Miracle-dz/UniFAR-FTUs huggingface dataset:
Multicomponent Seismic Technology

A principle that is emphasized throughout this book is that the physics of any multicomponent seismic technology cannot be understood unless that technology is viewed in terms of the particle-displacement vectors associated with the various modes of a seismic wavefield. This material therefore begins with a discussion of seismic vector-wavefield behavior to set the stage for subsequent chapters. Several approaches can be used to explain why each wave mode of nine-component (9C) and three-component (3C) seismic data that propagates through subsurface geology provides a different amount and type of rock/fluid information about the geology that the wave modes illuminate. Some approaches appeal to people who have limited interest in mathematics. Other options need to be structured for people who have an appreciation of the mathematics of wavefield reflectivity. Another argument that can be used focuses on the fundamental differences in P-wave and S-wave radiation patterns and the distinctions in target illuminations associated with 9C and 3C seismic sources. We will consider all of those paths of logic. A principle that will be stressed is that each mode of a multicomponent seismic wavefield senses a different earth fabric along its propagation path because its particle-displacement vector is oriented in a different direction than are the particle-displacement vectors of its companion modes. Although estimations of earth fabric obtained from various modes of a multicomponent seismic wavefield can differ, each estimate still can be correct because each wave mode deforms a unit volume of rock in a different direction, depending on the orientation of its particle-displacement vector. Those deformations sense a different earth resistance in directions parallel to and normal to various symmetry planes in real-earth media. The logic of that nonmathematical approach appeals to people who are interested in the geologic and petrophysical information that multicomponent seismic data can provide and are less concerned about theory and mathematics. A second approach that is helpful for distinguishing one-component (1C), 3C, and 9C wavefield behavior focuses on the mathematics of the reflectivity equation associated with each mode of the full-elastic seismic wavefield. The mathematical structure of the reflectivity equation associated with each seismic wave mode describes why and how petrophysical properties of the propagation medium affect different wave modes in different ways. The logic of that analytical approach is appreciated by scientists who are comfortable with mathematics. All of these concepts lead to the development of a new seismic-interpretation science based on multicomponent seismic data called elastic wavefield seismic stratigraphy.
EVALUATION OF ALGEBRAIC REYNOLDS-STRESS MODELS FOR SEPARATED HIGH-SPEED FLOWS

High Reynolds number supersonic flowfields were generated numerically in order to assess the performance of three explicit algebraic Reynoldsstress turbulence models. The configurations consist of a shock/boundary-layer interaction and a 24 deg compression ramp, both of which exhibit an appreciable region of separated flow. Solutions were also obtained using standard zero-equation and k — e models. Details of the computations are summarized, and the accuracy of numerical results is established via grid resolution studies. Comparisons are made with experimental data in terms of surface pressure and skin friction, as well as off-surface profiles of mean velocity and components of the Reynolds-stress tensor. For the flows considered here, it is found that the algebraic-stress models offer little improvement over existing closures.
Research on ISAR imaging of the complexly moving target based on the time-chirp distribution

The change in chirp rate caused by the complex motion of the ship target deteriorates the azimuth focusing quality.This paper proposes a new imaging method based on TC-DechirpClean(DechirpClean searching method based on the time-chirp distribution),which makes use of the changing rate of scatterers' chirp to search their chirp rate and change rate of the chirp rate in the time-chirp distribution plane.At the same time,we do FFT after compensating the higher-order phase term to acquire the information about the center frequency and magnitude of these scatterers according to the maximum magnitude criteria.Finally,we can reconstruct the echo signal and obtain an instantaneous ISAR image.The imaging result of real data confirms that this method can greatly improve an unfocused ISAR image caused by the change rate of the chirp rate.
FRET from Multiple Pathways in Fluorophore-Labeled DNA

Because of their ease of design and assembly, DNA scaffolds provide a valuable means for organizing fluorophores into complex light harvesting antennae. However, as the size and complexity of the DNA–fluorophore network grows, it can be difficult to fully understand energy transfer properties because of the large number of dipolar interactions between fluorophores. Here, we investigate simple DNA–fluorophore networks that represent elements of the more complex networks and provide insight into the Forster Resonance Energy Transfer (FRET) processes in the presence of multiple pathways. These FRET networks consist of up to two Cy3 donor fluorophores and two Cy3.5 acceptor fluorophores that are linked to a rigid dual-rail DNA scaffold with short interfluorophore separation corresponding to 10 DNA base pairs (∼34 A). This configuration results in five FRET pathways: four hetero-FRET and one homo-FRET pathway. The FRET properties are characterized using a combination of steady-state and time-resolved spectrosc.
How I read an article that uses machine learning methods

Machine learning (ML) has revolutionized many industries including the health care industry by providing innovative solutions to some of the most pressing problems. With the advancement of technology and increasing amounts of data being generated, ML has become a central tool for health care professionals in various ﬁ elds, such as diagnostics, drug discovery
Integrative proteomics and metabolomics analysis of non‐observable acute effect level PM2.5 induced accumulative effects in AC16 cells

Chronic exposure to very low ambient PM2.5 has been linked to cardiovascular risks in epidemiological observation, which also brought doubts on its safety threshold. In this study, we approached this question by chronic exposure of AC16 to the non‐observable acute effect level (NOAEL) PM2.5 5 μg/mL and its positive reference 50 μg/mL, respectively. The doses were respectively defined on the cell viabilities >95% (p = 0.354) and >90% (p = 0.004) when treated acutely (24 h). To mimic the long‐term exposure, AC16 was cultured from the 1st to 30th generations and treated with PM2.5 24 h in every three generations. The integration of proteomic and metabolomic analysis was applied, and 212 proteins and 172 metabolites were significantly altered during the experiments. The NOAEL PM2.5 induced both dose‐ and time‐dependent disruption, which showed the dynamic cellular proteomic response and oxidation accumulation, the main metabolomics changes were ribonucleotide, amino acid, and lipid metabolism that have involved in stressed gene expression, and starving for energy metabolism and lipid oxidation. In summary, these pathways interacted with the monotonically increasing oxidative stress and led to the accumulated damage in AC16 and implied that the safe threshold of PM2.5 may be non‐existent when a long‐term exposure occurred.
A Weakly Supervised Gradient Attribution Constraint for Interpretable Classification and Anomaly Detection

The lack of interpretability of deep learning reduces understanding of what happens when a network does not work as expected and hinders its use in critical fields like medicine, which require transparency of decisions. For example, a healthy vs pathological classification model should rely on radiological signs and not on some training dataset biases. Several post-hoc models have been proposed to explain the decision of a trained network. However, they are very seldom used to enforce interpretability during training and none in accordance with the classification. In this paper, we propose a new weakly supervised method for both interpretable healthy vs pathological classification and anomaly detection. A new loss function is added to a standard classification model to constrain each voxel of healthy images to drive the network decision towards the healthy class according to gradient-based attributions. This constraint reveals pathological structures for patient images, allowing their unsupervised segmentation. Moreover, we advocate both theoretically and experimentally, that constrained training with the simple Gradient attribution is similar to constraints with the heavier Expected Gradient, consequently reducing the computational cost. We also propose a combination of attributions during the constrained training making the model robust to the attribution choice at inference. Our proposition was evaluated on two brain pathologies: tumors and multiple sclerosis. This new constraint provides a more relevant classification, with a more pathology-driven decision. For anomaly detection, the proposed method outperforms state-of-the-art especially on difficult multiple sclerosis lesions segmentation task with a 15 points Dice improvement.
Activator-induced conformational changes regulate division-associated peptidoglycan amidases

Significance Peptidoglycan amidases break the peptidoglycan layer during cell division and maintain integrity of the cell envelope. Here, we present structures of an isolated peptidoglycan hydrolase in an autoinhibited (“off”) state and a second amidase bound to the activating LytM domain of EnvC revealing the active (“on”) state. A comparison of these structures provides important molecular insights into the activation of peptidoglycan hydrolases by their cognate activators.
Membrane vesicle delivery of a streptococcal M protein disrupts the blood–brain barrier by inducing autophagic endothelial cell death

Significance Streptococcus equi subsp. zooepidemicus (SEZ) are Group C streptococci that cause meningitis in animals and humans. Here, we show SEZ releases membrane vesicles (MVs) that contain the SEZ M protein, SzM. MV provides an efficient means of delivery of SzM to host cells. Endocytosis of these vesicles results in autophagic cell death in hBMECs (human brain endothelial microvascular cells) and disruption of the BBB (blood–brain barrier) in mice. Blockade of MV endocytosis or inactivation of autophagic death attenuated SEZ pathogenicity in mice. Together, these findings provide therapeutic targets for treatment of SEZ infection and extend our knowledge of streptococcal virulence mechanisms.
NALCN‐mediated sodium influx confers metastatic prostate cancer cell invasiveness

There is growing evidence that ion channels are critically involved in cancer cell invasiveness and metastasis. However, the molecular mechanisms of ion signaling promoting cancer behavior are poorly understood and the complexity of the underlying remodeling during metastasis remains to be explored. Here, using a variety of in vitro and in vivo techniques, we show that metastatic prostate cancer cells acquire a specific Na+/Ca2+ signature required for persistent invasion. We identify the Na+ leak channel, NALCN, which is overexpressed in metastatic prostate cancer, as a major initiator and regulator of Ca2+ oscillations required for invadopodia formation. Indeed, NALCN‐mediated Na+ influx into cancer cells maintains intracellular Ca2+ oscillations via a specific chain of ion transport proteins including plasmalemmal and mitochondrial Na+/Ca2+ exchangers, SERCA and store‐operated channels. This signaling cascade promotes activity of the NACLN‐colocalized proto‐oncogene Src kinase, actin remodeling and secretion of proteolytic enzymes, thus increasing cancer cell invasive potential and metastatic lesions in vivo. Overall, our findings provide new insights into an ion signaling pathway specific for metastatic cells where NALCN acts as persistent invasion controller.
Analysis of Functionally Graded Piezoelectric Cylinders in a Hygrothermal Environment

This paper presents an analytical solution for the interaction of electric potentials, electric displacement, elastic deformations, and describes hygrothermal effect responses in hollow and solid cylinders, subjected to mechanical load and electric potential. Exact solutions for displacement, stresses and electric potentials in functionally graded piezoelectric material are determined using the infinitesimal theory. The material properties coefficients of the present cylinder are assumed to be graded in the radial direction by a power law distribution. Numerical examples display the significant of influence of material inhomogeneity. It is interesting to note that selecting a specific value of inhomogeneity parameter can optimize the piezoelectric hollow and solid cylinders responses, which will be of particular importance in modern engineering designs.
Lessons learned from talking with adults about nutrition: A qualitative study in the PREPARED project

Abstract Improving diet and dietary behaviour of men and women before pregnancy has the potential to benefit both their current and long‐term health and the health of their children. Little is known, however, about adults' perception of diet's role in prepregnancy health. This study aimed to explore the state of knowledge and awareness of preconception nutritional health in adults within the fertile age range and what they perceived could motivate healthy eating using the self‐determination theory as a theoretical framework. We analysed 33 short exploratory interviews with men (n = 18) and women (n = 15) aged 18–45 years. Participants were grab sampled from three different public locations in the southern part of Norway. Interviews were audio‐recorded, transcribed verbatim in 2020 and analysed using a thematic analysis with a semantic approach in 2022. The findings suggest that adults within the fertile age range are not intrinsically motivated to eat healthily, but when they do, it is because eating healthily often aligns with other goals consistent with their values, that is, getting fit or looking good. They possess some basic knowledge of healthy behaviours during pregnancy but are generally unaware of the importance of preconception health and nutrition. There is a need to increase awareness of the impact of preconception health on the health of this and future generations. Improved nutritional education on the significance of diet before conception might facilitate optimal conditions for conceiving and for pregnancy in the adult population within fertile age range.
Comparison between Two Different Handgrip Systems and Protocols on Force Reduction in Handgrip Assessment

Introduction: Fatigue resistance (FR) can be assessed as the time during which grip strength (GS) drops to 50% of its maximum during a sustained maximal voluntary contraction. For the first time, we compared force-time characteristics during FR test between two different handgrip systems and investigated age- and clinical-related differences in order to verify if a briefer test protocol (i.e., until 75%) could be sufficiently informative. Methods: A cohort of young healthy controls (Y, <30 y, 24 ± 3 y, 54% women), middle-aged (MA, 30–65 y, 47 ± 11 y, 54% women), and older (OLD, >65 y, 77 ± 7 y, 50% women) community-dwelling persons, and hospitalized geriatric patients (HOSP, 84 ± 5 y, 50% women) performed the FR test. For this purpose, an adapted vigorimeter (original rubber bulb of the Martin Vigorimeter connected to a Unik 5000 pressure gauge) here defined as “pneumatic handgrip system” (Pneu) and Dynamometer G200 system (original Jamar Dynamometer handle with an in-build strength gauge) here defined as “hydraulic handgrip system” (Hydr) were used. Force-time curves were analysed from 100% to 75% and from 75% to 50% of the initial maximal GS during the FR test. The area under the curve (GW) was calculated by integrating the actual GS at each time interval (i.e., 1/5,000 s) and corrected for body weight (GW/body weight). Results: For both systems, we found fair associations between FR100–50 and FR100–75 (Pneu mean difference = 50.1 s [95% CI: 47.9–52.4], r2 = 0.48; Hydr mean difference = 28.4 s [95% CI: 27.0–29.7], r2 = 0.52, all p < 0.001) and also moderate associations between GW(100–50)/body weight and GW(100–75)/body weight (Pneu mean difference = 32.1 kPa*s/kg [95% CI: 30.6–33.6], r2 = 0.72; Hydr mean difference = 8.1 kg*s/kg [95% CI: 7.7–8.6], r2 = 0.68, all p < 0.001). Between MA and OLD, we found a significant age-related difference in the GW results in the first 25% strength decay for Pneu (10.2 ± 0.6 kPa*s/kg against 7.1 ± 1.2 kPa*s/kg, respectively). Conclusion: The brief test protocol is valid. Differences within the first 25% strength decay in GW between OLD and HOSP were identified when using Pneu but not when using Hydr. Therefore, a brief FR test protocol using a continuous registration of the strength decay seems to be sufficiently informative in a clinical setting to appraise muscle fatigability, however, only when using a Pneu system.
A data‐driven framework to model the organism–environment system

Organisms modify their development and function in response to the environment. At the same time, the environment is modified by the activities of the organism. Despite the ubiquity of such dynamical interactions in nature, it remains challenging to develop models that accurately represent them, and that can be fitted using data. These features are desirable when modeling phenomena such as phenotypic plasticity, to generate quantitative predictions of how the system will respond to environmental signals of different magnitude or at different times, for example, during ontogeny. Here, we explain a modeling framework that represents the organism and environment as a single coupled dynamical system in terms of inputs and outputs. Inputs are external signals, and outputs are measurements of the system in time. The framework uses time‐series data of inputs and outputs to fit a nonlinear black‐box model that allows to predict how the system will respond to novel input signals. The framework has three key properties: it captures the dynamical nature of the organism–environment system, it can be fitted with data, and it can be applied without detailed knowledge of the system. We study phenotypic plasticity using in silico experiments and demonstrate that the framework predicts the response to novel environmental signals. The framework allows us to model plasticity as a dynamical property that changes in time during ontogeny, reflecting the well‐known fact that organisms are more or less plastic at different developmental stages.
Temperature Patterns of Air Crossflow with Hollow-Cone Spray Evaporation

This work focused on the heat transfer of the mixing process resulting from a hollow-cone spray evaporation in high-temperature gas crossflow in a confined mixing space. The study was carried out in a rectangular duct with a cross-sectional area of 95×95 mm. The temperatures on four cross sections (45 measuring points on half of a cross section) of crossflow were measured using thermocouples. The temperature pattern of gas crossflow caused by the evaporation of hollow-cone spray was obtained, and the effects of factors such as crossflow velocity, crossflow temperature, spray droplet size, and spray injection angle on the temperature pattern were investigated. The main findings of this study were as follows: 1) The polydispersed hollow-cone spray droplets and the droplet-wall impingement made the heat transfer on the cross section of the flowfield inherently nonuniform. 2) The mixing flowfield fell into five regions characterized by different heat transfer mechanisms. 3) The temperature pattern of crossfl.
MiRNA-494 induces trophoblast senescence by targeting SIRT1

ABSTRACT Objective Although the mechanism underlying preeclampsia (PE) has been widely explored, the mechanisms related to senescence have not yet been fully revealed. Therefore, we investigated the role of the miR-494/longevity protein Sirtuin 1 (SIRT1) axis in PE. Methods Human placental tissue was obtained from severe preeclampsia (SPE) (n = 20) and gestational age-matched normotensive pregnancies (n = 20), and senescence-associated β-galactosidase (SAβG) and SIRT1 expression levels were measured. The TargetScan and miRDB databases predicted candidate miRNAs targeting SIRT1, and intersected with differentially expressed miRNAs in the GSE15789 dataset (p < 0.05, |log2FC|≥1.5). Subsequently, we showed that miRNA (miR)-494 expression was significantly elevated in SPE, revealing miR-494 as a candidate SIRT1-binding miRNA. A dual-luciferase assay confirmed the targeting relationship between miR-494 and SIRT1. The senescence phenotype, migration, cell viability, reactive oxygen species (ROS) production levels and inflammatory molecule expression levels were measured after miR-494 expression was altered. We conducted a rescue experiment using SIRT1 plasmids to further demonstrate the regulatory relationship. Results SIRT1 expression was lower(p < 0.01) and miR-494 expression was higher (p < 0.001) in SPE, and SaβG staining showed premature placental aging in SPE (p < 0.001). Dual-luciferase reporter assays revealed that miR-494 targeted SIRT1. Compared to control cells, HTR-8/SVneo cells with upregulation of miR-494 had remarkably downregulated SIRT1 expression (p < 0.001), more SAβG-positive cells (p < 0.001), cell cycle arrested (p < 0.05), and upregulated P21 and P16 expression (p < 0.01). miR-494 overexpression also decreased HTR-8/SVneo cell migration (p < 0.05) and ATP synthesis (p < 0.001), increased ROS levels (p < 0.001), and upregulated NLRP3 and IL-1β expression (p < 0.01). SIRT1-overexpressing plasmids partially reversed the effects of miR-494 overexpression in HTR-8/SVneo cells. Conclusion The miR-494/SIRT1 interaction plays a role in the mechanism of premature placental aging in PE patients. GRAPHICAL ABSTRACT
Racial and Socioeconomic Disparities in Risk and Reason for Revision in Total Joint Arthroplasty

Introduction: Data regarding racial/ethnic and socioeconomic differences in revision total hip arthroplasty (rTHA) and revision total knee arthroplasty (rTKA) have been inconsistent. This study examined racial/ethnic and socioeconomic disparities in comorbidity-adjusted risk and reason for rTHA and rTKA. Methods: Patients who underwent rTHA or rTKA between 2006 and 2014 in the National Inpatient Sample were identified. Multivariable logistic regression models adjusted for payer status, hospital geographic setting, and patient characteristics (age, sex, and Elixhauser Comorbidity Index) were used to examine the effect of race/ethnicity and socioeconomic status on trends in annual risk of rTHA/rTKA and causes of rTHA/rTKA. Results: Black patients were less likely to undergo rTHA and more likely to undergo rTKA while Hispanic patients were more likely to undergo rTHA and less likely to undergo rTKA (P < 0.001 for all) compared with White patients. Patients residing in areas of lower income quartiles were more likely to undergo rTHA and rTKA compared with those in the highest quartile (P < 0.001), and these disparities persisted and widened over time. Black, Hispanic, and Asian patients were less likely to undergo rTHA/rTKA because of dislocation compared with White patients (P < 0.001 for all). Patients from areas of lower income quartiles were more likely to undergo rTHA because of septic complications and less likely to require both rTHA and rTKA because of mechanical complications (P < 0.001 for all). Discussion: Racial/ethnic and socioeconomic disparities exist in risk and cause of rTHA and rTKA. Increasing awareness and a focus on minimizing variability in hospital quality may help mitigate these disparities.