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This work presents a new methodology for fabrication of membrane-assisted elongated YIG nanostructures through the sol-gel method using low-cost materials, and the estimation of the average size of the geometries formed within the pores through ferromagnetic resonance measurements. A precursor solution was deposited on the internal surface of porous aluminum oxide membrane, using an assembly consisting of a vacuum system coupled to an apparatus, which assists in the entry of the used precursor solution, breaking the barriers related to the existing surface tension, with subsequent heat treatment to form the single phase of yttrium iron garnet (YIG). The data collected by X-ray diffraction and Raman spectroscopy indicated this result. The study of the contact angle of the precursor solution and the alumina template indicated great compatibility, an angle of 35.4°. SEM analysis showed that elongated structures were deposited inside the pore’s walls, with different lengths up to 3 micrometers and the EDS analysis showed the presence of the main elements of the YIG phase. The Kittel’s equation and FMR spectral data were used to estimate the mean size of the elongated nanostructures. We found six different size categories with 1856, 1768, 1661, 1588, 1570, 1498 nm . The methodology proved to be efficient for the characterization of elongated YIG nanostructures, becoming a perspective of future applications. Graphical Abstract Highlights Setup for the infiltration of the alumina membrane with the YIG precursor was proposed. Elongated YIG structures were obtained with diverse potential applications. The FMR was used to estimate the mean size of elongated YIG structures.

The analysis of ferromagnetic resonance (FMR) through micromagnetic simulations is a powerful tool used to gain insight into the effects of shape on magnetization dynamics. Mathematical models incorporated into simulation programs have greatly facilitated the understanding of resulting magnetic behaviors. The present study aimed to investigate the influence of shape on the magnetization dynamics of Permalloy discs and stadium-like geometries of finite dimensions. The finite element numerical method was used to perform simulations, employing the Nmag simulator. To simulate the FMR spectra, the ringdown method was utilized, a common technique in computational micromagnetism. Resonance modes were identified using Fourier transform analysis. The novelty of this work is to demonstrate that in a film with a thickness of 50 nm and lateral dimensions less than 1000 nm, it cannot be considered as an infinite film. The results of the calculations showed that, for an in-plane field in a Py disk with these dimensions, there are resonance fields affected when the geometry is slightly stretched. This phenomenon was observed applying a field parallel to the plane of a stadium-shaped geometry. The effects of shape anisotropy remain relevant even in a 50 nm film with lateral dimensions exceeding 1000 nm. The aim of the study is to review results that are normally used for work with thin films. Assuming infinite dimensions and disregarding shape effects always requires care, since depending on the study in question, artifacts due to the shape effect may arise and be interpreted incorrectly.

High-quality single-phase YIG films prepared by metallo-organic decomposition (MOD) and suitable for the fabrication of ordered nanostructures using a focused ion beam are presented in this work. The YIG films were deposited both on Si and SiO2 substrates and the cleaning process of the substrate was evaluated as a parameter influencing the film homogeneity. X-ray diffraction and Raman spectroscopy data revealed that a single YIG resulted in all experiments. SEM and AFM showed that films are crack-free with porous morphology and the roughness is smaller than Rq < 0.2 nm. The methodology is scalable and low cost if compared to methods previously described in the literature. The resulting nanostructures are promising for studies in spintronics with thickness between 135 and 180 nm.

This study investigates the influence of sintering temperature on the structural and magnetic properties of Y 3 Fe 4,97 La 0,03 O 12 , elucidating the nucleation and growth mechanisms related to temperature. Through meticulous X-ray diffraction analysis, we confirmed the formation of a single YIG phase at 900 °C. Conversely, samples sintered at 1000 °C and 1100 °C reveal the presence of a second phase, attributed to YFeO 3 , highlighting the complex interaction between sintering temperature and material morphology. Moreover, magnetic characterization details how sintering temperatures directly influence the magnetic moment and saturation magnetization of the nanoparticles, presenting significant fluctuations in magnetic properties due to the presence of the secondary phase. This work not only sheds light on the subtle relationship between lanthanum doping, sintering temperature, and the resulting magnetic properties but also paves the way for fine-tuning these properties in advanced materials for specific technological applications.

Bacterial translocation is an important source of pancreas infection in acute pancreatitis. The effect of platelet-activating factor (PAF) in the pathogenesis of acute pancreatitis has been proved in various studies. The aim of this study was to determine whether potent PAF antagonists influence bacterial translocation in acute pancreatitis. Acute pancreatitis was induced in 62 Wistar rats by injection of 2.5% sodium taurocholate into the biliopancreatic duct. The rats treated with PAF factor antagonists received intravenous injection of WEB-2170 (10 mg/kg), lexipafant (5 mg/kg), and BN-52021 (5 mg/kg) 30 minutes before induction of acute pancreatitis. Six hours after induction of acute pancreatitis, bacteriologic cultures and histologic scoring of tissues were performed. There was a statistically significant reduction in bacterial translocation to the mesenteric lymph nodes and liver but not to the pancreas of the rats treated with PAF antagonists. No significant increase in the intestinal bacterial population of any group was found. There were no statistical differences between the pancreatic histologic scores of the groups. PAF antagonists reduced bacterial translocation to distant sites other than the pancreas, preventing the bacterial dissemination that occurs in the early phase of acute pancreatitis and may have beneficial effects on the evolution of this disease.

Climate change is producing shifts in the distribution and abundance of marine species. Such is the case of kelp forests, important marine ecosystem-structuring species whose distributional range limits have been shifting worldwide. Synthesizing long-term time series of kelp forest observations is therefore vital for understanding the drivers shaping ecosystem dynamics and for predicting responses to ongoing and future climate changes. Traditional methods of mapping kelp from satellite imagery are time-consuming and expensive, as they require high amount of human effort for image processing and algorithm optimization. Here we propose the use of mask region-based convolutional neural networks (Mask R-CNN) to automatically assimilate data from open-source satellite imagery (Landsat Thematic Mapper) and detect kelp forest canopy cover. The analyses focused on the giant kelp Macrocystis pyrifera along the shorelines of southern California and Baja California in the northeastern Pacific. Model hyper-parameterization was tuned through cross-validation procedures testing the effect of data augmentation, and different learning rates and anchor sizes. The optimal model detected kelp forests with high performance and low levels of overprediction (Jaccard’s index: 0.87 ± 0.07; Dice index: 0.93 ± 0.04; over prediction: 0.06) and allowed reconstructing a time series of 32 years in Baja California (Mexico), a region known for its high variability in kelp owing to El Niño events. The proposed framework based on Mask R-CNN now joins the list of cost-efficient tools for long-term marine ecological monitoring, facilitating well-informed biodiversity conservation, management and decision making.

The current practice for diagnosis of COVID-19, based on SARS-CoV-2 PCR testing of pharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk, likely underestimates the true prevalence of infection. Serologic methods can more accurately estimate the disease burden by detecting infections missed by the limited testing performed to date. Here, we describe the validation of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A comparison of antibody profiles detected on the array from control sera collected prior to the SARS-CoV-2 pandemic versus convalescent blood specimens from virologically confirmed COVID-19 cases demonstrates near complete discrimination of these two groups, with improved performance from use of antigen combinations that include both spike protein and nucleoprotein. This array can be used as a diagnostic tool, as an epidemiologic tool to more accurately estimate the disease burden of COVID-19, and as a research tool to correlate antibody responses with clinical outcomes. COVID-19 diagnosis is commonly performed by PCR testing, however, serologic methods are more accurate and versatile for monitoring disease burden and epidemiology. Here the authors report a protein microarray with antigens from SARS-CoV-2, SARS-CoV, MERS-CoV as well as common human respiratory viruses.

Focal cortical dysplasia (FCD) is a brain malformation that causes medically refractory epilepsy. FCD is classified into three categories based on structural and cellular abnormalities, with FCD type II being the most common and characterized by disrupted organization of the cortex and abnormal neuronal development. In this study, we employed cell-type deconvolution and single-cell signatures to analyze bulk RNA-seq from multiple transcriptomic studies, aiming to characterize the cellular composition of brain lesions in patients with FCD IIa and IIb subtypes. Our deconvolution analyses revealed specific cellular changes in FCD IIb, including neuronal loss and an increase in reactive astrocytes (astrogliosis) when compared to FCD IIa. Astrogliosis in FCD IIb was further supported by a gene signature analysis and histologically confirmed by glial fibrillary acidic protein (GFAP) immunostaining. Overall, our findings demonstrate that FCD II subtypes exhibit differential neuronal and glial compositions, with astrogliosis emerging as a hallmark of FCD IIb. These observations, validated in independent patient cohorts and confirmed using immunohistochemistry, offer novel insights into the involvement of glial cells in FCD type II pathophysiology and may contribute to the development of targeted therapies for this condition.

We use 47 gravitational wave sources from the Third LIGO–Virgo–Kamioka Gravitational Wave Detector Gravitational Wave Transient Catalog (GWTC–3) to estimate the Hubble parameter H(z), including its current value, the Hubble constant H 0. Each gravitational wave (GW) signal provides the luminosity distance to the source, and we estimate the corresponding redshift using two methods: the redshifted masses and a galaxy catalog. Using the binary black hole (BBH) redshifted masses, we simultaneously infer the source mass distribution and H(z). The source mass distribution displays a peak around 34 M ⊙, followed by a drop-off. Assuming this mass scale does not evolve with the redshift results in a H(z) measurement, yielding H0=68−8+12kms−1Mpc−1 (68% credible interval) when combined with the H 0 measurement from GW170817 and its electromagnetic counterpart. This represents an improvement of 17% with respect to the H 0 estimate from GWTC–1. The second method associates each GW event with its probable host galaxy in the catalog GLADE+, statistically marginalizing over the redshifts of each event’s potential hosts. Assuming a fixed BBH population, we estimate a value of H0=68−6+8kms−1Mpc−1 with the galaxy catalog method, an improvement of 42% with respect to our GWTC–1 result and 20% with respect to recent H 0 studies using GWTC–2 events. However, we show that this result is strongly impacted by assumptions about the BBH source mass distribution; the only event which is not strongly impacted by such assumptions (and is thus informative about H 0) is the well-localized event GW190814.

The use of digital images could be a faster and cheaper alternative technique to assess BW, HCW, and body composition of beef cattle. The objective of this study was to develop equations to predict body and carcass weight and body fat content of young bulls using digital images obtained through a Microsoft Kinect device. Thirty-five bulls with an initial BW of 383 (±5.38) kg (20 Black Angus, 390 [±7.48] kg initial BW, and 15 Nellore, 377 [±8.66] kg initial BW) were used. The Kinect sensor, installed on the top of a cattle chute, was used to take infrared light-based depth videos, recorded before the slaughter. For each animal, a quality control was made, running and pausing the video at the moment that the animal was standing with its body and head in line. One frame from recorded videos was selected and used to analyze the following body measurements: chest width, thorax width, abdomen width, body length, dorsal height, and dorsal area. From these body measurements, 23 indexes were generated and tested as potential predictors. The BW and HCW were assessed with a digital scale, whereas empty body fat (EBF) was estimated through ground samples of all tissues. To better understand the relationship among the measurements, the correlations between final BW (488 [±10.4] kg), HCW (287 [±12.5] kg), EBF (14 [±0.610] % empty BW) content, body measurements (taken through digital images), and developed indexes were evaluated. The REG procedure was used to develop the regressions, and the important independent variables were identified using the options STEPWISE and Mallow's Cp in the SELECTION statement. Chest width was the trait most related to weights and the correlations between this measurement and BW and HCW were above 0.85. The analysis of linear regressions between observed and predicted values showed that all models pass through the origin and have a slope of unity (null hypothesis [H]: = 0 and = 1; ≥ 0.993). The models to estimate BW and HCW of Angus and Nellore presented between 0.69 and 0.84 ( < 0.001), whereas from equations to estimate the EBF were lower ( = 0.43-0.45; ≤ 0.006). Index I5 [(chest width) × body length], related to the animal volume, was significant in all models created to estimate BW and HCW, and it explained more than 70% of the variation. This study indicates that digital images taken through a Microsoft Kinect system have the potential to be used as a tool to estimate body and carcass weight of beef cattle.