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Amorphous solid dispersion (ASD) in a polymer matrix is a powerful method for enhancing the solubility and bioavailability of otherwise crystalline, poorly water-soluble drugs. 6-Carboxycellulose acetate butyrate (CCAB) is a relatively new commercial cellulose derivative that was introduced for use in waterborne coating applications. As CCAB is an amphiphilic, carboxyl-containing, high glass transition temperature (Tg) polymer, characteristics essential to excellent ASD polymer performance, we chose to explore its ASD potential. Structurally diverse drugs quercetin, ibuprofen, ritonavir, loratadine, and clarithromycin were dispersed in CCAB matrices. We evaluated the ability of CCAB to create ASDs with these drugs and its ability to provide solubility enhancement and effective drug release. CCAB/drug dispersions prepared by spray drying were amorphous up to 25 wt % drug, with loratadine remaining amorphous up to 50% drug. CCAB formulations with 10% drug proved effective at providing in vitro solubility enhancement for the crystalline flavonoid drug quercetin as well as ritonavir, but not for the more soluble APIs ibuprofen and clarithromycin and the more hydrophobic loratadine. CCAB did provide slow and controlled release of ibuprofen, offering a simple and promising Long-duration ibuprofen formulation. Formulation with clarithromycin showed the ability of the polymer to protect against degradation of the drug at stomach pH. Furthermore, CCAB ASDs with both loratadine and ibuprofen could be improved by the addition of the water-soluble polymer poly(vinylpyrrolidone) (PVP), with which CCAB shows good miscibility. CCAB provided solubility enhancement in some cases, and the slower drug release exhibited by CCAB, especially in the stomach, could be especially beneficial, for example, in formulations containing known stomach irritants like ibuprofen.
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Migration of microplastics (MPs) in soil-groundwater systems plays a pivotal role in determining its concentration in aquifers and future threats to the terrestrial environment, including human health. However, existing models employing an advection-dispersion equation are insufficient to incorporate the holistic mechanism of MP migration. Therefore, to bridge the gap associated with MP migration in soil-groundwater systems, a dispersion-drag force coupled model incorporating a drag force on MPs along with dispersion is developed and validated through existing laboratory and field-scale experiments. The inclusion of the MP dispersion notably increased the global maximum particle velocity (vmaxp) of MPs, resulting in a higher concentration of MPs in the aquifer, which is also established by sensitivity analysis of MP dispersion. Additionally, increasing irrigation flux and irrigation areas significantly accelerates MP migration downward from soil to deep saturated aquifers. Intriguingly, vmaxp of MPs exhibited a nonlinear relationship with MPs' sizes smaller than 20 µm reaching the highest value (=1.64 × 10-5 m/s) at a particle size of 8 µm, while a decreasing trend was identified for particle sizes ranging from 20 to 100 µm because of the hindered effect by porous media and the weaker effect of the drag force. Moreover, distinct behaviors were observed among different plastic types, with poly(vinyl chloride), characterized by the highest density, displaying the lowest vmaxp and minimal flux entering groundwater. Furthermore, the presence of a heterogeneous structure with lower hydraulic conductivity facilitated MP dispersion and promoted their migration in saturated aquifers. The findings shed light on effective strategies to mitigate the impact of MPs in aquifers, contributing valuable insights to the broader scientific fraternity.
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In this study, we propose a novel strategy utilizing deep eutectic solvents (DESs) as both the extraction solvent and dispersing liquid, with nanometer zinc oxide (ZnO) serving as the adsorbent. This method incorporates ultrasound-assisted matrix solid phase dispersion (UA-MSPD) for the extraction of six active components (salidroside, echinacoside, acteoside, specnuezhenide, nuezhenoside G13, and oleanolic acid) from Ligustri Lucidi Fructus samples. The extracts were then analyzed using high-performance liquid chromatography equipped with a diode array detector. The effects of various parameters such as dispersant dosage, DESs volume, grinding time, ultrasonication duration, and eluent volume on extraction recovery were investigated and optimized using a central composite design under response surface methodology. The optimized conditions yielded detection limits ranging from 0.003 to 0.01 mg/g and relative standard deviations of 8.7% or lower. Extraction recoveries varied between 93% and 98%. The method demonstrated excellent linearity for the analytes (R2 ≥ 0.9997). The simple, green, and efficient DESs/ZnO-UA-MSPD technique proved to be rapid, accurate, and reliable for extracting and analyzing the six active ingredients in Ligustri Lucidi Fructus samples.
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Ligustrum , Extracción en Fase Sólida , Ondas Ultrasónicas , Óxido de Zinc , Extracción en Fase Sólida/métodos , Óxido de Zinc/química , Ligustrum/química , Disolventes Eutécticos Profundos/química , Cromatografía Líquida de Alta Presión , Frutas/química , Extractos Vegetales/química , Extractos Vegetales/análisis , Tamaño de la Partícula , Solventes/químicaRESUMEN
OBJECTIVE: Recurrent pregnancy loss (RPL) has a multifactorial etiology, with a majority of cases remaining unexplained. To account for these unexplained cases, possible male factors are being explored. Conventional semen analysis lacks a qualitative assessment of sperms and information regarding sperm DNA integrity. Sperm DNA fragmentation (SDF) has diagnostic value in unexplained RPL, and it may account for a number of unexplained cases. Hence, we planned a study to explore and evaluate the impact of sperm DNA fragmentation in couples with unexplained recurrent pregnancy losses. STUDY DESIGN: Analytical cross-sectional study was conducted at a tertiary-level referral facility in India between August 2021 and July 2023. Participants (n = 70) were divided into two groups-male partners of couples with unexplained RPL (following spontaneous conceptions) (n = 35) and men with at least one previous live birth (spontaneous or following fertility treatments for female factor infertility such as ovulation induction or intrauterine insemination) as controls (n = 35). Neither of the two groups of couples recruited for this study had undergone ART as fertility treatment. Primary outcome assessed was mean DNA fragmentation index (DFI). Secondary outcomes included differences in semen parameters such as sperm concentration, progressive sperm motility and morphology, proportion of men with high (≥30%) and low DFI in the two groups, and the association between various semen parameters and DFI. RESULTS: Univariate logistic regression revealed that sperm DNA fragmentation was higher in men with unexplained RPL (30.0; IQR (interquartile range) 19.0, 46.0) as compared to controls (22.0; IQR 14.0, 30.0) although it was not statistically significant (OR, odds ratio, 1.02; 95% CI 1.0-1.1, p = 0.08). A higher proportion of men with unexplained RPL had DFI ≥30% compared to controls (54.2% vs. 25.7%; OR 3.43 (95% CI 1.2-9.4); p = 0.02). No statistically significant differences were observed in semen volume, sperm concentration, progressive motility, and morphology between the two groups. Sperm DNA fragmentation index also showed a weak but significant inverse relationship with sperm morphology (r = -0.336, p = 0.004). CONCLUSION: The current study did not show any significant difference in the mean sperm DNA fragmentation levels in male partners of couples with unexplained RPL compared to controls. However, a higher proportion of men with DFI ≥30% were observed in unexplained RPL population when compared to controls.
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Odor pollution is the biggest source of complaints from citizens concerning environmental issues after noise. Often, the need for corrective actions is evaluated through simulations performed with atmospheric dispersion models. To save resources, air pollution control institutions perform a first-level odor impact assessment, for screening purposes. This is often based on Gaussian dispersion models (GDM), which does not need high computational power. However, their outputs tend to be conservative regarding the analyzed situation, rather than representative of the real in-site conditions. Hence, regulations and guidelines adopted at an institutional level for authorization/control purposes are based on Lagrangian particle dispersion models (LPDM). These models grant a more accurate simulation of the pollutants' dispersion even if they are more demanding regarding both technical skills and computing power. The present study aims to increase the accuracy of screening odor impact assessment by identifying the correlation function of the outputs derived from the two simulation models. The case study is placed in northern Italy, where a single-point source, with various stack heights, was considered. The case study is placed in northern Italy, where a single-point source, with various stack heights, was considered. The obtained correlation functions allow the practitioner to have a more accurate first-level odor impact assessment, to save time for training, and to reduce the site-specific meteorological data before proceeding with the simulation. The identified functions could allow institutions to estimate the results that would have been forecasted with the application of the more complex LPDM, applying, however, the much simpler GDM. This solution grants an accurate tool which can be used to address citizens' concerns while saving workforce and technical resources. Limitations are related to the specificity of the method regarding type sources, orography, and meteorological conditions. Comparison with other screening tools is also presented and discussed.
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With the vigorous development and huge demand for portable wearable devices, wearable electronics based on functional fibers continue to emerge in a wide range of energy storage, motion monitoring, disease prevention, electromagnetic interference (EMI) shielding, etc. MXene, as an emerging two-dimensional inorganic compound, has shown great potential in functional fiber manufacturing and has attracted much research attention due to its own good mechanical properties, high electrical conductivity, excellent electrochemical properties and favorable processability. Herein, this paper reviews recent advances of MXene-based fibers. Speaking to MXene dispersions, the properties of MXene dispersions including dispersion stability, rheological properties and liquid crystalline properties are highlighted. The preparation techniques used to produce MXene-based fibers and application progress regarding MXene-based fibers into supercapacitors, sensors, EMI shielding and Joule heaters are summarized. Challenges and prospects surrounding the development of MXene-based fibers are proposed in future. This review aims to provide processing guidelines for MXene-based fiber manufacturing, thereby achieving more possibilities of MXene-based fibers in advanced applications with a view to injecting more vitality into the field of smart wearables.
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OBJECTIVES: The aim of this study was to evaluate the diagnostic performance of shear wave elastography (SWE), shear wave dispersion (SWD), and attenuation imaging (ATI) in assessment of hepatic parenchyma in patients with liver tumors before resection. METHODS: Patients with liver tumors were prospectively enrolled in this study. All participants underwent SWE, SWD, and ATI examinations. Fibrosis stage, necroinflammatory activity and hepatic steatosis grade were determined histopathologically. We evaluated the stability of ATI, SWE and SWD examinations. Multivariable linear regression analyses were conducted to determine the determinant factors for SWE, SWD, attenuation coefficient (AC) values. A receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic performance of multiparametric US (ultrasond). RESULTS: A total of 280 participants were enrolled in this study. TG (triglyceride) and steatosis for AC value were significant determinant factors. PLT (platelet), PT (prothrombin time), GGT (glutamyl transpeptidase), and fibrosis stage for SWE value were significant determinant factors. PLT, fibrosis stage and inflammation activity for SWD value were significant determinant factors. AC value was correlated with hepatic steatosis. Both SWE and SWD values were correlated with fibrosis stage, inflammation activity, respectively. The area under the ROC (AUROC) curve of ATI for predicting hepatic steatosis grade were 0.910(≥ S1), 0.927(≥ S2), 0.962(= S3), respectively. The AUROC curve of SWE for predicting fibrosis stage were 0.923(≥ S1), 0.934(≥ S2), 0.930(≥ S3), 0.895(= S4), respectively. The AUROC curve of SWD for predicting fibrosis stage were 0.858(≥ S1), 0.886(≥ S2), 0.866(≥ S1) (≥ S3), 0.825(= S4). The AUROC curve of SWE for predicting inflammation activity were 0.846(≥ G1), 0.724(≥ G2), 0.787 (≥ G3), respectively. The AUROC curve of SWD for predicting inflammation activity were 0.777(≥ G1), 0.727(≥ G2), 0.803 (≥ G3), respectively. CONCLUSIONS: For patients with liver tumors, ATI technology showed excellent feasibility and diagnostic performance for detecting and grading hepatic steatosis, SWE was more accurate in detecting fibrosis stage than SWD, SWD was not superior to SWE in detecting inflammation activity.
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Modelling and prediction of air quality facilitates the drafting of efficient guidelines and, in turn, proper management of adversely affected areas. In order to depict the air pollutants in urban centres, this research analyses two modelling tools: AERMOD and CALINE4. Both technologies provide distinct capabilities in the modelling of air quality from vehicular and other emissions. CALINE4, a Gaussian dispersion model, specifies pollutant dispersion from mobile sources along roadways. It boasts a user-friendly interface and road-specific modelling capabilities, factoring in traffic speed and vehicle emissions. However, it simplifies intricate flow patterns and relies on primary meteorological data. On the other hand, AERMOD is a versatile model suitable for various emission sources, including both mobile and stationary sources. It excels at capturing diverse atmospheric processes but demands precise meteorological, terrain, and emission data. AERMOD is often preferred for regulatory compliance assessments, although it entails a steeper learning curve and higher computational requirements. The choice between CALINE4 and AERMOD hinges on study needs, data availability, and desired modelling precision. This review offers an overview to assist researchers in making informed model selections for assessing vehicle-related pollution, critical aspects of urban sustainability, and air quality management.
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The Mediterranean Sea is one of the most critically polluted areas due to its semi-enclosed structure and its highly anthropized shoreline. Rivers are significant vectors for pollutant transfers from the continental to the marine environment. In this context, a 3D Lagrangian simulation of the dispersion of riverine microplastics (MPs) was performed, which included the application of a recently developed model that reassessed the MP fluxes discharged by rivers. MP physical properties from river samples were further investigated to approximate vertical displacement in modeled ocean currents. The use of a high-resolution circulation model, integrating Stokes drift, turbulent diffusion, and MP sinking and rising velocities, enabled us to establish stock balances. Our simulation suggested that 65% of river inputs may be made of floating MPs drifting in the surface layer and 35% of dense MPs sinking to deeper layers. The Eastern Mediterranean tends to accumulate floating MPs, primarily originating from the Western Mediterranean Basin, where major river sources are concentrated. After 2 years of simulation, modeled stranding sequestered 90% of the MP inputs, indicating relatively short average residence times from a few days to months at most for particles at sea. Although spatial distribution patterns stabilized after this period and a steady state may have been approached, the surface concentrations we modeled generally remained below field observations. This suggested either an underestimation of sources (rivers and unaccounted sources), by a factor of 6 at most, or an overestimation of MP withdrawal through stranding, to be reduced from 90 to around 60% or less if unaccounted sinks were considered.
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The nanodrug delivery system-based nasal spray (NDDS-NS) can bypass the blood-brain barrier and deliver drugs directly to the brain, offering unparalleled advantages in the treatment of central nervous system (CNS) diseases. However, the current design of NNDS-NS is excessively focused on mucosal absorption while neglecting the impact of nasal deposition on nose-to-brain drug delivery, resulting in an unsatisfactory nose-to-brain delivery efficiency. In this study, the effect of the dispersion medium viscosity on nasal drug deposition and nose-to-brain delivery in NDDS-NS was elucidated. The optimized formulation F5 (39.36 mPa·s) demonstrated significantly higher olfactory deposition fraction (ODF) of 23.58%, and a strong correlation between ODF and intracerebral drug delivery (R2 = 0.7755) was observed. Building upon this understanding, a borneol-modified lipid nanoparticle nasal spray (BLNP-NS) that combined both nasal deposition and mucosal absorption was designed for efficient nose-to-brain delivery. BLNP-NS exhibited an accelerated onset of action and enhanced brain targeting efficiency, which could be attributed to borneol modification facilitating the opening of tight junction channels. Furthermore, BLNP-NS showed superiority in a chronic migraine rat model. It not only provided rapid relief of migraine symptoms but also reversed neuroinflammation-induced hyperalgesia. The results revealed that borneol modification could induce the polarization of microglia, regulate the neuroinflammatory microenvironment, and repair the neuronal damage caused by neuroinflammation. This study highlights the impact of dispersion medium viscosity on the nose-to-brain delivery process of NDDS-NS and serves as a bridge between the formulation development and clinical transformation of NDDS-NS for the treatment of CNS diseases.
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Based on a search of publications in the scientific literature as well as international reports available online, I draw up a list of 25 documents which include cross-references to the terms offshore wind farms (OFW), and non-indigenous species (NIS). This review shows that no relationship has yet been clearly established between the implementation of OFWs and the colonization of NIS on turbine foundations and scour protections. Evidence for such an effect needs to be documented and confirmed in the future.
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Especies Introducidas , Invertebrados , Viento , Animales , Conservación de los Recursos Naturales , BiodiversidadRESUMEN
Background: Dispersion presents both a challenge and a diagnostic opportunity in shear wave elastography (SWE). Shear Wave Rheometry (SWR) is an inversion technique for processing SWE data acquired using an acoustic radiation force impulse (ARFI) excitation. The main advantage of SWR is that it can characterize the shear properties of homogeneous soft media over a wide frequency range. SWR was used here to measure the shear properties of bovine liver tissue. Assumptions associated with SWR include tissue homogeneity, tissue isotropy, and axisymmetry of the ARFI excitation. Objective: Evaluate the validity of the SWR assumptions in ex vivo bovine liver. Approach: SWR was used to measure the shear properties of bovine liver tissue as a function of frequency, over a large frequency range. Assumptions associated with SWR (homogeneity, isotropy and axisymmetry) were evaluated through measurements performed at multiple locations and probe orientations. Main results: Measurements of shear properties were obtained over the 25-250 Hz range, and showed a 4-fold increase in shear storage modulus (from 1 to 4 kPa) and over a 10-fold increase in the loss modulus (from 0.2 to 3 kPa) over that decade-wide frequency range. Measurements under different conditions were highly repeatable, and model error was low in all cases. Significance and Conclusion: SWR depends on modeling the ARFI-induced shear wave as a full vector viscoelastic shear wave resulting from an axisymmetric source; it is agnostic to any specific rheological model. Despite this generality, the model makes three main simplifying assumptions. These results show that the modeling assumptions used in SWR are valid in bovine liver, over a wide frequency band.
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The concept of a 2D cylindrical High Pass Ladder (2D c-HPL) is used in the development of this ultra high radio frequency (UHRF) volumetric head coil for 7T tuned at the Larmor frequency of 298 MHz. The architecture of the 2D c-HPL helps to overcome the challenges associated with non-uniform magnetic field distribution. The prototype consists of an individual resonating array of inductance-capacitance (LC) elements and each component is tuned to the precise f o frequency. The tuning of the (i) inductance, (ii) capacitance, (iii) mesh size, and (iv) coupling coefficient play critical roles to attain the desired Larmor frequency. For this proof-of-concept, the prototype of a volumetric head coil consists of a cylindrical array size of 4 ×6, with individual LC components of inductance magnitude, 98 nH and four fixed value capacitors and one tunable capacitor that allowed to achieve the desired precession frequency, f r = 298 M H z . The model was tested for three different f o values of 269 MHz, 275 MHz and 286 MHz. The mutual coupling and the eigenfrequencies were compared through bench testing and dispersion equation. The experimental data were in good agreement (< 5%) with the theoretical eigenfrequencies from the dispersion relation. The theoretical eigenfrequencies and the experimental eigenfrequencies are in good agreement for eigenmodes (1,2), (1,3), (2,2), (2,3) and (4,3).
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PURPOSE: This work aims to unravel the intricacies of adiabatic rotating frame relaxometry in biological tissues. THEORY AND METHODS: The classical formalisms of dipolar relaxation R 1 ρ $$ {R}_{1\rho } $$ and R 2 ρ $$ {R}_{2\rho } $$ were systematically analyzed for water molecules reorienting on "fast" and "slow" timescales. These two timescales are, respectively, responsible for the absence and presence of R 1 ρ $$ {R}_{1\rho } $$ dispersion. A time-averaged R 1 ρ $$ {R}_{1\rho } $$ or R 2 ρ $$ {R}_{2\rho } $$ over an adiabatic pulse duration was recast into a sum of R 1 $$ {R}_1 $$ and R 2 $$ {R}_2 $$ , but with different weightings. These weightings depend on the specific modulations of adiabatic pulse waveforms. In this context, stretched hyperbolic secant ( HSn $$ HSn $$ ) pulses were characterized. Previously published H S 1 $$ HS1 $$ R 1 ρ $$ {R}_{1\rho } $$ , continuous-wave (CW) R 1 ρ $$ {R}_{1\rho } $$ , and R 1 $$ {R}_1 $$ measures from 12 agarose phantoms were used to validate the theoretical predictions. A similar validation was also performed on previously published HSn $$ HSn $$ R 1 ρ $$ {R}_{1\rho } $$ ( n $$ n $$ =1, 4, 8) and HS 1 $$ HS1 $$ R 2 ρ $$ {R}_{2\rho } $$ from bovine cartilage specimens. RESULTS: Longitudinal relaxation weighting decreases for HSn $$ HSn $$ pulses as n $$ n $$ increases. Predicted CW R 1 ρ cal $$ {R}_{1\rho}^{cal} $$ values from agarose phantoms align well with the measured CW R 1 ρ exp $$ {R}_{1\rho}^{exp} $$ values, as indicated by a linear regression function: R 1 ρ cal = 1.04 * R 1 ρ exp - 1.96 $$ {R}_{1\rho}^{cal}={1.04}^{\ast }{R}_{1\rho}^{exp}-1.96 $$ . The predicted adiabatic R 1 ρ $$ {R}_{1\rho } $$ and R 2 ρ $$ {R}_{2\rho } $$ from cartilage specimens are consistent with those previously measured, as quantified by: R 1 ρ , 2 ρ cal = 1.10 * R 1 ρ , 2 ρ exp - 0.41 $$ {R}_{1\rho, 2\rho}^{cal}={1.10}^{\ast }{R}_{1\rho, 2\rho}^{exp}-0.41 $$ . CONCLUSION: This work has theoretically and experimentally demonstrated that adiabatic R 1 ρ $$ {R}_{1\rho } $$ and R 2 ρ $$ {R}_{2\rho } $$ can be recast into a sum of R 1 $$ {R}_1 $$ and R 2 $$ {R}_2 $$ , with varying weightings. Therefore, any suggestions that adiabatic rotating frame relaxometry in biological tissues could provide more information than the standard R 1 $$ {R}_1 $$ and R 2 $$ {R}_2 $$ warrant closer scrutiny.
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Increasing attention is being afforded to understanding the bidirectional relationship that exists between oral drugs and the gut microbiota. Often overlooked, however, is the impact that pharmaceutical excipients exert on the gut microbiota. Subsequently, in this study, we contrasted the pharmacokinetic performance and gut microbiota interactions between two commonly employed formulations for poorly soluble compounds, namely 1) an amorphous solid dispersion (ASD) stabilised by poly(vinyl pyrrolidone) K-30, and 2) a lipid nanoemulsion (LNE) comprised of medium chain glycerides and lecithin. The poorly soluble antipsychotic, lurasidone, was formulated with ASD and LNE due to its rate-limiting dissolution, poor oral bioavailability, and significant food effect. Both the ASD and LNE were shown to facilitate lurasidone supersaturation within in vitro dissolution studies simulating the gastrointestinal environment. This translated into profound improvements in oral pharmacokinetics in rats, with the ASD and LNE exerting comparableâ¯â¼â¯2.5-fold improvements in lurasidone bioavailability, compared to the pure drug. The oral formulations imparted contrasting effects on the gut microbiota, with the LNE depleting the richness and abundance of the microbial ecosystem, as evidenced through reductions in alpha diversity (Chao1 index) and operational taxonomical units (OTUs). In contrast, the ASD exerted a 'gut neutral' effect, whereby a mild enrichment of alpha diversity and OTUs was observed. Importantly, this suggests that ASDs are effective solubility-enhancing formulations that can be used without comprising the integrity of the gut microbiota - an integral consideration in the treatment of mental health disorders, such as schizophrenia, due to the role of the gut microbiota in regulating mood and cognition.
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In the current environment whereby new sources of proteins are extracted from plant material, it is also important to study the potential use of the resulting side streams. Although a number of studies have been conducted on various polysaccharides extracted from plant raw material, a polysaccharide fraction extracted from lupin bean is yet to be explored, in spite of the emerging interest in this crop as a source of food ingredients. In this work lupin soluble polysaccharide (LuPS) was obtained with a recovery as high as 46â¯% by extraction at pHâ¯8, 120⯰C, for 90â¯min. This fraction, named LuPS-8, was composed of a mostly linear pectic polysaccharide with a weight average molecular mass of 6608â¯kg/mol, and containing 71.0â¯% galactose, with minor amounts of arabinose (16.0â¯%), glucuronic acid 4.6â¯%, and galacturonic acid 4.1â¯%. When added to an acid milk dispersion, LuPS-8 improved its dispersibility, providing storage stability against sedimentation over a wider pH range than a HM-pectin reference, between 3.6-4.4. This research demonstrated the potential for upcycling of a side stream of lupin protein production, by the creation of value-added novel functional polysaccharide.
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This article presents a method to use the dispersive behavior of ultrasonic guided waves and neural networks to determine the isotropic elastic constants of plate-like structures through dispersion images. Therefore, two different architectures are compared: one using convolutions and transfer learning based on the EfficientNetB7 and a Vision Transformer-like approach. To accomplish this, simulated and measured dispersion images are generated, where the first is applied to design, train, and validate and the second to test the neural networks. During the training of the neural networks, distinct data augmentation layers are employed to introduce artifacts appearing in measurement data into the simulated data. The neural networks can extrapolate from simulated to measured data using these layers. The trained neural networks are assessed using dispersion images from seven known material samples. Multiple variations of the measured dispersion images are tested to guarantee the prediction stability. The study demonstrates that neural networks can learn to predict the isotropic elastic constants from measured dispersion images using only simulated dispersion images for training and validation without needing an initial guess or manual feature extraction, independent of the measurement setup. Furthermore, the suitability of the different architectures for generating information from dispersion images in general and an image-to-regression visualisation technique, are discussed.
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INTRODUCTION: Intraindividual variability across a battery of neuropsychological tests (IIV-dispersion) can reflect normal variation in scores or arise from cognitive impairment. An alternate interpretation is IIV-dispersion reflects reduced engagement/invalid test data, although extant research addressing this interpretation is significantly limited. METHOD: We used a sample of 97 older adult (mean age: 69.92), predominantly White (57%) or Black/African American (34%), and predominantly cis-gender male (87%) veterans. Examinees completed a comprehensive neuropsychological battery, including measures of reduced engagement/invalid test data (a symptom validity test [SVT], multiple performance validity tests [PVTs]), as part of a clinical evaluation. IIV-dispersion was indexed using the coefficient of variance (CoV). We tested 1) the relationships of raw scores and "failures" on SVT/PVTs with IIV-dispersion, 2) the relationship between IIV-dispersion and validity/neurocognitive disorder status, and 3) whether IIV-dispersion discriminated the validity/neurocognitive disorder groups using receiver operating characteristic (ROC) curves. RESULTS: IIV-dispersion was significantly and independently associated with a selection of PVTs, with small to very large effect sizes. Participants with invalid profiles and cognitively impaired participants with valid profiles exhibited medium to large (d = .55-1.09) elevations in IIV-dispersion compared to cognitively unimpaired participants with valid profiles. A non-significant but small to medium (d = .35-.60) elevation in IIV-dispersion was observed for participants with invalid profiles compared to those with a neurocognitive disorder. IIV-dispersion was largely accurate at differentiating participants without a neurocognitive disorder from invalid participants and those with a neurocognitive disorder (areas under the Curve [AUCs]=.69-.83), while accuracy was low for differentiating invalid participants from those with a neurocognitive disorder (AUCs=.58-.65). CONCLUSIONS: These preliminary data suggest IIV-dispersion may be sensitive to both neurocognitive disorders and compromised engagement. Clinicians and researchers should exercise due diligence and consider test validity (e.g. PVTs, behavioral signs of engagement) as an alternate explanation prior to interpretation of intraindividual variability as an indicator of cognitive impairment.
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Radiological assessments on zones to take protective actions in case of a nuclear or radiological emergency involve a series of real-time forecasts of radiological impact on the public at various distances from the release point, using actual weather or forecast data, information on the source term or facility status, and primary radiation monitoring data. This practice is implemented during the operation of emergency centers around the world in order to promptly report the occurrence and possible consequences of radiological accidents in the country and abroad in the event of a possible transboundary impact. Since the Chornobyl disaster, a lot of emergency exercises, research programs and projects, in particular, benchmarking, have served as international platforms for improving modeling capacity in atmospheric dispersion. This activity is carried out both on the basis of past severe accidents with significant atmospheric releases and corresponding radiological consequences, and on the basis of specific conditional (hypothetical) events that are developed in accordance with the purpose of the study. The paper is focused on the comparison results performed under the international project "Benchmarking on Assessment of Radiological COnsequences" (BARCO) conducted in 2020-2021 between five technical support organisations - members of the European Technical Safety Organisations Network (ETSON). The work contains a short overview of relevant international activity conducted in the past, a description of the BARCO project and its objectives, a list of participants, project tasks, initial data (source term, meteorology, list of benchmarking quantities, approach to data exchange, codes used). The study presents some of comparative analysis results obtained via two techniques such as code-to-code analysis (CTCA) and matched-pair analysis (MPA). The results discussion concentrates on the overall recommendations for code users. Conclusions provide the main outputs of the project.
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This work provides a procedure and database for obtaining the vibrational frequency scale factors that align quantum chemically computed harmonic frequencies with experimental vibrational spectroscopic data. The database comprises 441 molecules of various sizes, from diatomics to the buckminsterfullerene C60. We provide scale factors for 27 dispersion-corrected methods, 24 of which are DF-Dn/B with DF=BLYP, PBE, B3LYP, PBE0, Dn=D3(BJ), D4, and B=6-31G, def2-SVP, def2-TZVP, and three of them are the 3c-family composite methods (HF-3c, PBEh-3c, and r2$SCAN-3c). The two scale factors are derived for each method: the absolute scaling, minimizing the absolute deviation of the scaled harmonic frequency from the experimental value, and the relative scaling, which minimizes an analogous relative deviation. The absolute type of scaling is recommended for frequencies above 2000 cm-1, while the relative scaling is optimal for frequencies below 2000 cm-1.