Ellagic acid, a polyphenolic compound present in fruits and berries, has recently been object of extensive research for its antioxidant activity, which might be useful for the prevention and treatment of cancer, cardiovascular pathologies, and neurodegenerative disorders. Its protective role justifies numerous attempts to include it in functional food preparations and in dietary supplements not only to limit the unpleasant collateral effects of chemotherapy. However, ellagic acid use as chemopreventive agent has been debated because of its poor bioavailability associated to low solubility, limited permeability, first pass effect, and interindividual variability in gut microbial transformations. To overcome these drawbacks, various strategies for oral administration including solid dispersions, micro-nanoparticles, inclusion complexes, self-emulsifying systems, polymorphs have been proposed. Here, we have listed an updated description of pursued micro/nanotechnological approaches focusing on the fabrication processes and the features of the obtained products, as well as on the positive results yielded by in vitro and in vivo studies in comparison to the raw material. The micro/nano-sized formulations here described might be exploited for pharmaceutical delivery of this active, as well as for the production of nutritional supplements or for the enrichment of novel foods.

Selenium (Se) is an essential element of the human diet. Therefore, it is necessary to implement Se in agricultural fertilization, although it is not considered as an essential element for plants, Se provides benefits at the level of redox metabolism, increasing the resistance of plants to various stress factors. The increase of the availability of selenium with the use of biopolymer complexes was sought in Great Lakes lettuce grown in substrate pots treated with SeO₂ (5 mg L Se), Cs-PAA + Se (5 mg L Se), and Cs-PAA. The redox metabolism was modified by increasing the enzymatic activity of glutathione peroxidase. The use of Cs-PAA + Se biopolymer complexes increase selenium up to 24 mg/Kg dry weight (DW) in plant tissues.

We describe our investigations of the surface physicochemical and biological properties of polylactic acid modified by silver, argon and carbon ion implantation to doses of 1 × 10¹⁴, 1 × 10¹⁵ and 1 × 10¹⁶ ion/cm² at energies of 20 keV (for C and Ar) and 40 keV (for Ag). X-ray analysis shows enhancement of coherent scattering regions and lattice constant increase after ion implantation. Secondary electron mass-spectrometry indicates that Ag concentration in the subsurface layer is less than 80%, but at a depth of 500 nm does not exceed 1–2%. The silver forms metal particles in the subsurface layer rather than making additional chemical bonds with polymer atoms. Atomic force microscopy reveals that the higher the irradiation dose the larger the surface roughness of the samples. Ag-irradiated samples implanted to a dose of 1 × 10¹⁶ ions/cm² have the highest roughness, 190 nm. Our investigation of the cytotoxicity of two individual donor macrophages shows that Ag-implanted polylactic acid has no negative impact on immune system cells and could be a promising material for biomedical application.

Cervical Cancer affects a large part of female population that makes the prediction of this disease based on Machine Learning (ML) by outmost importance. ML algorithms can be integrated in complex intelligent agent-based systems that can offer decision support to the resident medical doctors or even to experienced medical doctors. For instance can be mentioned the situation when an experienced medical doctor diagnose a case but he/she needs expertise support that is related to another medical specialty. Data imbalance is frequent in healthcare data and has a negative influencing effect in making predictions using ML algorithms. Cancer data generally and cervical cancer data particularly are frequently imbalanced. Based on this fact the study of data imbalance impact on diverse state-of-the-art ML prediction algorithms is important. This research subject is also motivated by the fact that in many research are presented experimental evaluations of algorithms without characterization of the data on that they have been applied. Such characterizations could give clear indication to other researchers regarding the applicability of the algorithms on their specific data. Specifically, if the data have the respective characteristics than are expectable the same performance evaluation results like those in the reported research. For the study we chosed a messy real-life Cervical Cancer dataset available in a recognized data repository included a large amount of missing and noisy values. To identify the best imbalanced technique for this medical dataset, it is compared the performance of eleven important resampling methods combined with the following state-of-the-art ML models: K-Nearest Neighbours (with k values of 2 and 3), binary Logistic Regression, and Random Forest, that are frequently applied in prediction types of researches in healthcare. The studied resampling methods includes seven undersampling methods namely Condensed Nearest Neighbour, Tomek Links, Edited Nearest Neighbours, Repeated Edited Nearest Neighbours, All K-Nearest Neighbours, NearMiss, Neighbourhood Cleaning Rule, and Instance Hardness Threshold, and four oversampling methods namely Synthetic Minority Oversampling Technique (SMOTE), Adaptive Synthetic Sampling Approach for Imbalanced Learning SMOTE, Support Vector Machine SMOTE and Borderline SMOTE. In the case of the dataset for the confidence interval with 95% confidence level was between 9.23 and 16.22, while the imbalance ratio is 12.73. The obtained results show that resampling methods help the learning models to improve the classification ability of cervical cancer. The applied oversampling techniques generally showed better results than undersampling methods. In the case of Logistic Regression classifier had the highest impact on balanced techniques, while Random Forest had promising performance, even before balancing techniques and KNN2 was generally better than KNN3.

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment–based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

As part of valorisation of agricultural waste into bioactive compounds, a series of structurally novel oleanolic acid ((3β-hydroxyolean-12-en-28-oic acid, OA-1)-phtalimidines (isoindolinones) conjugates 18a-v bearing 1,2,3-triazole moieties were designed and synthesized by treating a previously azide 4 prepared from OA-1 isolated from olive pomace (Olea europaea L.) with a wide range of propargylated phtalimidines using the Cu(I)-catalyzed click chemistry approach. OA-1 and its newly prepared analogues 18a-v were screened in vitro for their antibacterial activity against two Gram-positive bacteria, Staphylococcus aureus and Listeria monocytogenes; and two Gram-negative bacteria, Salmonella thyphimurium and Pseudomonas aeruginosa. Attractive results were obtained notably against L. monocytogenes. Compounds 18d, 18g and 18h exhibited the highest antibacterial activity when compared with OA-1 and other compounds in the series against tested pathogenic bacterial strains. Molecular docking study was performed to explore the binding mode of the most active derivatives against the target protein from L. monocytogenes. Results showed the importance of both hydrogen bonding and hydrophobic interactions with the target protein and are in favor to the experimental data.

An electrochemical bioassay based on the rotating droplet electrochemistry by using electron transfer mediator was developed for the evaluation of a wide variety of pollutants such as antibiotics, heavy metals and pesticides in the water environment. Ferricyanide was used as electron transfer mediator for obtaining the catalytic response of Escherichia coli. The electrochemical response of E.coli was measured via hydrodynamic chronoamperometry in a microdroplet on a screen-printed carbon electrode (SPCE). The constructed electrode system successfully evaluate the catalytic response of E.coli solution in presence of ferricyanide. The assay for antibiotic toxicity on E.coli was carried out. The EC50 for ampicillin, sulfamonomethoxine, chlorotetracycline, tetracycline and oxytetracycline valuated by the pre-incubation method were 0.26, 0.77, 5.25, 18.5, 19.0 µM, respectively. The toxicity order was ampicillin > sulfamonomethoxine > chlorotetracycline > tetracycline>oxytetracycline. The proposed method can be used to evaluate the antibiotic toxicities in different real sample, such as pond water, powder and raw milk. Recoveries were found in the range 90 and 99%. The developed methods do not require additional incubation time to evaluate toxicity.

Based on PVDF (piezoelectric sensing techniques), this paper attempts to study the propagation law of shock waves in brittle materials during the process of three-wavelength laser irradiation of polysilicon, and discusses the formation mechanism of thermal shock failure. The experimental results show that the vapor pressure effect and the plasma pressure effect in the process of pulsed laser irradiation lead to the splashing of high temperature and high density melt. With the decrease of the laser wavelength, the laser breakdown threshold decreases and the shock wave is weakened. Because of pressure effect of the laser shock, the brittle fracture zone is at the edge of the irradiated area. The surface tension gradient and surface shear wave caused by the surface wave are the result of coherent coupling between optical and thermodynamics. The average propagation velocity of laser shock wave in polysilicon is 8.47×103m/s, and the experiment has reached the conclusion that the laser shock wave pressure peak exponentially distributes attenuation in the polysilicon.

Confronting the dual challenges of rapid urbanization and climate change, although extensive research has investigated the influencing factors and practical strategies of urban carbon emissions and urban vibrancy, respectively, the unclear mutual nexus between them and the development strategy of collaborative optimization requires further in-depth analysis. This study explores the delicate balance between urban vibrancy and low-carbon sustainability within the confines of Beijing’s Fifth Ring Road. By integrating OpenStreetMap, land use, population, and building carbon emission data, we have developed a reproducible method to estimate total carbon emission and emission intensity per capita. Furthermore, we have introduced vibrancy index data to distinguish the vibrancy evaluation of residential and non-residential land and applied cross-combinational classification technology to dissect the spatial correlation between urban carbon emissions and urban vibrancy. The results reveal that the four combination typologies show more significant differences and regularity in residential land. Based on the discovery of spatial correlation, this study puts forward corresponding development strategy suggestions for each typology based on geographical location and the requirements of urban development policies of these four combination typologies. In conclusion, our study highlights the importance of integrating carbon emissions and urban vibrancy comprehensively in sustainable urban planning and proposes that various land use combinations need targeted development strategies to achieve this goal, which need to consider population, energy, service facilities, and other diverse aspects.

A predictive approach to the phase behavior of four-component poly-mer-water-surfactant-electrolyte systems is formulated, by viewing the four-component system as a binary polymer-pseudosolvent system, with the pseudosolvent representing water, surfactant, and the electrolyte. The phase stability of this binary system is examined using the framework of the lattice fluid model of Sanchez and Lacombe. In the lattice fluid model, a pure component is represented by three equation of state parameters, the hard-core volume of a lattice site ( ), the number of lattice sites occupied by the component (r) and its characteristic energy ( ). We in-troduce the extra thermodynamic postulate that r and for the pseudosolvent are the same as for water and all surfactant-electrolyte composition dependent characteristics of the pseudosolvent can be represented solely through its characteristic energy parameter. The key implication of the postulate is that the phase behavior of polymer-pseudosolvent systems will be identical for all pseudosolvents with equal values of the characteristic energy, despite their varying real compo-sitions. Based on the pseudosolvent model, illustrative phase diagrams have been computed for several four-component systems containing alkyl sulfonate/sulfate surfactants, electrolytes and anionic or nonionic polymers. The pseudosolvent model is shown to describe all important trends in experimentally observed phase behavior, pertaining to polymer and surfactant molecular characteristics. Most importantly, the pseudosolvent model allows one to construct a priori phase diagrams for any polymer-surfactant-electrolyte system, knowing just one experimental com-position data for a system at the phase boundary, using available thermodynamic data on sur-factants and electrolytes and without requiring any information on the polymer.

UV-digital printing belongs to the commonly used method for custom large-area substrate decoration. Despite low surface energy and adhesion, transparent polymer materials, such as polymethylmethacrylate (PMMA) and polycarbonate (PC), represent an ideal substrate for such purposes. The diffuse coplanar surface barrier discharge (DCSBD) in a novel compact configuration was used for substrate activation to improve ink adhesion to the polymer surface. This industrially applicable version of DCSBD was prepared, tested, and successfully implemented for the UV-digital printing process. Furthermore, wettability and surface free energy measurement, X-ray photoelectron spectroscopy, atomic force and scanning electron microscopy evaluated the surface chemistry and morphology changes. The changes in adhesion of the surface and of ink were analyzed by a peel-force and a crosscut test, respectively. A short plasma treatment (1-5 s) enhanced the substrate's properties of PMMA and PC while providing the pre-treatment suitable for further in-line UV-digital printing. Furthermore, we did not observe damage or significant change of roughness affecting the substrate's initial transparency.

The present article addresses the long-standing problem of the polymer brush bilayers under stationary shear flow at non-linear response regime where the system gets a non-Newtonian fluid. The main idea behind this research would be the fact that the immense lubricity of the polymer brush bilayers originates from a global restructuring that takes place at large shear rates. It is shown here that physical quantities like, stress tensor, viscosity tensor, the friction coefficient and the chain extensions could become dependent on the shear rate at non-Newtonian regime. Apparently, the sub-linear scaling of the physical quantities at large shear rates is solely due to the fact that the chains stretch in the shear direction.

Natural fibers are a gift from nature that we yet fully utilized until now. It can be classified into several groups and bast fibers are the group having the most promising performance when reinforced in polymer composites. However, numerous factors have been reported that influences mechanical properties of fiber reinforcements in the composite. In this review, bast fiber retting process and the effect of enzymatic retting on fiber and fibers reinforced polymer composites have been discussed and reviewed for the latest researches. Retting precedes mechanical processing (i.e. scutching) of the fiber from the stem and is essential for reduction of fiber breakage. All retting methods except chemical retting process are involving secretes of enzymes by bacteria or fungi under controlled (enzymatic retting) or random conditions (water and dew retting). Besides, enzymatic retting is claimed to have more environmentally friendly wastewater products, shorter retting period and controllable fiber biochemical components under mild incubation conditions. This review comprehensively assesses the enzymatic retting process for producing high-quality bast fiber and will become a reference for future development on bast fiber reinforced polymer composites.

Solvent-free, single-ion conducting electrolytes are sought after for use in electrochemical energy storage devices. Here, we investigate the ionic conductivity and how this property is influenced by segmental mobility and conducting ion number in crosslinked single-ion conducting polyether-based electrolytes with varying tethered anion and counter-cation types. Crosslinked electrolytes are prepared by the polymerization of poly(ethylene glycol) diacrylate (PEGDA), poly(ethylene glycol) methyl ether acrylate, and ionic monomers. The ionic conductivity of the electrolytes is measured and interpreted in the context of differential scanning calorimetry and Raman spectroscopy measurements. A lithiated crosslinked electrolyte prepared with PEG₃₁DA and STFSI monomers is found to have a lithium ion conductivity of 3.2 × 10^-6 and 1.8 × 10⁻⁵ S/cm at 55 and 100 °C, respectively. The percentage of unpaired anions for this electrolyte was estimated at about 23% via Raman spectroscopy. Despite the large variances in metal cation – STFSI binding energies as predicted via DFT and large variations in ionic conductivity, STFSI-based crosslinked electrolytes with the same charge density and varying cations (Li, Na, K, Mg, and Ca) were estimated to all have unpaired anion populations in the range of 19 to 29%.

In the last two decades, the application of composite structures in many industrial sectors has been made progressively. For the current major scientific and technological challenge, the energy transition with sustainable and eco-friendly initiatives, the polymer matrix laminated composites have been revealed as an excellent alternative for the renewable energy sector. In this context, the knowledge about mechanical behavior of multiphase materials is required. Then, researches related to macro, mesomechanical and multiscale approaches are very important to improve accuracy of the models to predict effective mechanical properties and to develop a better understanding about complex phenomena such as progressive damage, creep and fatigue. Due to theses needs, this research is a synthesis of fundamentals and advanced topics concerning to global modeling of laminated composite structures, layerwise analyzes and micro-macromechanical models, in which mainly fiber, matrix, interface and damage characteristics are studied and used in the macroscale approach. At the end of this study, some final remarks and a trend analysis are proposed based on literature consulted, in other words, expectations for the future works are made by the authors.

An optical fiber scale sensor based on the detection principle of surface plasmon resonance (SPR) was developed for the rapid, high-sensitivity real-time evaluation of scale precipitation from geothermal fluids. The optical fiber SPR scale sensor was fabricated by depositing a gold thin film on the surface of an optical fiber with an exposed core. The optimal gold film thickness of the sensor was determined to be 30 nm, which achieved a refractive index sensitivity of 2140 nm per refractive index unit. A field test was conducted using geothermal brine from the Obama Binary Geothermal Power Plant in Unzen, Nagasaki Prefecture. A conventional optical fiber scale sensor and the SPR sensor were simultaneously assessed using raw and pH-adjusted brines. For the SPR sensor, a peak shift of 0.27 nm/min was observed at a response time of 1 min, whereas no change in transmittance was observed for the conventional sensor until 180 min. After the experiments, scanning electron microscopy–energy-dispersive spectroscopy analysis was conducted on the sensors, and findings showed that the deposition of Mg–SiO2 scale did not significantly differ between the two sensors. The developed SPR sensor achieved faster scale precipitation detection (tens of minutes to hours) than the conventional sensor.

Biosolids from stabilized sludge presents a high fertilization potential due to its rich content of nutrients and organic matter. Three formulas of organo-mineral fertilizers based on biosolids were manufactured having at least 2 % N, 2 % P2O5, and 2 % K2O and characterized by classical and advanced methods. The content of N and P in the final formula was measured using specific reactants combined with VIS-nearIR spectroscopy. Additionally, all three formulas were characterized by advanced 1H NMR relaxometry, double-quantum and FT-IR spectroscopy. Structural characterization was performed using SEM, EDX and X-ray diffraction. Four dynamical components were identified in the T2-distribution showing that the rigid component is into a percentage larger than 90 %. In order to evaluate the release properties of organo-mineral fertilizers dynamic measurements of electric conductivity and pH were performed, by placing 0.25 g of formulas (V1, V2 and V3) in 200 ml of distillate water. It was found that V3 present the smallest release velocity, but release the largest amount of fertilizers. Two release mechanisms were also observed.

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

This study aimed to investigate the effect of potassium poly-γ-glutamate (PGA-K) on mice fed a high-fat diet consisting of 60% of total calories for a duration of 12 weeks. PGA-K administration reduced the increase in body weight, epididymal fat, and liver weight caused by a high-fat diet compared to the obese group. The triglyceride, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol levels, which are blood lipid indicators, were significantly increased in the obese group but were significantly decreased in the PGA-K-treated group. The administration of PGA-K resulted in a significant inhibition of pro-inflammatory cytokines, including tumor necrosis factor α and interleukin 6. Moreover, the levels of leptin and insulin, which are insulin resistance indicators, significantly increased in the obese group but were significantly decreased in the PGA-K-treated group. These results suggest that PGA-K exhibits a protective effect against obesity induced by a high-fat diet, underscoring its potential as a candidate for obesity treatment.

In the field of human in vitro fertilization (IVF), selecting the best oocyte for freezing or embryo for transfer remains an important focus of clinical practice. Although several techniques are and have been used for this goal, results have generally not been favorable and/or are invasive such that damage to some embryos occurs, resulting in a reduced number of healthy births. Therefore, the search continues for non-invasive oocyte and embryo quality markers that signal the development of high-quality embryos. Multiple studies indicate the important positive effects of retinoic acid (RA) on oocyte maturation and function. Here, we present evidence that part of these effects are via the ability of RA to regulate the activity of connexin 43 (Cx43), the main subunit of gap junction channels in human cumulus granulosa cells (CGC). These channels play an important role in regulating the micronutrient environment of the oocyte by allowing the transfer of ions, metabolites, and small molecules. Multiple studies have demonstrated the requirement for Cx43 in CGC for the normal progression of folliculogenesis, and that increased expression of this connexin is linked to improved developmental competence of the oocyte. The data has shown that RA can up-regulate gap junction intercellular communication (GJIC) in the cumulus-oocyte complex by a non-genomic mechanism that results in the dephosphorylation of Cx43 and enhanced GJIC. Recognizing the positive role played by gap junctions in CGC on oocyte development and the regulation of Cx43 by RA, the findings have highlighted the possibility that CGC RA levels may serve as a non-invasive indicator for selecting high-quality oocytes for IVF procedures. In addition, the data suggests that manipulation of Cx43 with retinoid compounds could provide new pharmacological approaches to improve IVF outcomes in cases of failed implantation, recurrent miscarriage, or in certain diseases that are characterized by reduced fecundity, such as endometriosis.

Acid mine drainage (AMD) contamination is the primary environmental issue in industrial areas and where geological mining occurs. The oxidative dissolution of sulphide minerals causes AMD, natural ecosystems depend on microbial diversity and functioning at their best. This review presents the long-term effects of AMD water such as pollution from heavy metals (HM) on humans and plants, and the solution to the problem of heavy metal pollution by microbes metal interactions.

Lactic acid bacteria are traditionally applied in a variety of fermented food products and have the capability to produce a wide range of bioactive ingredients during fermentation including vitamins, bacteriocins, bioactive peptides and bioactive compounds. The bioactivity and health benefits associated with these ingredients have gained interest in applications in the functional dairy market and have relevance both as components produced in situ and as functional additives. This review provides a brief description of the regulations regarding the functional food market in the European Union as well as an overview of some of the functional dairy products currently available in the Irish and European markets. A better understanding of the production of these ingredients excreted by lactic acid bacteria can further drive the development and innovation of the continuously growing functional food market.

A large number of microplastics (MPs) have been found in various stages of wastewater treatment plants, which may affect the functional microbial activity in activated sludge and lead to unstable pollutant removal performance. In this study, the effects of different concentrations of polylactic acid microplastics (PLA MPs) on system performance, nitrification and phosphorus (P) removal activities, and extracellular polymeric substances (EPS) were evaluated. The results showed that under the same influent conditions, low concentrations (50 particles/(g TS)) of PLA MPs had no significant effect on effluent quality. The average removal efficiencies of chemical oxygen demand, phosphate and ammonia were all above 80%, and the average removal efficiencies of total nitrogen remained above 70%. High concentrations (200 particles/(g TS)) of PLA MPs inhibited the activities of polyphosphate accumulating organisms (PAOs) and nitrifying bacteria. The specific anaerobic P release rate decreased from 37.7 to 23.1 mg P/(g VSS·h), and the specific aerobic P uptake rate also decreased significantly. The specific ammonia oxidation rate decreased from 0.67 to 0.34 mg N/(g VSS·h), while the change in specific nitrite oxidation rate was not significant. The dosing of PLA MPs decreased the total EPS and humic acid content. As the concentration of PLA MPs increased, microbial community diversity increased. The relative abundance of potential PAOs (i.e., Acinetobacter) increased from 0.08% to 12.57%, while the relative abundance of glycogen accumulating organisms (i.e., Competibacter and Defluviicoccus) showed no significant changes, which would lead to improved P removal performance. The relative abundance of denitrifying bacteria (i.e., Pseudomonas) decreased from 95.43% to 58.98%, potentially contributing to the decline in denitrification performance.

Febuxostat (FBX), a selective xanthine oxidase inhibitor, belongs to BCS class II showing low solubility and high permeability with a moderate F value (< 49%). Recently, FBX/L-pyroglutamic acid cocrystal (FBX-PG) was developed with improving 4-fold increase of the FBX solubility. Nevertheless, in vivo pharmacokinetic property of FBX-PG has not been evaluated yet. Therefore, the pharmacokinetic feasibility of FBX in FBX and FBX-PG-treated rats and mice was compared in this study. The results showed that the F values of FBX were 210% and 159% in FBX-PG rats and mice, respectively. The 2.10-fold greater AUC of FBX was due to the increased absorption (i.e., 2.60-fold higher Cmax,1 at 15 min) and entero-hepatic circulation of FBX (i.e., 1.68-fold higher Cmax,2 at 600 min) in FBX-PG rats compared to the FBX rats. The 1.59-fold greater AUC of FBX was due to a 1.65-fold higher Cmax,1 at 5 min, and 1.15-fold higher Cmax,2 at 720 min of FBX in FBX-PG mice than those in FBX mice. FBX was highly distributed in the liver, stomach, small intestine, and lungs in both groups of mice, and the FBX distributions to the liver and lungs were increased in FBX-PG mice compared to FBX mice. The results suggest the FBX-PG has a suitable pharmacokinetic profile of FBX for improving its oral F value.

Finishing coatings used in the wood-based composites industry play a key role in the final appearance of the finished product. However, the use of such coatings is not only for aesthetic purposes but also to protect the product against surface damage and moisture or minimize the emission of harmful substances. The latter is an extremely important factor in terms of safety for both the manufacturer and the user, which is why the emissivity test is one of the most important tests in the case of finishing coatings. Such a role can be played by carbon-rich materials, such as those remaining from the extraction of birch bark. In this article, an attempt was made to create coatings in the form of a film by combining a biopolymer with suberinic acid residues (SAR). There were two types of biopolymers used – polylactide (PLA) and polycaprolactone (PCL), in various polymer-SAR ratios. SAR as a residue, is a material that bounds CO2 from the atmosphere and creates a possibility of further use. As part of this study, the obtained coatings were tested in terms of resistance to scratch, relative hardness, cold liquids, total volatile organic compounds (TVOC) and formaldehyde emission, surface absorption etc. Differences in the polymers used and the effect of the SAR additive on selected surface properties were demonstrated. The addition of carbon-rich SAR significantly improves the gas barrier properties of the surface finishing materials based on PLA and PCL. The relative hardness and scratch resistance has also increased with raising SAR content. However, the increasing content of SAR filler act as a limiter in the depth of penetration of deposited surface finishing materials onto the wood surface.

In this study, composite nanofiber films comprising polyvinyl alcohol, wheat gluten, and glucose (PWG) were fabricated using electrospinning, followed by cross-linking via the Maillard cross-linking. Various mass concentrations of ferulic acid (FA) were incorporated into the PWG films. The results indicate that the average diameter of the FA-PWG films decreased from 449 nm to 331 nm as the concentration of FA increased, until reaching a concentration of 12%, after which a significant increase in diameter was observed. Subsequent Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and differential scanning calorimetry (DSC) results suggested that FA was distributed in the sample films in an amorphous form through hydrogen and ester bonds. Additionally, release experiments and antimicrobial tests on FA-PWG sample films showed good con-trolled release of FA and excellent anti-Escherichia coli and Staphylococcus aureus activity of this film. These findings all indicate that the FA-PWG nanofiber film is a potential candidate for food active packaging.

Water deficit is one of the factors that most influence plant growth and yield. Thus, this study aimed to evaluate the effect of silicon and salicylic acid application and water deficit on the growth and photosynthetic and osmoregulatory metabolism of Talisia esculenta Radlk seedlings and their recovery potential after the resumption of irrigation. Six treatments were performed: irrigation, irrigation suspension, irrigation suspension + silicon at 0.5 g L−1, irrigation suspension + silicon at 1.0 g L−1, irrigation suspension + salicylic acid at 50 mg L−1, and irrigation suspension + salicylic acid at 100 mg L−1. The evaluations were carried out at the beginning of the experiment (T0), at 10 and 15 (DIS) days after irrigation suspension, when the seedlings showed a photosynthetic rate close to zero, and at recovery (REC). The plants were submitted to water restriction for up to 15 days, being then re-irrigated until the recovery point, which was monitored based on the photosynthetic rate. Silicon application attenuated the harmful effects of water deficit on gas exchange, initial fluorescence, promoted proline accumulation in the leaf and root, and provided higher seedling quality. Salicylic acid application contributed to the maintenance of the relative water content of leaves during the water deficit period. Silicon and salicylic acid applications can attenuate the harmful effects of water stress, with silicon being the most effective agent in maintaining its growth and metabolism.

This paper represents a thermodynamic and chemical reactivity study regarding the possible formation of four proteinogenic amino acids: glutamic acid, glutamine, lysine and arginine, starting from three synthons: methylene, nitrene and carbon monoxide. All intermediates are specified: neutral molecules and radicals involved in the formation of these four proteinogenic amino acids. The study is based on the synthonic theory of the formation of the first proteinogenic amino acids and their corresponding polypeptides. The thermodynamic quantitative data are obtained from mechanical-quantum calculations mainly by the DFT-B88-LYP methods, DZVP basis set.

Regulatory macrophages (Mregs) are unique in that they have anti-inflammatory and immunosuppressive properties. Thus, treating inflammatory diseases using Mregs is an area of active research. Human Mregs are usually generated by culturing peripheral blood monocytes stimulated by macrophage colony-stimulating factor with interferon (IFN)-. Here, we generated Mregs with an elongated cell morphology from THP-1 cells stimulated with phorbol 12-myristate 13-acetate and cultured with arginylglycylaspartic acid and vitamin D3. These Mregs regulated macrophage function, and respectively downregulated and upregulated the expression of pro-inflammatory and immunosuppressive mediators. They also expressed Mregs-specific marker, such as dehydrogenase/reductase 9, even when exposed to inflammatory stimulants such as IFN-, lipopolysaccharide, purified xenogeneic antigen, and xenogeneic cells. The Mregs also exerted anti- inflammatory and anticoagulatory actions in response to xenogeneic cells and immunosuppressive effects on mitogen-induced Jurkat T-cell proliferation. Our method of generating functional Mregs in vitro without cytokines is simple and cost-effective.

Acetic acid bacteria (AAB) form a bacterial film on the surface of alcoholic solutions and ferment ethanol to acetic acid while also producing bioactive compounds. To discover functional AAB for industrial use, we isolated and selected strains from farm-produced vinegars using a CaCO3-containing medium. The seven strains belonged to Acetobacter cerevisiae and A. pasteurianus. Physiological properties were determined, including ethanol tolerance at up to 12% (v/v). Acidification at a growth temperature of 40 ℃ was seen for GHA 7, GYA 23, JGB 21-17, and GHA 20 strains, which may be useful in vinegar production where thermotolerant AAB are required. The seven AAB isolates had strong antibacterial activity against Staphylococcus aureus. Antioxidant activity was 2- and 4-fold higher, respectively, for A cerevisiae and A. pasteurianus than for the control, 1% acetic acid. We also observed 91.3% inhibition of angiotensin-converting enzyme activity for the KSO 5 strain, higher than that for the positive control, 0.1% captopril (76.9%). All strains showed complete inhibition of α-glucosidase, except JGB 21-17 and GHA 7 with 98.3% inhibition. Our work suggests usefulness of the strains selected as seed strains for highly efficient production of functional vinegar and illustrates identification of useful functional characteristics on a scientific basis.

Mixed cadmium tellurides – cadmium sulfides thin layers were formed on the polyamide PA 6. Monotelluropentathionic acid (H2TeS4O6) was used as precursor of tellurium and sulfur. We applied a low-temperature, nontoxic and cost-effective SILAR method. Cadmium telluride (CdTe) and sulfide (CdS) layers were formed through consecutive reactions of sorbed/diffused chalcogens species from telluropentathionate anion (TeS4O62–) with functional groups of polyamide and alkaline cadmium sulfate. The pseudo-second-order rate and Elovich kinetic models best fitted to quantify an uptake of chalcogens and cadmium on PA6. The effects of chalcogens and Cd on the structure and optical properties of PA6 were characterized using UV/Vis and IR spectra. The clear changes of these properties found in dependence on the concentration and exposure time in precursor's solutions. Fourier transform infrared spectroscopy and an ultraviolet-visible spectroscopy were applied in order to evaluate the effect of the chalcogens having particles on the changes in structure of polyamide 6 films depending on the exposure time in the solution of the chalcogens precursor and its concentration. The optical band gap energy of formed layers was found to be in the order of 1.52–2.36 eV. Studies of scanning electron microscopy and atomic force microscopy reveal that the diameter of the average grain is about 30 nm. The grains are conical in shape and unevenly distributed all over the surface of the substrate.

Long-chain omega-3 fatty acid status during pregnancy may influence newborn anthropometry and duration of gestation. Evidence from high-quality trials from LMICs is limited. We conducted a double-blind, randomized, placebo-controlled trial among 957 pregnant women (singleton gestation, 14-20 weeks’ gestation at enrollment) in India to test the effectiveness of 400 mg/d algal docosahexaenoic acid (DHA) compared to placebo provided from enrollment through delivery. Among 3379 women who were screened, 1171 were found eligible; 957 enrolled and were randomized. The intervention was two microencapsulated algal DHA (200 X 2= 400 mg/d) or two microencapsulated soy and corn oil placebo tablets to be consumed daily from enrollment (20 weeks) through delivery. The primary outcome was newborn anthropometry (birth weight, length, head circumference). Secondary outcomes were gestational age and 1 and 5 min Appearance, Pulse, Grimace, Activity, and Respiration (APGAR) score. The groups (DHA; n=478 and placebo; n=479) were well balanced at baseline. There were 902 live births. Compliance with the intervention was similar across groups (DHA: 88.5%; placebo: 87.1%). There were no significant differences between DHA and placebo group for birth weight (2750.6 ± 421.5 vs. 2768.2 ± 436.6 g, p=0.54), length (47.3 ± 2.0 vs. 47.5 ±2.0 cm, p=0.13) or head circumference (33.7 ± 1.4 vs 33.8 ± 1.4 cm, p=0.15). The mean gestational age at delivery was similar between groups (DHA: 38.8 ± 1.7 placebo: 38.8 ± 1.7 wk, p= 0.54) as were APGAR scores at 1 and 5 min. Supplementing mothers through pregnancy with 400mg/d DHA did not impact the offspring birthweight, length or head circumference.

Abstract: Polylactic acid (PLA) is brittle in nature with extensive deformation property. For improvement of the end-use quality, it is of significant importance to enhance the producibility of fused deposition modeling (FDM)-printed objects in PLA. The purpose of this investigation is to boost toughness and to reduce the production cost of the FDM-printed tensile test samples with the desired part thickness. To attain the research purpose number of experiments are designed and analyzed by the Response Surface Method (RSM). The statistical analysis is performed to deal with this concern considering layer thickness, infill percentage, and extruder temperature as controlled factors. The tensile test specimens are printed based on the designed experiments, and the tensile strength tests are conducted by SANTAM 150 universal testing machine based on ASTM D638. The honeycomb internal fill pattern is applied for the production of light-weight and high-strength specimens. The area under Force- Extension curve up to fracture is acquired as the toughness of the printed specimens. This study also developed a modeling process using ANN and ANN-GA techniques for developing an accurate estimation for toughness, part thickness, and production cost as dependant variables. Results were evaluated by correlation coefficient and RMSE values. According to the modeling results, ANN-GA as a hybrid ML technique could successfully improve the accuracy of modeling about 7.5, 11.5 and 4.5 % for toughness, part thickness, and production cost, respectively, in comparison with those for the single ANN method. In the other side, the optimization results confirm that the optimized specimen is cost-effective and able to comparatively undergo deformation, which develops the usability of printed PLA objects. The research is accomplished under the constraints of PLA compatibility with existing fused deposition modeling setup without changing the functional hardware/software of the machine. Although the mechanical properties and dimensional accuracy of PLA have already been studied, there is little literature on the toughness of the printed PLA with honeycomb internal fill pattern.

Palmitic acid metabolism involves delta-9 and delta-6 desaturase enzymes forming palmitoleic acid (9cis-16:1; n-7 series) and sapienic acid (6cis-16:1; n-10 series), respectively. The corresponding biological consequences and lipidomic research on these positional MUFA isomers are under development. Furthermore, sapienic acid can bring to the de novo synthesis of the n-10 polyunsaturated fatty acid (PUFA) sebaleic acid (5cis,8cis-18:2), but such transformations in cancer cells are not known. The model of Caco-2 cell line was used to monitor sapienic acid supplementation (150 and 300 μM) and evidence the formation of n-10 fatty acids as well as their incorporation at levels of membrane phospholipids and triglycerides. Comparison with palmitoleic and palmitic acids evidenced that lipid remodeling was influenced by the type of fatty acid and positional isomer, with increase of 8cis-18:1, n-10 PUFA and decrease of saturated fats in case of sapienic acid. Cholesteryl esters were formed only in case of sapienic acid. EC₅₀ of sapienic acid (232.3 μM at 96 hrs) was the highest found among the tested fatty acids, thus influencing cell viability that was only reduced at 25% at 300 μM, whereas palmitoleic acid induced cell death. Two-photon fluorescent microscopy with Laurdan as a fluorescent dye provided information on membrane fluidity, highlighting that sapienic acid increases the distribution of fluid regions, probably connected with the formation of 8cis-18:1 and the n-10 PUFA in cell lipidome. Our results bring evidence for MUFA positional isomers and de novo PUFA synthesis for developing lipidomic analysis and cancer research.

Emergence of more virulent forms of human pathogenic bacteria with multi drug resistance is a serious global issue and requires alternative control strategies. The current study was focused to investigate the antibacterial and antibiofilm potential of ferulic acid grafted chitosan (CFA) against Listeria monocytogenes (LM), Pseudomonas aeruginosa (PA), and Staphylococcus aureus (SA). The present result showed that CFA at 64 µg/mL concentration exhibit bactericidal action against LM and SA (>4 log reduction) and bacteriostatic action against PA (<2 log CFU) within 24 h of incubation. Further studies based on propidium iodide uptake assay, measurement of material released from the cell, and electron microscopic analysis revealed that the bactericidal action of CFA was due to the altered membrane integrity and permeability. CFA dose-dependently inhibited biofilm formation (52-89% range), its metabolic activity (30.8-75.1% range) and eradicated mature biofilms, and reduced viability (71-82% range) of the test bacteria. Also, the swarming motility of LM was differentially affected at sub-MIC concentration of CFA. In the present study, the ability of CFA to kill and alter the virulence production in human pathogenic bacteria will insight a new scope for the application of these biomaterials in healthcare to effectively treat bacterial infections.

The pharmacokinetics of salicylic acid (SA) in sheep was evaluated following intravenous (IV) and oral administration of sodium salicylate (sodium salt of salicylic acid) at different doses. Six healthy sheep were administered sodium salicylate (SS) IV at doses of 10, 50, 100 and 200 mg/kg body weight and another six sheep were drenched with 100 and 200 mg/kg of SS orally. Both studies were randomised crossover trials. A one-week washout period between each treatment was allowed in both studies. Blood samples were collected at 0, 15, 30 minutes and 1, 2, 4 and 6 hours after IV and oral SS administrations. Plasma SA concentrations were determined using high performance liquid chromatography with diode array detection method. Pharmacokinetic variables were calculated in a non-compartmental model. The elimination half-life (T_{1/2 el}) of SA after IV administration of 200 mg/kg SS was 1.16 ± 0.32 hours. Mean bioavailability of SA was 64%, and mean T_{1/2 el} was 1.90 ± 0.35 hours, after 200 mg/kg of oral SS. The minimum plasma SA concentration (16.8 µg/mL) required to produce analgesia in humans was achieved after IV administration of 100 and 200 mg/kg SS in sheep for about 0.17 hour in this study. Experiments on pharmacokinetic-pharmacodynamics modelling are required to determine the actual effective plasma concentration range of SA in sheep.

Gold-centered carbene-metal-amides (CMAs) containing cyclic (alkyl)(amino)carbenes (CAACs) are promising emitters for thermally activated delayed fluorescence (TADF). Aiming at design and optimization of new TADF emitters, we report a density functional theory study of over 60 CMAs with various CAAC ligands, systematically evaluating computed parameters in relation to photoluminescence properties. We demonstrate that the efficiency of TADF of CMAs, arising from a compromise of exchange energy and oscillator strength, is governed by the overlap of HOMO and LUMO orbitals, where HOMO is localized on amide and LUMO on Au-carbene. The S0 ground states and excited T1 states of the CMAs adopt approximately coplanar geometries of carbenes and amides, but rotate perpendicular in the excited S1 states, resulting in degeneracy or near-degeneracy of S1 and T1, accompanied with lowering of the S1-S0 oscillator strength from its maximum at coplanar geometries to near zero at rotated geometries. Based on computations, promising new TADF emitters are proposed and synthesized. Bright CMA complex (Et2CAAC)Au(carbazolide) is obtained and fully characterized to demonstrate that high radiative rates up to 106 s-1 can be obtained for the gold-CMA complexes with small CAAC-carbene ligands.

The mechanistic pathway of TEMPO/I₂-mediated oxidative cyclization of N,N-diaryl amino alcohols 1 is investigated in this study. Based on our direct empirical experiments, three key intermediates (the aminium radical cation 3, the α-aminoalkyl radical 4, and the iminium 5), four kind reactive species (radical TEMPO, cationic TEMPO, TEMPO-I and iodo radical) and three kind pathways (1. SET/PCET mechanism, 2. HAT/1,6-H transfer mechanism, 3. Ionic mechanism) were assumed. Under the assumption, nine free energy diagrams are acquired through DFT calculation. From the comparison of the solution phase free energy, some possibility can be excluded and then the chosen plausible mechanisms are concretized with the more stable intermediate 7.

Depression is the commonest mental disorder worldwide. Both antidepressants and psychotherapy are effective in treating depression, but response to these treatments is often incomplete. Yoga-based interventions (YBIs) have emerged as a promising adjunctive treatment for depression. Recent research has attempted to identify the biological mechanisms associated with the antidepressant actions of YBIs. In this scoping review, conducted according to the PRISMA-ScR guidelines, the PubMed and Scopus databases were searched to retrieve research on biomarkers of response to YBIs in patients with depression. Eleven studies were included in the review. Based on these studies, YBIs may improve depression through beneficial effects on systemic inflammation, stress axis regulation, cardiac autonomic functioning, and possibly reductions in oxidative stress-related cellular damage. Increases in brain-derived neurotrophic factor (BDNF) may represent a final common pathway upon which these processes converge. Though these results are theoretically plausible, they should be interpreted with caution due to certain methodological limitations in the existing research. Replication of these results and improvements in study methodology, and the evaluation of other biomarkers relevant to the pathophysiology of depression, could further elucidate the mechanism of action of YBIs in this disorder, and identify which patients would benefit most from this treatment approach.

Microplastics (MPs) quantification in benthic marine sediments is typically performed by time-consuming and moderately accurate mechanical separation and microscopy detection. In this paper we describe the results of our innovative Polymer Identification and Specific Analysis (PISA) of microplastic total mass, previously tested on either less complex sandy beach sediment or less demanding (because of the high MPs content) wastewater treatment plant sludges, applied to the analysis of benthic sediments from a sublittoral area north-west of Leghorn (Tuscany, Italy). Samples were collected from two shallow sites characterized by coarse debris in a mixed seabed of Posidonia oceanica, and by a very fine silty-organogenic sediment, respectively. After sieving at &lt;2 mm the sediment was sequentially extracted with selective organic solvents and the two polymer classes polystyrene (PS) and polyolefins (PE and PP) were quantified by pyrolysis-GC/MS. A contamination in the 8-65 ppm range by PS could be accurately detected. Acid hydrolysis on the extracted residue to achieve total depolymerization of all natural and synthetic polyamides, tagging of all aminated species in the hydrolyzate with a fluorophore, and reversed-phase HPLC (RP-HPLC) analysis, allowed to quantify within the 137-1523 ppm range the individual mass of contaminating Nylon 6 and Nylon 6,6, based on the detected amounts of the respective monomeric amines 6-aminohexanoic acid (AHA) and hexanediamine (HMDA). Finally, alkaline hydrolysis of the residue from acid hydrolysis followed by RP-HPLC analysis of the purified hydrolysate showed contamination by polyethylene terephthalate (PET) in the 12.1-2.7 ppm range, based on the content of its comonomer, terephthalic acid.

The feasible, reliable and selective multi-template molecularly imprinted polymers (MT-MIPs) based on SBA-15 (SBA-15@MT-MIPs) for the selective separation and determination of the trace level of ginsenoside Rb₁ (Rb₁), ginsenoside Rg₁ (Rg₁) and notoginsenoside R₁ (R₁) (Panax notoginseng saponins, PNS) from biological samples were developed. The polymers were constructed by SBA-15 as support, Rb₁, Rg₁, R₁ as multi-template, acrylamide (AM) as functional monomer and ethylene glycol dimethacrylate (EGDMA) as cross-linker. The new synthetic SBA-15@MT-MIPs were satisfactorily applied to solid-phase extraction (SPE) coupled with high performance liquid chromatography (HPLC) for the separation and determination of trace PNS in plasma samples. Under the optimized conditions, the limits of detection (LODs) and quantitation (LOQs) of the proposed method for Rb₁, Rg₁ and R₁ were in the range of 0.63-0.75 ng mL^-1 and 2.1-2.5 ng mL^-1, respectively. The recoveries of R₁, Rb₁ and Rg₁ were obtained between 93.4% and 104.3% with relative standard deviations (RSDs) in the range of 3.3-4.2%. All results show that the obtained SBA-15@MT-MIPs could be a promising prospect for the practical application in the selective separation and enrichment of trace PNS in the biological samples.

Back-care knowledge and behaviour may play a vital role in preventing musculoskeletal current and future discomfort and injuries. The aim of the current survey was to explore the level of knowledge regarding ergonomics and posture together with postural behaviour and the incidence of musculoskeletal pain (MSP) in university students in the northeast of England. A mixed methods survey was conducted on a convenience sample of 55 university students. The 32-item valid and reliable questionnaire contains questions on socio-demographics, MSP, knowledge regarding ergonomics and posture (8 closed ended and 8 open-ended items) as well as postural behaviour. Nearly 1.8%, 20% and 78.2% of the university students had poor, fair and good knowledge of ergonomics and posture respectively. Among the 37 students who carried a backpack, 51.4% were found to have poor postural behaviour, 37.8% had fair behaviour and 10.8% had good postural behaviour. Of the 18 students who did not carry a backpack, 55.6% were found to have poor postural behaviour, 27.8% had fair behaviour and 16.6% had good postural behaviour. 70.9% of the students experienced MSP with the most prevalent site of pain being the lower back region. The key themes that emerged from qualitative data (8 open-ended questions) were: “Comfortable posture”, “Correct spinal alignment”, “Spine support”, “less pain and injuries”, “Use knees not the back”, “Keep the object close to body”, “Hands on desk”, “Feet flat on floor” as well as “eyes at screen level”. The findings of this study can be used to develop targeted interventions aimed at educating university students about ergonomics and posture in order to prevent the incidence of MSP. Future research in this field with a large and more representative sample of the university students’ population is strongly recommended to fully understand their knowledge of ergonomics and posture, postural behaviour as well as incidence of MSP.

The construction time of concrete structures in hydraulic tunnels is long, the construction environment is complex, and there are many influencing factors. The requirements for construction quality are high, not only to meet the strength requirements, but also to meet the design requirements of erosion resistance, crack resistance, and seepage resistance according to its specific operating environment. Therefore, evaluating the construction quality of concrete structures in hydraulic tunnels is of great significance. Considering the randomness and fuzziness of factors affecting the construction quality of concrete structures in hydraulic tunnels, this paper proposes a comprehensive evaluation model based on Combined Weighting (CWM) and Uncertainty Measurement Theory (UM). The IAHP method and CRITIC method are used to determine the subjective and objective weights of evaluation indicators, combined weighting is based on the principle of minimum entropy, and the UM method is used to evaluate the construction quality level. Finally, taking a hydraulic tunnel as an example, its construction quality grade is calculated to be III according to the evaluation model proposed in this paper, which matches with the engineering reality, and a comparative study is made with the mixture element topology theory at the same time. It is verified that the evaluation model can scientifically and reasonably evaluate the construction quality level of concrete structures in hydraulic tunnels.

Single-phase-to-ground fault in non-effectively grounded systems poses serious public safety concern. Along with increasing deployment of low-voltage (LV) sensors, new opportunities and ways are created for solving this traditional problem in distribution systems. A new approach, identifying primary single-phase-to-ground line fault and locating it through measurement data from smart sensors deployed in the secondary side of distribution transformers, is proposed in this paper. When a fault occurs in primary distribution feeder, the transient aerial mode voltage (AMV) of each LV smart sensor is calculated. The fault line can be identified by an abrupt change value of AMV at LV side. Next, by finding the position of the maximum value of this AMV from LV sensors on the fault line, the fault location can be pinpointed to two neighboring distribution transformers. The proposed method has been proven to be efficient and reliable by simulation studies.

Epidemiological and clinical evidence have extensively documented the role of obesity in the develop-ment of endometrial cancer. However, the effect of fatty acids on cell growth in endometrial cancer has not been widely studied. Here we reported that palmitic acid significantly inhibited cell proliferation of endometrial cancer cells and primary cultures of endometrial cancer, and reduced tumor growth in a transgenic mouse model of endometrial cancer, in parallel with increased cellular stress and apoptosis and decreased cellular adhesion and invasion. Inhibition of cellular stress by N-acetyl-L-cysteine effec-tively reversed the effects of palmitic acid on cell proliferation, apoptosis and invasive capacity in the endometrial cancer cells. Palmitic acid increased the intracellular formation of lipid droplets in a time- and dose-dependent manner. Depletion of lipid droplets by blocking DGAT1 and DGAT2 effectively increased the ability of palmitic acid to inhibit cell proliferation and induce cleaved caspase 3 activity. Collectively, this study provides new insight into the effect of palmitic acid on cell proliferation, inva-sion and the formation of lipid droplets that may have potential clinical relevance in the treatment of obesity-driven endometrial cancer

Inhibition of quorum sensing (QS)-dependent biofilm formation and virulence is extensively investigated as a novel approach to combat bacterial pathogens by impeding their ability to cause antibiotic-tolerant diseases. Such strategies are considered a promising alternative to conventional antibacterial therapy since interrupting the central cell-to-cell communication system imposes less selective pressure on the target pathogen. In this study, novel hybrid compounds composed of anthranilic acids substituted with halogens at different positions of the phenyl ring, and 4-(2-aminoethyl/4-aminobuthyl)amino-7-chloroquinoline linked via 1,3,4-oxadiazole were synthesized using standard procedures. Their anti-QS activities were evaluated using Chromobacterium violaceum ATCC31532 (anti-biofilm and bactericidal activities) and Pseudomonas aeruginosa PAO1 (anti-biofilm/-virulence activities). The results showed that compounds 15–19 and 23 inhibited the production of violacein, the QS-inducible pigment, in C. violaceum to a similar extent as the model QS inhibitor - quercetin (83.5–90%). Compound 15 exhibited the strongest effect on P. aeruginosa in the anti-biofilm screening, reducing its ability to form biofilm by almost 50%, while compounds 16 and 19 were able to reduce the biofilm formation by approximately 30%. However, compound 23 did not demonstrate significant anti-biofilm activity and only inhibited pyocyanin production in P. aeruginosa. In conclusion, this study suggests that 1,3,4-oxadiazoles 15, 16, and 19 are the most promising compounds for future research as novel QS inhibitors against Gram-negative bacteria equipped with different QS signaling pathways.

Meta-aminobenzoic acid, an important model system in the study of polymorphism and crystallization of active pharmaceutical ingredients, exist in water in both the nonionic (mABA) and zwitterionic (mABA^±) forms. However, the constituent molecules of the polymorph that crystallizes from aqueous solutions are zwitterionic. This study reports atomistic simulations of the events surrounding the early stage of crystal nucleation of meta-aminobenzoic acid from aqueous solutions. Ab initio molecular dynamics was used to simulate the hydration of mABA± and mABA, and to quantify the interaction of these molecules with the surrounding water molecules. Density functional theory calculations were conducted to determine the low-lying energy conformers of meta-aminobenzoic acid dimers and compute the Gibbs free energies in water of nonionic, (mABA)₂, zwitterionic, (mABA^±)₂ and nonionic-zwitterionic, (mABA)(mABA^±), species. Classical molecular dynamics simulations of mixed mABA–mABA^± aqueous solutions were carried out to examine the aggregation of meta-aminobenzoic acid. According to these simulations the selective crystallization of the polymorph which constituent molecules are zwitterionic is driven by the formation of zwitterionic dimers in solution, which are thermodynamically more stable than (mABA)₂ and (mABA)(mABA^±) pairs. This work represents a paradigm of the role of molecular processes during the early stages of crystal nucleation in affecting polymorph selection during crystallization from solution.

Understanding the distribution of rock glaciers provides key information for investigating and recognizing the status and changes of the periglacial environment. Deep learning algorithms and red-green-blue (RGB) bands from high-resolution satellite images have been extensively employed to map rock glaciers. However, the near-infrared (NIR) band offers rich spectral information and sharp edge features that could significantly contribute to semantic segmentation tasks, but it is rarely utilized in constructing rock glacier identification models due to the limitation of three input bands for classical semantic segmentation networks, like DeeplabV3+. In this study, a dual-encoder DeeplabV3+ network (DEDNet) was designed to overcome the flaws of classical DeeplabV3+ network (CDNet) when identifying rock glaciers using multispectral remote sensing images by extracting spatial and spectral features from RGB and NIR bands, respectively. This network, trained with manually labeled rock glacier samples from QiLian Mountains, established a model with accuracy, precision, recall, specificity, and mIoU (Mean Intersection over Union) of 0.9131, 0.9130, 0.9270, 0.9195, and 0.8601, respectively. The well-trained model was applied to identify new rock glaciers in a test region, achieving a producer's accuracy of 93.68% and a user's accuracy of 94.18%. Furthermore, the model was employed to two study areas in northern Tien Shan (Kazakhstan) and Daxue Shan (Hengduan Shan, China) with high accuracy, which proved that the DEDNet offers an innovative solution to more accurately map rock glaciers on a larger scale due to its robustness across diverse geographic regions.

Simple Summary: The distribution of typical bacterial redox enzymes such as pyruvate-ferredoxin oxidoreductase (PFOR) in protozoa remains interestingly puzzling. Previous studies have demonstrated diverse cellular localizations of PFOR in some amitochondriate anaerobic protozoa. PFOR is of particular pharmacological importance because it catalyzes the reductive bio-activation of nitro-based prodrugs to cytotoxic radical metabolites. Metronidazole was developed primarily as an antiprotozoal agent against infections caused by Trichomonas vaginalis. However, its antimicrobial spectrum was subsequently expanded to cover anaerobic bacterial infections. It has been shown that mutations in the genes encoding PFOR result in inherent resistance of PFOR-possessing anaerobic protozoa and bacteria to nitro-based prodrugs. Deciphering the evolutionary history of PFOR is crucial in deepening our understanding of the evolution of anaerobic pathogens and unfold new approaches for drug discovery and targeting in pathogen chemotherapy. Abstract: The present frontrunners in the chemotherapy of infections caused by protozoa are nitro-based prodrugs that are selectively activated by PFOR-mediated redox reactions. This study seeks to analyze the distribution of PFOR in selected protozoa and bacteria by applying comparative bioinformatics approaches to test the hypothesis that PFOR was most likely acquired through horizontal gene transfer (HGT) from bacteria. Furthermore, to identify other genes that were putatively acquired using proteome-wide and gene expression analyses. A plausible explanation for the patchy occurrence of PFOR in protozoa is based on the hypothesis that bacteria are potential sources of genes that enhance optimal adaptation of protozoa in hostile environments. The exclusively expressed proteins obtained from Entamoeba histolytica and the putative gene donor, Desulfovibrio vulgaris, showed an over-expression of eleven genes involved in intermediary metabolism. If these results can be reproduced in other PFOR-possessing protozoa, it would provide a more validated evidence to support the horizontal transfer of pfor from bacteria.

The intelligent elderly care model places new demands on the skills of aging caregivers. The identification and development of forward-thinking, high-potential nursing talent is essential for advancing the intelligent elderly care sector. Multi-benchmarking selection and competitive analysis is used to evaluate and identify nursing personnel in the rehabilitation treatment center of a hospital in Hefei City. Using proxy evaluation and democratic evaluation model, three types of benchmarks such as single item benchmark, individual benchmark and group benchmark were identified and selected, and the professional nursing team was constructed based on the evaluation results. Different from the traditional other-directed evaluation, multi-benchmarking selection and competitive analysis is self-directed evaluation, this method is more conducive to the identification of high-potential and digital nursing talents by intelligent elderly service organizations, and facilitates the formation of professional nursing teams with complementary strengths and cross-fertilization, so as to satisfy the diversified and multi-level needs of the elderly for intelligent elderly services.

Hepatitis E virus (HEV) is responsible for large waterborne epidemics of hepatitis in endemic countries and is an emerging zoonotic pathogen worldwide. In endemic regions, HEV-1 or HEV-2 genotypes are frequently associated with fulminant hepatitis in pregnant women, while with zoonotic HEV (HEV-3 and HEV-4), chronic cases of hepatitis and severe neurological disorders are reported. Hence, it is important to characterize the interactions between HEV and its host. Here, we investigated the ability of the non-structural polyprotein encoded by the first open reading frame (ORF1) of HEV to modulate the host early antiviral response and in particular the type I interferon (IFN-I) system. We found that the amino-terminal region of HEV-3 ORF1 (MetPCP), containing a putative methyltransferase (Met) and a papain-like cysteine protease (PCP) functional domain, inhibited IFN-stimulated response element (ISRE) promoter activation and the expression of several IFN-stimulated genes (ISGs) in response to IFN-I. We showed that the MetPCP domain interfered with the Janus kinase (JAK)/signal transducer and activator of transcription protein (STAT) signalling pathway by inhibiting STAT1 nuclear translocation and phosphorylation after IFN-I treatment. By contrast, MetPCP had no effect on STAT2 phosphorylation and a limited impact on the activation of the JAK/STAT pathway after IFN-II stimulation. This inhibitory function seemed to be genotype-dependent as MetPCP from HEV-1 had no significant effect on the JAK/STAT pathway. Overall, this study provides evidence that the predicted MetPCP domain of HEV ORF1 antagonises STAT1 activation to modulate the IFN response.

(1) Background: TNF inhibitors (TNFi) have revolutionized the treatment of rheumatoid arthritis (RA). However, 30-40 % of RA patients do not respond adequately to those biologics. In addition to neutralizing soluble TNF, TNFi have the ability to bind the transmembrane form of TNF, tmTNF. Importantly, tmTNF can act itself as a receptor that induces a “Reverse Signaling” (RS) in cells. We previously showed that certolizumab, a Fab’ TNFi, activates RS in human primary monocytes, at least in part through the transcription factor NRF2 that is known to regulate the expression of genes involved in anti-inflammatory response and oxidative stress. (2) Methods: Here, we have developed an assay for the prediction of clinical response of RA patients to TNF inhibitors. This assay is based on mRNA quantitation of CD36 activation and of 6 genes induced by NRF2 following tmTNF RS in fresh monocytes. (3) Results: We could predict the response to anti-TNF monoclonal antibodies (mAbs) with 93.3 % accuracy. However, our method was not suitable for the prediction of the response to TNF soluble receptor etanercept. (4) Conclusions: We have developed a rather simple, short-term, test that can be standardized. Predicting the response to TNF mAbs will help physicians offer the best available treatment and provide patients with personalized medicine.

Aiming at the APF algorithm in the collision-free path planning and LQR algorithm tracking process, there are problems such as unreachable target points, local optimization, low safety coefficient of autonomous lane change collision avoidance tracking control and poor stability, this paper proposes an optimized APF method, which solves the defects of the traditional artificial potential field method by adding the distance adjustment factor, the safety distance protection model and the sub-target virtual potential field, and at the same time generates the autonomous driving car collision-free path. The path tracking control system is designed based on feed-forward control and DLQR controller, in which the vehicle dynamics state space model is used as the basis, the model is linearized and discretized, and the corresponding constraint variables are set to minimize the control command objective cost function under the constraints, and the objective of the DLQR controller.The objective is to accurately determine the steering angle in order to achieve path tracking and eliminate the lateral error between the reference path and the actual path caused by external interference.Finally, the simulink model and CarSim parameter configuration joint simulation platform are built, and different obstacle scenarios and different speeds are selected for collision-free path planning and tracking motion simulation research and analysis, which verifies the accuracy and practicability of the algorithm, and shows more obvious advantages in obstacle avoidance ability, path smoothing degree, and collision avoidance safety stability. The ideas proposed in this paper are expected to be further extended and popularized to actual path planning problems, which has important practical significance and engineering value.

This article aims to analyze household energy data to predict electricity self-sufficiency and identify the key features that impact it. For this purpose, we use SHAP (Shapley Additive Explanations), LightGBM (Light Gradient Boosting Machine), and a correlation heatmap-based framework to analyze 12 months of energy and questionnaire survey data collected from over 200 smart houses in Kitakyushu, Japan. We use the SHAP summary plot to identify the impact-wise order of key features influencing the electricity self-sufficiency rate (ESSR). Using SHAP, we demonstrated that key features are; housing types, average monthly electricity bill, floor heating, electric capacity, number of washing and drying machines, fee plans, occupation of household head, total floor area, average monthly gas bill, cooking equipment, etc. Furthermore, we adopted the LightGBM classifier with $\ell^1$ regularization to extract the most significant features and predict the electricity self-sufficiency rate of households. This LightGBM-based model can also predict the electricity self-sufficiency rate of households that did not participate in the questionnaire survey. A heat map is also used to analyze the correlation among household variables. The findings discussed in this article offer valuable insights for energy policymakers to achieve the targets of energy self-sufficient houses.

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.

We describe a forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) to operationally forecast conditions in Northern and Central California. It was established in 2014 and has been periodically improved. In the current configuration, WRF forecasts are routinely performed multiple times each day on a 2-km grid, and the results are used as input to wildfire fuel moisture, fire probability, and wildfire spread models. Components of the system include a stochastically perturbed ensemble; an annually updated reanalysis covering more than 30 years; and validation against PG&E’s extensive mesonet and other observing networks. We describe the development and validation of the next operational edition. Configurations tested include irrigation triggered by crop growing season and an ensemble-based approach with intelligently sub-selected Global Ensemble Forecast System (GEFS) members. The latter approach allows for enhanced uncertainty sampling in WRF forecasts and can greatly improve WRF forecasts when calibrated by observations.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article, and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions. Python, a versatile programming language, holds vast potential for Sentiment Analysis (SA). Leveraging the Requests and TextBlob libraries, we have crafted a user-friendly code that enables Industrial Engineers (IE) and managers, particularly those who are new to Python, to extract and analyze sentiment efficiently. We aim to provide IE/managers in service companies requiring SA capabilities with a simple yet effective Python solution. While machine learning resources like PyTorch/TensorFlow are commonly utilized in SA, offering pre-built algorithms and tools for training, and implementing machine learning models, we sought to exploit Python's versatility by integrating additional web-scraping libraries. Thus, by using a lexicon-based approach, we intend to deliver an informative and practical article. The code in this article is twofold; firstly, it can be easily adapted by IE/managers possessing basic Python skills; secondly, we aim to inspire junior IE/managers to develop their own customized coding solutions tailored to specific organizational needs.

With recent advancements in network technology and spread of Internet, use of social network services and Internet of Things devices has flourished, leading to a continuous generation of large volumes of graph stream data, where changes, such as additions or deletions of vertices and edges occur over time. Additionally, owing to the need for efficient use of storage space and security requirements, graph stream data compression has become essential in various applications. Even though various studies on graph compression methods have been conducted, most of them do not fully reflect the dynamic characteristics of graph streams and complexity of large graphs. In this paper, we propose a compression scheme using provenance data to efficiently process and analyze large graph stream data. It obtains provenance data by analyzing graph stream data and builds a pattern dictionary based on this to perform dictionary-based compression. By improving the existing dictionary-based graph compression methods, it enables more efficient dictionary management through tracking pattern changes and evaluating their importance using provenance. Furthermore, it considers the relationships among sub-patterns using an FP-tree and performs pattern dictionary management that updates pattern scores based on time. Our experiments show that the proposed scheme outperforms existing graph compression methods in key performance metrics, such as compression rate and processing time.

The detection and recognition of tables in image-based documents is a challenging and essential task for automated data extraction and anal- ysis. This paper introduces a methodology that utilizes Convolutional Neural Networks (CNNs) to address this problem. By harnessing the ro- bust visual recognition abilities of CNNs, the proposed method effectively detects and extracts tables from image-based documents. Additionally, an Encoder-Dual Decoder (EDD) architecture is employed to extract the textual content from table cells, enabling the transformation of visual data into structured, machine-readable formats. This structured data is then further processed using a Vector Space Model (VSM)-based language modeling technique for query-based table retrieval. The methodology’s accuracy is assessed by analyzing the spatial relationships between the extracted cells and comparing them against a pre-defined table structure. The results provide an evidence to the effectiveness of the proposed ap- proach, with an impressive 85% accuracy rate and a corresponding error rate of 15%. This accurate extraction and recognition of tables from image-based documents can significantly enhance applications in data analysis, information retrieval, and knowledge extraction.

Particulate Organic Carbon (POC) plays a crucial role in the marine carbon cycle, influencing carbon flux and many important ocean biogeochemical processes in the Bay of Bengal. The purpose of this study was to examine the seasonal and annual variability of POC in the Bay of Bengal (BoB) region and its correlation with Sea Surface Temperature (SST) and Chlorophyll-a (Chlor_a). This study uses level-3 POC, Chlor_a, and SST data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua satellite. The surface POC concentration in the Bay of Bengal declined at a rate of -1.30 mgm^-3y^-1 over a ten-year period (2003-12) and ranged from 86.48 mgm^-3 to 110.93 mgm^-3 with an average of (93.74±7.50 mgm^-3). Seasonally, the mean POC was highest (97.40 mgm^-3) during the post-monsoon (October-November) and lowest (79.36 mgm^-3) in the pre-monsoon (March-May). Seasons were observed to have statistically significant differences in POC concentration in the study area (F_(3,2155) = 6.298; p <0.05). A strong positive correlation between POC and Chlorophyll was observed whereas a week positive correlation between POC and SST was observed. POC was observed to be very prominent in post-monsoon (97.40 mgm^-3) and in northeast-monsoon (97.14 mgm^-3) and moderate to low in southwest (81.12 mgm^-3) and pre-monsoon (79.36 mgm^-3). The Bay of Bengal’s annual mean POC:Chlor_a ratio ranged from 97.56 mgm^-3 to 332.89 mgm^-3, indicating a significant impact of biological processes on POC composition. To see how POC fluctuation affects biogeochemical processes in the Bay of Bengal, deeper investigation is required.

Obesity is a risk factor for the development of gestational diabetes mellitus (GDM). However, the most optimal type of nutritional intervention to prevent GDM in high-risk women is not clearly defined. This study investigates if nutritional treatment based on the Mediterranean diet (MedDiet) before 12th gestational week (GW) in women at high risk due to a body mass index (BMI)≥25kg/m2, reduces the rate of GDM and metabolic syndrome (MetS) at 3 years postpartum. We performed a post-hoc analysis of the San Carlos Gestational Prevention Study. A total of 735 women with BMI≥25kg/m2 were evaluated between 2015-2018, 246 in standard diet control group (CG) and 489 in MedDiet intervention group (IG). The rate of GDM was significantly lower in IG compared to CG (25.1%vs31.7%;p=0.037). Postnatal follow-up was completed by 141 women in CG (57%) and 312 women in IG (64%). At 3 years postpartum, we observed a reduction (relative risk 95% confidence interval) in the rates of impaired fasting glucose (IFG) (0.51 (0.28-0.92);p=0.019), obesity (0.51 (0.28-0.92),p=0.041), waist circumference (WC)≥89.5cm (0.54 (0.31-0.94);p=0.022) and MetS (0.56 (0.33-0.94);p=0.003). MedDiet reduces the rate of GDM and postpartum MetS in women with BMI)≥25kg/m2, suggesting that its implementation should be routinely recommended from the first GWs.

A paper recently published by eLife on forebrain cortical synaptic plasticity reports that retinoic acid (RA) alters synaptopodin-dependent metaplasticity in mouse dentate granule cells (Lenz et al., 2021). RA is the active form of vitamin A that functions as a ligand for nuclear RA receptors that directly bind genomic control regions to regulate gene expression (Chambon, 1996; Ghyselinck and Duester, 2019). However, some studies have suggested that RA may have nongenomic effects outside of the nucleus, particularly with regard to synaptic plasticity (Aoto et al., 2008; Zhang et al., 2018). The current results reported by Lenz et al. demonstrate that treatment with pharmacological levels of RA can alter synaptic plasticity which may be useful to treat neurological diseases (Lenz et al., 2021). However, the results reported here and those reported by others have not shown that endogenous RA is normally required for synaptic plasticity (or any other nongenomic effect) as there are no reports of genetic loss-of-function studies that remove endogenous RA in adult brain. The implication is that pharmacological levels of RA result in nongenomic effects, some of which may be helpful to treat certain diseases but in other cases this may cause unwanted side-effects.

Mango (Mangifera indica L.) is an allotetraploid (2n = 4X= 40) drupe fruit and has high nutritional value belongs to genus Mangifera and family Anacardiaceae. Mango cultivars are used with worldwide acceptance to pharmacological, ethnomedical, and phytochemical industries. Assessment of the genetic distinctiveness of a cultivar through morphological descriptors is an important tool for both the registration and the protection. New mango genotypes have been improved using valuable diverse germplasm resources to ensure food security. DNA fingerprinting based simple sequence repeats (SSR)-markers have been the most broadly used, effective and accurate in evaluation of genetic characterization of a cultivar. Molecular breeding is an effective source of genetic gain after improvement of fruit trees using marker assisted genomic selection. Total genomic DNA (gDNA) was generated using CTAB method from each cultivar. The most effective 50 hyper-variable SSR markers were selected. Highly specific DNA fingerprints were identified in the candidate line ‘Azeem Chaunsa’ compared with three standard cultivars using SSR-PCR. An agglomerative hierarchical clustering method was used to construct dendrogram based on the UPGMA clustering method. Cultivar identification diagram (CID) was constructed to evaluate association among standard cultivars and Azeem Chaunsa. Our results showed that SSR markers could efficiently assess genetic diversity in mango. The genetic similarity coefficients were recorded between the cultivars of mango ranged from 0.49 to 0.67. CID results concluded that cultivar ‘Azeem Chaunsa’ varied significantly from the check cultivar, Sindhri (46.2%), S.B Chaunsa (45%) and Sufaid Chaunsa (46.7%). The results obtained in this study will orient cultivar identification strategies for a successful future.

The manufacturing method influences the properties of the produced components. This work investigates the influence of manufacturing methods such as fused filament fabrication (3D printing) and injection molding on water absorption, mechanical and thermal properties of the specimens produced from neat biobased poly(lactic acid) (PLA) polymer and poly(lactic acid)/wood composites. Acrylonitrile butadiene styrene (ABS) acts as the reference material due to its low water absorption and good functional properties. The printing layer thickness is one of the factors that affects the properties of a 3D printed specimen. The investigation includes two different layer thicknesses (0.2 mm and 0.3 mm) while maintaining uniform overall thickness of the specimens across two manufacturing methods. 3D printed specimens absorb significantly higher amounts of water than the injection molded specimens, and the increase in the layer thickness of the 3D printed specimens contributes to further increased water absorption. However, the swelling due to water absorption in 3D printed specimens decreases on increased layer thickness. Tensile, flexural and impact properties of all the specimens decrease after water absorption while the properties improve on decreasing the layer thickness. Higher porosity on increasing the layer thickness is the predominant factor. The results from dynamic mechanical analysis and microscopy validate the outcomes.

Automatic and blind parameter estimation based on the inherent features of wireless signals is a major research area due to the fact that these techniques lead to the simplification of receivers, especially in terms of coarse synchronization, more importantly reduce down the signaling load at the control channels. Thus, in the literature many techniques are proposed to estimate a vast set of parameters including modulation types and orders, data and chip rates, phase and frequency offsets and so on. In this paper, a cyclostationary feature detection based method is proposed to estimate the carrier numbers and carrier spacing of carrier-aggregated direct sequence spread spectrum cellular signals blindly. The particular chip rate of the signal is also estimated through the process jointly. In the paper, after the proposed method is formulated, the measurement setup which is developed to collect the data for the validation of the proposed method is introduced. The measurement results are post-processed for performance analysis purposes. To that end, the method is investigated in terms of SNR values, different channel conditions, and measurement durations. Furthermore, the performance of the proposed method is compared with that of energy detection. Measurement results indicate superior performance of the proposed method under significant wireless channel impairments and in low-SNR regions.

The elderly population is particularly susceptible to myocardial damage caused by heat stress (HS). With the continuous increase in global temperatures, this poses an undeniable challenge to human health. This study aimed to investigate the therapeutic effect of Shikimic Acid (SA) in treating HS-induced myocardial damage through network pharmacology, molecular docking, molecular dynamics (MD) simulations, and in vitro experiments. Network pharmacology analysis revealed that SA alleviates the inflammatory response in the heart muscle associated with HS by targeting 60 disease-related targets, such as TP53, TNF, and IL-6. The tumor proteoglycan, the PI3K-Akt signaling pathway, and hepatitis B were identified as the primary therapeutic pathways. Molecular docking and MD simulation results confirmed that SA can stably bind to both TNF (-6.642 kcal/mol) and IL-6 (-7.261 kcal/mol), and the complexes of Shikimic Acid-IL-6 and Shikimic Acid-TNF did not undergo significant changes within 100 ns. In addition, the in vitro experiment showed that 250 μM SA significantly increased the survival rate of HL-1 cells exposed to 43°C for 2 h by 71.1% and promoted the proliferation of HL-1 cells by 30.7%. Overall, these findings provide substantial evidence for the therapeutic potential of SA in HS-induced myocardial damage.

The sleeping and grazing behaviors of horses play a crucial role in their health and welfare. In the horse industry, with the prevalent trend of individual single-stall farming in stable, accurately identifying various behaviors of horses within stables is imperative. This study has established a spatio-temporal dataset for horse postures and behaviors, proposed an algorithm utilizing a SE-SlowFast network with an enhanced loss function. This algorithm achieves automatic recognition of multiple postures and behaviors of horse simultaneously. The model developed in this study demonstrates high accuracy in identifying three postures within the stable: Standing, Crouching, and Lying, achieving respective accuracies of 92.73%, 91.87%, and 92.58%. Additionally, it accurately recognizes two behaviors: Sleeping and Grazing, achieving best accuracies of 93.56% and 98.77%. The overall best accuracy of the model is 93.9%. Experiments on video recognition confirm that the suggested model recognizes horse video data accurately. This study marks the first time computer vision technology has been used in the horse farming industry, achieving non-intrusive recognition of multiple horse postures and behaviors. This study provides valuable data support for livestock managers to evaluate the health conditions of horses, enhances the welfare of horses in stables, and contributes to the advancement of modern horse husbandry practices.

Small cellular particles are released into the surroundings of cells and are proposed to play an important role in intercellular communication and consequently the responses of microbial com-munities to environmental stressors. We studied the connection between the small cellular parti-cles and the efficiency of three culture series of the microalge Phaeodactylum tricornutum and bac-teria (axenic microalgae, bacterial culture and co-culture of the two) in removing bisphenols from their growth medium. The microorganism growth rate was determined by flow cytometry, protein profiles were examined by protein gel electrophoresis, cultures and small cellular particle isolates were imaged by scanning electron microscopy, and bisphenols were analyzed using gas chroma-tography coupled with tandem mass spectrometry (GC-MS/MS). Higher growth rates of microal-gae were observed in the co-culture than in the axenic microalgal culture, while the presence of bisphenols neither influenced the morphology of the microalgal cells, protein profiles, nor the small cellular particle isolates. Biotic removal of bisphenols ranged from 0% to 71% and differed among the culture series in a compound-specific manner. However, it remains unclear which mechanisms influenced algal growth and bisphenol removal. Further research on the mechanisms of interspecies communication is needed to advance our understanding of microbial communities at the nano-level.

Sustainable development and education in sustainable development (ESD) are crucial and interconnected topics under wide discussion today. Young adults need to be educated in how to help bring about change. Thus, the dynamic relationship between school and home is important. In education, use could be made of English language classes, especially since English is a global language that enables access to the sustainability literature and facilitates discussion in global conferences and meetings. Consequently, English as a foreign language (EFL) students could gain confidence from being able to understand and use the terminology of, for example, sustainability. In this paper, the use of competence-based language teaching (CBLT) is proposed as a means of introducing sustainability topics into EFL writing classes at a university in Saudi Arabia. Students’ competence in sustainable development is therefore considered based on their ability to write about suggested sustainable development topics, measured on a scale for five dimensions of ESD proposed by Michelsen and Fischer (2017). The results demonstrate that the students possessed competence in sustainable development and intended to participate in its implementation. Thus, recommendations are made for the stakeholders in the education sector to include sustainable development topics as an initial offering in the curricula of various specialties using the CBLT approach.

In this study, the coating order of two monomers in the shell polymerization process of core–shell nanoparticles was altered to facilitate easy coating and optimize the properties of the coated surface to simplify the additional coating formulation process. To obtain a glass transition temperature suitable for coating, a core was synthesized by the copolymerization of an acryl monomer. A perfluoro monomer and silane monomer were additionally added to synthesize nanoparticles exhibiting both water–oil repellency and anchoring properties. In order to realize various surface properties, the nanoparticles underwent surface modification and cellulose fiber was introduced. Through the various data described in this text, the surface properties improved with the order of introduction of the two monomers.

Background: Pharmacists need up-to-date knowledge and decision-making support in HIV care. We aim to develop MARVIN-Pharma, an adapted artificial intelligence-based chatbot initially for people with HIV, to assist pharmacists, considering evidence-based needs. Methods: From Dec 2022 to Dec 2023, an online needs-assessment survey evaluated Québec pharmacists' knowledge, attitudes, involvement, and barriers relative to HIV care, alongside perceptions relevant to the usability of MARVIN-Pharma. Recruitment involved convenience and snowball sampling, targeting National HIV and Hepatitis Mentoring Program affiliates. Results: Forty-one pharmacists (28 community, 13 hospital-based) across 15 Québec municipalities participated. Participants perceived their HIV knowledge as moderate (M=3.74/6). They held largely favorable attitudes towards providing HIV care (M=4.02/6). They reported a “little” involvement in the delivery of HIV care services (M=2.08/5), most often ART adherence counseling, refilling, and monitoring. The most common barriers reported to HIV care delivery were a lack of time, staff resources, clinical tools, and HIV information/training, with pharmacists at least somewhat agreeing that they experienced each (M≥4.00/6). On average, MARVIN-Pharma's acceptability and compatibility were in the ‘undecided’ range (M=4.34, M=4.13/7, respectively), while pharmacists agreed to their self-efficacy to use online health services (M=5.6/7). Conclusion: MARVIN-Pharma might help address pharmacists' knowledge gaps and barriers to HIV treatment and care, but pharmacist engagement in the chatbot’s development seems vital for its future uptake and usability.

Aim: To analysis the relationship between healthy adults right ventricular diameter (RVD) and geographical factors. Location: China’s 22 provinces, municipalities and autonomous regions. Methods: Using correlation analysis the relationship between RVD and nine geographic factors, build predictive models by factor analysis. Results: There is significant correlation between RVD and geographical factors, and the annual average temperature is most relevant geographical factors, a predictive model was built by factor analysis: Ŷ = 19.46 + 0.0007072X1 + 0.001034X2 -0.05412X3 -0.001405X4 -0.0006351X5 + 0.02903X6 + 0.01243X7 -0.01033X8 + 0.03816X9 ± 0.63. Then using Kriging interpolation interpolate the geographical distribution of Chinese healthy adult right ventricular diameter reference value in ArcGIS software. Main Conclusion: If geographic factors can be derived in anywhere of China, RVD can be calculated by the model, you can also get RVD from geographical distribution.

The vast array of omics data in microbiology presents significant opportunities for studying bacterial pathogenesis and creating computational tools for predicting pathogenic potential. However, the field lacks a comprehensive, curated resource that catalogs bacterial strains and their ability to cause human infections. Current methods for identifying pathogenicity determinants often introduce biases and miss critical aspects of bacterial pathogenesis.In response to this gap, we introduce BacSPaD (Bacterial Strains’ Pathogenicity Database), a thoroughly curated database focusing on pathogenicity annotations for a wide range of high-quality, complete bacterial genomes. Our rule-based annotation workflow combines metadata from trusted sources with automated keyword matching, extensive manual curation, and detailed literature review. Our analysis classified 5,502 genomes as pathogenic to humans (HP) and 490 as non-pathogenic to humans (NHP), encompassing 532 species, 193 genera, and 96 families. Statistical analysis demonstrated a significant but moderate correlation between virulence factors and HP classification, highlighting the complexity of bacterial pathogenicity and the need for ongoing research. This resource is poised to enhance our understanding of bacterial pathogenicity mechanisms and aid in the development of predictive models. To improve accessibility and provide key visualization statistics, we developed a user-friendly web interface, accessible at https://bacspad.altrabio.com.

Artificial Intelligence (AI) and Deep Reinforcement Learning (DRL) have revolutionised e-learning by creating personalised, adaptive, and secure environments. However, challenges such as privacy, bias, and data limitations persist. E-FedCloud aims to address these issues by providing more agile, personalised, and secure e-learning experiences. This study introduces E-FedCloud, an AI-assisted adaptive e-learning system that automates personalised recommendations and tracking, thereby enhancing student performance. It employs federated learning-based authentication to ensure secure and private access for both course instructors and students. Intelligent Software Agents (ISAs) evaluate weekly student engagement using the Shannon Entropy method, classifying students into either engaged or not-engaged clusters. E-FedCloud utilises weekly engagement status, demographic information, and an innovative DRL-based early warning system, specifically ID2QN, to predict the performance of not-engaged students. Based on these predictions, the system categorises students into three groups: risk of dropping out, risk of scoring lower in the final exam, and risk of failing the end exam. It employs a multi-disciplinary ontology graph and an attention-based capsule network for automated, personalised recommendations. The system also integrates performance tracking to enhance student engagement. Data is securely stored on a blockchain using the LWEA encryption method.

The weight coefficients of the diaphragm spring depend on experiences in the traditional optimization. However, this method not only cannot guarantee the optimal solution but it is also not universal. Therefore, a new optimization target function is proposed. The new function takes the minimum of average compress force changing of the spring and the minimum force of the separation as total objectives. Based on the optimization function, the result of the clutch diaphragm spring in a car is analyzed by the non-dominated sorting genetic algorithm (NSGA-II) and the solution set of Pareto is obtained. The results show that the pressing force of the diaphragm spring is improved by 4.09%by the new algorithmand the steering separation force is improved by 6.55%, which has better stability and steering portability. The problem of the weight coefficient in the traditional empirical design is solved. The pressing force of the optimized diaphragm spring varied slightly during the abrasion range of the friction film, and the manipulation became remarkably light.

The Double U-pipe ground heat exchanger, recognized for its straightforward process, cost-effectiveness, high heat exchange efficiency, and low thermal resistance, stands as the predominant ground heat exchanger type in today's shallow geothermal energy development and utilization. Recent years have seen significant research into the heat transfer influencing factors and heat exchange performance of Double U-pipe ground heat ex-changers via experimental testing methods. Yet, studies integrating numerical simulation with in-situ testing have been less frequent. Drawing on the cylindrical heat source model theory and the outcomes of regional in-situ thermal response tests, this paper develops a Double U-pipe ground heat transfer model by establishing physical, mathematical, and heat transfer geometric models. It assesses the impact of varying inlet temperatures, flow rates, and initial ground temperatures on heat exchange efficiency under heating conditions. The results validate the precision of the double U-pipe ground heat exchanger model based on in-situ testing. They show that enhancing the temperature differential between the inlet and initial temperatures, elevating the initial ground temperature, and moderately increasing the flow rate can boost the system's heat exchange efficiency.

Currently, urban renewal activities in China are booming. And promoting the renovation of public buildings is the key due to its large scale, high cost and significant impact to the nature and social environment. To reduce the ambiguity and uncertainty in evaluating the potential for renewal of existing public buildings, a renewal potential evaluation model combining game theory combination weighting method and cloud model theory is proposed. The paper constructs a comprehensive evaluation index system based on relevant standards and literature. Game theory is used to optimize the weights obtained by AHP and entropy weight methods to obtain a combined weight. MATLAB programming is used to calculate the comprehensive cloud parameters of the evaluation index for the potential renewal of existing public buildings and therefore generate cloud Graphs. Through case study in Nanjing of China, it has been demonstrated that the combination empowerment cloud model can objectively reflect the relationship between the fuzziness and randomness of evaluation indicators for public building renewal potential. The expression of cloud Graphs can intuitively reflect the magnitude of renewal and renovation potential and the degree of uncertainty in evaluation results. The research result provides useful references for the sustainable utilization of building resources in the era of building.

Surveys on the optimum seismic design of structures reveal that many investigations focus on how to minimize its initial cost while satisfying the performance constraints. Although reducing the initial cost while complying with the requirements of earthquake design codes of practice will significantly guarantee the life safety of occupants against earthquakes, it may still cause considerable economic losses to residents and fatalities. Accordingly, calculating the possible earthquake damages caused during the structure's lifetime may become essential from the optimal Life Cycle Cost (LCC) design point of view. LCC analysis is used to evaluate economic feasibility including construction, operation, occupancy, maintenance and end-of-life costs. For optimization, the population-based, meta-heuristic algorithm based on the Ideal Gas Molecular Movement (IGMM), has established its capability in solving highly nonlinear mono and multi-objective engineering problems. Therefore, this paper investigates the LCC -based mono and multi-objective optimum design of a 3-D four-story concrete building structure combined with the Endurance Time (ET) competence. The results show that, apart from substantially reducing the total number of analyses required, the proposed technique significantly affected dipping minor injury cost, rental, and income costs by 22%, 16%, and 16%, respectively. In total, a 10% reduction in all structural life-cycle costs was achieved, which could well be considered significant.

Crash prediction of the sharp horizontal curve segment (SHCS) of a freeway is an important tool in analyzing safety of SHCSs and in building a crash prediction model (CPM). The design and crash report data of 88 SHCSs from different institutions were surveyed and three negative binomial (NB) regression models and three generalized negative binomial (GNB) regression models were built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The study demonstrates the effective use of the GNB model in analyzing the interactive influence of explanatory variables and in predicting freeway basic segments. Traffic volume, highway horizontal radius, and curve length have been formulated as explanatory variables. Subsequently, we performed statistical analysis to determine the model parameters and conducted sensitivity analysis. Among the six models, the result of model 6, which considered interactive influence, is much better than those of the other models by fitting rules. We also compared the actual results from crashes of 88 SHCSs with those predicted by models 1, 3, and 6. Results demonstrate that model 6 is much more reasonable than models 1 and 3.

The transferability of structure-property relationships for laser-pretreated metal adhesive joints to laser-pretreated metal – carbon fiber reinforced plastic (CFRP) bonds is investigated. Single-lap shear tests were performed on hybrid AW 6082-T6 – CFRP specimens pretreated with the same pulsed laser surface parameter sets on the metal surface as previously tested AW 6082-T6 – E320 metal adhesive joints. The fracture surfaces were characterized to determine the type of failure and elucidate differences and commonalities in the link between surface structures and single-lap shear strengths. Digital image analyses of the hybrid specimens fractured surfaces were used to quantify remaining CFRP fragments on the metallic joint side. The results indicate that high surface enlargements and the presence of undercut structures leads to single-lap shear strengths exceeding 40 MPa and 35 MPa for unaged and aged hybrid specimens respectively. While for the metal-polymer joints the trend from high strength to weakly bonded specimens was largely continuous with the degree of surface structuring, hybrid metal – CFRP joints exhibit a drastic drop in joint performance after aging if the laser-generated surface structures are less pronounced with low surface enlargements and crater depths. Surface features and hydrothermal aging determine whether the specimens fail cohesively or adhesively.

Since its introduction, back in the late 1970s, the non-affine or slip parameter, ξ, has been routinely employed by numerous constitutive models as a constant parameter. However, the evidence seems to imply that it should be a function of polymer deformation. In the present work, we phenomenologically modify a constitutive model for the rheology of unentangled polymer melts [P. S. Stephanou et al. J. Rheol. 53, 309 (2009)] to account for a non-constant slip parameter. The revised model predictions are compared against newly accumulated rheological data for a C48 polyethylene melt obtained via direct non-equilibrium molecular dynamics simulations in shear. We find that the conformation tensor data are very well predicted; however, the predictions of the material functions are noted to deviate from the NEMD data, especially at large shear rates.

We report the results of the characterization of local Monte Carlo (MC) dynamics of an equilibrium bond fluctuation model polymer matrix (BFM), in time interval typical for MC simulations of non-linear optical phenomena in host-guest systems. The study contributes to the physical picture of the dynamical aspects of quasi-binary mosaic states characterized previously in the static regime. The polymer dynamics was studied at three temperatures (below, above and close to the glass transition), using time-dependent generalization of the static parameters which characterize local free volume and local mobility of the matrix. Those parameters play the central role in the kinetic MC model of host-guest systems. The analysis was done in terms of the probability distributions of instantaneous and time-averaged local parameters. The main result is the characterization of time scales characteristic of various local structural processes. Slowing down effects close to the glass transition are clearly marked. The approach yields an elegant geometric criterion for the glass transition temperature. A simplified quantitative physical picture of the dynamics of guest molecules dispersed in BFM matrix at low temperatures offers a starting point for stochastic modeling of host-guest systems.

Bamboo biomass is a potential source for the production of monomeric sugars containing high cellulose content with low amount of lignin. However, for efficient hydrolysis, the biomass treatment by effective pretreatment technique is required to minimize lignin content and other barrier components. During present study, the bamboo biomass was treated with different physical, chemical, biological and combined treatments to reduce the lignin content. Among all the pretreatments, the maximum lignin removal (14.5%) was obtained with the combined chemical and biological treatment under 2% NaOH+1% H2O2 +WDP2 fungal culture (5 plugs) conditions. In addition, lignolytic fungus and NaOH pretreatment was mainly effective in removing lignin, whereas the H2O2 pretreatment efficiently minimize cellulose crystallinity. To analyze structural changes of raw and treated biomass, we used scanning electron microscopy and fourier transform infrared spectroscopy. The structural analysis indicated that all treatments causes disruption in the biomass structure and loses the compactness of the biomass which facilitates the biomass conversion during hydrolysis process. The findings of the present study indicate effective pretreatment methods in breaching the recalcitrancy of the potential lignocellulosic biomass for maximum hydrolysis.

This communication reports an improvement of the quality of the electrical data obtained from the application of electrical resistivity tomography method on archaeological studies. The electrical contact between ground and electrode enhances significantly by using carbomer-based gel during the electrical resistivity tomography measurements. Not only does the gel promote the conservation of the building surface under investigation, but it also virtually eliminates the necessity of conventional spike electrodes, which in many archaeological studies are inadequate or not permitted. Results evidenced an enhancement in the quality of the electrical data obtained in the order of thousands of units compared with those without using the carbomer-based gel. The potential and capabilities of this affordable gel make it appropriate to be applied to other geoelectrical studies beyond archaeological investigations. Moreover, it might solve corrosion issues on conventional spike electrodes, and electrical multicore cables usually provoked for added saltwater attempting to improve the electrical contact.

Extensive experimental and theoretical research over the past several decades has culminated in the understanding of the mechanisms behind nanoparticle-mediated enhancements on the mechanical properties of hydrogels. This information is not only crucial to realizing applications that directly benefit from developing hydrogels with high mechanical strength, but also to guide the development of strategies to further enhance hydrogel properties by combining different approaches. In our study, we investigated the effect of combining two approaches – addition of nanoparticles and crosslinking two different polymers (to create double-network hydrogels) – on the mechanical properties of hydrogels. Our studies revealed that these approaches may be combined to synthesize hydrogel composites with enhanced properties; however, both polymers in the double-network hydrogel must strongly interact with the nanoparticles to fully benefit from the addition of nanoparticles. Moreover, the concentration of hydrogel monomers used for the preparation of the double-network hydrogels had a significant effect on the extent of nanoparticle-mediated enhancements; double-network hydrogel nanocomposites prepared using lower monomer concentrations showed higher enhancements in elastic moduli compared to those prepared using high monomer concentrations. Collectively, these results demonstrate that the hypotheses previously developed to understand the role of nanoparticles on the mechanical properties of hydrogel nanocomposites may be extended to double-network hydrogel systems and guide the development of next generation hydrogels with extraordinary mechanical properties through a combination of orthogonal approaches.

Random copolymers made of both (PIM-polyimide) and (6FDA-durene-PI) were prepared for the first time by a facile one-step polycondensation reaction. By combining the highly porous and contorted structure of PIM (polymers with intrinsic microporosity) and high thermomechanical properties of PI (polyimide), the membranes obtained from these random copolymers [(PIM-PI)x-(6FDA-durene-PI)y] showed high CO₂ permeability (> 1047 Barrer) with moderate CO₂/N₂ (> 16.5) and CO₂/CH₄ (> 18) selectivity, together with excellent thermal and mechanical properties. The membranes prepared from three different compositions of two comonomers (1:4, 1:6 and 1:10 of x:y), all showed similar morphological and physical properties, and gas separation performance, indicating ease of synthesis and practicability for large-scale production. The gas separation performance of these membranes at various pressure ranges (100–1500 torr) was also investigated.

A multiscale modelling approach was developed in order to estimate the effect of defects on the strength of unidirectional carbon fiber composites. The work encompasses a micromechanics approach, where the known reinforcement and matrix properties are experimentally verified and a 3D finite element model is meshed directly from micrographs. Boundary conditions for loading the micromechanical model are derived from macroscale finite element simulations of the component in question. Using a microscale model based on the actual microstructure, material parameters and load case allows realistic estimation of the effect of a defect. The modelling approach was tested with a unidirectional carbon fiber composite beam, from which the micromechanical model was created and experimentally validated. The effect of porosity was simulated using a resin-rich area in the microstructure and the results were compared to experimental work on samples containing pores.

Optimum selectivity of enhanced oil recovery techniques would play a substantial role in the economic prosperity of petroleum industries which might be virtually eliminated unnecessary expenditures. In this paper, the simultaneous utilization of foaming agent, surfactant polymer (SP), and supercritical carbon dioxide were taken into the investigation under the miscible condition to evaluate the efficiency of each scenario on the cumulative recovery factor, water cut and pressure drop. According to the results of this experimental evaluation, SP-foam flooding had witnessed the highest blockage which is caused to have the maximum recovery factor due to the mobilization of more oil volume in the low permeable pores and cracks. Furthermore, the utilization of surfactant with supercritical carbon dioxide had experienced the least recovery factor regarding the insufficient foam generation which is led to less mobilization of oil phase in the pore throats.

In this study, the values of the interfacial energies of seven different polymer-water systems obtained by Sessile Drop Accelerometry (SDACC) are compared with the values obtained by the Young’s-equation-based Owens-Wendt method. The SDACC laboratory instrument –a combination of a drop shape analyzer with high-speed camera and a microgravity tower- and the evaluation algorithms, are designed to measure the interfacial energies as a function of the geometrical changes of a sessile droplet shape due to the effect of “switching off” gravity during the experiment. The method bases on Thermodynamics of Interfaces and differs from the conventional aproach of the two hundred-years-old Young’s equation in that it assumes a thermodynamic equilibrium between interfaces, rather than a balance of forces on a point of the solid-liquid-gas contour line. A comparison of the mathematical model that supports the SDACC method with the widely accepted Young`s equation is discussed in detail in this study.

According to current forecasts, global heating is likely to exceed 2,8°C by the end of the century. This makes substantial adaptation measures necessary to secure a broad basis for livelihoods provision and the conservation of biodiversity. While the implementation of top-down and technocratic adaptation efforts is the majority, related adaptation shortcomings of socio-economic and ecological nature are becoming more and more apparent. Community-based adaptation (CBA) with its participatory, inclusive and needs-based bottom-up approach offers a promising and powerful alternative. This article uses a semi-systematic literature review approach to screen the current literature and identify core issues of CBA. Linking communality, locality, multidimensionality, power imbalances, transformative potential, localisation, the triad of adaptation metrics and adaptation with nature to corresponding potential actions for practical implementations provides a more holistic conceptualisation and broadens the horizons for further learnings, research and improved application.

Protected and conserved areas are a key area-based strategy to address the biodiversity and climate change crises. Fundamental to understand their performance over time are indicators. The Digital Observatory for Protected Areas (DOPA) was born in 2013 as a set of open access web services and applications to be used to assess, monitor, and report on protected and conserved areas. For over a decade it has delivered over 50 indicators to support policy processes, national and regional governments, and practitioners. DOPA has also developed a versatile and efficient back-end approach that is widely applicable in other area-based conservation contexts. Here, we describe the methods and workflows behind DOPA´s back end and provide examples of policy relevant questions it can answer. We discuss key advantages and limitations of this systematic and replicable approach and explore the use of this back-end architecture to inform progress in area-based conservation targets for the following decades. This approach, embedded in multiple services provided by the Knowledge Centre for Biodiversity of the European Commission (KCBD), can also support the implementation and monitoring of area-based targets of the Kunming Montreal Global Biodiversity Framework at international, regional, and national levels.

Background: Study to assess glucose levels of people with type 1 diabetes (T1D) overnight based on insulin type and timing. Methods: Real-world, retrospective study in T1D using multiple daily insulin injections. Contin-uous glucose monitoring and insulin injections data were collected for ten hours after dinner us-ing the Insulclock® connected cap. Meal events were identified using ROC detection methodology. The timing of rapid insulin, second injections, and the type of insulin analogs used were evaluat-ed. Results: Nocturnal profiles (n=775, 49 subjects) were analyzed. Higher glucose AUC over 180mg/dL was observed in delayed injections (number; %; mg/dL x h): -45-15min (n=136; 17.5%, 175.9 ±271.0); -15-0min (n= 231; 29.8%, 164.0 ±237.1); 0+45min (n= 408; 52.6%, 203.6 ±260.9), (p 0.049). The use of ultrarapid (FiAsp®) (URI) vs rapid insulin analogs (RI) was associated with less hypoglycemia events (7.1 vs 13.6%; p 0.005) and TBR70 (1.7 +6.9 vs 4.6 +13.9%; p 0.003). Us-ers of glargine U300 vs degludec had higher TIR (70.7 vs 58.5 %) (Adjusted R-squared: 0.22, p < 0.001). The use of a correction injection (n= 144, 18.6%) was associated with higher hypoglycemia events (18.1 vs 9.5%; p 0.003), TBR70 (5.5 +14.2 vs 3.0 +11.1%; p 0.003), glucose AUC over 180 mg/dL (226.1 +257.8 vs 178.0 +255.3 mg/dL x h; p 0.001), and lower TIR (56.0 +27.4 vs 62.7 +29.6 mg/dL x h; p 0.004). Conclusions: Dinner rapid insulin timing, insulin types and correction injections affect nocturnal glucose profile in T1D.

Cerebral palsy (CP) presents challenges in movement and posture due to central nervous system damage, necessitating lifelong management. The COVID-19 pandemic has limited access to traditional treatments, increasing demand for home-based therapies and digital resources. This study analyzed the qualitative and quantitative aspects of YouTube videos focusing on CP therapy for children. In total, 95 videos were evaluated for content quality, therapeutic program efficacy, and popularity. Most videos were uploaded by health professionals. Neuromotor therapy types varied, with Bobath therapy being prominent. The quality assessments revealed moderate to high reliability in video content; nonetheless, shortcomings in addressing uncertainties were observed. Therapeutic programs often lack crucial details such as intensity and outcome assessment methods. No significant differences were found between professional and non-professional uploads. Classifiable videos based on exercise type, in contrast to the types of neuromotor therapy, exhibited better therapeutic quality than unclassified ones. Notably, video popularity did not correlate with quality. This study underscores the need for improved educational content on YouTube, particularly in providing comprehensive therapeutic information for CP management. Further refinement of evaluation tools is essential for assessing the rationale behind neuromotor therapeutic modalities for children with CP.

Fluorophores with a tetraphenylethylene (TPE) core are attracting increasing interest because of their aggregation-induced emission (AIE) behaviour, which makes them particularly suitable when dispersed in thin-layer films. We propose the synthesis and use of a novel TPE fluorophore (hereafter called TPE-BPAN) decorated with two dimethylamino push groups and a 4-biphenylacetonitrile pull moiety. In tetrahydrofuran solutions, TPE-BPAN showed a broad absorption spectrum, and an intense emission is observed when a non-solvent as water is added in amounts of 70% and above. We selected and synthetized five different polymer matrices for TPE-BPAN with decreasing polarity: a) poly(methylmetacrylate) homopolymer (PMMA); b), c), and d) three copolymers of methyl methacrylate and cyclohexyl methacrylate at different compositions (P(MMA-co-CHMA) 75:25, 50:50, 25:75 mol%); e) poly(cyclohexyl methacrylate) homopolymer (PCHMA). The presence of a less polar comonomer as cyclohexyl methacrylate appeared to enhance the emission behaviour of TPE-BPAN, which displayed the highest quantum yield (QY) in P(MMA-co-CHMA) 75:25 in all the range of concentration studied from 0.4 wt.% to 2.0 wt.%. Further reduction in polarity lowered QY to the values of PMMA films; also, lower adhesion to the glass and a marked fragility of the films were observed. Referring to the P(MMA-co-CHMA) 75:25 films, QY values decreased from over 40% at 0.4 wt.% to about 30% at 2.0 wt.%, which is still helpful for energy harvesting applications such as luminescent solar concentrators (LSC). LSC performances were not significantly affected by the matrix's lower polarity and resulted in around one-third of the state-of-the-art due to the lower QY of TPE-BPAN. The theoretical investigation on density functional theory (DFT) clarified the origin of the observed AIE and the role played by the environment in modulating the photophysical behaviour.

Most of the pore-scale imaging and simulations of non-Newtonian fluid are based on the simplifying geometry of network modeling and overlook the fluid rheology and heat transfer. In the present paper, we developed a non-isothermal and non-Newtonian numerical model of the flow properties at pore-scale by direct simulation of the 3D micro-CT images using a Finite Volume Method (FVM). The numerical model is based on the resolution of the momentum and energy conservation equations. Owing to an adaptive meshing technique and appropriate boundary conditions, rock permeability and mobility are accurately computed. A temperature and concentration-dependent power-law viscosity model in line with the experimental measurement of the fluid rheology is adopted. The model is first applied at isothermal condition to 2 benchmark samples, namely Fontainebleau sandstone and Grosmont carbonate, and is found to be in good agreement with the Lattice Boltzmann method (LBM). Finally, at non-isothermal conditions, an effective mobility is introduced that enables to perform a numerical sensitivity study to fluid rheology, heat transfer, and operating conditions. While the mobility seems to evolve linearly with polymer concentration, the effect of the temperature seems negligible by comparison. However, a sharp contrast is found between carbonate and sandstone under the effect of a constant temperature gradient. Besides concerning the flow index and consistency factor, a good master curve is derived when normalizing the mobility for both the carbonate and the sandstone.

Abstract Background: Hypochlorous acid (HA) is a potent disinfectant with broad-spectrum antimicrobial activity against bacteria, fungi, and viruses. Aim: This study aimed to investigate the factors that influence the stability of hypochlorous acid (HOCl) and their impact on its disinfectant properties Methods: This study explored the stability of hypochlorous acid, emphasizing factors that affect its disinfectant efficiency, such as pH level, temperature, and the presence of organic materials. Findings: Our investigation revealed that HOCl is the most stable and effective disinfectant under weakly acidic conditions, where the undissociated form of hypochlorous acid is predominant. Although it is stable under various conditions, its efficacy is compromised by the presence of heavy metals, organic matter, and UV radiation. Conclusions: This comprehensive analysis concludes that, while hypochlorous acid is a highly effective disinfectant, understanding and maintaining the optimal conditions for its stability is crucial for maximizing its disinfection potential. Implications: The findings can be used to formulate new guidelines and regulations to guide the proper formulation, storage, and use of stable HOCL as disinfectants.

It is currently believed that the cause of superior mesenteric artery syndrome (SMAS) is compression of the duodenum in the angle between the aorta and superior mesenteric artery (SMA). It is recognized that a decrease in aortomesenteric angle (AMA) <25° and intervascular distance < 8 mm, caused by fat loss, is characteristic of SMAS. Based on these statements, surgeons operate on patients with symptoms of dyspepsia only based on a reduction of AMA. This study is devoted to the analysis of the literature, including four own studies on this issue. Results: Measurement of the length of the constriction in the third part of the duodenum on radiograms from available sources showed that its true length ranged from 2.5 to 4.2 (3.30±0.15) cm and began a few centimeters cranial to the AMA. Therefore, it could not have been caused by compression in the AMA. In terms of length (3.20±0.15 cm) and location, this constriction corresponded to Ochsner’s sphincter, which normally short-term contracts to prevent the penetration of an acid bolus into the jejunum. Conscientious studies have shown that AMA is proportional to BMI, i.e., a decrease in AMA is observed in all thin people. An analysis of 211 cases of SMAS made it possible to differentiate two types of diseases. In 101 patients, the disease occurred acutely 1–53 (8.2 ± 1.9) days after stressful situations, accompanied by a catabolic reaction and hypersecretion of hydrochloric acid. In 110 patients, SMAS developed 3-72 (17.2±3.2) months after the diagnosis of acid-dependent diseases. Conclusion: The analysis of the literature led to the conclusion that hypersecretion of hydrochloric acid causes damage to the upper level of the digestive system, including duodenal dyskinesia. One of the manifestations of duodenal dyskinesia is an increase in tone and hypertrophy of the Ochsner’s sphincter. The clinic of the disease depends on the varying degree of Ochsner’s sphincter dyskinesia. In severe cases, partial or complete intestinal obstruction. New ideas about the etiology and pathogenesis of the so-called SMAS have made it possible to propose a tactic for the diagnosis and treatment of Ochsner’s sphincter dyskinesia, where there is no place for surgical treatment.

This study investigated the potential of electrospun collagen/Hyaluronic Acid nanofibers in biomedicine and skincare. Needleless electrospinning technology employed in the production process resulted in nanofibers with consistent fiber diameters and improved mechanical properties. The composite nanofibers demonstrated impressive tensile strength and elongation capabilities, indicating a favorable interaction between collagen and HA. Cellular assays revealed that the collagen/HA scaffolds facilitated superior cell adhesion and proliferation compared to the control scaffolds, indicating their biocompatibility and potential for tissue engineering. This biomaterial offers an environment-friendly alternative to conventional skincare products by eliminating the need for preservatives and reducing waste. Although the initial costs are high, the long-term benefits of material durability and active ingredient efficacy provide a compelling case for industrial adoption. Our findings suggest that collagen/HA nanofibers have the potential to be next-generation materials for regenerative medicine and skincare, and further research is needed to optimize their production and assess the economic feasibility of skincare and tissue engineering applications.

A key response to glucose stress is an increased production of unsaturated fatty acids to balance the increase of saturated fatty acids in the membrane. The C. elegans homolog of stearoyl-CoA desaturase, FAT-7, introduces the first double bond into saturated C18 fatty acids yielding oleic acid and is a critical regulatory point for surviving cold and glucose stress. Here, we incorporated 13C stable isotopes into the diet of nematodes and quantified the 13C-labelled fatty acid by GC-MS and HPLC/MS-MS to track the metabolic response to various concentrations of glucose. Previous work has analyzed membrane composition of C. elegans when responding to mild glucose stress and showed few alterations in overall fatty acid composition in the membrane. Here, in nematodes exposed to higher concentrations of glucose, a specific reduction of oleic acid and linoleic acid was observed. Using time courses and stable isotope tracing, the response of fatty acid me-tabolism to increasing levels of glucose stress has been characterized, revealing a funneling of monounsaturated fatty acids to preserve polyunsaturated fatty acid abundance. Taken together, higher levels of glucose unveil a specific reduction of oleic and linolenic acid in the metabolic re-wiring required to survive glucose stress.

Nuclear receptors (NRs) constitute a superfamily of ligand-activated transcription factors with a paramount role in ubiquitous physiological functions such as metabolism, growth, and reproduction. Owing to their physiological role and druggability, NRs are deemed attractive and valid targets for medicinal chemists. Pentacyclic triterpenes (PTs) represent one of the most important phytochemical classes present in higher plants, where oleanolic acid (OA) is the most studied PTs representative owing to its multitude of biological activities against cancer, inflammation, diabetes, and liver injury. PTs possess a lipophilic skeleton that imitates the NRs endogenous ligands. Herein, we report a literature overview on the modulation of metabolic NRs by OA and its semi-synthetic derivatives, highlighting their health benefits and potential therapeutic applications. Indeed, OA exhibited varying pharmacological effects on FXR, PPAR, LXR, RXR, PXR, and ROR in a tissue-specific manner. Owing to those NRs modulation, OA exhibited prominent hepatoprotective properties comparable to ursodeoxycholic acid (UDCA) in a bile duct ligation mice model and antiatherosclerosis effect as simvastatin in a model of New Zealand white (NZW) rabbits. It also demonstrated a great promise in alleviating non-alcoholic steatohepatitis (NASH) and liver fibrosis, attenuated alpha-naphthol isothiocyanate (ANIT)-induced cholestatic liver injury, and controlled blood glucose levels, making it a key player in the therapy of metabolic diseases. We also compiled OA semi-synthetic derivatives and explored their synthetic pathways and pharmacological effects on NRs, showcasing their structure-activity relationship (SAR). To the best of our knowledge, this is the first review article to highlight OA activity in terms of NRs modulation.