-driven candidal inhibition.

Cloud-induced atmospheric extinction and occlusion have a major effect on the effectiveness and quality of telescope observations. Real-time cloud cover distribution and long-term statistical data are essential for astronomical siting and telescope operations. At ground-based astronomical telescope sites, cloud cover distribution is currently analyzed using manual observation methods. However, the main disadvantages of manual observation methods are human subjective, heavy workloads and poor real-time performance. Therefore, a real-time automatic cloud images classification method is desperately needed. This paper presents a new cloud identification method, which is named PSO+XGBoost model by combining eXtreme Gradient Boosting (XGBoost) and Particle Swarm Optimization (PSO). The entire cloud image is divided into 37 sub-regions in order to more precisely identify the distribution of the clouds. 19 features are then extracted, including the sky background, star density, lighting conditions, and subregion grayscale values. The experimental results have shown that the overall classification accuracy of 96.91% and our model is able to outperform several state-of-the-art baseline methods. Our approach achieves high accuracy in comparison with the manual observation methods. Moreover, this method meets telescope real-time scheduling requirements.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

Much research has been conducted to determine how hair regeneration is regulated, as this could provide therapeutic, cosmetic, and even psychological interventions for hair loss. The current study focused on the hair growth effect and effective utilization of fatty oil obtained from Bryde's whales through high-throughput DNA microarray approach in conjunction with immunohistochemical observations. The research also examined the mechanisms and factors involved in hair growth. In an experiment using female C57BL/6J mice, the vehicle control group (VC: propylene glycol: ethanol: water), the positive control group (MXD: 3% minoxidil), and the experimental group (WO: 20% Whale Oil) were topically applied to the back of the mouse. The results showed that 3% MXD and 20% WO were more effective than VC in promoting hair growth, especially 20% WO. Furthermore, in hematoxylin and eosin-stained skin tissue, an increase in the number of hair follicles and subcutaneous tissue thickness was observed with 20% WO. Whole-genome transcriptomic analysis also showed that 20% WO may have lower stress- and inflammation-related responses than 3% MXD. Therefore, whale oil can be expected to be used as a safe hair growth agent.

This study uses machine learning to identify key factors influencing the cost-effectiveness of over-the-counter (OTC) medications. By developing a novel cost-effectiveness rating (CER) from user ratings and prices, we analyzed data from Amazon. The findings indicate that FSA/HSA eligibility, symptom treatment range, safety warnings, special effects, active ingredients, and packaging size significantly impact cost-effectiveness across cold, allergy, digestion, and pain relief medications. Medications eligible for FSA or HSA funds, treating a broader range of symptoms, and having smaller packaging are perceived as more cost-effective. Cold medicines with safety warnings were found to be cost-effective due to their lower average price and effective ingredients like phenylephrine and acetaminophen. Allergy medications with kid-friendly features showed higher cost-effectiveness, and ingredients like calcium, famotidine, and magnesium boosted the cost-effectiveness of digestion medicines. These insights help consumers make informed purchasing decisions and assist manufacturers and retailers in enhancing product competitiveness. Overall, this research supports better decision-making in the pharmaceutical industry by highlighting factors that drive cost-effective medication purchases.

Augmented and Virtual Reality have been experiencing a rapidly growth in recent years, but there is not still a deep knowledge on their capabilities and where they could be explored. In that sense, this paper presents a study on the accuracy and repeatability of the Microsoft's HoloLens 2 (Augmented Reality device) and HTC Vive (Virtual Reality device) using an OptiTrack system as ground truth. For the HoloLens 2, the method used was hand tracking, while in HTC Vive, the object tracked was the system's hand controller. A series of tests in different scenarios and situations were performed to explore what could influence the measures. The HTC Vive obtained results in the millimetre scale, while the HoloLens 2 revealed not so accurate measures (around 2 centimetres). Although the difference can seem to be considerable, the fact that HoloLens 2 was tracking the user's hand and not an inherit controller made a huge impact. The results were considered a significant step for the on going project of developing a human-robot interface to program by demonstration an industrial robot using Extended Reality, which shows great potential to succeed based on this data.

As Artificial Intelligence (AI) technology, particularly Machine Learning algorithms, becomes increasingly ubiquitous, our abilities to understand and interpret AI and machine learning algorithms are becoming increasingly desirable. Visualization has been used as a common tool to view and understand complex machine learning processes. In this paper, we will focus on developing a general framework for the visualization of machine learning models as a scalar valued multi-dimensional function to help users understand how the models behave over different viewing spaces. We first give a formal definition of the visualization problem. Interpolation-based morphing and subspace sampling techniques are applied to generate various renderings through projections and cross-sections of the model space as 3D surfaces or heatmap images. This method will be applied to two real-world datasets and applications: the diagnosis of Alzheimer's Disease (AD) using a human brain networks dataset and a real-world benchmark dataset for predicting home credit default risks. The visualizations show that different machine learning algorithms can behave quite differently under different conditions.

The theory of water transport in trees, according to which the main driving force of water movement is the suction created by the evaporation of water by the meniscus (the curved surface of the capillary liquid column) on the evaporating elements, supported from below by root pressure, is flawed. The capillary effect in nature is around one meter. In the case of open-air gaps, the leaf cannot suck in the water against gravity because, in this case, the plant would not be sucking in water, but air through the open-air gap. If not, how do trees transport water? When evaporation occurs, there is no suction towards the canopy, but pressure is due to a reduction in the cross-section of the water pipe caused by heat loss through evaporation. At night, when evaporation stops, a thermal equilibration process is triggered, which restores the original cross-section of the pipe. This generates suction and draws water from the soil. As the hydrostatic pressure in the pipe is high for tall trees, the pipe is cut off. To prove my theory, I have given several examples. Water transport is not based on physical mechanical laws alone. There may be complex physiological, biochemical, and biophysical processes behind the operation of the pipe system.

Stroke constitutes a significant public health concern due to its impact on mortality and morbidity. This study investigates the utility of machine learning algorithms in predicting stroke and identifying key risk factors using data from the Suita study, comprising 7,389 participants and 53 variables. Initially, unsupervised K-prototype clustering categorized participants into risk clusters, while five supervised models including Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosted Machine (Light-GBM) were employed to predict stroke outcomes. Stroke incidence disparities among identified risk clusters using the unsupervised K-prototype clustering method are substantial, according to the findings. Supervised learning, particularly RF was a preferable option because of the higher levels of performance metrics. The Shapley Additive Explanations (SHAP) method identified age, systolic blood pressure, hypertension, estimated glomerular filtration rate, metabolic syndrome, and blood glucose level as key predictors of stroke, aligning with findings from the unsupervised clustering approach in high-risk groups. Additionally, previously unidentified risk factors such as elbow joint thickness, fructosamine, hemoglobin, and calcium level demonstrate potential for stroke prediction. In conclusion, machine learning facilitated accurate stroke risk predictions and highlighted potential biomarkers, offering a data-driven framework for risk assessment and biomarker discovery.

Plant transcriptomes are an extremely dynamic entities shaped spatially and temporally by many intracellular and environmental cues. In this review, we first summarize the complexity and diversity of plant genomes and transcriptomes as a start point for the multitude of transcriptomic responses. Numerous alterations within various tissue and organ-specific transcriptomes as well as the most relevant transcriptomic responses associated with plant acclimation to selected abiotic and biotic stress conditions, from the current studies employing high-throughput transcriptomic analysis are widely discussed. Understanding changes within plant transcriptomes, revealed by in silico functional analysis, allows for the characterization of stress-affected genes and stress acclimatory mechanisms, as well as allows to perform plant metabolic engineering. The latter allow cultivars to produce more secondary metabolites in the future, which are often desirable substances in the biomedical industry. Accordingly, in this review special attention was also paid to characterize the potential of transcriptomic analyses of medicinal species, particularly to search for new cultivars. Extensive characterization of transcriptomic responses in stress would also result in the development of new cultivars that display physiological and molecular mechanisms that allow them to cope with adverse environmental conditions more adequately.

Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive signals, specifically integrating Photoplethysmogram (PPG) and Electrocardiogram (ECG), for enhancing early detection and diagnosis of heart failure. Leveraging a dataset from the MIMIC-III database, encompassing 682 heart failure patients and 954 controls. Feature selection techniques were used to systematically select key features which were identified for their clinical relevance and significance in capturing cardiovascular dynamics and to reduce computational complexity and to decrease the chance of overfitting the ML algorithms. These features are then utilized to train and evaluate machine learning algorithms, resulting in a model with an impressive accuracy of 98%, sensitivity of 97.60%, specificity of 96.90%, and precision of 97.20%. The integrated approach outperforms single-signal strategies, showcas-ng its potential for early, precise, and non-invasive heart failure diagnosis. Furthermore, the study underscores the significance of continuous monitoring through wearables, emphasizing the benefits of integrating multiple signals for a comprehensive evaluation of cardiovascular health. The proposed approach holds promise for implementation in hardware systems to enable continuous monitoring, aiding in early detection and prevention of critical health conditions.

Background: Despite recent advancements, medical technology has not yet reached its peak. Precision medicine is growing rapidly, thanks to machine learning breakthroughs powered by increased computational capabilities. This article explores a deep-learning application for computer-aided diagnosis in dermatology. Methods: Using a custom model based on EfficientNetB3 and deep learning, we propose an approach for skin lesion classification that offers superior results with smaller, cheaper, and faster inference times compared to other models. The skin images dataset used for this research includes 8,222 files selected from the authors' collection and the ISIC2019 archive, covering six dermatological conditions. Results: The model achieved 95.4% validation accuracy on four categories—melanoma, basal cell carcinoma, benign keratosis-like lesions, and melanocytic nevi—using an average of 1,600 images per category. Adding two categories with fewer images (about 700 each)—squamous cell carcinoma and actinic keratoses—reduced the validation accuracy to 88.8%. The model maintained accuracy on new clinical test images taken under the same conditions as the training dataset. Conclusions: The custom model demonstrated excellent performance on the diverse skin lesions dataset, with significant potential for further enhancements.

Here we report the preparation and characterization of a novel biomimetic toothpaste containing morphogenetically active amorphous polyphosphate (polyP) microparticles enriched with retinyl acetate (“a-polyP/RA-MP”). The spherical microparticles (average size, 550±120 nm), prepared by co-precipitating sodium-polyP with calcium chloride and supplemented with retinyl acetate, were incorporated into a basis toothpaste at a final concentration of 1% or 10%. The paste containing “a-polyP/RA-MP” significantly increased the growth of human mesenchymal stem cells (MSC), compared to a commercial toothpaste which acts rather inhibitory and the paste without polyP and retinyl acetate. qRT-PCR experiments revealed that the retinoid causes an induction of the expression of the MSC marker genes for osteoblast differentiation encoding collagen type I and alkaline phosphatase. On the other hand, the polyP ingredient, supplied as Zn-polyP microparticles (“Zn-a-polyP-MP”) strongly inhibited the growth of the cariogenic bacterium Streptococcus mutans. We demonstrate that the amorphous polyP-containing toothpaste, enriched with retinyl acetate, efficiently repairs both cracks/fissures and carious lesions in the tooth enamel, and reseals dentinal tubules, already after a 5 d treatment (brushing) of teeth twice daily for 5 min as examined by SEM and quantitative EDX analysis. The stability of the occlusion of dentin cracks even turned out to resist against short high power sonication treatment. Our results demonstrate that the novel toothpaste prepared here, containing amorphous polyP and retinyl acetate, is particularly suitable for prevention/repair of (cariogenic) damages of tooth enamel/dentin and for treatment of dental hypersensitivity.

To address the problems of insufficient semantic fusion between text and questions and the lack of consideration of global semantic information encountered in machine reading comprehension models, we proposed a machine reading comprehension model called BERT_hybrid based on BERT and hybrid attention mechanism. In this model, BERT is utilized to separately map the text and questions into the feature space. Through the integration of Bi-LSTM, attention mechanism, and self-attention mechanism, the proposed model achieves comprehensive semantic fusion between text and questions. The probabilities distribution of answers is computed using Softmax. Experimental results on the public dataset DuReader demonstrate that the proposed model achieves improvements in BLEU-4 and ROUGE-L scores compared to existing models. Furthermore, to validate the effectiveness of the proposed model design, we analyze the factors influencing the model’s performance.

The volume of fluid (VOF) method is a popular technique for the direct numerical simulations of flows involving immiscible fluids. A discrete volume fraction field evolving in time represents the interface, in particular, to compute its geometric properties. The height function method (HF) is based on the volume fraction field, and its estimate of the interface curvature converges with second-order accuracy with grid refinement. Data-driven methods have been recently proposed as an alternative to computing the curvature, with particular consideration for a well-balanced input data set generation and symmetry preservation. In the present work, a two-layer feed-forward neural network is trained on an input data set generated from the height function data instead of the volume fraction field. The symmetries for rotations, reflections, and the anti-symmetry for the phase swapping have been considered to reduce the number of input parameters. The neural network, establishing a correlation between curvature and height function values, can efficiently predict the local interface curvature. We compare the trained neural network to the standard Height Function method to assess its performance and robustness.

In the intersection of the Internet of Things (IoT) and Machine Learning (ML), the choice between high-level and low-level programming libraries presents a significant dilemma for developers, impacting not only the efficiency and effectiveness of ML models but also their environmental footprint. We have proposed a comprehensive framework to aid in this decision-making process, underpinned by a detailed comparative analysis of both types of libraries on one of the key IoT ML task; image classification. We have introduced a novel algorithm designed to calculate the green footprint of ML model training, factoring in execution time, memory utilization, power consumption, and CPU temperature, addressing the urgent need for sustainable ML practices. Through an empirical evaluation of popular libraries such as PyTorch for high-level and Libtorch for low-level development, we have assessed their performance, development efficiency, and hardware compatibility. The culmination of our research is a decision support system that synthesizes the experimental findings to guide developers toward choices that harmonize model performance with environmental sustainability.

This paper presents a new semi-explicit algorithm for parameters estimation in a time-fractional generalization of dual-phase-lag heat conduction model with the Caputo fractional derivatives. It is shown that this model can be derived from a general linear constitutive relation for the heat transfer by conduction when the heat conduction relaxation kernel contains the Mittag-Leffler function. The model can be used to describe heat conduction phenomena in a material with power-law memory. The proposed algorithm of parameters estimation is based on the time integral characteristics method. The explicit representations of the thermal diffusivity and the fractional analogues of the thermal relaxation time and the thermal retardation are obtained via a Laplace transform of the temperature field and utilized in the algorithm. An implicit relation is derived for the order of fractional differentiation. In the algorithm, this relation is resolved numerically. An example illustrates the proposed technique.

A severe consequence of SARS-CoV-2 infection that manifests as systemic inflammation and multi-organ involvement is called Multisystem Inflammatory Syndrome in Children (MIS-C). This review examines the possible relationship between gut barrier integrity, the microbiome, dysregulation of interleukin-6 (IL-6) signaling, and MIS-C. Clinical and biochemical features of MIS-C are similar to those of other hyperinflammatory syndromes, suggesting a dysregulated immune response. One possible explanation for the systemic inflammation seen in MIS-C patients is SARS-CoV-2-induced dysregulation of the IL-6 signaling pathway. In addition, new data suggest a reciprocal link between gut barrier integrity and IL-6. SARS-CoV-2 exhibits bacteriophage-like behavior, highlighting the role of bacteria as a reservoir for the virus and emphasizing the importance of understanding the bacteriophagic mechanism of the virus in fecal-oral transmission. Increased translocation of viral products and bacterial toxins may result from disrupting the intestinal barrier and cause systemic inflammation. On the other hand, systemic inflammation can weaken the integrity of the intestinal barrier, which feeds back into the loop of immunological dysregulation. In the context of MIS-C, understanding the interaction between SARS-CoV-2 infection, IL-6, and gut barrier integrity may shed light on the etiology of the disease and guide treatment options.

The integration of modern technologies like intramedullary fixators and advanced biometallic alloys has revolutionized traumatology and orthopedics. While these innovations have improved treatment, the exploration of new materials for implants persists. Tantalum and niobium, both non-toxic with similar properties, are preferred for titanium-based biomedical alloys due to their exceptional biocompatibility and corrosion resistance. Acting as stabilizers in titanium alloys, they form passive oxide layers resisting corrosion and remain compatible with biological systems. The novel Ti21Nb6Ta (TNT) alloy promises enhanced osteosynthesis outcomes. Our in vivo research on experimental animals evaluated the biocompatibility and osteoinduction of TNT compared to Ti-6Al-4V (BT-6) alloy (control group). The study comprised three experiments across different animal species, assessing acute toxicity, irritant effects, and long-term biocompatibility and osteoinduction through simulated osteosynthesis. Results indicated that aqueous extracts from both alloys were non-toxic and non-irritating. Furthermore, both demonstrated high biocompatibility and active osteoinduction potential after three months of implantation.

. Protein cysteine S-glycosylation is a relatively rare and less well characterized post-translational modification (PTM). Creating reliable model proteins that carry this modification is challenging. The lack of available model or natural S-glycosylated proteins significantly hampers the development of MS-based methodologies for detecting protein cysteine S-glycosylation in real-world proteomic studies. There is also limited MS-sequencing data describing easier to create synthetic S-glycopeptides. Here, we present the results of an in-depth manual analysis of automatically annotated CID/HCD spectra for model S-glucopeptides. The CID spectra show a long series of y/b-fragment ions with retained S-glucosylation, regardless of the dominant m/z signals corresponding to neutral loss of 1,2-anhydroglucose from the precursor ions. In addition, the spectra show signals manifesting glucosyl transfer from the cysteine position onto Lys, Arg side chains, and a peptide N-terminus. Other spectral evidence indicates that the N-glucosylated initial products of transfer are converted into N-furanosylated (i.e., glycated) structures due to Amadori rearrangement. We discuss the peculiar transfer of the glucose oxocarbenium ion (Glc+) to positively charged guanidinium residue (ArgH+) and propose a mechanism for the gas-phase Amadori rearrangement involving a hydride ion shift.

In this study, the friction factor of turbulent pipe flow for dried rice malt extract solutions is reduced experimentally to that of a Newtonian fluid. The friction factor is measured for four types of solutions at different culture times and concentrations. The results indicate that the experimental data points of the test solutions diverge from the maximum drag reduction asymptote at and above Re√f ≅ 200 and align parallel to those of Newtonian fluids. This drag reduction phenomenon differs from that of artificial high molecular polymer solutions. It is classified as a Type B drag reduction phenomenon of biopolymer solutions and fine solid particle suspensions. The order of drag reduction corresponds approximately to that of 5–50 ppm xanthan-gum solutions reported previously. Furthermore, the velocity profile in a turbulent pipe flow was predicted using a semi-theoretical equation, in which the friction factors were determined using the difference between the experimental results of the tested solutions and Newtonian fluids. The results indicate a more considerable thickening of the viscous sublayer in the turbulent pipe flow of the test solutions than that of Newtonian fluids.

The purpose of this paper is to explore the implementation of Retrieval-Augmented Gen- 14 eration (RAG) technology with open-source Large Language Models (LLMs). For this purpose, a 15 web-based application named PaSSER that integrates RAG with three models - Mistral:7b, 16 Llama2:7b: Orca2:7b, is developed. In its development various technologies are used, including 17 Blockchain for managing and storing assessment results of built-in testing modules. PaSSER em- 18 ploys a set of evaluation metrics for LLMs’ performance - METEOR, ROUGE, BLEU, Perplexity, 19 Cosine similarity, Pearson correlation, and F1 score. The specialized knowledge base is in the smart 20 agriculture domain. As an illustration, the paper presents results and analysis of two tests. First one 21 is assessing the performance of LLMs across different hardware configurations, the other is deter- 22 mining the model that delivers most accurate and contextually relevant responses within the RAG. 23 The paper also discusses the integration of blockchain technology with LLMs to manage and store 24 assessment results within a blockchain environment. The tests revealed that Mistral:7b demon- 25 strates the best results across most of the evaluated metrics. The discussion section comments on 26 technical and hardware considerations that affect the performance of LLMs. Future development 27 will focus in leveraging new larger pre-trained open-source LLMs, exploring different finetuning 28 approaches, and further integration with Blockchain and IPFS.

As a special class of “green” elastomers, thermoplastic vulcanizates (TPVs) have been widely used in industries due to the combination of the excellent resilience of conventional elastomers and the easy recyclability of thermoplastics. Here, the morphology evolution of TPVs based on polyamide 6/ethylene-propylene-diene rubber (PA6/EPDM) blends was investigated by varying the content of the curing agent, phenolic resin (PF). With the incorporation of 6 wt% PF, the gel content of the EPDM phase reaches a high value of 49.6wt% and a typical sea-island structure is formed with EPDM domain in a micro-nano size. The dynamic rheology behaviors of TPVs showed that with the curing degree of EPDM phase increasing, a denser network of EPDM particles is formed in PA6 matrix. Also, a lower crystal degree and crystal peak temperature are observed, indicating that the presence of a growth restriction of PA6 crystal plate induced by a thinner plastic layer between the adjacent EPDM particles. However, the crystal form of PA6 is not changed with the increasing curing degree of the EPDM phase. This study provides an effective strategy to realize a new kind of TPVs, which can be easily introduced into industrial applications.

A hybrid material, consisting of commercially available nitrocellulose (NC) membrane non-covalently modified with amino-polyethylene glycol functionalized reduced graphene oxide (NH2-PEG-rGO) nanoparticles, was successfully synthesized for oligonucleotide extraction. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the modification of the NC membrane, revealing characteristic peaks of both compounds NC and NH2-PEG-rGO. Scanning Electron Microscopy (SEM) exhibited morphological changes in the NC/NH2-PEG-rGO hybrid membrane, marked by the introduction of NH2-PEG-rGO particles, resulting in a distinctly smothered surface compared to the porous surface of the NC control membrane. Wettability assays revealed hydrophobic behavior for the NC/NH2-PEG-rGO hybrid membrane, with a water contact angle exceeding 90°, contrasting with the hydrophilic behavior characterized by a 16.7° contact angle in the NC membrane. The performance of the NC/NH2-PEG-rGO hybrid membrane was evaluated for the extraction of ssDNA with fewer than 50 nucleotides from solutions containing various ionic species (MnCl2, MgCl2, and MnCl2/MgCl2). The NC/NH2-PEG-rGO hybrid membrane exhibited optimal performance when incubated in MgCl2, presenting the highest fluorescence emission at 525 relative fluorescence units (r.f.u.). This corresponds to the extraction of approximately 610 pg (≈13%) of the total oligo-DNA, underscoring the efficacy of the pristine material, which extracts 286 pg (≈6%) of oligo-DNA in complex solutions.

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 increased prevalence of obesity worldwide has been implicated for the alarming rise of the incidence of gestational diabetes and preeclampsia as well, both considered as threatening conditions for both mother and fetus. We studied gene polymorphisms of the proinflammatory cytokine Interleukin 6 (IL-6) and the gene expression levels of VEGF and VEGF-receptor all known to be involved in pregnancy complications aiming to identify possible predisposing risk factors in pregnancies with obesity. G allele of IL-6 was found to correspond with an increased risk for gestational diabetes and preeclampsia occurrence. Furthermore, in obese pregnant mothers with either gestational diabetes or pre-existing type 2 diabetes and to those developed preeclampsia it was confirmed that gene expression levels of VEGF were reduced while they were increased for VEGF receptor. We conclude that the genetic profile of the obese pregnant woman shares a common background with that of a pre-existing type 2 diabetes mellitus and therefore predisposes to complications in pregnancy.

PgRMC1 (progesterone receptor membrane component 1) is a progesterone-binding protein highly expressed in various cancer cells. Its expression has been associated with cancer development, chemoresistance, and poor prognosis in breast cancer through the regulation of drug and sterol metabolism, cell cycle, and apoptosis. However, the precise functions of PgRMC1 remain unclear. We examined PgRMC1 expression in breast cancer tissues and analyzed its correlation with clinicopathological characteristics and treatment response (n=112). PgRMC1 expression was detected in breast cancer tissue, while no immunoreactivity for PgRMC1 was observed in normal breast tissue. Notably, PgRMC1 expression levels were high in the HER2 subtype. Among patients treated with neoadjuvant chemotherapy, those with a poor pathological response had significantly higher PgRMC1 expression than those with a good response. PgRMC1 overexpression in breast cancer cell lines reduced chemosensitivity. Real-time qPCR analyses revealed that PgRMC1 induced the expression of differentiation markers, including CDH1 and KRT19, indicating that PgRMC1 is involved in the suppression of epithelial-mesenchymal transition and mammary luminal epithelial differentiation. Our findings suggest that PgRMC1 may contribute to chemoresistance and serve as a putative biomarker for assessing neoadjuvant chemotherapy sensitivity.

From grape cultivation to ripening and harvest timing to processing, each step can be a critical point when it comes to wine quality and phenolic composition. In this study, the influence of winemaking technology on resveratrol and quercetin content, as well as other polyphenolic compounds, was investigated. Resveratrol is a non-flavonoid polyphenolic stilbene synthesized by grape skin when damaged by infectious diseases or ionizing radiation. Quercetin is a phenol found in grape skins and stems and is produced to protect grapes from UV light damage. Trans-resveratrol and quercetin are known to act as antioxidants, reduce the risk of atherosclerosis and type 2 diabetes, inhibit the growth of cancer cells, and prevent the release of allergic and inflammatory molecules. However, the question was whether red wine could be enriched with these phenols using an innovative winemaking technology. The innovative idea was to completely replace the cold maceration process with maceration with the addition of wild yeast (Torulaspora delbrueckii, Td). Maceration with the addition of wild yeast (Td) offers the following advantages over traditional cold maceration: (1) higher concentrations of trans-resveratrol (>35-40%) and quercetin (>35-40%) in the final wine, (2) the new wine has a higher potential for human health, (3) the wine has a better aroma and stability due to the higher mannoprotein content, and (4) the better energy efficiency in the production process. The study of stability during storage and aging also included derivatives of benzoic acid and hydroxycinnamic acid, piceid, catechin, naringenin, rutin, kaempherol, hesperetin, and anthocyanins. The study found that younger wines had higher phenolic content, while storage of the wine resulted in a decrease in total phenolic content, especially monomeric stilbenes and quercetin.

To enhance the applicability of dual-phase high-entropy alloys (HEAs) like Fe32Cr33Ni29Al3Ti3, fabricated via selective laser melting (SLM), a focus on improving their mechanical properties is essential. As part of this effort, heat treatment was explored. This study compares the microstructure and mechanical properties of the as-printed sample with those cooled in water after undergoing heat treatment at temperatures ranging from 1000 to 1200 ℃ for 1 hour. Both pre- and post-treatment samples reveal a dual-phase microstructure comprising FCC and BCC phases. Although heat treatment led to a reduction in tensile and yield strength, it significantly increased ductility compared to the as-printed sample. This strength-ductility trade-off is related to changes in grain sizes with ultrafine grains enhancing strength and micron grains optimizing ductility, also the influence of the content of FCC/BCC phases and dislocation density. In particular, the sample heat-treated at 1000 °C for 1 hour and then water-cooled exhibited a better combination of strength and ductility, a yield strength of 790 MPa, and an elongation of 13%. This research offers innovative perspectives on crafting dual-phase HEA of Fe32Cr33Ni29Al3Ti3, allowing for tailorable microstructure and mechanical properties through a synergistic approach involving SLM and heat treatment.

New fluorinated pentaphene derivative has been obtained as a potential precursor for fluorinated polycyclic aromatic hydrocarbons. In this work 7,7-difluoropentaphen-6(7H)-one was prepared from 1,1-difluoroanthracen-2(1H)-one via Diels-Alder reaction with o-quinodimethane generated in situ from o-bis(dibromomethyl)benzene. The structure of newly synthesized compound was confirmed by 1H, 13C, 19F NMR, IR and UV/Vis spectroscopy as well as high-resolution mass spectrometry.

Mutations in epidermal growth factor receptor (EGFR) occur in about 48% of Asian and 19% of Western patients with lung adenocarcinoma (LUAD), leading to its constitutive activation and subsequent uncontrolled cell proliferation. To counteract this, tyrosine kinase inhibitors (TKIs) have been developed, targeting EGFR activity. However, the emergence of metastases and resistance mutations often undermines the durability of the treatment response. Knowledge-based mechanistic models that replicate existing clinical trial outcomes, tailored to specific population characteristics, provide invaluable assistance in designing future clinical trials. These models are particularly effective in identifying optimal responders to specific treatments, thereby enhancing therapeutic efficacy. We have developed physiologically based pharmacokinetic (PBPK) models for gefitinib and osimertinib, representing two distinct generations of EGFR TKIs, to accurately simulate the drugs’ distribution within the primary tumor and metastatic sites following oral administration. These models were integrated with a pathophysiological mechanistic model of EGFR-mutant LUAD, enabling the representation of the effects of both gefitinib and osimertinib on EGFR activation-induced signaling pathways. This comprehensive model outputs detailed evolutions of the primary tumor and each metastatic site, facilitating the evaluation of patient progression in alignment with RECIST guidelines (version 1.1). Notably, the model encapsulates the heterogeneity within the tumor, through the representation of various subclones, each characterized by unique mutation profiles, thereby reflecting differential responses to treatment. Calibration of the model was achieved using publicly available data from the NEJ002 and FLAURA clinical trials. Rigorous visual predictive checks and statistical tests were employed to ensure the proper behavior of the model. The model adeptly replicated the time to progression observed in real clinical trials in EGFR-mutant LUAD patients receiving gefitinib or osimertinib as first-line therapy. In addition, the model was able to reproduce the results from a retrospective study comparing gefitinib and osimertinib, a study that was not used to inform the model. With a consistent virtual population as a reference, the combined model facilitated a comparative analysis of the efficacy of both treatments, thereby underscoring its utility in evaluating therapeutic strategies. The faithful replication of real-world data significantly enhances the credibility of our model, rendering it a vital investigational tool for deriving pertinent insights and informing treatment strategies, particularly in identifying optimal responders to various generations of EGFR TKIs. Following its consecutive prospective validations in the FLAURA2 and MARIPOSA trials, the model is poised to facilitate the generation of synthetic control arms in future clinical trials. This advancement promises a more nuanced analysis of covariate relationships, especially when comparing investigational treatments to established standards of care. Additionally, it potentially reduces the required patient cohort size in such trials, optimizing resource utilization.

Background. Malignant pleural mesothelioma (MPM) is still a rather incurable disease. Many classes of compounds with various mechanisms of action have been tested in vivo and ex-vivo, with rather disappointing results. This is partly due to preclinical studies mostly performed in models that fail to recapitulate MPM complexity and do not retain the intra-tumor heterogeneity, a propelling force for tumor progression. Additionally, we and others have shown that, under stress-induced chemotherapy, profound rearrangements take place in MPM cultures to fuel the emergence of chemoresistant cell subpopulations. Thus, finding clinically actionable modulators of MPM resistance is still a very urgent need. Methods. Setup and propagation of patient-derived organoid cultures from MPM pleural effusions; flow cytometry-based validation of organoid cultures, isola-tion and propagation of mesothelioma-associated fibroblasts; co-cultures, Lu-minex-based Cytokine array, ELISA assay to quantitate IL-6 in the conditioned media, qRT-PCR to assess mRNA expression of cancer stem cell markers and fibroblast markers. Results. Organoid cultures were obtained from eight MPM patients by using specific growth media and conditions to propagate pleural effusion-derived cells. We proved that primary MPM specimens and serially passaged (mesothelio-ma-Patient-Derived-Organoids) mPDOs were cytologically similar, with the obtained mPDOs expressing mesothelial markers similarly to the originating specimen. As expected from a clinically relevant model, the size and number of mPDOs were altered, in a patient-specific way, when pharmacologically relevant doses of chemotherapy drugs were added. We derived Mesothelio-ma-Associated-Fibroblasts (MAFs) and the addition of MAFs, to various ratios, altered the response of the mPDOs to pemetrexed + cisplatin, toward a reduced sensitivity to the latter anticancer agents. Additionally, organoid formation and size were altered by MAF-conditioned media, and this correlated with increased expression of cancer stem cell markers. We showed increased levels of IL-6 in the media of the treated cocultures and showed that this latter was derived from the MAFs. Conclusions. Increased secretion of IL-6 by mesothelioma-associated fibroblasts (MAFs) contributes to the resistance of the MPM to therapy.